Financial Value Transparency and Gainful Employment

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Federal RegisterOct 10, 2023
88 Fed. Reg. 70004 (Oct. 10, 2023)

AGENCY:

Office of Postsecondary Education, Department of Education.

ACTION:

Final regulations.

SUMMARY:

The Secretary establishes and amends regulations related to gainful employment (GE) to address ongoing concerns about educational programs designed to prepare students for gainful employment in a recognized occupation, but that instead leave them with unaffordable amounts of student loan debt in relation to their earnings, or with no gain in earnings compared to others with no more than a high school education. The Secretary separately seeks to enhance transparency by providing information about financial costs and benefits to students at nearly all academic programs at postsecondary institutions that are eligible to participate in title IV of the Higher Education Act of 1965, as amended (HEA).

DATES:

These regulations are effective July 1, 2024.

FOR FURTHER INFORMATION CONTACT:

Joe Massman. Telephone: (202) 453–7771. Email: GE24@ed.gov.

If you are deaf, hard of hearing, or have a speech disability and wish to access telecommunications relay services, please dial 7–1–1.

SUPPLEMENTARY INFORMATION:

Executive Summary

Purpose of This Regulatory Action

The Federal Government makes significant annual investments under title IV of the HEA through programs that provide financial assistance to help students pay for postsecondary education and training. This includes both Federal grants and Federal loans, with the largest amount of such aid flowing through Pell Grants and Direct Loans. These investments in education amount to well over $100 billion in new Pell Grants and Direct Loans in total made each year.

Note that the dollar figure in the text above refers to the sum of all Pell Grants and Direct Loans made each year. The cost of Direct Loans, which is the lion's share of this amount, to the Federal Government is less than the amount disbursed since borrowers repay, as expanded on below. This final rule affects a small fraction of the total amount, as detailed below.

The Federal Government's commitment to postsecondary education and training is well-justified. Postsecondary education and training generate important benefits both to the students pursuing new knowledge and skills and to the Nation overall. Higher education increases wages and lowers unemployment risk, and leads to myriad non-financial benefits including better health, job satisfaction, and overall happiness. In addition, increasing the number of individuals with postsecondary education creates social benefits, including productivity spillovers from a better educated and more flexible workforce, increased civic participation, improvements in health and well-being for the next generation, and innumerable intangible benefits that elude quantification. In addition, the improvements in productivity and earnings lead to increases in tax revenues from higher earnings and lower rates of reliance on social safety net programs. These downstream increases in net revenue to the Government can be so large that public investments in higher education, including those that Congress established in title IV, HEA, more than pay for themselves.

Barrow, L. & Malamud, O. (2015). Is College a Worthwhile Investment? Annual Review of Economics, 7(1), 519–555. Card, D. (1999). The Causal Effect of Education on Earnings. Handbook of Labor Economics, 3, 1801–1863.

Oreopoulos, P. & Salvanes, K.G. (2011). Priceless: The Nonpecuniary Benefits of Schooling. Journal of Economic Perspectives, 25(1), 159–184.

Moretti, E. (2004). Workers' Education, Spillovers, and Productivity: Evidence from Plant-Level Production Functions. American Economic Review, 94(3), 656–690.

Dee, T.S. (2004). Are There Civic Returns to Education? Journal of Public Economics, 88(9–10), 1697–1720.

Currie, J. & Moretti, E. (2003). Mother's Education and the Intergenerational Transmission of Human Capital: Evidence from College Openings. The Quarterly Journal of Economics, 118(4), 1495–1532.

Hendren, N. & Sprung-Keyser, B. (2020). A Unified Welfare Analysis of Government Policies. The Quarterly Journal of Economics, 135(3), 1209–1318.

These benefits are not guaranteed, however. Research has demonstrated that the returns, especially the gains in earnings students enjoy as a result of their education, vary dramatically across institutions and among programs within those institutions. As we illustrate in the Regulatory Impact Analysis (RIA) of this final rule, even among the same types of programs—that is, among programs with similar academic levels and fields of study—both the costs and the outcomes for students differ widely. Most postsecondary programs provide benefits to students in the form of higher wages that help them repay any loans they may have obtained to attend the program. But too many programs fail to increase graduates' wages, having little or even negative effects on graduates' earnings. At the same time, too many programs charge much higher tuition than similar programs with comparable outcomes, leading students to borrow much more than they would have needed had they chosen a more affordable program.

Hoxby, C.M. (2019). The Productivity of U.S. Postsecondary Institutions. In Productivity in Higher Education, Hoxby, C.M. & Stange, K.M. (eds). University of Chicago Press. Lovenheim, M. & Smith, J. (2023). Returns to Different Postsecondary Investments: Institution Type, Academic Programs, and Credentials. In Handbook of the Economics of Education Volume 6, Hanushek, E., Woessmann, E. & Machin, S. (eds). New Holland.

Cellini, S. & Turner, N. (2018). Gainfully Employed? Assessing the Employment and Earnings of For-Profit College Students Using Administrative Data. Journal of Human Resources, 54(2).

While increased borrowing is indicative of higher education costs-of-attendance, financing the costs of postsecondary education and training with Federal student loans creates significant risk for borrowers and the Federal Government (as well as taxpayers). In particular, if students' earnings after college are low, then they are likely to face difficulty in repaying their loans and will be more likely to default. The associated penalties and delays in repayment make the student loan more costly to repay, and, by damaging the borrower's credit, may also increase costs of other borrowing considerably. From the Federal Government's perspective, if borrowers earn less, then they are also entitled to repay less of their loans under Income-Driven Repayment (IDR) plans and can have their loans forgiven after preset amounts of time in repayment. And if borrowers default on a loan, they may end up repaying less than they borrowed depending on the success of various collections tools available to the Government. As a result, low labor market earnings and low earnings relative to debt both drive up the costs, to both the borrower and taxpayers, of postsecondary investments financed with student loans.

For example, a 2023 Consumer Financial Protection Bureau analysis suggests that a default on a borrower's credit record could lower their credit score by about 50 points, which might result in an additional cost of $1,700 on a typical auto loan due to less favorable interest terms. Gibbs, Christa (2023). Initial Fresh Start Program Changes Followed by Increased Credit Scores for Affected Student Loan Borrowers. Consumer Financial Protection Bureau ( https://www.consumerfinance.gov/about-us/blog/initial-fresh-start-program-changes-followed-by-increased-credit-scores-for-affected-borrowers/ ).

With college tuition consistently rising faster than inflation, and given the growing necessity of a postsecondary credential to compete in today's economy, it is critical for students, families, and taxpayers alike to have accurate and transparent information about the possible financial consequences of their postsecondary program options. Providing information on the typical earnings outcomes, borrowing amounts, costs of attendance, and sources of financial aid—and providing it directly to prospective students in a salient way at a key moment in their decision-making process—would help students make more informed choices. The same information will also allow taxpayers and college stakeholders to better assess whether public and private resources are being effectively used. For many students, and for many stakeholders, these financial considerations would, appropriately, be just one of many factors used in deciding whether and where to enroll. But as noted throughout this final rule including the RIA, it is clear that both prospective students and the population in general consider these financial factors as among the most important in assessing postsecondary education performance.

For programs that consistently produce graduates with very low earnings, or with earnings that are too low to repay the amount the typical graduate borrows to complete a credential, additional measures are needed to protect students from financial harm. Making information available has been shown to improve consequential financial choices across a variety of settings. But it has also been shown to be a limited remedy, especially for more vulnerable populations who may struggle to access the information, or who have less support in interpreting and acting upon the relevant information.

Baker, Dominique J., Cellini, Stephanie Riegg, Scott-Clayton, Judith & Turner, Lesley J. (2021). Why Information Alone Is Not Enough to Improve Higher Education Outcomes. The Brookings Institution ( www.brookings.edu/blog/brown-center-chalkboard/2021/12/14/why-information-alone-is-not-enough-to-improve-higher-education-outcomes/ ). Steffel, Mary, Kramer II, Dennis A., McHugh, Walter & Ducoff, Nick (2019). Information Disclosure and College Choice. The Brookings Institution ( www.brookings.edu/wp-content/uploads/2020/11/ES-11.23.20-Steffel-et-al-1.pdf ).

To address these issues, the Department establishes subparts Q and S of part 668, and makes supporting amendments to §§ 600.10, 600.21, 668.2, 668.13, 668.43, and 668.91.

(1) In subpart Q, we establish a financial value transparency framework. That framework will increase the quality and availability of information provided directly to students about the costs, sources of financial aid, and outcomes of students enrolled in all eligible programs. In part, the transparency framework establishes measures of enhanced earnings and affordable debt—more specifically, the earnings premium (EP measure) that typical program graduates experience relative to the earnings of typical high school graduates, as well as the debt service burden (debt-to-earnings ratio or D/E rates measure) for typical graduates. It further establishes performance benchmarks for each measure, denoting a threshold level of performance below which the program may have adverse financial consequences to students. This information will be made available to all students via a program information website maintained by the Department and described in amended § 668.43. For programs that do not meet the performance benchmarks for the D/E rates measure, prospective students will be required to acknowledge having viewed these disclosures before entering into enrollment agreements with an institution. Further, the Department's program information website will provide the public, taxpayers, and the Government with relevant information with which they may act to better safeguard the Federal investment in these programs. The transparency framework will also provide institutions with meaningful information that they can use to compare their performance to other institutions and improve student outcomes in these programs.

(2) In subpart S, we establish an accountability and eligibility framework for gainful employment programs. This GE program accountability framework is specific to educational programs that, as a statutory condition of eligibility to participate in title IV, HEA, are required to provide training that prepares students for gainful employment in a recognized occupation or profession (GE programs). GE programs include nearly all educational programs at for-profit institutions of higher education, as well as non-degree programs at public and private nonprofit institutions such as community colleges. The GE program eligibility framework will use the same earnings premium and debt-burden measures from the transparency framework to determine whether a GE program remains eligible for title IV, HEA participation. The GE eligibility criteria define what it means to prepare students for gainful employment in a recognized occupation, and they tie program eligibility to whether GE programs provide education and training to their title IV, HEA students that lead to earnings beyond those of high school graduates and sufficient to allow students to repay their student loans. GE programs that fail the same measure in any two out of three consecutive years for which the measure is calculated will not be eligible to participate in title IV, HEA programs.

The Department has previously issued regulations on these issues three times. We refer to those regulatory actions as the 2011 Prior Rule (76 FR 34385), the 2014 Prior Rule (79 FR 64889), and the 2019 Prior Rule (84 FR 31392), which rescinded the 2014 Prior Rule. For a detailed discussion of the history of these regulations, please see the Background section of the notice of proposed rulemaking that was published in the Federal Register on May 19, 2023 (88 FR 32300) (NPRM). This final rule departs from the 2019 Prior Rule and partly reinstates provisions of the 2014 Prior Rule, but this final rule also departs in certain respects from the 2014 Prior Rule to improve the regulations in light of new data and current circumstances, as discussed in the NPRM.

88 FR 32300, 32306 (May 19, 2023).

The financial value transparency framework covers all programs that participate in the title IV, HEA programs, and it will dramatically enhance the quality of information available to all students so that they may better assess the financial consequences of their education choices. As explained in the NPRM and elaborated below, the framework will improve on the information currently available to students by generating program-level information on cost of attendance and available aid for all types of students and by ensuring the information is delivered to students. The acknowledgment requirements ensure this information is viewed before students enroll when performance measures indicate a heightened risk of adverse borrowing outcomes for students.

With respect to GE programs, the Department remains concerned about the same problems that motivated our 2011 and 2014 Prior Rules. These included the growth in student loan debt generally, and especially increased borrowing at private for-profit colleges, increasingly high rates of default, higher costs, and lawsuits and investigations into the deceptive practices of many institutions.

Overall, the amount of outstanding student loan debt is even higher than it was at the time of the 2014 Prior Rule. Then we cited a total portfolio of $1,096.5 billion. It is now 49 percent larger—at $1,634 billion outstanding. The number of individuals with outstanding student loans is also 3.5 million higher.

U.S. Department of Education, Federal Student Aid (2023). Federal Student Aid Portfolio Summary (data set). National Student Loan Data System (NSLDS) ( https://studentaid.gov/sites/default/files/fsawg/datacenter/library/PortfolioSummary.xls ).

The 2011 and 2014 rules were issued during a time of growth at private for-profit colleges when the Department was concerned about the effects of such growth. While the sector is not currently growing at the rates it did at that time, its 12-month full-time-equivalent enrollment in 2020–21 was above its levels in 2017–18. During those years, enrollment in private for-profit colleges grew 5 percent even as public and private nonprofit institutions saw a 7 percent decline. Similarly, the share of title IV, HEA funds going to private for-profit colleges in 2020–21 was at the same level as in 2016–17.

See U.S. Department of Education, National Center for Education Statistics (2021). Table 8. Twelve-month full-time-equivalent enrollment at Title IV institutions, by student level, level and control of institution: United States, 2020–21. IPEDS Data Explorer ( https://nces.ed.gov/ipeds/Search?query=&query2=&resultType=all&page=1&sortBy=date_desc&overlayTableId=32468 ). U.S. Department of Education, National Center for Education Statistics (2018). Table 8. Twelve-month full-time-equivalent enrollment at Title IV institutions, by student level, level and control of institution: United States, 2017–18. IPEDS Data Explorer ( https://nces.ed.gov/ipeds/Search?query=&query2=&resultType=all&page=1&sortBy=date_desc&overlayTableId=25212 ).

U.S. Department of Education, Federal Student Aid (2023). 2022–2023 Grant and Loan Volume by School Type (data set). FSA Data Center ( https://studentaid.gov/sites/default/files/fsawg/datacenter/library/SummarybySchoolType.xls ).

Loan usage at private for-profit colleges also remains high. In the 2014 Prior Rule we noted concerns that the borrowing rate in 2011–12 among less-than-two-year institutions was 60 percent at private for-profit institutions versus 10 percent at public institutions. Data from 2019–20 show that 63 percent of students in less-than-two-year private for-profit institutions took out loans compared to 18 percent of those at public colleges, though the estimate for public colleges has a high standard error. In fact, the borrowing rate at two-year and less-than-two-year private for-profit colleges in 2019–20 was higher than in 2015–2016. And among two-year for-profit colleges it even exceeds the rates in 2011–12.

U.S. Department of Education (2014). Program Integrity: Gainful Employment. 79 FR 65033, October 31, 2014. Federal Register , 34 CFR parts 600 and 668 (Docket ID ED–2014–OPE–0039) ( https://www.federalregister.gov/d/2014-25594/p-2324 ).

Cameron, M., Johnson, R., Lacy, T.A., Wu, J., Siegel, P., Holley, J., Wine, J. & RTI International (2023). Table A–1. Selected financial aid receipt: Percentage of undergraduates receiving selected types of financial aid. In 2019–20 National Postsecondary Student Aid Study (NPSAS:20) First Look at Student Financial Aid Estimates for 2019–20 (NCES 2023–466). U.S. Department of Education ( https://nces.ed.gov/pubs2023/2023466.pdf ).

Compare the previous citation with Radwin, D., Wine, J., Siegel, P., Bryan, M. & RTI International (2013). Table 1. Percentage of undergraduates receiving selected types of financial aid, by type of institution, attendance pattern, dependency status, and income level: 2011–12. In 2011–12 National Postsecondary Student Aid Study (NPSAS:12) Student Financial Aid Estimates for 2011–12 (NCES 2013–165). U.S. Department of Education ( https://nces.ed.gov/pubs2013/2013165.pdf ). Radwin, D., Conzelmann, J. G., Nunnery, A., Lacy, T. A., Wu, J., Lew, S., Wine, J., Siegel, P. & RTI International (2018). Table 1. Percentage of undergraduates receiving selected types of financial aid, by control and level of institution, attendance pattern, dependency status, and income level: 2015–16. In 2015–16 National Postsecondary Student Aid Study (NPSAS:16) Student Financial Aid Estimates for 2015–16 First Look (NCES 2018466). National Center for Education Statistics ( https://nces.ed.gov/pubs2018/2018466.pdf ).

Issues with default rates also did not abate between 2014 and the national pause on student loan payments and interest in 2020 due to the COVID–19 national emergency. From 2015 to 2019 there were still more than 1 million new Direct Loan defaults a year. And the number of new Direct Loan defaults in the 2019 fiscal year was higher than in 2015. The official cohort default rates did see slight declines from fiscal year 2012 to fiscal year 2017 (the last cohort before the pause would affect results). But the decline in the overall rate was nearly double what it was at private for-profit colleges (a reduction of 2.1 percentage points versus 1.1 percentage points). And this is despite the closure of large for-profit colleges with poor track records, such as ITT Technical Institute and Corinthian Colleges.

U.S. Department of Education (Sept. 14, 2023). Direct Loans Entering Default. National Student Loan Data System (NSLDS) ( https://studentaid.gov/sites/default/files/DLEnteringDefaults.xls ).

Federal Student Aid Office, U.S. Department of Education (2016). National Student Loan Default Rates from its 2016 Official FY2013 Cohort Default Rate Briefing ( https://fsapartners.ed.gov/sites/default/files/attachments/eannouncements/2016OfficialFY2013CDRBriefing.pdf ). Federal Student Aid Office, U.S. Department of Education (2020). FY 2017 Official National Cohort Default Rates with Prior Year Comparison and Total Dollars as of the Date of Default and Repayment. In 2020 Cohort Default Rate National Briefing for FY2017 ( https://fsapartners.ed.gov/sites/default/files/attachments/2020-09/093020CDRNationalBriefingFY17Attach_0.pdf ).

Regarding lawsuits and investigations, the Department notes that these actions still continue today. Just last year the California Department of Justice won its case against Ashford University, and the Secretary has concluded substantial misrepresentations brought to light in that case continued until 2020. The U.S. Department of Justice has also continued to settle cases involving for-profit colleges. Other State attorneys general or city officials have also reached settlements with for-profit institutions over allegations about the same type of behavior identified by the Department in the 2014 rule, though these settlements did not come with an admission of wrongdoing.

California Department of Justice, Office of the Attorney General (Mar. 7, 2022). Attorney General Bonta: Ashford University Must Pay $22 Million in Penalties for Defrauding California Students ( https://oag.ca.gov/news/press-releases/attorney-general-bonta-ashford-university-must-pay-22-million-penalties ). U.S. Department of Education (Aug. 30, 2023). Biden-Harris Administration Approves $72 Million in Borrower Defense Discharges for over 2,300 Borrowers Who Attended Ashford University ( h ttp s ://www.ed.gov/news/press-releases/biden-harris-administration-approves-72-million-borrower-defense-discharges-over-2300-borrowers-who-attended-ashford-university ).

U.S. Attorney's Office, Middle District of Louisiana (June 23, 2017). School Owner and CEO Convicted of Federal Financial Aid Fraud Offenses and Money Laundering. U.S. Department of Justice ( https://www.justice.gov/usao-mdla/pr/school-owner-and-ceo-convicted-federal-financial-aid-fraud-offenses-and-money ). U.S. Attorney's Office, District of Connecticut (May 27, 2022). School and Owner Pay Over $1 Million to Resolve Allegations of Attempts to Improperly Influence the School's Student Loan Default Rate. U.S. Department of Justice ( https://www.justice.gov/usao-ct/pr/school-and-owner-pay-over-1-million-resolve-allegations-attempts-improperly-influence ).

Office of Attorney General Maura Healey (Aug. 8, 2018). American Military University Pays $270,000 for Alleged Failure to Disclose Job Prospects, High-Pressure Enrollment Tactics. Mass.gov ( https://www.mass.gov/news/american-military-university-pays-270000-for-alleged-failure-to-disclose-job-prospects-high-pressure-enrollment-tactics ). Department of Consumer and Worker Protection (Oct. 3, 2022). Department of Consumer and Worker Protection Settles With ASA College for Deceptive Advertising Targeting Immigrants and Other Vulnerable New Yorkers. NYC.gov ( https://www.nyc.gov/site/dca/media/pr100322-DCWP-Settles-With-ASA-College-for-Deceptive-Advertising.page ).

According to the Department's data and analyses, which are presented in the RIA of this final rule, GE programs account for a disproportionate share of students who complete programs with very low earnings and unmanageable debt. The expansion of IDR plans for Federal student loans, which has risen since the 2014 Prior Rule was released, partially shields borrowers from these risks. But such after-the-fact protections do not address underlying program failures to prepare students for gainful employment in the first place, and they shift the risks of nonpayment of loans from students with poor labor market outcomes and high debt to taxpayers. The reasons for the departure from the 2019 rescission are discussed in detail in the NPRM of the rule, with detail on particular points discussed further below.

See Tables 4.4, 4.5, 4.8, and 4.9 below.

In light of the HEA differentiation between career training (GE) programs and other eligible programs, through statutory language that defines title IV-eligible career training programs as those that prepare students for gainful employment, the Department has different responsibilities with respect to GE programs and different tools available in administering the title IV, HEA programs. For these programs, where labor market outcomes are central to their mission, the Department establishes a clear and administrable GE program accountability framework based on the EP and D/E measures, which the Department will use to evaluate what it means to prepare students for gainful employment in a recognized occupation and whether a GE program is eligible to participate in title IV, HEA.

While the financial value transparency framework and the GE program accountability framework are both designed to improve student financial outcomes, they differ in scope and approach, derive from the Department's exercise of different regulatory authorities. The two frameworks are intended to function independently, and their respective components are intended to be severable. Elsewhere we discuss the complementary nature of the two frameworks as well as their severability, and we address the Department's authority to take action in the next section. In subsequent sections we explain our reasoning and the evidence relevant to the positions that we adopt, and we identify a number of constructive public comments that, upon reflection, have convinced the Department to modify certain proposals made in the NPRM. But our core conclusions remain the same. Considering the promise of postsecondary education and training in its many forms alongside the Federal Government's investment therein and all applicable law, the Department adopts this final rule.

See the NPRM, 88 FR 32300, 32341 (May 19, 2023), for a detailed discussion of how these regulations are intended to be severable.

Authority for This Regulatory Action

To address the need for regulatory action, the Department amends §§ 600.10, 600.21, 668.2, 668.13, 668.43, and 668.91, and establishes subparts Q and S of part 668.

The Department's authority to establish the financial value transparency framework and the GE program accountability framework is derived primarily from: first, the Secretary's generally applicable rulemaking authority, which includes but is not limited to provisions regarding data collection and dissemination; second, authorizations and directives within title IV of the HEA regarding the collection and dissemination of potentially useful information about higher education programs, as well as provisions regarding institutional eligibility to benefit from title IV; and third, the further provisions within title IV, HEA that address the eligibility of GE programs.

As for general and crosscutting rulemaking authority, section 410 of the General Education Provisions Act (GEPA) grants the Secretary authority to make, promulgate, issue, rescind, and amend rules and regulations governing the manner of operation of, and governing the applicable programs administered by, the Department. This authority includes the power to promulgate regulations relating to programs that we administer, such as the title IV, HEA programs that provide Federal loans, grants, and other aid to students. Moreover, section 414 of the Department of Education Organization Act (DEOA) authorizes the Secretary to prescribe those rules and regulations that the Secretary determines necessary or appropriate to administer and manage the functions of the Secretary or the Department.

Section 431 of GEPA grants the Secretary additional authority to require institutions to make data available to the public about the performance of their programs and about students enrolled in those programs. That section directs the Secretary to collect data and information on applicable programs for the purpose of obtaining objective measurements of the effectiveness of such programs in achieving their intended purposes, and also to inform the public about federally supported education programs. This provision lends additional support to the reporting requirements and the Department's program information website, which will enable the Department to collect data and information for the purpose of developing objective measures of program performance, not only for the Department's use in evaluating programs but also to inform students, their families, institutions, and others about those federally supported programs.

20 U.S.C. 1231a(2)–(3). “Applicable program” means any program for which the Secretary or the Department has administrative responsibility as provided by law or by delegation of authority pursuant to law. 20 U.S.C. 1221(c)(1).

As for provisions within title IV, HEA, several of them address the effective delivery of information about postsecondary education programs. For example, section 131 of the Higher Education Act of 1965, as amended (HEA), provides that the Department's websites should include information regarding higher education programs, including college planning and student financial aid, the cost of higher education in general, and the cost of attendance with respect to all institutions of higher education participating in title IV, HEA programs. Those authorizations and directives expand on more traditional methods of delivering important information to students, prospective students, and others, including within or alongside application forms or promissory notes for which acknowledgments by signatories are typical and longstanding. Educational institutions have been distributing information to students at the direction of the Department and in accord with the applicable statutes for decades.

See, for example, 20 U.S.C. 1015(e).

20 U.S.C. 1015(a)(3), (b), (c)(5), (e), (h). See also section 111 of the Higher Education Opportunity Act, 20 U.S.C. 1015a, which authorizes the College Navigator website and successor websites.

See, for example, 20 U.S.C. 1082(m), regarding common application forms and promissory notes or master promissory notes. See also 34 CFR 685.304(a)(3), regarding Direct Loan counseling and acknowledgments.

A compilation of the current and previous editions of the Federal Student Aid Handbook, which includes detailed discussion of consumer information and school reporting and notification requirements, is posted at https://fsapartners.ed.gov/knowledge-center/fsa-handbook.

The GE program accountability framework also is supported by the Department's statutory responsibilities to observe eligibility limits in the HEA. Section 498 of the HEA requires institutions to establish eligibility to provide title IV, HEA funds to their students. Eligible institutions must also meet program eligibility requirements for students in those programs to receive title IV, HEA assistance.

One type of program for which certain categories of institutions must establish program-level eligibility is, in the words of section 101 and section 102 of the HEA, a “program of training to prepare students for gainful employment in a recognized occupation.” Section 481 of the HEA articulates this same requirement by defining, in part, an “eligible program” as a “program of training to prepare students for gainful employment in a recognized profession.” The HEA does not more specifically define “program of training to prepare,” “gainful employment,” “recognized occupation,” or “recognized profession” for purposes of determining the eligibility of GE programs for participation in title IV, HEA. The Secretary and the Department have a legal duty to interpret, implement, and apply those terms in order to observe the statutory eligibility limits in the HEA. In the section-by-section discussion in the NPRM, we explained further the Department's interpretation of the GE statutory provisions and how those provisions should be implemented and applied.

The statutory eligibility criteria for GE programs are one part of the foundation of authority for warnings from institutions to prospective and enrolled GE students. In the GE context, the Department has not only a statutory basis for pursuing the effective dissemination of information to students about a range of GE program attributes and performance metrics, but also the authority to use certain metrics to determine that an institution's program is not eligible to benefit, as a GE program, from title IV, HEA assistance. When an institution's program is at risk of losing eligibility based on a given metric, the Department may then require the institution that operates the at-risk program to alert prospective and enrolled students that they may not be able to receive title IV, HEA assistance for enrollment in the program in future years. Without a direct communication from the institution to prospective and enrolled students, the students may lack information critical to their program enrollment decisions contrary to the text, purpose, and traditional understandings of the relevant statutes as described above.

See Ass'n of Priv. Sector Colleges & Universities v. Duncan, 110 F. Supp. 3d 176, 198–200 (D.D.C. 2015) (recognizing statutory authority to require institutions to disclose certain information about GE programs to prospective and enrolled GE students), aff'd, 640 F. App'x 5, 6 (D.C. Cir. 2016) (per curiam) (unpublished) (indicating that the plaintiff's challenge to the GE disclosure provisions was abandoned on appeal).

The above authorities collectively empower the Secretary to promulgate regulations to (1) require institutions to report information about their programs to the Secretary; (2) require prospective students, with respect to certificate programs and graduate degree programs that do not meet certain financial value measures established by the Department, to acknowledge having viewed the information on the Department's program information website before entering into an enrollment agreement; (3) establish measures to determine the eligibility of GE programs for participation in title IV, HEA; and (4) require institutions to provide warnings to students and prospective students with respect to GE programs that may lose their title IV, HEA eligibility in the next year, and require the students to acknowledge having viewed the warning through the Department's program information website. We provide additional detail on these provisions in the discussions below.

Summary of the Major Provisions of This Regulatory Action

As discussed under “Purpose of This Regulatory Action,” these regulations establish a financial value transparency framework and a GE program accountability framework.

Through this regulatory action, the Department establishes the following:

(1) In subpart Q, a financial value transparency framework that will increase the quality and availability of information provided directly to students about the costs, sources of financial aid, and outcomes of students enrolled in all title IV, HEA eligible programs. As part of this framework, we establish a measure of the earnings premium that typical program graduates experience relative to the earnings of typical high school graduates. As part of this framework, we also establish a mechanism for measuring the debt service burden for typical graduates. Further, we establish performance benchmarks for each measure, denoting a threshold level of performance below which students' enrollment in the program may have adverse financial consequences. This information will be made available via a program information website maintained by the Department, and, for certificate programs and graduate degree programs with poor outcomes under the debt-burden measures, prospective students will be required to acknowledge viewing this information before entering into enrollment agreements with an institution. Further, through the Department's program information website, we will provide the public, taxpayers, and the Government with relevant information which they can use to better safeguard the Federal investment in these programs. Finally, the financial value transparency framework will provide institutions with meaningful information that they can use to compare the performance of the programs to that of other institutions and improve student outcomes in these programs. For a detailed discussion of the financial transparency framework, see the “Financial Value Transparency Framework” section of the NPRM.

88 FR 32300, 32325 (May 19, 2023).

(2) In subpart S, we create an accountability framework for career training programs (also referred to as gainful employment programs or GE programs) that uses the same earnings premium and debt-burden measures as subpart Q to determine whether a GE program remains eligible for participation in title IV, HEA. The GE eligibility criteria are used to identify those programs that prepare students for gainful employment in a recognized occupation, as that language is used in the HEA, and they tie program eligibility to whether GE programs provide education and training to their title IV, HEA students that lead to earnings beyond those of high school graduates and sufficient to allow students to repay their student loans. GE programs that fail the same measure in any two out of three consecutive years for which the measure is calculated will lose eligibility for participation in title IV, HEA programs. Relatedly, for GE programs that may lose their title IV, HEA eligibility in the next year, institutions must provide warnings to those programs' enrolled and prospective students, and those students must acknowledge having viewed the warning through the Department's program information website before certain specified events occur, including the signing of an enrollment agreement or the disbursement of title IV funds. For a detailed discussion of the GE program accountability framework, see the “Gainful Employment Criteria” section of the NPRM.

88 FR 32300, 32343 (May 19, 2023).

Specifically, the final regulations adopt the following changes.

  • Amend § 600.10 to require an institution seeking to establish the eligibility of a GE program to add the program to its application.
  • Amend § 600.21 to require an institution to notify the Secretary within 10 days of any update to information included in the GE program's certification.

• Amend § 668.2 to define certain terminology used in subparts Q and S, including “annual debt-to-earnings rate,” “classification of instructional programs (CIP) code,” “cohort period,” “credential level,” “debt-to-earnings rates (D/E rates),” “discretionary debt-to-earnings rates,” “earnings premium,” “earnings threshold,” “eligible non-GE program,” “Federal agency with earnings data,” “gainful employment program (GE program),” “institutional grants and scholarships,” “length of the program,” “poverty guideline,” “prospective student,” “student,” and “substantially similar program.”

  • Amend § 668.43 to establish a Department website with program-level financial information, and to require institutions to inform a prospective student how to access that website before the student enrolls, registers, or makes a financial commitment to the institution.
  • Amend § 668.91 to provide that a hearing official must terminate the eligibility of a GE program that fails to meet the GE program accountability metrics established in this rule, unless the hearing official concludes that the Secretary erred in the calculation.
  • Add § 668.401 to identify the scope and purpose of the newly established financial value transparency regulations in subpart Q.
  • Add § 668.402 to provide a framework for the Secretary to determine whether a program leads to high debt burden or low earnings, including establishing annual and discretionary D/E rate metrics and associated outcomes, and establishing an earnings premium metric and associated outcomes.
  • Add § 668.403 to establish a methodology to calculate annual and discretionary D/E rates, including parameters to determine annual loan payment, annual earnings, loan debt, and assessed charges, as well as to provide exclusions, and specify when D/E rates will not be calculated.
  • Add a new § 668.404 to establish a methodology to calculate a program's earnings premium measure, including parameters to determine median annual earnings, as well as to provide exclusions, and specify when the earnings threshold measure will not be calculated.
  • Add § 668.405 to establish a process by which the Secretary will obtain administrative and earnings data to issue D/E rates and the earnings premium measure.
  • Add § 668.406 to require the Secretary to notify institutions of their financial value transparency metrics and outcomes.
  • Add § 668.407 to require current and prospective students to acknowledge having seen the information on the website maintained by the Secretary if a program has failed the D/E rates measure, to specify the content and delivery parameters of such acknowledgments, and to require that students must provide the acknowledgment before entering an enrollment agreement with an institution.
  • Add § 668.408 to establish institutional reporting requirements for students who enroll in, complete, or withdraw from a program and to define the timeframe for institutions to report this information.
  • Add § 668.409 to establish severability protections ensuring that if any provision in subpart Q is held invalid, the remaining provisions of that subpart and other subparts would continue to apply.
  • Add § 668.601 to identify the scope and purpose of newly established GE regulations under subpart S.
  • Add § 668.602 to establish criteria for the Secretary to determine whether a GE program prepares students for gainful employment in a recognized occupation.
  • Add § 668.603 to define the conditions under which a failing GE program would lose title IV, HEA eligibility, to provide the opportunity for an institution to appeal a loss of eligibility solely on the basis of a miscalculated D/E rate or earnings premium, and to establish a period of ineligibility for failing GE programs that lose eligibility or voluntarily discontinue eligibility.
  • Add § 668.604 to require institutions to provide the Department with transitional certifications, as well as to certify, when seeking recertification or the approval of a new or modified GE program, that each eligible GE program offered by the institution is included in the institution's recognized accreditation or, if the institution is a public postsecondary vocational institution, that the program is approved by a recognized State agency.
  • Add § 668.605 to require warnings to current and prospective students if a GE program is at risk of a loss of title IV, HEA eligibility, to specify the content and delivery requirements for such warnings, and to provide that students must acknowledge having seen the warning before the institution may disburse any title IV, HEA funds.
  • Add § 668.606 to establish severability protections ensuring that if any GE provision under subpart S is held invalid, the remaining provisions of that subpart and of other subparts would continue to apply.

Summary of the Costs and Benefits

The Department estimates that the final regulations will generate benefits to students, postsecondary institutions, and the Federal Government that exceed the costs. The Department also estimates substantial transfers, primarily in the form of title IV, HEA aid shifting between students, postsecondary institutions, and the Federal Government, generating a net budget savings for the Federal Government. Net benefits are created primarily by shifting students from low-financial-value to high-financial-value programs or, in some cases, away from low-financial-value postsecondary programs to non-enrollment. These shifts would be due to improved and standardized market information about all postsecondary programs that would facilitate better decision making by current and prospective students and their families; the public, taxpayers, and the Government; and institutions. Furthermore, the GE program accountability framework will improve the quality of student options by directly eliminating the ability of low-financial-value GE programs to receive title IV, HEA funds. This enrollment shift and improvement in program quality will result in higher earnings for students, which will generate additional tax revenue for Federal, State, and local governments. Students will also benefit from lower accumulated debt and lower risk of default.

The primary costs of the final regulations related to the financial value transparency and GE accountability requirements are the additional reporting required by institutions and the time for students to acknowledge having seen the program information website. The final regulations may also result in some students at failing programs deciding to end their educational pursuits, even if they would benefit from re-enrollment. See “Discussion of Costs, Benefits, and Transfers” in the RIA in this document for a more complete discussion of the costs and benefits of the regulations.

The NPRM and Public Comment

The NPRM included proposed regulations on five topics—Financial Value Transparency and Gainful Employment, Financial Responsibility, Administrative Capability, Certification Procedures, and Ability to Benefit. These final regulations contain only provisions on Financial Value Transparency and GE. We will publish another final rule with the remaining four topics at a later date. The later rule will include summaries and responses to comments that made some references to the GE program accountability framework but are primarily concerned with the financial responsibility, administrative capability, or certification procedures sections.

In response to our invitation in the NPRM, 7,583 parties submitted comments on the proposed regulations. While the majority of respondents commented on the provisions we address in this final rule, the number includes all who commented on any of the five topics addressed in the NPRM.

In the NPRM, we discussed the background of the regulations, the relevant data available, and the key regulatory changes that the Department was proposing, including the changes from the 2019 Prior Rule currently in effect, and the differences between the NPRM's proposal and the now-rescinded 2014 Prior Rule. Terms used but not defined in this document have the meanings set forth in the NPRM. The final regulations contain a number of changes from the NPRM. We fully explain the changes in the Analysis of Comments and Changes section of the preamble that follows.

88 FR 32300, 32306 (May 19, 2023).

88 FR 32300, 32392 (May 19, 2023).

88 FR 32300, 32317 (May 19, 2023).

We discuss substantive issues under the sections of the proposed regulations to which they pertain. Generally, we do not address technical or other minor changes or recommendations that are out of the scope of this regulatory action or that would require statutory changes.

Analysis of Public Comments and Changes: Analysis of the comments and of any changes in the regulations since publication of the NPRM follows.

General

Rulemaking Process

Comments: Several commenters asked the Department to extend the public comment period an additional 30 days. These commenters contended that, given the length of the NPRM, they needed more time to review it if they were to provide informed comment. The commenters also observed that Executive Orders 12866 and 13563 cite 60 days as the recommended length for public comment.

Discussion: The Department believes the public comment period was sufficient for commenters to review and provide meaningful feedback on the NPRM. We note that the public comment period for the 2019 Prior Rule also was 30 days. In response to the NPRM we received comments from more than 7,500 individuals and entities, including many detailed and lengthy comments. Those comments have helped the Department identify many areas for improvements and clarification that result in an improved final rule. Moreover, the negotiated rulemaking process, including multiple negotiating sessions, provided a significant additional opportunity for public engagement and feedback that exceeds what is typically available in notice-and-comment rulemaking outside the HEA's statutory framework. The Department began the rulemaking process by inviting public input through a series of public hearings in June 2021. We received more than 5,300 public comments as part of the public hearing process. After the hearings, the Department sought non-Federal negotiators for the negotiated rulemaking committee who represented constituencies that would be affected by our rules. As part of these non-Federal negotiators' work on the rulemaking committee, the Department asked that they reach out to the broader constituencies for feedback during the negotiation process. During each of the three negotiated rulemaking sessions, we provided opportunities for the public to comment, including in response to draft regulatory text, which was available prior to the second and third sessions. The Department and the non-Federal negotiators considered those comments to inform further discussion at the negotiating sessions, and we used the information when preparing our proposed rule. The Executive orders recommend an appropriate period for public comment, but they do not require more than 30 days, nor do their recommendations account for the HEA's negotiated rulemaking requirements, which the Department followed here as described.

See 83 FR 40167, 40168 (Aug. 14, 2018).

Changes: None.

Comments: Several commenters asserted that only two days of the negotiated rulemaking process were specifically devoted to a discussion of the proposed GE regulations, which they contended was not adequate time.

Discussion: The Department disagrees. There were multiple opportunities throughout the rulemaking process for people to submit comments on the proposed GE regulations. We held public hearings to obtain initial public input. We also included daily public comment periods during three weeks of negotiation sessions and devoted two days to discuss the topic exclusively. Non-Federal negotiators solicited feedback from their constituents on our proposals during and between negotiation sessions. Finally, we provided the public with a 30-day period to comment on the NPRM.

Changes: None.

Comments: A few commenters believed that the Department is rushing the implementation of the GE regulations. These commenters argued that programs need more time to comply with these new rules.

Discussion: The Department disagrees with the commenters who believe that there is not adequate time to comply with the new GE regulations. The Department gave notice of its intent to regulate in the Spring 2021 Unified Agenda. We conducted hearings to obtain public input and held negotiated rulemaking sessions in the Spring of 2022 where the Department's distributed plans for the rule and provided detailed data on the projected outcomes of GE programs. Accordingly, we believe there has been, and will continue to be prior to the effective date, ample time for institutions to take the necessary steps to be able to meet their reporting obligations under the final rule. In addition, we note that the lengthy period beginning with the Spring 2021 Unified Agenda, taken together with the transition period built into the GE program accountability framework, will further allow institutions to take steps to improve their programs' outcomes after the regulation takes effect. Adding more time would further delay the effective date of the GE regulations and would unnecessarily increase the likelihood that students would continue to invest their time and money in postsecondary programs that do not meet the minimum standards of these regulations. The Department believes that we must implement these rules as quickly as possible to protect students and taxpayers, and that there is enough time for programs to comply.

Changes: None.

Statutory Authority; Other General Legal Support

Comments: Some commenters acknowledged that the Department has authority to implement the financial value transparency framework.

Discussion: We agree with these commenters that the Department has well established authority to implement the financial value transparency framework. As discussed in more detail under “Authority for this Regulatory Action” in this document, this framework is supported in principal part by the Secretary's generally applicable rulemaking authority, which includes provisions regarding data collection and dissemination, and which applies in part to title IV of the HEA, as well as authorizations and directives within title IV of the HEA regarding the collection and dissemination of potentially useful information about higher education programs.

Comments: Several commenters asserted that the proposed GE program accountability framework exceeds the Department's statutory authority. Some commenters argued that the description of GE programs in the HEA—that those programs must prepare students for gainful employment in recognized occupations—does not provide clear congressional intent to support the eligibility requirements in the proposed regulations. Some of these commenters contended that the HEA does not require the Department to establish a mathematical framework to determine when a program adequately prepares students for gainful employment in a recognized occupation, nor provide any explicit congressional authorization to do so. Similarly, some commenters asserted that the GE provisions in the HEA are too vague and ambiguous to support an eligibility framework based on student outcomes. Some commenters said the litigation addressing prior GE rules never identified clear congressional authorization for the Department to establish an eligibility framework for GE programs. Commenters also asserted that the variations in the prior and proposed GE regulations constitute further proof that there is no clear congressional authorization tied to the proposed GE regulations. In addition, some commenters viewed the proposed GE program eligibility framework in its use of two outcome measures as a significant expansion of the prior GE regulations and argued that such a framework could only be supported with clear authorization from Congress.

Discussion: As discussed in detail in the NPRM and summarized in this document under “Authority for this Regulatory Action,” the GE program accountability framework is supported by the Department's statutory responsibilities to enforce eligibility limits in title IV of the HEA as well as the Department's generally applicable rulemaking authority.

88 FR 32300, 32321–22 (May 19, 2023).

As for the latter, Federal statutes grant the Secretary general crosscutting rulemaking authority that includes and extends beyond title IV of the HEA. Section 410 of the General Education Provisions Act (GEPA) provides the Secretary with authority to make, promulgate, issue, rescind, and amend rules and regulations governing the manner of operations of, and governing the applicable programs administered by, the Department. This authority includes the power to promulgate regulations relating to programs that we administer, such as the title IV, HEA programs that provide Federal loans, grants, and other aid to students. Furthermore, section 414 of the DEOA authorizes the Secretary to prescribe such rules and regulations as the Secretary determines necessary or appropriate to administer and manage the functions of the Secretary or the Department. These provisions, together with the provisions in the HEA regarding GE programs, authorize the Department to promulgate regulations that establish measures to determine the eligibility of GE programs for title IV, HEA program funds; require institutions to report information about GE programs to the Secretary; require institutions to provide information about GE programs to students, prospective students, and others; and establish certification requirements regarding an institution's GE programs.

As for title IV of the HEA and its eligibility requirements, institutions must meet institution-level as well as program-level eligibility requirements for students in those programs to receive title IV assistance in the form of loans or grants. HEA sections 101 and 102 state that one type of program for which certain categories of institutions must establish program-level eligibility is a “program of training to prepare students for gainful employment in a recognized occupation.” HEA section 481 articulates this same requirement by defining, in part, an “eligible program” as a “program of training to prepare students for gainful employment in a recognized profession.”

The Department has increased its focus on these eligibility requirements over time as key circumstances have changed. College tuition levels have continued to rise relative to inflation, and student borrowing levels have reached very high levels. The earnings of college graduates have not risen apace, however, and earnings outcomes are not tightly correlated with borrowing levels. Moreover, cases of institutions using deceptive recruiting and advertising practices to lure students into postsecondary programs with little return on investment remain too common. All of these factors combine to strand many graduates with unaffordable education debt and little enhancement to their earnings—too often leaving them worse off financially than if they had not pursued postsecondary education at all. While the financial returns to college remain high overall for the average student, in recent years these trends have contributed to increased skepticism about the value of going to college —threatening one of the key pathways to upward mobility in the United States.

Several surveys have documented declines in the share of individuals who believe college is worth the cost. For example, see Education Expectations: Views on the Value of College and Likelihood to Enroll (June 15, 2022). Strada ( https://stradaeducation.org/report/pv-release-june-15-2022/ ). Klebs, Shelbe, Fishman, Rachel, Nguyen, Sophie & Hiler, Tamara (2021). One Year Later: COVID–19s Impact on Current and Future College Students. Third Way ( https://www.thirdway.org/memo/one-year-later-covid-19s-impact-on-current-and-future-college-students ). See also Board of Governors of the Fed. Reserve Sys. (May 2022). Economic Well-Being of U.S. Households in 2021 ( https://www.federalreserve.gov/publications/files/2021-report-economic-well-being-us-households-202205.pdf ).

We recognize that these forces are an issue across sectors. However, by defining GE programs as programs that prepare students for gainful employment, Congress indicated that the value of adding such programs to the Federal student loan program and to title IV of the HEA more broadly lies in their financial outcomes. Yet, despite that statutory focus, GE programs account for a disproportionate share of students who complete programs with very low earnings and unmanageable debt. An essentially transparency-only approach to GE programs, which is reflected in the 2019 Prior Rule, has not substantially improved the most troubling trends. To address both the Department's obligation to oversee that the statutory eligibility requirements are met and to address the specific need for regulatory action within the sector, the GE program accountability framework specifies what it means to prepare students for gainful employment in a recognized occupation. The framework does so by establishing clear and administrable measures that are tied to student financial outcomes and that the Department will use to evaluate whether a GE program is eligible for title IV, HEA program funds. One measure focuses on manageable debt (the D/E rates measure), the other on enhanced earnings (the EP measure). We believe the D/E and EP measures, singly and taken together, will help promote the goal of career programs actually providing financial value to their graduates—consistent with the statutory definition of GE programs and in service of the specific need for regulatory action.

For a detailed discussion of how the D/E rates measure and the EP measure assess whether a program is preparing students for gainful employment in a recognized occupation, see the Gainful Employment Criteria section in the NPRM, 88 FR 32300, 32343 (May 19, 2023).

The GE accountability rules effectuate core statutory provisions in practical and administrable ways. The definitions of “gainful employment” programs are central to the statutory scheme regarding GE programs, and those provisions establish limits on the programs that may receive taxpayer support through title IV, HEA loans and grants to students in those programs. The measures adopted in the GE program eligibility framework are designed to ensure eligible programs leave students with affordable debt and enhanced earnings, consistent with the ordinary meaning of the operative words in the statute. It is not only reasonable but also in accord with all indications of Congress's intent to conclude that a program does not prepare students for gainful employment in a recognized occupation if typical program graduates are left with unaffordable debt, or if they earn no more than comparable high school graduates. Students in such programs receive no financial gain, and may even experience financial loss, as a result of attending their career training programs. Those results indicate failure, not success, as a title IV, HEA eligible GE program. To be sure, as shown Tables 4.8 and 4.9 in the RIA, the Department estimates that most of the existing GE programs serving the majority of GE students will not fail these metrics, let alone be ineligible for title IV, HEA participation by failing in two of three consecutive years for which results are issued. In any event, the programs that may lose title IV, HEA eligibility under these rules are the programs that perform especially poorly for students and, consequentially, taxpayers.

Some commenters criticized the Department's position in favor of performance measures for GE programs as focusing overly much on the two words, “gainful employment.” In our view, that criticism understates the depth of analysis and breadth of considerations that support the Department's position—including our attention to the GE provisions as a whole as well as the structure of the Higher Education Act more broadly. This criticism also undervalues the enacted text, however many or few words are relevant to the issue of GE performance measures. We are unpersuaded by arguments that appear to place little value, and consequently no serious limits, on the terms of the gainful employment provisions in the statute.

Moreover, in past litigation involving affordable debt metrics, courts have accepted that reasonable performance measures may be used to evaluate the eligibility of GE programs for title IV, HEA participation. Those courts based those decisions on the text, structure, and purposes of the relevant statutory provisions. Thus, in reviewing previous GE rules, courts have examined the GE provisions of the HEA and explained, for example, that “train” and “prepare” are terms that “suggest elevation to something more than just any paying job. They suggest jobs that students would less likely be able to obtain without that training and preparation.” Courts have further concluded that “it is reasonable to consider students' success in the job market as an indication of whether those students were, in fact, adequately prepared,” and that “examining [GE] programs' outputs in terms of earnings and debts” is consistent with the HEA. Accordingly, the basic question of whether the HEA authorizes nonarbitrary GE performance measures has been resolved repeatedly in the Department's favor. There are, of course, issues of detail to settle in formulating particular outcome measures that are clear, workable, and suited to their purposes. Indeed, questions of how exactly to specify the GE performance measures involve complex assessments of how best to evaluate whether programs prepare students for gainful employment, which the Department is statutorily authorized and well-positioned to resolve given the Department's experience, knowledge, and expertise. The Department administers the relevant statutes, and it has used the negotiated rulemaking process to inform its views and gather and consider a broad range of perspectives before adopting these final rules. Importantly, the Department now has better data and data analysis than ever previously available.

Ass'n of Priv. Sector Colleges & Universities v. Duncan, 640 F. App'x 5, 8 (D.C. Cir. 2016) (per curiam).

Ass'n of Proprietary Colleges v. Duncan, 107 F. Supp. 3d 332, 362 (S.D.N.Y. 2015) (internal quotation marks omitted) (quoting Ass'n of Priv. Colleges & Universities v. Duncan, 870 F. Supp. 2d 133, 147–48 (D.D.C. 2012)).

Ass'n of Priv. Sector Colleges & Universities v. Duncan, 110 F. Supp. 3d 176, 187–88 (D.D.C. 2015) (emphasis omitted), aff'd, 640 F. App'x 5 (D.C. Cir. 2016) (per curiam); id. at 187 n.4 (explaining by way of analogy that there is “no irreconcilable conflict” between a concentration on “inputs” such as pre-match training and “outputs” in terms of match performance).

See the RIA in this document for analyses of how the D/E rates metric and the earnings premium metric provide objective, data-driven assessments of whether GE programs are preparing their students for gainful employment in a recognized occupation or whether they are instead leaving their students with unmanageable debt or no better off than if they had not pursued a postsecondary credential. See also the discussion below of the earnings premium metric and reasons for its adoption, in light of recent developments and new evidence, in this final rule.

The foregoing points and discussion elsewhere in this document and the NPRM are sufficient to establish the Department's authority to adopt the GE program eligibility framework. If additional support were needed, statutory history and legislative history confirm that program performance, including performance related to enhanced earnings and affordable debt, has been a focus of the relevant statutory provisions from the beginning. Such program performance was addressed in legislative history of the National Vocational Student Loan Insurance Act (NVSLIA), Public Law 89–287 (1965)—which is the statute that first permitted students to obtain federally financed loans to enroll in vocational programs. Both the ability of students to repay loans and the benefits to students from training were identified as principal issues during the development of that legislation. Indeed, the Senate Report that accompanied the NVSLIA quoted extensively from testimony on behalf of the American Personnel and Guidance Association, which supported the legislation for the purpose of enabling students to ensure their financial security by “acquiring job skills which will allow them to enter and compete successfully in our increasingly complex occupational society,” while also emphasizing, based on an early study, that “sufficient numbers” of graduates of such programs “were working for sufficient wages to make the concept of student loans to be [repaid] following graduation a reasonable approach to take.”

See generally Ass'n of Priv. Colleges & Universities v. Duncan, 870 F. Supp. 2d 133, 138–41 (D.D.C. 2012) ( APCU) (reviewing statutory history and legislative history).

S. Rep. No. 89–758 (1965), reprinted in 1965 U.S.C.C.A.N. 3742, 3748–49 (quoting testimony of Professor Dr. Kenneth B. Hoyt); id. at 3749 (further quoting Hoyt's testimony as finding no reason to believe that making government funds available would be unjustified “in terms of benefits accruing to both these students and to society in general, nor that they would represent a poor financial risk”); id. at 3744 (explaining that the testimony “confirmed the committee's estimate of the need for such legislation”); APCU, 870 F. Supp. 2d at 139 (stating that both House and Senate subcommittees “placed considerable weight on Dr. Hoyt's testimony”).

The statutory framework has not changed in relevant part, and the taxpayer interest in safeguarding the use of Federal funds persists today. Under the loan insurance program enacted in the NVSLIA, the specific potential loss to taxpayers of concern was the need to pay default claims to banks and other lenders if the borrowers defaulted on the loans. After its passage, the NVSLIA was merged into the HEA which, in title IV, part B, has both a direct Federal loan insurance component and a Federal reinsurance component that require the Federal Government to reimburse State and private nonprofit loan guaranty agencies upon their payment of default claims. Under either HEA component, taxpayers and the Government assume the direct financial risk of default. Since the Health Care and Reconciliation Act of 2010, all Federal loans have been originated as Direct Loans from the Federal Government. As the originator and owner of Federal loans, the Federal Government (funded by taxpayers) bears the cost of any unpaid loans. Costs are generated by borrowers defaulting on their loans, but increasingly costs are also generated by borrowers electing to repay their loans on income driven repayment (IDR) plans. Under these plans, borrowers can pay a fixed share of the portion of their income exceeding a threshold level ( i.e., their discretionary income) for a preset period of time, and then have the remaining balance forgiven. When borrowers' debts are high relative to their income, they are more likely to not fully repay their loans. To avoid adverse repayment risks both from default or loan forgiveness via IDR plans, taxpayers have an interest in financing career training programs that leave students better off in terms of earnings, and with debt in reasonable proportion to their earnings. Participation in IDR plans has increased by approximately 50 percent since 2016 to about 9 million borrowers and is likely to increase more with the introduction of the new and more generous Saving on a Valuable Education (SAVE) IDR plan. Accordingly, the Department has a significant interest, on behalf of taxpayers, in ensuring the funds disbursed through title IV, HEA loans are invested responsibly, further supporting the use of performance measures to assess a program's eligibility to participate in the title IV, HEA programs as a GE program.

20 U.S.C. 1078(c) (Federal reinsurance for default claim payments); 20 U.S.C. 1080 (Federal insurance for default claims).

Public Law 111–152.

With regard to the earnings premium measure, we offer further discussion below. We note here that, to receive title IV funds, section 484 of the HEA generally requires that students already have a high school diploma or recognized equivalent. That requirement makes high-school-level achievement the presumptive starting point for title IV, HEA funds. The EP measure adopts that statutory starting point by comparing the earnings of typical program completers with those of comparable high school graduates. As with the debt-to-earnings measure, the earnings premium measure is consistent with the text, structure, and purposes of the statute.

We disagree with the commenters who contended that the differences between the 2014 Prior Rule and the GE program accountability framework in these regulations suggest a lack of statutory authority. In the NPRM, we discussed the background of the regulations, the relevant data available, and the major changes proposed in that document, including the changes from the 2014 Prior Rule and the 2019 Prior Rule. Although the GE program accountability framework in this final rule differs from the 2014 Prior Rule, including in the addition of a standalone earnings premium measure, we have demonstrated how the D/E rates measure and the EP measure, singly and taken together, are reasonable, evidence-based metrics that both serve to meet the statutory eligibility requirements and address the specific need for regulatory action in the sector. The fact that this final rule varies from prior GE regulations is not indicative of lack of authority for the Department to implement the statutory provisions related to GE programs and to develop rules to properly administer the title IV, HEA programs. Rather, the development of this rule reflects the reality that the Department's judgments and policies on a variety of issues may change over time in light of experience, information, and analysis—which the law permits, as long as the Department's rules remain within the boundaries of the applicable statutes and the Department provides a reasoned basis for the change in position.

88 FR 32300, 32306 (May 19, 2023).

88 FR 32300, 32392 (May 19, 2023).

88 FR 32300, 32317 (May 19, 2023).

See, for example, FCC v. Fox Television Stations, Inc., 556 U.S. 502, 515–16 (2009).

The Department, therefore, disagrees with commenters who believe that the GE program accountability framework is not within the Department's statutory authority, and further disagrees with claims that GE program results are not relevant to GE program eligibility for title IV, HEA funding. The Department also disagrees with suggestions that we should implement the statute without clear and administrable rules for evaluating whether GE programs are meeting statutory eligibility requirements. Without relatively specific rules, the Department could not adequately ensure that title IV, HEA funds are properly channeled to students attending programs that prepare students for gainful employment; institutions would not have clarity as to the standards for GE programs that the Department applies; and we would not be able to address the need for regulatory action in the sector.

In suggesting that congressional intent regarding GE programs indicates relatively narrow authority for the Department, a commenter pointed to post-enactment statements by Members of Congress as well as unsuccessful legislation. The Department is attentive to input from Members of Congress, but we disagree that the statutory authority for these rules is limited by unenacted bills or policy positions. To the extent that the 2019 Prior Rule can somehow be read to adopt a contrary position, that position cannot be sustained. See, for example, Bostock v. Clayton County, 140 S. Ct. 1731, 1747 (2020) (“All we can know for certain is that speculation about why a later Congress declined to adopt new legislation offers a `particularly dangerous' basis on which to rest an interpretation of an existing law a different and earlier Congress did adopt.”) (quoting Pension Ben. Guar. Corp. v. LTV Corp., 496 U.S. 633, 650 (1990)). In this rulemaking, we have emphasized, among other sources, statutory text, structure, purpose, and past judicial decisions, as well as the Department's well-reasoned choices on matters of detail in the exercise of its authority to administer the relevant statutes and in light of the Department's experience and expertise. Nothing in the 2019 Prior Rule, and its more limited review of the foregoing considerations, prevents the Department from engaging in this analysis and reaching the conclusions set forth herein.

We note, finally, that all or nearly all of the commenters' arguments against any GE performance measure have been raised and rejected during previous rulemaking efforts and in litigation over previous versions of the Department's GE program accountability rules. The statutory arguments against considering GE program outcomes of any kind are not more persuasive now than they were in past years. In fact, new data, data analysis, and the Department's experience in attempting to enforce the statutory limits on GE programs have convinced us that these performance measures are more, not less, urgently needed.

Changes: None.

Comments: Some commenters questioned the Department's authority, at least at this time, to adopt performance measures for GE program eligibility including the earnings premium (EP) measure. Some commenters noted that the EP measure is a new standard and argued that the measure was beyond the Department's authority to adopt for evaluating the eligibility of GE programs to participate in title IV, HEA. Some commenters asserted that the Department had not adequately supported the EP measure in the NPRM, or that the Department's support for the EP measure is arbitrary. While many commentators did not focus on the EP measure in terms of the Department's statutory authority, some commenters did make general challenges to the GE program accountability framework that applied to the EP measure as well as the debt-to-earnings (D/E) rates. Some of those challenges were based on the commenters' interpretation of “gainful employment” in the GE statutory provisions to mean any job that pays any amount, and on the contention that the Department is arbitrarily changing its position from the 2019 Prior Rule.

Discussion: In several respects, this final rule differs from the 2019 Prior Rule as well as the 2014 Prior Rule. We have acknowledged those differences and offered reasons for them in this document and in the NPRM. One difference is the addition of an earnings premium measure, which will operate alongside the debt-to-earnings rates measure in evaluating GE program eligibility. Further details and reasons for adopting the EP measure are presented below and in the NPRM. In this discussion, we summarize several connected reasons for adopting the EP measure for GE program eligibility in these final rules.

See 88 FR 32300, 32307–08 (May 19, 2023); id. at 32309–11, 32342–43 (providing reasons for the adoption of GE accountability rules at this time, in view of the 2019 Prior Rule and subsequent developments).

See, for example, 88 FR 32300, 32308, 32325–28, 32343–44 (May 19, 2023). Those discussions also address the D/E rates measure.

First of all, the Department's careful review of applicable law and public comments leave us convinced that the EP measure is within the Department's statutory authority. Statutory text, structure, and purpose support that conclusion. If program completers' earnings fall below those of students who never pursue postsecondary education in the first place, programs cannot fairly be said to “train” postsecondary students to “prepare” them for “gainful employment” in recognized professions or occupations. Those statutory terms indicate that eligible GE programs must make students ready or able to achieve gainful employment in such professions or occupations—consistent with a statutory purpose of improving students' ultimate job prospects and income over what they would be in the absence of such training and preparation. As the D.C. Circuit stated when it reviewed the D/E measure in the 2014 Prior Rule, those statutory terms “suggest elevation to something more than just any paying job. They suggest jobs that students would less likely be able to obtain without that training and preparation.” At minimum, the statutory language permits the conclusion that the Department adopts here.

20 U.S.C. 1002(b)(1)(A), (c)(1)(A). See also 20 U.S.C. 1088(b)(1)(A)(i), which refers to a recognized profession.

Ass'n of Priv. Sector Colleges & Universities v. Duncan, 640 F. App'x 5, 8 (D.C. Cir. 2016) (per curiam). Although the courts were likewise reviewing D/E measures for GE program eligibility rather than EP measures, generally supportive language also appears in Ass'n of Priv. Sector Colleges & Universities v. Duncan, 110 F. Supp. 3d 176, 187–88 (D.D.C. 2015) (stating that “examining [GE] programs' outputs in terms of earnings and debts” is consistent with the HEA) (emphasis omitted), aff'd, 640 F. App'x at 6; Ass'n of Proprietary Colleges v. Duncan, 107 F. Supp. 3d 332, 362 (S.D.N.Y. 2015) (concluding that “it is reasonable to consider students' success in the job market as an indication of whether those students were, in fact, adequately prepared”) (internal quotation marks omitted) (quoting Ass'n of Priv. Colleges & Universities v. Duncan, 870 F. Supp. 2d 133, 147–48 (D.D.C. 2012)).

Importantly, the overall structure of the applicable statutes reinforces our adoption of the EP measure. The basic starting point for students at eligible GE programs is a high school education or its equivalent, as we pointed out in the NPRM. The HEA generally requires students who receive title IV assistance to have already completed a high school education, and then, from that starting point, the statute requires GE programs to prepare those high school graduates for gainful employment in a recognized occupation. Whatever ambiguity or vagueness there might be in the HEA, clearly GE programs are supposed to enhance earnings power beyond that of what high school graduates, not leave them where they started. The EP measure reflects that premise of the applicable statutes. It will measure post-high school gain, in part, with an administrable test that reflects earnings beyond a typical high school graduate.

See, for example, 88 FR 32300, 32308, 32333, 32327 (May 19, 2023).

Regarding a high school education as the starting point, 20 U.S.C. 1001 states that an institution of higher education must only admit as regular students those individuals who have completed their secondary education or met specific requirements under 20 U.S.C. 1091(d), which includes an assessment that they demonstrate the ability to benefit from the postsecondary program being offered. The definitions for a proprietary institution of higher education or a postsecondary vocational institution in 20 U.S.C. 1002 maintain the same requirement for admitting individuals who have completed secondary education. Similarly, there are only narrow exceptions for students beyond the age of compulsory attendance who are dually or concurrently enrolled in postsecondary and secondary education. The apparent purpose of such limitations is to help promote that postsecondary programs build skills and knowledge that extend beyond what is taught in high school.

The discussions in this document and in the NPRM are more than sufficient to establish the Department's authority to adopt the GE eligibility rules, including the EP measure.

The Department recognizes again, as we did in the NPRM, that the EP measure will be new to the Department's regulations. More broadly, we recognize that until 2010 the Department did not specify through regulations an administrable test to identify which programs qualify as eligible GE programs under the statutes. Nevertheless, we do not believe that the meaning of the applicable statutes becomes narrower because the agency initially refrained from issuing regulations that incorporated specific performance tests. The need for such rules became clearer over time. In addition to the points made above, new data and analyses have underscored the need for performance-based limits on GE program eligibility, including a test for enhanced student earnings. Acting now will enable the Department to respond to that emerging need with administrable tests of program performance that accord with statutory text, structure, and purpose.

See 88 FR 32300, 32307–11 (May 19, 2023).

An EP measure for GE eligibility finds support in recent evidence and studies. Within the last several years, a number of researchers have recommended that the Department reinstate the 2014 GE rule with an added layer of accountability through a high school earnings metric. That goal of ensuring that students benefit financially from their career training fits with broader research on the economics of postsecondary education. Similar earnings premium metrics are used ubiquitously by economists and other analysts to measure the earnings gains associated with college credentials relative to a high school education. Furthermore, there is increasing public recognition that some higher education programs are not “worth it” and do not promote economic mobility. While the D/E rates measure identifies programs where debt is high relative to earnings, the EP measure assesses the economic boost a program provides to its students independent of the debt incurred. After all, students and families invest their own time and money in postsecondary education in addition to the amount they borrow. The EP measure therefore provides a different measure than the D/E metric of whether a program prepares its students for gainful employment in a recognized occupation. Adopting an EP measure for GE programs that seek to participate in title IV, HEA fits within such recent recommendations, data analysis, and mainstream thinking about which career training programs should be considered gainful.

See, for example, Matsudaira, Jordan D. & Turner, Lesley J. (2020). Towards a Framework for Accountability for Federal Financial Assistance Programs in Postsecondary Education. The Brookings Institution ( www.brookings.edu/wp-content/uploads/2020/11/20210603-Mats-Turner.pdf ). Cellini, Stephanie R. & Blanchard, Kathryn J. (2022). Using a High School Earnings Benchmark to Measure College Student Success Implications for Accountability and Equity. The Postsecondary Equity and Economics Research Project. ( www.peerresearchproject.org/peer/research/body/2022.3.3PEER_HSEarnings-Updated.pdf ). Itzkowitz, Michael (2020). Price to Earnings Premium: A New Way of Measuring Return on Investment in Higher Education. Third Way ( https://www.thirdway.org/report/price-to-earnings-premium-a-new-way-of-measuring-return-on-investment-in-higher-ed ). For further discussion of such research, see the Regulatory Impact Analysis below.

See, for example, Autor, D.H. (2014). Skills, Education, and the Rise of Earnings Inequality Among the “Other 99 Percent.” Science, 344 (6186), 843–851. Baum, S. (2014). Higher Education Earnings Premium: Value, Variation, and Trends. Urban Institute. Carnevale, A.P., Cheah, B. & Rose, S.J. (2011). The College Pay Off. Daly, M.C. & Bengali, L. (2014). Is It Still Worth Going to College. FRBSF Economic Letter, 13 (2014), 1–5. Li, A., Wallace, M. & Hyde, A. (2019). Degrees of Inequality: The Great Recession and the College Earnings Premium in US Metropolitan Areas. Social Science Research, 84, 102342; Oreopoulos, P. & Petronijevic, U. (2013). Making College Worth It: A Review of Research on the Returns to Higher Education. NBER Working Papers, (19053); and Broady, Kristen E. & Herschbein, Brad (2020). Major Decisions: What Graduates Earn Over Their Lifetimes. The Hamilton Project.

See, for example, polling evidence in https://www.wsj.com/articles/americans-are-losing-faith-in-college-education-wsj-norc-poll-finds-3a836ce1. A 2022 survey by the Federal Reserve shows that more than one-third of workers under the age of 45 say the benefits of their education did not exceed the costs ( https://www.federalreserve.gov/publications/files/2022-report-economic-well-being-us-households-202305.pdf ).

Furthermore, the EP measure that we adopt will set only minimal and reasonable expectations for programs that are supposed to help students move beyond a high school baseline. The rule marks an incremental and commonsense change that we are confident is within the Department's authority. In particular, we observe that the median earnings of high school graduates is about $25,000 nationally, which corresponds to the earnings of a full-time worker who makes about $12.50 per hour. We also reiterate that the EP measure does not demand that every individual who attends a GE program must earn more than a high school graduate; instead, the measure requires only that at least half of those who actually complete the program are earning at least slightly more than individuals who had never completed postsecondary education. The vast majority of students cite the opportunity for a good job or higher earnings as a key, if not the most important, reason they chose to pursue a college degree. While the 2014 Prior Rule justifiably emphasized that borrowers should be able to earn enough to afford to repay their debts, the Department recognizes here that borrowers must be able to afford more than ”just” their loan payments and that postsecondary GE programs should help students reach a minimal level of labor market earnings.

That figure is lower than the minimum wage in 15 States. See https://www.dol.gov/agencies/whd/mw-consolidated.

See 88 FR 32300, 32333, 32327 (May 19, 2023). The EP measure simply compares program completers' earnings with high school graduates' earnings and therefore does not reflect tuition costs or debt. See id. at 32327. Note that these EP features are not unique to the GE program eligibility provisions. These EP features apply within the financial value transparency provisions as well.

For example, a recent survey of 2,000 persons aged 16 to 19 and 2,000 recent college graduates aged 22 to 30 rated affordable tuition, higher income potential, and lower student debt as the top 3 to 4 most important factors in choosing a college ( https://www.nytimes.com/2023/03/27/opinion/problem-college-rankings.html ). The RIA includes citations of other survey results with similar findings.

Although modest in several respects, the EP measure for GE program eligibility is nonetheless likely to deliver important benefits and substantially further statutory purposes. We are convinced of these prospective gains by recent evidence. For example, recent research indicates that the EP measure will help protect students from the adverse borrowing outcomes prevalent among programs with very low earnings. Research conducted since the 2014 Prior Rule as well as new data analyses shown in this RIA illustrate that, for borrowers with low earnings, even small amounts of debt—including levels of debt that would not trigger failure of the D/E rates—can be unmanageable. We now can be reasonably confident that default rates tend to be especially high among borrowers with lower debt levels and very low earnings, because at low earnings levels any amount of debt in unaffordable. Analyses in this RIA show that the default rate among students in programs that pass the D/E rates thresholds but fail the earnings premium are very high. In fact, those default rates are even higher than programs that fail the D/E rates measure but pass the EP measure. In that sense, the EP measure is an important separate measure of gainfulness, providing some added protection to borrowers who have relatively low balances, but who have earnings so low that even low levels of debt payments are unaffordable.

See Brown, Meta et al. (2015). Looking at Student Loan Defaults Through a Larger Window. Liberty Street Economics, Fed. Reserve Bank of N.Y. ( https://libertystreeteconomics.newyorkfed.org/2015/02/looking_at_student_loan_defaults_through_a_larger_window/ ).

In addition, we reaffirm that the EP measure will help protect taxpayers. Borrowers with low earnings are eligible for reduced loan payments and loan forgiveness, which increase the costs of the title IV, HEA loan program to taxpayers. While income-driven repayment (IDR) plans for Federal student loans partially shield borrowers from default due to inability to make payments, such after-the-fact protections do not address underlying program failures to prepare students for gainful employment in the first place, and they exacerbate the impact of such failures on taxpayers as a whole when borrowers are unable to pay. Not all borrowers participate in these repayment plans and, where they do, the risks of nonpayment are shifted to taxpayers when borrowers' payments are not sufficient to fully pay back their loans. This is true because borrowers with persistently low incomes who enroll in IDR—and thereby make payments based on a share of their income that can be as low as $0—will have their remaining balances forgiven at taxpayer expense after a specified number of years in repayment. Both the EP and D/E measures for GE program eligibility will help protect taxpayers, because both measures are well-designed to screen out GE programs that generate a disproportionate share of the costs to taxpayers and negative borrower outcomes. In support of this conclusion, the final RIA as well as the NPRM's RIA presented estimates of loan repayment under the hypothetical assumption that all borrowers pay on the SAVE plan announced by the Department in July 2023. These analyses show that both D/E and EP measures are strongly correlated with an estimated subsidy rate on Federal loans, which measures the share of a disbursed loan that will not be repaid, and thus provides a proxy for the cost of loans to taxpayers. Although many commenters disagreed with at least part of the Department's approach to GE programs, commenters did not appear to take issue with the proposition that taxpayer protection is a purpose to be served by the GE provisions in the HEA.

See, for example, 88 FR 32300, 32307–09 (May 19, 2023).

See 88 FR 1894 (Jan. 11, 2023). The Department's final rule for IDR can be found at 88 FR 43820 (July 10, 2023).

See Table 2.10 in the RIA for this document.

Thus, the EP and D/E measures serve some of the same purposes, but we observe again that they measure importantly distinct dimensions of gainful employment. The distinctions support the Department's decision to require that GE programs not (repeatedly) fail either measure if those programs are to receive title IV, HEA support. D/E rates measure debt-affordability, indicating whether the typical graduate will have earnings enough to manage their debt service payments without incurring undue hardship. For any median earnings level of a program, the D/E rates and thresholds imply a maximum level of total borrowing beyond which students should be concerned that they may not be able to successfully manage their debt. The EP measure tests whether programs leave their completers with greater earnings capacity than those who do not enroll in postsecondary education, which represents a minimal benchmark that students pursuing postsecondary credentials likely expect to achieve. And while the EP measure provides additional protection to borrowers and taxpayers, it attends to a distinct aspect of determining whether a program prepares its students for gainful employment in a recognized occupation—namely, the extent to which the program helps students attain a minimally acceptable earnings enhancement.

See, for example, 88 FR 32300, 32308, 32327, 32344 (May 19, 2023). We reiterate that the D/E and EP measures are severable. The severability provisions in these final rules are §§ 668.409 and 668.606. For the Department's discussions of severability generally and as applied to the D/E and EP measures, please see the NPRM, 88 FR 32300, 32341–42, 32349 (May 19, 2023).

Accordingly, we disagree with commenters who argue that the Department either generally lacks authority to adopt the EP measure for GE program eligibility, or that the Department chose the wrong time to adopt that measure. We understand the opinions of those who prefer that the Department not adopt administrable and clear rules to test GE program performance. Unlike the rules as they stood after the 2019 rescission, these final rules will demand that GE programs not have a track record of failure on certain basic measures of performance if they seek to benefit from title IV, HEA taxpayer funds. Some GE programs will repeatedly fail those measures, although we point out that some of those programs will survive without support from the Federal Government through title IV, HEA. Regardless, we are convinced that these rules are within the Department's statutory authority, and that recent events and new information confirm the importance of acting now. If the Department does not act effectively at the front end to screen out the subset of GE programs that do not meet minimal performance standards of enhanced earnings and affordable debt, students and taxpayers will continue to suffer the consequences at the back end. Those consequences have grown larger and clearer, and the Department has decided to respond decisively yet reasonably. A clear earnings premium rule for GE program eligibility is one part of that measured response.

Comments: Several commenters contended that there is an increased burden on the Department to demonstrate congressional authorization for its proposed GE metrics under West Virginia v. Environmental Protection Agency and the major questions doctrine. These commenters described the proposed eligibility framework as a major shift in the way GE programs maintain title IV, HEA eligibility that would impact the funding for many students and institutions, and asserted that the framework creates burdensome new reporting requirements. These commenters concluded that the statutory language relied upon—that GE programs “prepare students for gainful employment in a recognized occupation”—is not a sufficiently explicit statement of congressional intent to support such a change.

142 S. Ct. 2587 (2022).

Discussion: We disagree that the major questions doctrine applies such that the Department needs an especially clear grant of statutory authority to adopt performance standards in the GE program accountability framework. Having considered the factors that courts have used to identify exceptional circumstances in which such clarity is required, we do not believe that the doctrine applies here. If the doctrine did apply, we believe that the Department's authority to adopt performance standards for GE program eligibility is adequately clear based on ordinary tools of statutory interpretation.

See, for example, id. at 2608 (discussing extraordinary cases in which the breadth, history, and economic and political significance of asserted agency authority provide reason to hesitate before concluding that Congress conferred such authority).

As discussed above and in the NPRM, we believe performance measures for GE accountability rules are firmly grounded in the text, structure, and purposes of tile IV, HEA, including its gainful employment provisions. Furthermore, and for reasons also discussed above, GE performance measures are neither novel nor surprising. We have noted past litigation and court opinions. And given the grounding of performance measures in the text of core statutory provisions in the HEA regarding GE programs, there is nothing “ancillary” about those statutory provisions such that the major questions doctrine might apply on that basis.

88 FR 32300, 32306 (May 19, 2023).

See cases cited in notes 50–52 above, within that earlier discussion of authority for the GE program accountability framework.

Compare Whitman v. Am. Trucking Ass'ns, 531 U.S. 457, 468 (2001) (“Congress, we have held, does not alter the fundamental details of a regulatory scheme in vague terms or ancillary provisions—it does not, one might say, hide elephants in mouseholes.”); Ass'n of Priv. Colleges & Universities v. Duncan, 870 F. Supp. 2d 133, 148 (D.D.C. 2012) ( APCU) (reviewing the 2011 Prior GE Rule, distinguishing Whitman, and explaining that “[n]either the elephant nor the mousehole is present here. . . . Concerned about inadequate programs and unscrupulous institutions, the Department has gone looking for rats in ratholes—as the statute empowers it to do.”); Ass'n of Proprietary Colleges v. Duncan, 107 F. Supp. 3d 332, 361 (S.D.N.Y. 2015) (reviewing the 2014 Prior GE Rule and quoting APCU).

And far from taking any step toward mandating specific curricula when institutions prefer other educational strategies, these performance measures simply evaluate whether programs should receive taxpayer support based on commonsense financial outcomes: affordable debt and enhanced earnings. Those outcomes plainly are related to whether a program actually prepares students for gainful employment in a recognized occupation or profession, instead of leaving the typical program completer with unaffordable debt burdens or no greater earnings than they could secure without career training. These performance measures are based on the text, structure, and purposes of the governing statutes. Such rules are, moreover, within the heartland of the Department's experience and expertise. Among the Department's longstanding missions are enforcing the limits on title IV, HEA eligibility for GE programs, and gathering, analyzing, and using data to evaluate education programs including GE programs. Accordingly, GE performance measures are not beyond the agency's core competence such that the major questions doctrine might apply on that basis.

Under section 103 of the Department of Education Organization Act, 20 U.S.C. 3403(b), the Department is generally prohibited from exercising any direction, supervision, or control over the curriculum, program of instruction, administration, or personnel of an educational institution, school, or school system.

Compare W. Virginia v. EPA, 142 S. Ct. at 2612–13 (indicating that presumably Congress does not task an agency with making policy judgments in which the agency has “no comparative expertise”); Biden v. Missouri, 142 S. Ct. 647, 653 (2022) (“[T]here can be no doubt that addressing infection problems in Medicare and Medicaid facilities is what [the Secretary of Health and Human Services] does.”).

In addition, available data indicate that the GE program accountability framework will have important yet limited effects. The available data, presented in RIA Tables 4.8 and 4.9, indicate that most existing GE programs will not fail the D/E rates or EP measure when they are applied, let alone fail two out of three years for which program results are issued. Our estimates suggest about 1,700 GE programs will fail the D/E rates or EP measure—representing about 5.3 percent of all GE programs, and only 1.1 percent of all higher education programs attended by federally aided students. While the share of students currently enrolled in such programs is higher—23.7 percent of federally aided students in career training programs, and 3.6 percent of all federally aided students—it is important to note these students have other options. Analyses presented in Tables 4.25 and 4.26 of the RIA show that the majority of students have similar program options that do not fail the D/E rates or EP measure and are nearby, or even at the same institution. These analyses are supported by external research, suggesting that most students in institutions closed by accountability provisions successfully reenroll in higher performing colleges. More generally, many more students will pursue a postsecondary education in the future, relative to the number enrolled now. As programs with poor performance close, these future college goers will benefit from better options to choose from and are unlikely to otherwise be affected by programs closed today. In any event, nearly three-quarters of institutions of higher education that participate in title IV, HEA programs have no enrollment in failing GE programs that might be subject to eligibility loss.

Cellini, S.R., Darlie, R. & Turner, L.J. (2020). Where Do Students Go When For-Profit Colleges Lose Federal Aid? American Economic Journal: Economic Policy, 12 (2): 46–83.

Those predicted effects do not establish the kind of transformation or upheaval in higher education that might trigger the major questions doctrine. Indeed none of the above considerations indicates the special circumstances under which courts have invoked the major questions doctrine to demand especially clear statutory authorization for agency action.

Compare W. Virginia v. EPA, 142 S. Ct. at 2610 (addressing what the Court characterized as agency authority to “substantially restructure the American energy market,” and an “unheralded power” that would represent a “transformative expansion” of agency authority) (internal quotation marks omitted); Biden v. Nebraska, 143 S. Ct. 2355, 2373 (2023) (discussing what the Court described as a “fundamental revision of the statute” and a decision with “staggering” economic and political significance).

Of course, the GE program accountability framework is not irrelevant as a matter of economics or politics. Every student who ends up with enhanced earnings or more affordable debt is important, in the Department's view, as is every Federal dollar saved from expenditure on poorly performing GE programs. And we acknowledge that there is disagreement among those who are engaged in the relevant policy debates about the appropriate content for the GE rules. We likewise acknowledge that the precise content of the GE rules and their effects are important to institutions, students, and taxpayers. In fact, the HEA requires that limits on GE programs be recognized and enforced; the Department is not free to ignore those limits as if the applicable sections were surplusage, and that point is not insignificant to the statutory scheme. But in this instance, the Department is adopting relatively modest, commonsense, minimum performance standards that most GE programs seeking government support can and should pass without trouble, and that do not preempt, through agency action, any widespread political controversy that Congress intended to reserve for itself. Although the Department must make judgments about the details of performance measures to make the rules clear and easily administrable, those choices of detail are, by definition, not subject to the major questions doctrine.

We also observe that the Department has followed and benefitted from an extensive process before issuing these final rules on GE accountability. The Department used the negotiated rulemaking provisions in the HEA, with notice and comment rulemaking, which is the process that was created for the Department to consider the interests of title IV, HEA participants, among others. In this context, reestablishing an eligibility framework for GE programs fits well with the financial value transparency framework for all programs while setting an outcome-based limit for GE programs.

Changes: None.

Comments: Some commenters contended that a lack of congressional authorization to use outcomes-based measures for GE programs is shown by other eligibility requirements in the HEA, including cohort default rates, the 90/10 revenue requirement, and limitations on correspondence courses. A commenter also asserted that Congress created cohort default rates (CDRs) as a performance measure for institutions rather than directing the Department to set program-based outcomes as eligibility requirements. Some commenters argued that the framework of detailed program requirements under title IV of the HEA, including institutional CDR, institutional disclosure requirements, restrictions on student loan borrowing, and other financial aid requirements, prevents the Department from adopting debt measures to determine whether a GE program is eligible to receive title IV, HEA program funds.

Discussion: The Department disagrees that GE performance measures are somehow precluded by distinct and complementary safeguards elsewhere in law. There is no express support in the statutes for that position, which would diminish protections for students and taxpayers. Instead, the commenters are suggesting an inference of exclusivity with inadequate support in the statutes. Taking other safeguards as exclusive would effectively ignore the statutorily prescribed limits on GE programs as the HEA defines them. The Department can find no sound reason, in law or policy, for treating the GE provisions as surplusage. The Department's specification of details in clear and administrable rules helps us to implement and enforce these provisions appropriately, and the specific rules for these GE provisions are entirely consistent with the specific requirements in other statutory provisions.

The Department accordingly disagrees with the commenters' assertions that the HEA's provisions on CDR, student borrowing, and other financial aid matters prevent the Department from implementing the specific HEA provision limiting title IV eligibility to programs that provide training that prepares students for gainful employment in a recognized occupation. The different Department rules implement different statutory provisions. For example, the CDR and GE regulations serve related but different purposes. Congress enacted the CDR provision, which measures loan defaults from all programs at the institutional level, as one mechanism—not the sole, exclusive mechanism—for dealing with abuses in Federal student aid programs. Congress did not, in enacting the CDR provision or at any other time, limit the Department's authority to promulgate regulations to effectuate and specify limits on GE programs. Nor did Congress alter the existing statutory language regarding GE program eligibility when it passed the CDR provision. Moreover, the CDR provision operates at the institutional level while the GE provisions and these GE accountability rules operate at the program level. In addition to statutory eligibility requirements at the institution level, each program must be evaluated for title IV, HEA eligibility as well.

That conclusion regarding the non-exclusivity of CDR is consistent with relevant legislative history. See H.R. Rep. No. 110–500, at 261 (2007) (“Over the years, a number of provisions have been enacted under the HEA to protect the integrity of the federal student aid programs. One effective mechanism was to restrict federal loan eligibility for students at schools with very high cohort loan default rates.”) (emphasis added).

Contrast the prohibition on Department regulations in 20 U.S.C. 1015b(i), regarding student access to affordable course materials. See id. (“The Secretary shall not promulgate regulations with respect to this section.”).

See Ass'n of Priv. Colleges & Universities v. Duncan, 870 F. Supp. 2d 133, 147 (D.D.C. 2012). In that case, the court recognized that the “statutory cohort default rule . . . does not prevent the Department from adopting the debt measures” for GE programs. Id. (citing Career Coll. Ass'n v. Riley, 74 F.3d 1265, 1272–75 (D.C. Cir. 1996), for the proposition that the Department's authority to establish “`reasonable standards of financial responsibility and appropriate institutional capability' empowers it to promulgate a rule that measures an institution's administrative capability by reference to its cohort default rate—even though the administrative test differs significantly from the statutory cohort default rate test.”).

The GE program accountability rules are also consistent with other provisions of the HEA aimed at curbing abuses in the title IV, HEA programs. For example, Congress capped the amount of title IV revenues that proprietary institutions could receive at 85 percent in the 1992 HEA reauthorization as a condition of institutional eligibility, with subsequent changes that increased the percentage to 90 percent and that tied a loss of eligibility to two years of failing the 90 percent measure instead of one year. More recently, Congress also expanded the definition of Federal education funds to include military benefits to service members and families as a part of the funds included in the 90 percent limit. The 90/10 provisions were put in place to require proprietary institutions to generate some revenue from non-Federal sources. Those changes fit within a larger framework where Congress also specified that a participating “institution will not provide any commission, bonus, or other incentive payment based directly or indirectly on success in securing enrollments or financial aid to any persons or entities engaged in any student recruiting or admission activities or in making decisions regarding the award of student financial assistance.” Additionally, to prevent schools from improperly inducing people to enroll, Congress prohibited participating institutions from engaging in a “substantial misrepresentation of the nature of its educational program, its financial charges, or the employability of its graduates.” Congress also required a minimum level of State oversight of eligible schools. The GE program accountability rules adopted here are consistent and compatible with such additional and separate regulations, including those that apply to institutions that seek eligibility for title IV, HEA support.

20 U.S.C. 1094(a)(20). As one court explained, “The concern is that recruiters paid by the head are tempted to sign up poorly qualified students who will derive little benefit from the subsidy and may be unable or unwilling to repay federally guaranteed loans.” United States ex rel. Main v. Oakland City Univ., 426 F.3d 914, 916 (7th Cir. 2005).

Changes: None.

Comments: Some commenters asserted that the Department is misinterpreting the GE program statutory language and suggested that the language is better read as referring to the type and content of the program an institution is offering rather than measuring any outcomes of the program graduates. Other commenters similarly stated that “gainful employment” was intended to refer to the nature of the employment associated with the training and not any type of outcome-based framework, noting that outcome-based standards provide no basis for new programs to establish eligibility under the HEA before there would be any program outcomes to measure. Another commenter referred to administrative decisions from the Department that also described GE programs as types of programs leading to recognized occupations. One commenter claimed that the Department has previously defined the phrase “gainful employment in a recognized occupation” in the context of conducting administrative hearings and argued that the Department did not adequately explain in the NPRM why it was departing from its prior use of the term.

Discussion: The GE program accountability framework builds on the Department's regulation of institutions participating in the title IV, HEA programs to protect students and taxpayers, as Congress authorized. For reasons given in this document and the NPRM, the Department is adopting GE rules that consider program performance in eligibility determinations for GE programs. The Department disagrees with the commenters' claims that the GE provisions address program content and curriculum alone. Whatever the extent of the Department's authority to consider GE program content—and the Department is not asserting such authority in these GE rules—the Department may assess GE program performance through student outcomes.

88 FR 32300, 32344 (May 19, 2023).

Furthermore, the rules adopted here allow for new as well as existing GE programs. Although parts of the GE rules are performance-based, these rules will not exclude programs from title IV, HEA eligibility until they build a track record to evaluate them. The Department must have student outcomes data to measure program performance, which can only come after a period of time. Moreover, the rules are designed as reasonable, minimum standards whereby title IV, HEA eligibility as a GE program is not precluded until a program fails one of the two GE metrics in two out of three consecutive years for which the Department can issue results. Under these rules, new programs that otherwise qualify as GE programs do not have to show performance results that are not yet available.

We further disagree that a previous administrative decision on GE program eligibility forecloses the adoption of these final rules. The Department would not be prevented from changing its position in this rulemaking, of course, even if an older agency decision during an administrative adjudication conflicted with our decision here. We provide numerous and extensive reasons for the rules that we are adopting. But in this instance, no such conflict exists. The argument was vetted and rejected more than 10 years ago. Challenging the 2011 Prior Rule and referring to a decision by an administrative law judge (ALJ), the Association of Private Colleges and Universities contended that the Department previously defined gainful employment in a recognized occupation in a manner that conflicted with those outcome-based rules. The adjudication involved the question whether a program in Jewish culture prepared students enrolled in the program for gainful employment in a recognized occupation. As the court understood, the ALJ did not purport to comprehensively decide what it means to prepare a student for gainful employment in a recognized occupation; instead the ALJ merely stated that any preparation must be for a specific area of employment. Therefore, the Department did not depart from the ALJ's interpretation when the Department adopted outcome-based measures for GE programs in the 2011 Prior Rule. Nor is the Department departing from that interpretation with these regulations.

Association of Private Sector Colleges and Universities (APSCU) v. Duncan, 870 F. Supp. 2d 133, 150 (D.D.C. 2012). The adjudication involved the question whether a program in Jewish culture prepared students enrolled in the program for gainful employment in a recognized occupation.

See id. In any event, the Department has provided ample reasons for disagreeing with narrower positions on the GE provisions and in favor of its positions on outcome-based measures, as reflected in these rules.

Changes: None.

Comments: A few commenters argued that the Department does not provide adequate reasons for changing approaches from the 2019 Prior Rule, which rescinded the 2014 Prior Rule.

Discussion: We discussed departures from the 2019 rescission in the “Background” section of the NPRM. Specifically, the Department remains concerned about the same problems documented in the 2011 and 2014 Prior Rules. Too many borrowers struggle to repay their loans, and the RIA shows these problems are more prevalent among programs where graduates have high debts relative to their income, and where graduates have low earnings. The Department recognizes that, given the high cost of education and correspondingly high need for student debt, students, families, institutions, and the public have an acute interest in knowing whether higher education investments payoff through positive repayment and earnings outcomes for graduates.

88 FR 32300, 32306–11 (May 19, 2023).

Changes: None.

Comments: One commenter asserted that the Department's 2019 action to rescind the 2014 GE regulation created a serious reliance interest, which will cause institutions to incur costs to comply with the requirements in this final rule. Another commenter noted that there is little correlation between the earnings data the Department relied upon in the NPRM RIA and the earnings data that has been posted on College Scorecard. This commenter believed that institutions have a reliance interest in how the Department has previously measured debt and earnings.

Discussion: The NPRM contained a Reliance Interests section, where the Department acknowledged and considered reliance interests generally. We reiterate and reaffirm here that the Department's prior regulatory actions would not have encouraged reasonable reliance on any particular regulatory position. The 2019 Prior Rule was issued to rescind the 2014 Prior Rule at a point when no program had yet been denied title IV, HEA eligibility as a GE program due to failing GE outcome measures over multiple years. Thus, institutions that were operating programs with title IV, HEA support at the time of the 2019 rescission could not have reasonably relied on continuing eligibility based on their title IV support between the 2014 and 2019 Prior Rules, and in any case the absence of eligibility denials limited the practical differences across rule changes for institutions and other interested parties. As we discuss elsewhere in this document, including the RIA, we do anticipate positive effects from this final rule, but we also observe that effects such as ineligibility of GE programs for participation in title IV, HEA will not occur immediately. Institutions and others will have some time to adjust. Furthermore, as various circumstances have changed, in law and otherwise, and as more information and further analyses have emerged, the Department's position and rules have changed since the 2011 Prior Rule. Such alterations in rules do not establish a firmly stable foundation on which interested parties may develop reasonable and legitimate reliance interests in a particular set of rules that they prefer. In any event, we find no reasonable reliance interest in the 2019 rescission persisting such that the Department could not revise its approach and, for example, observe meaningful performance-based limits on the eligibility of gainful employment programs for title IV, HEA participation. The commenters did not offer useful evidence or other bases on which the Department could reasonably conclude that asserted reliance interests, as to the prior rules or the College Scorecard, are real and significant rather than theoretical and speculative. On balance, the reliance interests asserted by the commenters have not changed our position that there are no plausible reliance interests that are strong enough to lead us to fundamentally alter these final regulations.

88 FR 32300, 32316 (May 19, 2023).

Our conclusions regarding reliance interests are guided by judicial opinions including FCC v. Fox Television Stations, Inc., 556 U.S. 502, 515–16 (2009).

Changes: None.

General Comments on the Financial Value Transparency Framework (§§ , 668.43, 668.401, 668.402, 668.403, 668.404, 668.405, 668.406, 668.407, 668.408, and 668.409)

General Support and Opposition

Comments: We received many comments expressing support for the financial value transparency framework as a means of protecting students and improving higher education outcomes. Commenters urged prioritizing the establishment of the program information website so that students have clear information about the institutions and programs they are attending or considering attending. These commenters supported efforts that would help students identify “high-debt-burden” and “low-earning” programs and urged the Department to keep these strong transparency provisions in the final rule to protect students and taxpayers. Several commenters argued that this information would allow students to make informed decisions about their education.

Discussion: We thank the commenters for their support. Under § 668.43(d)(1), the Department will provide, through a website hosted by the Department, program-level information on the typical earnings outcomes for graduates and their borrowing amounts, cost of attendance, and sources of financial aid for all programs where it can be calculated to help students make more informed choices. We agree that this information will help students make more informed choices and allow taxpayers and other stakeholders to better monitor whether public and private resources are being well used.

Changes: None.

Comments: Many commenters supported the proposed transparency framework as a way to provide prospective students with relevant information about the programs and professions they may wish to pursue. Commenters noted that it was often difficult for students to understand total college costs in comparison to employment rates and post-graduate earnings and said that the information provided in the transparency framework could fill in some information gaps for students. Some commenters believed that this platform would, over time, encourage students to select the institutions and programs that are more likely to meet their needs and standards. Other commenters noted that interests in certain job fields drive career paths, so some students would not be interested in information about different programs that offered higher pay.

Discussion: We appreciate the comments recognizing the benefits to students and families that the increased transparency framework will provide in conjunction with information institutions provide about programs and services they offer.

Changes: None.

Comments: One commenter asserted that we need more empirical evidence that publishing data will change student outcomes. Other commenters suggested that interests in certain job fields drive career paths, so some students would not be interested in information about different programs that offered higher pay.

Discussion: The Department discussed the substantial evidence base around the role of transparency and student choice in postsecondary education in the NPRM and in the “Outcome Differences Across Programs” section of RIA. Information does not always sway student choice, but research suggests that providing students with comparable, timely information from a trusted source can influence their decisions. The Department believes that the financial value transparency framework serves as an evidence-based approach to provide relevant, trusted, and timely information for student decision-making.

88 FR 32300, 32322 (May 19, 2023).

Steffel, Mary, Kramer, Dennis A. II, McHugh, Walter & Ducoff, Nick (2019). Information Disclosure and College Choice. The Brookings Institution ( www.brookings.edu/wp-content/uploads/2020/11/ES-11.23.20-Steffel-et-al-1.pdf ).

We understand that some students may be committed to pursuing a particular field and may not be swayed by information about other fields. But as the data in this RIA demonstrate, there are vast differences in earnings and debt outcomes for programs with the same credential level and field, and we anticipate that students already committed to a particular degree will benefit from being able to find programs with the best outcomes.

Changes: None.

Comments: A few commenters argued that the certain terms used in the NPRM to label programs that do not pass the D/E rates or EP measures could mislead students or misrepresent other positive aspects of the program. Commenters identified terms like “high debt burden” or “low earning” as overly pejorative.

Discussion: The D/E rates thresholds are based on research into how much debt service payments are affordable based on an individual's earnings. Programs do not meet the D/E criteria when a program's discretionary D/E rate is above 20 percent, and the annual D/E rate is above 8 percent. As discussed in the NPRM, the discretionary D/E rate threshold is based on research conducted by economists Sandy Baum and Saul Schwartz, and the annual D/E rate threshold is grounded in mortgage-underwriting standards. While the rules do not require the Department to use particular labels to describe the outcomes of programs under the D/E rates measure, we intend to use clear descriptive language to communicate these outcomes to students. For example, informing students that such programs are “high debt burden” provides context for the amount of debt that the student will take on relative to their early career earnings.

Baum, Sandy & Schwartz, Saul (2006). How Much Debt is Too Much? Defining Benchmarks for Managing Student Debt ( eric.ed.gov/?id=ED562688 ).

Similarly, the EP threshold is based on the median earnings of high school graduates in the labor force in the institution's State. When the median earnings for graduates from a postsecondary program are lower than this threshold, terming the program, for example, “low earning” is appropriate. The Department views these terms as examples of clear and transparent descriptors for potential students; we believe that less direct phrasing would make it harder for students to interpret the information. However, while the Department believes that students should be informed about the consequences of their choices in programs, we will consider adding language to the Department's program information website noting that the debt and earnings outcomes of programs are a subset of the myriad of factors students may consider important in deciding where to attend.

Changes: None.

Comments: One commenter suggested that the Department and the stakeholder community further discuss the application of the D/E rates and earnings premium metrics to all programs at all institutions before addressing the issue of student acknowledgments. This commenter noted that the required reporting of data will add costs and burden to institutions, particularly under-resourced institutions.

Discussion: The Department disagrees that the decision to apply financial value transparency metrics to programs across sectors and credential levels requires any further discussion. Because students consider both GE and non-GE programs when making postsecondary enrollment choices, providing comparable information for students would help them find the program that best meets their needs across any sector. As discussed under “Reporting” above, while we are sensitive to the fiscal and logistical needs of institutions, we maintain that any burden on institutions to meet the reporting requirements is outweighed by the benefits of the transparency and accountability frameworks of the regulations to students, prospective students, their families, and the public.

Changes: None.

Financial Outcomes and Other Outcomes

Comments: Many commenters posited that although economic mobility is an important factor to many students, the value of higher education extends beyond purely financial benefits and the Department should recognize on the program information website, and on related warnings and acknowledgments, that there are many ways to measure the value of postsecondary education, such as increased civic participation and engagement; better health and well-being; increased sense of work engagement; lower reliance upon social safety-net programs; decreased rates of incarceration; decreased risk of homelessness; increased personal security; improved social status; and sense of personal achievement. Commenters said that focusing on program earnings for all programs promoted a false equivalency that all educational programs should be measured on this basis. Some other commenters noted earnings may not fully capture the value of benefits, such as health insurance, and job amenities, such as a flexible schedule.

One commenter further cited a study highlighting additional individual and societal benefits of higher education, such as increased likelihood of employment; improved health choices; increased volunteerism; increased neighborhood interactions and trust; and intergenerational benefits.

Trostel, Philip (2015). It's Not Just the Money: The Benefits of College Education to Individuals and to Society. LUMINA Foundation ( www.luminafoundation.org/files/resources/its-not-just-the-money.pdf ).

Noting the numerous non-pecuniary benefits of postsecondary education, several commenters expressed concern that the nature of the D/E rates and EP measures is too simple to adequately reflect the full value of an education and one commenter opined that measuring a program's value based solely on the D/E rates and EP measures would be arbitrary and capricious. Many commenters noted that the D/E rates measure is not the only metric that can be used to assess the value of postsecondary programs and suggested that things like holistic value, social impact, import of work, or long-term economic value could also be used to measure the value of programs.

Discussion: The Department is not attempting to assess the full value of the education that programs provide based only on their debt and earnings outcomes through the D/E rates and EP measures. The Department recognizes that not all of the benefits of a postsecondary education are measurable or captured by debt and earnings, but low earnings or high debt burdens can significantly impact even those students who benefitted in other ways from their programs.

Further, while the Department agrees there are aspects of job quality that are distinct from earnings, we believe that earnings, which unlike non-monetary compensation can be calculated consistently for most graduates through administrative data sources, is the best way to capture the employment outcomes of program graduates for purposes of implementing the gainful employment statutory requirement. For instance, in most cases non-monetary compensation does not aid in assessing the ability of graduates to afford repayment of student debt.

The financial value transparency framework aims to provide transparency to students about dimensions of the financial consequences of attending postsecondary programs. In particular, these measures will be used to convey information to students about the typical costs, borrowing, and earnings outcomes for students who graduate from a program, and whether typical students who complete the program end up with high-debt-burdens, and therefore may be at elevated risk for associated adverse borrower outcomes. On the Department's program information website, a program's outcomes under the D/E rates and EP metrics will be provided to students alongside other financial value information to help students understand how the program may help in achieving their goals. As a steward of taxpayer funds charged with ensuring the proper administration of the title IV, HEA programs, the Department seeks to require that students are aware of such information before they enroll in programs with high-debt burdens. For non-GE programs, we do not limit aid or eligibility for such programs but allow students to decide whether, upon considering this information, the program has value to them.

Change: None.

Comments: Commenters also suggested that focusing on relative education debt could harm some students by encouraging them to limit education loan borrowing by sacrificing basic needs like food and housing or promoting some type of employment even when attending school full time.

Discussion: We believe it is reasonable for students to know what the average education debt and earnings are for an educational program and believe that this information can be considered along with many of the other factors suggested by the commenters. The information the Department will present is not describing debt as bad or to be avoided. Rather, it is giving students information about how affordable their debt payments will be based on the typical earnings of students in their programs. Students deserve to be aware of this information, and institutions have the capacity to control their pricing to avoid subjecting their students to unaffordable debts.

Changes: None.

Potential Impacts on Lower Earning Fields

Comments: Commenters suggested that focusing on program earnings takes a narrow view that higher education is primarily about securing a job and misses the value of a liberal arts education and the value to society from those graduates. Some commenters emphasized that many students pursue careers in fields that help people such as social work, counseling, leadership, teaching, and a variety of cosmetology programs including hairstylists and estheticians. Nursing was another field where commenters noted that some institutions prepare instructors and practitioners to work in health care services where some jobs would not produce high earnings. Commenters also suggested that teaching programs should be excluded from application of the GE program accountability framework.

Discussion: The Department does not agree that providing information about education debt and average earnings for program graduates to students and families ignores the value of programs that may have lower earnings outcomes. Again, the Department is attempting to make debt and earnings information available to students and families on a comparable basis for programs so that they can use it to support the different career choices that may be under consideration, or to find a program within a particular field that is most beneficial to them.

As we demonstrate in Table 4.11 in the RIA, most programs in most fields pass the D/E rates measure, including programs that provide training for occupations in healthcare. In healthcare (Health Professions and Related)—the program cited by the commenters—8.2 percent of GE programs did not pass the D/E rates or the EP measure and 2.0 percent of non-GE programs did not pass the D/E rates or the EP measure. Similarly, education training programs ( i.e., programs with a two-digit CIP code of 13) are less likely to fail the D/E rates or EP measure than other programs. We note that teaching programs that successfully place their students in teaching jobs are unlikely to fail to meet the earnings premium criteria. For example, data from the National Education Association's Teacher Salary Benchmark Report indicates that among reporting school districts, approximately 76 percent of teachers worked at schools that offered a starting teaching salary of at least $40,000. Even States with lower salaries have average starting salaries at least $5,000 higher than the State's EP threshold.

See Nat'l Ed. Ass'n (2022). Teacher Salary Benchmarks ( www.nea.org/resource-library/teacher-salary-benchmarks ).

See Nat'l Ed. Ass'n (2022). Teacher Salary Benchmarks ( www.nea.org/resource-library/teacher-salary-benchmarks ).

The Department fundamentally disagrees that ignoring the financial implications of students' college choices is an acceptable or necessary strategy to ensure that students pursue jobs in critical fields to society.

Changes: None.

Comments: Some commenters contended that publication of the financial value metrics could limit access to, or discourage students from enrolling in, arts and performing arts programs. These commenters stressed that these careers should be available to all and not just to affluent students who can attend without Federal financial aid.

Discussion: The Department believes that students of arts programs will benefit from consistent information about the typical debt and earnings experienced by a program graduate, particularly if the D/E outcomes for program graduates are in a range associated with high likelihood of student loan default. For non-GE programs, receiving this information does not preclude their ability to attend the program—it simply alerts them to the potential risk based on the program's students' outcomes. Approximately 12 percent of arts programs are GE programs.

Arts programs that fall under GE regulation have a failure rate that is similar to GE programs overall. According to the Program Performance Data (PPD) described in Table 4.11 of the RIA, 5.3 percent of all GE programs fail due to D/E, EP, or both. Among the 1,042 GE arts programs (programs with a two-digit CIP code of 50), a similar share, 5.5 percent, have a failing status. Among the 7,518 arts programs that are non-GE programs, failure rates are slightly higher than for programs overall, but still relatively low. Using the PPD, 1.2 percent of all non-GE programs fail debt-to-earnings (DTE), EP, or both, and 3.7 percent of arts programs fail.

Although commenters acknowledged that arts careers are financially undercompensated relative to other career paths, federally aided students enrolled in arts programs tend to come from backgrounds similar to students enrolled in other programs, indicating that, among federally aided students, students from economically disadvantaged backgrounds are not currently dissuaded from pursuing a career in the arts. For example, the share of students who are Pell recipients within arts programs is broadly similar to the share of recipients overall across programs (Table 1.1). Institutions that are concerned that financial transparency will dissuade students from lower-income backgrounds from pursuing arts degrees could take steps such as packaging additional aid for students pursuing arts programs. This would decrease the risk of a high DTE and potentially mitigate the effect of lower typical salaries in the first few years of an arts career.

Table 1.1—Mean and Median Pell Share, Across Programs

All programs Arts programs (CIP2 = 50)
Mean (%) Median (%) Number of programs Mean (%) Median (%) Number of programs
Credential Level: Undergraduate 18,033 453
(UG) Certificates 53 60 45 40
Associate 61 67 25,807 64 69 1,248
Bachelor's 38 36 47,643 41 40 3,792
Total 47 50 91,483 47 48 5,493
Source: 2022 Program Performance Data.

Changes: None.

Comments: Some commenters expressed concern that the focus on debt-to-earnings and earnings could lead students and prospective students to prioritize salary over public service. By publishing these data and possibly categorizing certain programs as “low value,” we may discourage students from pursuing careers that are less lucrative but that have substantial value, such as careers in government or the nonprofit sector.

Discussion: The Department acknowledges the concern that students may be dissuaded from pursing programs, and ultimately, careers, that are primarily in the public sector or with nonprofit organizations. National data from the American Community Survey (ACS) on earnings by sector show, however, that the typical associate or bachelor's degree graduate working for government or a nonprofit substantially out-earns similarly aged workers with only a high school credential (Table 1.1). We estimate that a government worker with an associate degree has median earnings more than $13,700 higher than the overall median earnings for those with a high school diploma. A government worker with a bachelor's degree has earnings that are more than $19,100 higher. Those working in the nonprofit sector earn around $7,100 (associate) and $15,200 (bachelor's degree) more relative to similar workers with a high school diploma.

Table 1.2—Median Earnings, Workers in Labor Force Age 25–34

Credential Overall Private sector Federal, state, or local govt. Nonprofit sector
High School or Equivalent $25,453 $25,569 $31,961 $21,582
Associate Degree 32,049 31,961 39,200 32,580
Bachelor's Degree 45,811 48,870 44,638 40,725
Graduate Degree 49,639 52,147 47,941 45,000
Source: American Community Survey, 2019, 5-year estimates.

These data indicate that workers within a given degree level tend to have relatively similar earnings across private sector, government, and nonprofit employers. And for those with an associate degree, employment within a Federal, State, or local government yields higher median earnings than employment in the private sector. While working in the private sector is more lucrative, at the median, for bachelor's degree and graduate degree holders, these differences are much smaller than the difference relative to the earnings premium threshold at the national level.

Changes: None.

Comments: A few commenters expressed concern that publication of financial value metrics could deter students from graduate education. Given differences in student loan eligibility and available Federal aid, commenters suggest that the proposed financial value metrics do not align well with the goals and earnings trajectories of those who enroll in graduate education.

Discussion: The Department aims to provide students with accurate information to help inform their choices. We acknowledge that some students might decide that not attending school might be the best option after obtaining the information.

Graduate students are eligible to borrow up to the cost of attendance for their program, while undergraduates are subject to substantially lower limits on borrowing, depending on their enrollment level and status as a dependent or independent student. Because of the increased eligibility for student loans and their generally higher earnings outcomes, graduate programs that do not pass the GE thresholds typically fail the D/E standard of the GE rule, rather than the EP.

The Department believes that the D/E metric is valid across both undergraduate and graduate programs. As noted above, few graduate programs have median earnings below the typical high school student, but many programs have very high debt levels due to the lack of loan limits. This can make debt unaffordable even on a middle-class salary. Moreover, from a taxpayer perspective, as shown in Table 2.10 of the RIA, D/E is highly correlated with the taxpayer subsidy on student loans—if debt is high relative to earnings, it is unlikely a borrower will fully payoff their loans while on an income driven repayment plan.

The Department also notes aspects of the rule that are favorable to graduate programs. First, the debt used in the actual D/E calculations will be capped at the total net cost for tuition, fees, and books. This cap particularly affects graduate programs, as many graduate students borrow substantially for living costs in addition to direct costs of the program. As we note in the RIA, we do not have data reported by institutions to estimate directly how this cap will affect the share of programs that pass the D/E rates. An analysis by New America, however, suggests that the debt cap might reduce the number of graduate programs projected to fail in the RIA substantially by about 50 percent. Because institutions have more control over direct program costs, some institution concerns about graduate financial value metrics will likely be mitigated. Furthermore, in the D/E rates calculation, graduate debt is amortized over a 15-year repayment period for master's degree programs and over a 20-year period for doctoral and first professional degrees. The use of a longer repayment period acknowledges the possibility that long term earnings are higher in proportion to earnings measured 3 years after graduation, the potentially larger amounts of debt that some graduate students may take on and allows for smaller annual payments based on a longer repayment period. We address additional concerns relevant to graduate programs, such as licensing and residencies for graduate programs that may result in lower initial earnings due to externally imposed constraints, in other sections of this preamble.

See Caldwell, Tia & Garza, Roxanne (2023). Previous Projections Overestimated Gainful Employment Failures: Almost All HBCUs & MSI Graduate Programs Pass. New America ( https://www.newamerica.org/education-policy/edcentral/ge-failures-overestimated/ ).

Changes: None.

Comments: Some commenters noted that many jobs in the entertainment industry may be impacted by the financial value and transparency regulations, given that a number of students in those fields are dependent upon Federal education assistance. The commenters suggested that those students may become more restricted in their opportunities to pursue careers in performing arts, music and education compared to students from more affluent families. Commenters noted that in general, the United States provides less support for students of the performing arts compared to other countries, and further opined that the lower wage for these jobs is beyond the control of the institutions providing those programs, notwithstanding the contributions those jobs make toward creativity and societal wellbeing.

Discussion: We recognize that educational programs can provide long term value and enrichment to students in multiple ways, and that some student may be interested in arts and entertainment careers for non-pecuniary reasons. We nonetheless note that the education debt and program earnings experienced by program graduates at specific institutions are a significant up-front consideration for any student to consider. Students looking at particular programs offered at multiple institutions may also consider the relative education debt and program earnings when selecting an institution. Institutions may also use the information about average education debt and earnings to consider program changes that would better serve students entering into careers with relatively large education debt compared to the near-term earnings. We appreciate the commenters' concerns about the level of support for performing arts relative to other countries, but respectfully note that such broader issues of the economic and social value of performing arts are beyond the scope of this rule.

Changes: None.

Data Concerns and Other Information or Metrics

Comments: Several commenters suggested including measures of student satisfaction among the other measures listed in § 668.43(d)(1)(ii) to include on the program information website to provide context for the financial value measures.

Discussion: We recognize that there are many factors students consider when choosing to enroll, or continue, in a program, and also that education can confer many benefits beyond financial value, including satisfaction with the program. However, we are here focused on factors that affect students' financial well-being, and the return on the title IV, HEA financial investment. Low earnings and high debt burdens can negatively affect students who might benefit in other ways from their programs. More generally, measures of student satisfaction do not exist for all programs and the Department has no way of collecting such data in a systematic fashion at present.

Changes: None.

Comments: A few commenters noted that program-level graduation rates could have a substantial impact on financial value measures. They noted that a program that graduates a small share of enrolled students may have strong financial value measures, but overall financial value results may be poor for those who never completed the program. The commenters suggested that we provide information on the likelihood of completing the program as important context for the financial value metrics.

Discussion: The financial value metrics measure the earnings and debt only for those who complete a given program. The Department believes that these measures best represent the outcomes for a student who naturally anticipates to complete a given program. Enrolled students who do not complete could have outcomes that are worse overall than those for completers, but this is not necessarily the case. For example, non-completers could leave a program because they were offered a job that pays more than they anticipate they would earn if they completed their program. Further, those who do not complete a program are likely to leave with less debt than those who do, potentially lowering D/E measures.

At present, program-level graduation rates are not consistently measured or collected by the Department. Measurement of program graduation rates raises several measurement challenges. For example, some bachelor's degree programs do not formally consider a student part of a program or major until their sophomore or junior year, which could substantially skew the graduation rate relative to a program which counts students starting from their freshman year. Still, the Department strongly agrees with the importance of holding institutions accountable for program completion and will explore development of accurate measures. The rule includes completion rates at the institution or program level among a set of important contextual information that may be included on the program information website.

Blagg, Kristin & Rainer, Macy (2020). Measuring Program-Level Completion Rates: A Demonstration of Metrics Using Virginia Higher Education Data. Urban Institute: Washington, DC ( www.urban.org/sites/default/files/publication/101636/measuring_program-level_completion_rates_1_3.pdf ).

Changes: None.

Comments: A few commenters requested that the Department include on the program information website information on cohort default rates, or a program's loan repayment rates, as additional context regarding a student's ability to manage or repay their debt.

Discussion: We agree that a program's loan repayment rate may be important information for students or taxpayers, and we note that this information was included in the list of proposed information under § 668.43(d)(1).

Although the cohort default rate (CDR) is an important measure of institutional accountability in ensuring that students do not experience exceptionally high default rates after leaving a program, an overall CDR does not measure outcomes of a given program. Moreover, graduate PLUS loans are not included as part of the CDR calculation, so these rates do not capture borrowers' outcomes even for broad sets of graduate programs. The Department will carefully consider what borrower outcome information will provide students with the clearest sense of the financial risks of their program choices, including whether institution level measures may be appropriate to provide where program level measures may be unavailable.

Changes: None.

Comments: Several commenters noted that high percentages of their career program graduates work in the fields associated with their training, unlike many students with associate degrees from public and nonprofit institutions that get jobs in unrelated fields. Commenters also noted that other jobs such as sales often start with lower salaries that increase over time as they learn their trades on the job.

Discussion: The regulations do not track earnings by source but provide some measure of the average education debt and average earnings that program graduates have. Graduates of career training programs who work in those fields may experience higher earnings than program graduates from nonprofit and public institutions who work in unrelated fields. The regulations will provide students considering either type of program with information about the education debt and earnings associated with those programs to support them making better informed choices when they enroll.

Changes: None.

Comments: One commenter asserted that 4-year degree programs can charge students higher prices despite having no industry connections. A few other commenters noted that many students in 4-year programs are unable to get jobs, while students in shorter career and technical education (CTE) programs (which cost less) are able to get jobs.

Discussion: We agree that CTE programs are important. By ensuring that programs subject to the GE program eligibility requirements, including CTE programs, prepare students for gainful employment in a recognized occupation, we expect that the GE program accountability framework will drive improvements in CTE programs that are not providing students with earnings that allow them to afford their debt or leaving them better off than if they had not pursued a postsecondary credential. For 4-year programs that are not subject to the GE program accountability framework, students will be able to obtain critical information about their financial value, including their costs and student debt and earnings outcomes, to inform their education decision making.

Changes: None.

Comments: Some commenters suggested that the Department should play a role identifying unique missions of institutions, such as historically black colleges and universities and Tribal colleges and universities because of the social and cultural impacts these institutions provide as non-financial value.

Discussion: Under § 668.43(d)(1), the Department will provide, through a website hosted by the Department, program-level information on the typical earnings outcomes for graduates and their borrowing amounts, cost of attendance, and sources of financial aid to help students make more informed choices and allow taxpayers and other stakeholders to better monitor whether public and private resources are being well used. Nothing in the regulations precludes institutions from supplementing the financial value information provided on the Department website with additional information about the institution and its programs, including information for students and families about their missions and values. However, the Department website will be focused on financial value, consistent with the Department's obligation to administer the title IV, HEA financial assistance programs.

Changes: None.

Comments: A few commenters noted that the debt and earnings data used in the financial value transparency metrics do not precisely align with those measures presented in the College Scorecard.

Discussion: The financial value transparency metrics are designed for accountability purposes (with respect to GE programs) as well as for transparency (with respect to GE and eligible non-GE programs). Because these data serve different, though complementary, purposes the metrics are not quite the same as those in the College Scorecard although there are strong correlations between the information in the two datasets. For example, median earnings in this rule, similar to the 2014 Prior Rule, is calculated as the median earnings among all program completers including the “zeros”— i.e., individuals successfully matched in the list of program completers who have no earnings from employment. Especially for career training programs this measurement choice captures whether students find employment as a measure of program success. Similarly, median debt under this regulation is calculated by capping individual borrowing amounts at the net direct costs charged by the institution. This attempts to isolate student borrowing linked to factors more directly controlled by institutions. Still, broader measures of debt can be calculated and used for transparency purposes. The Department will carefully consider how to present information to students to avoid potential confusion.

Changes: None.

General Comments on the GE Program Accountability Framework (§§ 600.10, 600.21, 668.91, 668.601, 668.602, 668.603, 668.604, 668.605, and 668.606)

General Support and Opposition

Comments: Many commenters expressed support for building on the 2014 GE Prior Rule, including the addition of the earnings premium metric. These commenters believed that this metric would ensure that students only enroll in programs that would result in them being gainfully employed upon completing the program. Commenters also supported the inclusion of the D/E rates metric, arguing that this measure would protect taxpayers and students. Some commenters suggested that because of the rule, students will shift from enrolling at low-performing programs to programs with better outcomes, including shifting across sectors, similar to what happened when institutions with high cohort default rates lost eligibility to participate in the Federal student aid programs.

Discussion: We thank the commenters for their support.

Changes: None.

Comments: One commenter asserted that these regulations would help to protect students from taking on high levels of debt to obtain credentials with little to no value. The commenter also contended that there should be greater consequences for schools that commit fraud.

Discussion: We agree there should be greater consequences for schools that commit fraud. The Department's Office of the Inspector General (OIG) identifies and investigates fraud, waste, abuse, and criminal activity involving Department funds. Where we believe it is warranted, we can refer a situation to the OIG, which conducts criminal and civil investigations. Additionally, members of the public may report suspected fraud, waste, abuse, or criminal activity—including fraud or misuse of Federal student aid funds. The OIG maintains a telephone hotline and an online form to facilitate submission of such reports.

While these regulations do not replace other robust Department efforts aimed at ensuring program compliance and program integrity, the rule should make predatory behavior less attractive and less lucrative if poorly performing GE programs are not eligible to participate in title IV, HEA.

Changes: None.

Comments: Many commenters supported the GE rule because they believe it will help stop predatory recruitment practices that specifically target marginalized and underserved communities, including people of color, people with low socioeconomic status, single parents, and veterans. These commenters claimed that programs at these predatory schools have low graduation rates, high student debt loads, high student loan default rates, and higher tuition than comparable programs at State and community colleges.

Several other commenters expressed support for the GE accountability provisions, noting that most borrower defense loan discharges have been for students who attended for-profit institutions, and said that most accountability measures should focus on the institutions where large costs to the taxpayers have been incurred. Commenters noted that many completers from some for-profit institutions have incomes that would qualify them to make zero payments under the Department's recently proposed income-driven repayment plan and create additional costs for taxpayers.

Discussion: We thank the commenters for their support and agree the GE rules apply to programs where students need protection.

Changes: None.

Purpose

Comments: Many commenters noted that the EP and D/E metrics do not capture all the ways that programs might be valuable for students and society, and thought the measures too narrowly focused on financial outcomes.

Discussion: In the GE program accountability framework, we use the EP and D/E metrics to assess whether programs are preparing students for gainful employment, consistent with statutory eligibility requirements. But, the use of particular performance metrics pursuant to the GE provisions of the HEA and the Department's rulemaking authority is not a commentary on the values that students and others may place on postsecondary education. As we demonstrate in Table 4.11 of the RIA, the majority of programs in most fields do not lead to high debt burdens or low earnings. As a result, we do not expect the rule to deprive students of postsecondary options that offer the nonfinancial benefits of greatest importance to them.

We underscore that the rule sets minimum standards of performance for career training programs, and for informing students in non-GE programs about potential financial risk. It does not attempt to distinguish among or rate programs based on their earnings above these standards beyond providing students with information. As such, we expect that programs meeting these minimum thresholds of financial outcomes for their students will still need to demonstrate how they help students in pursuing other goals that may be important to them.

Changes: None.

Comments: A few commenters suggested that the proposed GE program accountability framework will not fix the current systemic problems. Some commenters proposed that, rather than targeting so-called “low value programs,” we should address systemic issues contributing to the student debt crisis. For example, these commenters suggested that we provide adequate funding and resources to public institutions, implement more affordable tuition models, and expand financial literacy programs.

Discussion: The Department agrees that some systemic changes are needed to address the student debt crisis. And, in a variety of initiatives, the Department is responding to that crisis. For example, the Department recently published a new rule on IDR plans for student loans. Notwithstanding the importance of addressing systemic issues, the Department is charged with implementing and enforcing the HEA limits on title IV eligibility for GE programs and has concluded that programs that leave students unable to pay off their loans, or with earnings no greater than a comparable high school graduate, are not meeting the statutory requirements for title IV, HEA funding. The final rule will make meaningful strides in deterring students from attending programs that leave them with unaffordable debt and no improvement to their earnings. As noted in Tables 4.25 and 4.26 of the RIA, most students have available many alternative programs that do not fail the metrics, and these programs are very likely to lead to higher earnings and lower debt. Therefore, we expect the rule will result in students attending programs that require less borrowing or provide a better financial value in that they will lead to higher earnings relative to the amounts borrowed.

Changes: None.

Comments: Some commenters suggested that it would be more effective to limit borrowing in low-performing programs rather than to remove all Federal funding, noting that this would still protect students from high educational debt without limiting the types of programs that are available for them to pursue their passions and career goals in fields that may not be high-earning. One commenter noted that students have differing career objectives and was of the opinion that the Department and institutions offering those programs should strike a balance to keep these options open for students, suggesting that career counseling and accurate information could support those outcomes and a diverse workforce. Other commenters said that without striking a more holistic approach in the proposed regulations, there could be reductions in program diversity and more limited student choices available. Providing more quality assurance measures and a broader evaluation of other factors, such as curriculum, student satisfaction and achievements, were suggested as additional components to use with the financial-value measures in the proposed regulations. Commenters also suggested the Department should work with the higher education community to develop alternative metrics that speak to a more holistic spectrum of success determinants.

Discussion: We agree there are many potential ways that students might be shielded from unaffordable debt or programs that fail to boost their earnings. Institutions are in the best position to limit their costs and limit student borrowing for direct costs (the subset of borrowing measured under the metrics in these regulations), and to provide counseling and guidance to students in choosing programs that prepare them for success. The Department's authority and ability to monitor curriculum quality across programs is limited. As noted elsewhere, these rules do not attempt to serve as a holistic measure of program quality. Instead, they focus on setting minimum standards aimed at ensuring that career training programs prepare students for gainful employment, and, more generally, to protect students from programs that may not improve their financial well-being.

Changes: None.

Comments: One commenter argued that controlling college costs should not be part of the Department's role, but it should instead concern itself with reining in lending. The commenter argued that the Department should set aggregate loan limits for all students to current limits for undergraduate students.

Discussion: The Department disagrees with the commenter that its role does not include encouraging institutions to offer programs that are financially valuable to students when the students' debt and likely future earnings are taken into account. The Department also does not have the ability to reduce aggregate loan limits for graduate students, since those limits are established by statute.

Changes: None.

Comments: A few commenters argued that it is not a school's responsibility to ensure that a student pays back their loans. According to these commenters, that responsibility lies with the borrower.

Discussion: The Department believes that pursuant to the GE statutory requirement, career training programs should be held responsible for ensuring the amount their students need to borrow is reasonable relative to the earnings they might expect from the career for which they are being trained. If programs set unreasonable tuition levels that lead students to borrow more than they can afford to repay, this puts borrowers at risk of default and adverse impacts on their credit and puts the taxpayer at risk of having to bear the cost of the loans. Under the D/E rates measure, institutions are not held responsible for loan repayment outcomes. Rather, the D/E rates portion of the transparency framework provides a means to assess whether debt burdens are excessive given the typical earnings of program completers, and whether students' labor market earnings improve relative to students who do not pursue postsecondary credentials. The GE accountability framework applies this metric as a condition of eligibility for career programs. As addressed below, we believe the compliance burden created by these regulations is modest and well justified by the benefits expected from the rule.

Changes: None.

Scope

Comments: Several commenters stated that it is unfair to group together all private and for-profit schools when there are only a few “bad actors” causing problems. They asserted that these GE regulations will punish schools that are acting in good faith, and that there should not be a “one-size-fits-all” solution to these bad actors. They argued that different regulations should apply to for-profit and nonprofit schools since their missions differ.

Other commenters viewed the distinction between GE and non-GE programs as unclear, and argued that instituting sanctions for some programs, but not for others, based on sector or credential type is not appropriate. Commenters highlighted that an institution's tax status was not a good reason to treat programs differently under the proposed eligibility measures and voiced some concern that institutions with failing programs could change their tax status to avoid being held accountable under the eligibility provisions. Some commenters said the proposed regulations were politically motivated to target the career training programs and suggested that more emphasis should be placed on removing Federal funds from programs that pushed false information or promoted activism and political agendas. The regulations were described by these commenters as an effort to quickly eradicate the proprietary school sector instead of proposing a set of guardrails that would have encouraged institutions to operate within that system.

Discussion: The GE accountability framework applies to gainful employment programs through § 668.601. Section 668.2 defines “gainful employment program” as an educational program offered by an institution under § 668.8(c)(3) or (d) and identified by a combination of the institution's six-digit Office of Postsecondary Education ID (OPEID) number, the program's six-digit CIP code as assigned by the institution or determined by the Secretary, and the program's credential level. This definition is consistent with sections 101(b) and 102(b) and (c) of the HEA. Under the HEA, institutions must establish program-level eligibility for each “program of training to prepare students for gainful employment in a recognized occupation.” GE programs include nearly all educational programs at for-profit institutions of higher education, as well as non-degree programs at public and private nonprofit institutions, such as community colleges. With respect to comments that some institutions may change their tax status to remove their programs from being subject to the eligibility measures, applications to do so are reviewed independently by the Internal Revenue Service (IRS) and the Department to make sure the institution qualifies as a nonprofit entity.

20 U.S.C. 1002(b)(1)(A)(i), (c)(1)(A). See also 20 U.S.C. 1088(b)(1)(A)(i), which refers to a recognized profession. For further discussion in the NPRM, see 88 FR 32300, 32306–32311 (May 19, 2023).

In addition to being statutorily obligated to confirm whether GE programs are eligible for HEA assistance, we believe that it is appropriate to protect students in GE programs in all sectors, to help protect students pursuing career training through such programs from being left with unaffordable debt or with no improvement in their labor market prospects beyond what they might have achieved without earning a postsecondary credential. The GE accountability framework is based on objective and evidence-based measures of student outcomes and, rather than being a one-size-fits-all approach, its impact on institutions is directly in proportion to the number of students they have enrolled in programs that are not serving students well based on the D/E rates and EP measures. The GE framework, applied as a measure of a program's continuing title IV, HEA eligibility, will be similarly applied to all GE programs, regardless of location or student demographics. GE programs will be held to the standards for GE programs uniformly, regardless of whether they are taught at public, proprietary, or nonprofit private institutions.

The Department does not have authority to expand the definition of a GE program to include non-GE programs. The financial value transparency framework is the Department's attempt to account for eligible non-GE programs, by providing students in such programs with important information. Other statutory provisions apply more broadly to GE and non-GE programs, and the Department will use the tools at its disposal to protect students and improve outcomes. For example, we are also addressing eligible non-GE programs through other Department initiatives, such as the final rule we published last year on Change in Ownership and Change in Control.

87 FR 65426 (Oct. 28, 2022).

Changes: None.

Comments: Several commenters asserted that the Department could require the eligibility framework to apply to all programs, based upon the Department's authority under 20 U.S.C. 1087d(a)(4) or 20 U.S.C. 1087d(a)(6), to include additional conditions necessary to protect the interests of the United States when approving an institution's participation in the Direct Loan programs. Other commenters said it is arbitrary for the Department to treat comparable programs differently and suggested that this different treatment violated a requirement in the HEA that the Department's regulations must be uniformly applied and enforced.

Discussion: We disagree with the commenters' suggestions and criticism. The Department must use its statutory authority in ways that accord with the various distinctions drawn in the HEA. The HEA conditions eligibility of some, but not all, programs on preparing students for gainful employment in a recognized occupation or profession. The commenters did not explain how those HEA provisions regarding GE programs fit with the commenters' suggested use of the HEA provisions regarding program participation agreements. Likewise, we disagree with commenters' arguments regarding uniformity in Department regulations. The commenters did not identify a basis for their recommended conclusion in 20 U.S.C. 1232(c), which refers to uniform application and enforcement throughout the 50 States rather than across program types. Nor did commenters identify any other statutory provision that requires GE program regulations to bind non-GE programs. In addition, linking the program accountability framework to the Department's Direct Loan authority as the commenters suggest would exclude programs that do not participate in the Direct Loan program. The commenters may prefer that gainful employment results be expected of non-GE programs, and we understand the policy considerations associated with that issue, but we lack persuasive reasons to conclude that the Department's regulations must adopt that position as a matter of law.

Changes: None.

Comments: Several commenters stated that the proposed GE Accountability framework fails to account for the significant and multiple economic, social, and governmental differences between Puerto Rico and the United States. For example, these commenters stressed that Puerto Rico has no community college system and relies on proprietary institutions to provide a significant and varied portion of career-oriented educational opportunities. Therefore, these commenters advised that proprietary institutions in Puerto Rico award a far higher proportion of the island's postsecondary credentials than is the case on the mainland. The commenters contended that the proposed rule would place access to such programs in serious jeopardy. These same commenters stated if implemented as-is, without accounting for Puerto Rico's unique circumstances and challenges, the population, economy, and multiple industries on the Island will be adversely and irreparably harmed.

One commenter emphasized the ways in which earnings measurement issues are more a particular concern given the unique challenges facing Puerto Rico, stating that the justifications offered by the Department for not including an alternate earnings appeal fail to acknowledge the unique nature of Puerto Rico's economy. Citing the Department's claim that making accommodation for under-reporting of income would “differentially reward programs,” the commenter submitted that the desire to be evaluated based on accurate data is not a desire to be rewarded but to address the fact that nonreporting and underreporting of income are widely recognized challenges facing Puerto Rico.

Discussion: As we noted in the NPRM, the Department is aware that, in some cases, using earnings data for high school graduates to estimate an earnings threshold may not be as reliable as the earnings data from the ACS, and welcomed comment on what data might be available to estimate the threshold in U.S. Territories. In response to the commenters' concerns, the Department further investigated issues of data quality in Puerto Rico as well as other U.S. Territories and the freely associated states.

See 88 FR 32300, 32333 (May 19, 2023).

Through this investigation, we identified several concerns with data elements used in the rule with regard to their application to programs at institutions in U.S. Territories and freely associated states. First, there is no robust source of earnings information in most U.S. Territories that would allow us to measure high school earnings. While we considered using a different threshold, such as 150 percent of the Federal Poverty Level, available data (data on high school earnings from the Puerto Rico Community Survey) suggested this approach would yield a threshold that is dramatically higher than high school earnings. While data do exist for Puerto Rico, the coverage rate of the Puerto Rico Community Survey (PRCS) is significantly lower than that of the ACS. Moreover, the Federal Poverty Line (officially known as the poverty guidelines), used in the calculation of discretionary debt-to-earnings measures is not defined for the U.S. Territories and freely associated states. The Federal Poverty Line is a component of the D/E metric, used to define “discretionary earnings” by subtracting an estimate of the income required for necessary expenses. As a result, the Department is not confident that the thresholds used to determine an affordable amount of debt in the D/E rates calculations are appropriate for programs in these locations.

According to the Census, in the 2021 ACS and PRCS the coverage rate in Puerto Rico is 80.9 percent, relative to 94.5 percent in the United States and Washington, DC. The lowest state (Alaska) had a coverage rate of 88.0 percent. See www.census.gov/acs/www/methodology/sample-size-and-data-quality/coverage-rates/index.php. These figures indicate that Puerto Rico is an outlier.

Because of these concerns, the Department will exempt all programs located in the Territories or freely associated states from most of the requirements in the transparency framework under subpart Q, and from the GE accountability provisions under subpart S. We will still require such programs to comply with the reporting requirements in § 668.408, will still follow the procedures in §§ 668.403(b) and (d) and 668.405(b) and (c) to calculate median debt and obtain earnings information, and will include debt, earnings, and price information on the Department's program information website established in § 668.43.

Changes: We have revised § 668.401(b) to exempt the Territories and freely associated states from the application of subpart Q, except that such institutions remain subject to the reporting requirements in § 668.408 and the Department will follow the procedures in §§ 668.403(b) and (d) and 668.405(b) and (c) to calculate median debt and obtain earnings information for their GE programs and eligible non-GE programs, and we have revised § 668.601(b) to exempt the Territories and freely associated states from application of subpart S.

Comments: Some commenters urged the Department to exempt medical schools from the GE program accountability framework given the higher levels of borrowing students experience in those programs and the higher earnings later associated with those careers after physicians complete their residencies. Similar suggestions came from commenters to exclude law schools from the eligibility measures because the accreditation process provides oversight of admission standards, monitors faculty providing the coursework, reviews the academic engagement of the students, and sets benchmarks for graduates to pass the bar exams. These commenters believe that the law school accrediting process ensures students obtain long-term value from their legal education.

Discussion: As discussed in more detail in the Post-graduate Training Requirements section of this preamble which modifies the definition of the cohort period and adds a definition of a qualifying graduate program in § 668.2, these regulations already accommodate the commenters' concern about medical schools, by using a longer time horizon over which to measure graduates' earnings—six-years post-graduation rather than three. We do not agree that the accreditation process by itself provides adequate guardrails to ensure that students are not left with unaffordable debt or very low earnings. This is readily apparent in the Department's data, showing many accredited programs leave students with unaffordable debt.

Changes: None.

Comments: A few commenters requested that embedded certificates, stackable credentials, and transfer associate degrees be exempted from GE determinations because these programs are intended to combine into larger degree programs which, for public and nonprofit institutions, would not be subject to the GE accountability framework. One commenter requested further clarification about the treatment of certificates that are fully embedded into a degree program, in which students are not able to enroll in just the certificate program. The commenter was unsure of the extent to which a public/not-for-profit institution would need to report on students in a certificate program that is both embedded in a degree program and also available as a stand-alone certificate program.

Discussion: The metrics used for evaluating whether a program leads to gainful employment are based on students who complete various credentials at an institution, and if a student completes multiple credentials, they would typically only count in the metrics of the highest credential they earn. A student completing several stackable credentials would generally be included in the earnings and debt cohorts of their last or highest credential completed. Students completing a program with intermediate credentials may have higher program costs that would impact the debt outcome calculations for the program since the debt students accumulate at the same institution is generally all included.

We disagree that such programs should be exempted from the GE framework. If a student does take several intermediate credentials before obtaining a higher degree, then the student's cumulative debt and earnings outcomes are all, appropriately, associated with the higher credential. If they complete an intermediate credential but do not obtain the ultimate intended degree, then their debt and earnings outcomes are attributed to the last or highest credential they obtained.

Changes: None.

Comments: Some commenters suggested that credit-bearing non-degree programs at public and nonprofit institutions should be excluded from the eligibility framework if the institutions offering those programs also offered certified degree programs that used the identical CIP codes as the non-degree programs, particularly when there was overlap in the courses offered for the non-degree and degree programs that shared the same CIP code.

Discussion: We do not believe a such an exclusion is warranted. If students separately enroll in a certificate program at the institution, that program is a GE program for purposes of the eligibility framework. If students in a public or nonprofit program take courses in these programs but ultimately earn a credential, then those students will not be counted as they are not graduates of the program.

Changes: None.

Comments: Some commenters suggested that graduate programs not be included in the accountability framework because of the volatility of graduate career paths. Other commenters noted that doctorate programs leading to licensure should be excluded because the students are more mature and should have more experience in evaluating and selecting educational programs. Other commenters claimed that graduate Federal education funds were not included when proprietary schools were approved to participate in the grant and loan programs so there was no congressional design to apply the gainful employment requirement on those programs when they were subsequently made available to proprietary institutions. Other commenters drew the opposite conclusion, that graduate programs became eligible for student aid without any exception to the gainful employment requirement for degree programs offered by for-profit institutions. Those commenters suggested that the higher debt levels associated with many graduate programs favor using the eligibility framework to assess program earnings, describing those graduate programs as the highest priced, highest debt programs in the postsecondary educational system.

Discussion: Graduate programs offered by for-profit institutions and graduate non-degree programs offered by public and nonprofit institutions are subject to the GE program requirements in the HEA. Given high and growing graduate borrowing levels, which often do not correlate highly with earnings outcomes, the protections of the GE rule are necessary for graduate students. That said, we also agree that there are some considerations, such as postgraduation training requirements, required before a program's impact on earnings can be realized that are unique to graduate programs. We discuss those considerations in the “Measurement of Earnings” section, below.

Changes: None.

Comments: One commenter thanked the Department for confirming that comprehensive transition and postsecondary programs are excluded from the D/E rates and EP measures.

Discussion: We thank the commenter for noting agreement with the exclusion of students in these programs from the calculation of D/E rates and EP measures under §§ 668.403(c)(6) and 668.404(c)(6).

Changes: None.

Comments: Commenters objected to measures where the program outcomes in the proposed regulations would be based on periods before those regulations were in effect, saying it would be unfair to sanction institutions under the eligibility measures based upon program and pricing decisions that could not be undone or modified now. These commenters claimed that the resulting metrics would not account for program changes made in the intervening years and would, therefore, not be useful to prospective students. Commenters suggested that it would be fairer to only use outcome measures for informational purposes when the rates were based on periods before the regulations are in effect. Some commenters suggested that sanctions could not be based on retroactive periods without more explicit congressional authorization.

Discussion: The program information website and eligibility determinations based on past program performance, even performance that predates the effective date of the regulations, do not present a legal impediment to these regulations. A law is “not retroactive merely because the facts upon which its subsequent action depends are drawn from a time antecedent to the enactment.” This principle applies even when, as is the case with these regulations, the statutes or regulations at issue were not in effect during the period being measured. This principle has been confirmed in the context of the Department's use of institutional cohort default rates. The courts in these matters found that measuring the past default rates of institutions was appropriate because the results would not be used to undo past eligibility, but rather, to determine future eligibility. As with the institutional cohort default rate requirements, as long as it is a program's future eligibility that is being determined using the D/E rates and EP measure, the assessment can be based on prior periods of time. Indeed, the court in APSCU v. Duncan rejected this retroactivity argument with respect to the 2011 Prior Rule.

Reynolds v. United States, 292 U.S. 443, 449 (1934).

Career College Ass'n v. Riley, No. 94–1214, 1994 WL 396294 (D.D.C. July 19, 1994).

Ass'n of Accredited Cosmetology Schools v. Alexander, 979 F.2d 859, 860–62 (D.C. Cir. 1992).

Pro Schools Inc. v. Riley, 824 F. Supp. 1314 (E.D. Wis. 1993).

See, for example, Ass'n of Accredited Cosmetology Schools, 979 F.2d at 865.

Moreover, we believe that the program information website is of interest to current and prospective students, even when based on historical data, and provides helpful insight to students when comparing and selecting among program offerings. We further maintain that the transparency framework will be immediately useful to students, prospective students, institutions, and the public, by filtering out low-financial-value programs and enhancing competition among other programs.

Changes: None.

Comments: Some commenters believed it would be better to establish the financial value transparency framework for all institutions and not use that information for eligibility purposes until better data becomes available over time to monitor the results and assess the program outcomes.

Discussion: The Department disagrees that available data are not suitable to the task of measuring gainful employment. The Department has now over a decade of experience assessing the quality of program level measures of earnings and debt outcomes and is confident that both the earnings premium measure and debt to earnings measure capture the relevant dimensions of program performance. As we discuss elsewhere in this rule and in the NPRM, we believe that the transparency framework is critical, but that the GE eligibility provisions created by this rule provide critical additional protections for students and taxpayers in career training programs.

Changes: None.

Potential Impacts

Comments: Some commenters suggested some contradiction in policy measures like the transparency and GE accountability provisions in the rule that could discourage students from public service careers while also rewarding public service through loan forgiveness at a later career point. Commenters also recommended excluding public service educational programs whose graduates would qualify for Public Service Loan Forgiveness to avoid decreasing the number of graduates in fields that are already experiencing supply constraints.

Discussion: As noted elsewhere, the goal of these regulations is to ensure programs are not leaving students with unaffordable debt or with no enhancement to their earnings. Programs should ensure their students' do not need to borrow excessively, regardless of what repayment options may be available to them based on their career choices after graduating. In most cases, we expect that programs will serve both students likely to pursue public sector employment and students who will not enter the public sector, and all students should be protected from unaffordable levels of debt.

Changes: None.

Comments: Several commenters expressed concern that the GE program accountability framework would lead to the closure of smaller colleges and vocational schools serving students who may not thrive in traditional university settings. One of these commenters viewed the measures as discrimination against students who do not want a traditional college education and who want to work in the service industries.

Discussion: The Department disagrees with the commenters. The calculation and application of the D/E measure and the EP measure do not vary based upon the size of the institution or the type of learning environment it provides in its programs. They only vary to ensure there are sufficient students in the data to calculate results. The effects of the rule are driven by whether a program provides sufficient financial value, and there are many small institutions whose programs pass these metrics as well as larger institutions that see their programs fail. We also disagree that the rules discriminate based upon the type of postsecondary experience sought by students. There are significant numbers of all types of programs that pass the GE measures as shown in the RIA. The commenters did not provide any evidence as to how the non-traditional nature of the program could be expected to affect either the amount of debt students take on or their earnings.

Changes: None.

Comments: One commenter claimed that the regulations would lead to students shifting from larger institutions to smaller institutions that do not participate in title IV, HEA programs. The commenter further claimed that non-participating programs do not need to maintain any basic standards and therefore students will not be protected if they attend those schools.

Several other commenters also suggested that students dependent upon Federal student aid could be harmed if some institutions continued to offer programs that lost eligibility to students that could afford them without Federal student aid. Some commenters noted that programs at risk of losing Federal student aid might also lose access to State grants and further erode student access to some lower earnings programs.

Discussion: The Department expects one outcome of these regulations will be an enrollment shift from low-financial-value to high-financial-value programs or, in some cases, away from low-financial-value postsecondary programs to non-enrollment. It is also possible that some students will shift from low-financial-value postsecondary programs to programs where they cannot obtain title IV, HEA aid, though such transfers will likely be limited by the lack of Federal aid available to students at such programs. There is limited information about the outcomes of students at non-participating programs, making it difficult to estimate the consequences of such transfers (although research cited in the RIA finds that among cosmetology programs, non- participating programs have lower prices but similar licensure passage rates). However, the Department believes that the rule will lead to net benefits, as we expect that the availability of higher quality information about program-level student outcomes, and the loss of title IV, HEA eligibility by low value GE programs, will result in fewer defaults, higher earnings for students, and additional tax revenue for Federal, State, and local governments.

Changes: None.

Comments: One commenter argued that, in the NPRM, the Department promoted a false narrative that higher education is not a pathway to success for students and their families. This commenter worried that if we enact these rules, there will not be students qualified to fulfill workforce needs.

Discussion: The Department disagrees. As we noted in the NPRM, most postsecondary programs provide benefits to students in the form of higher wages that help them repay any loans they may have borrowed to attend the program. We believe that all students benefit from the availability of information about a program's debt and earnings outcomes provided under the financial value transparency framework. Moreover, by only providing title IV, HEA funding to GE programs that meet the GE eligibility requirements, the Department is encouraging students to pursue career pathways in higher education that will result in them being gainfully employed. It will provide students a pathway to success within higher education that does not leave them unable to pay their debt or with earnings no greater than a comparable high school graduate.

88 FR 32300, 32306 (May 19, 2023).

Changes: None.

Comments: Many commenters expressed that, by denying title IV, HEA eligibility to failing GE programs, the GE regulations will limit school choice for students. These commenters argued that students should choose where to attend school without being deterred by a lack of funding. Commenters asserted that it is unfair to limit student choices for educational programs by using the GE program accountability framework, and that doing so will perpetuate an uneven playing field for the for-profit institutions. One commenter opined that the GE program accountability framework will drive up the cost of higher education because it will reduce the number of schools available and decrease competition.

Commenters suggested that a better approach would be to provide more guidance and accept alternate measures of success for a GE program, such as graduation and placement rates, or establish more stringent requirements for those institutions with higher cohort default rates. Commenters asserted that graduation rates reported by the National Center for Educational Statistics (NCES) show that proprietary schools have higher graduation rates for first-time, full-time students for two-year programs of over 60 percent, compared to 52 percent for private nonprofits and 29 percent for public institutions.

Discussion: The Department disagrees. By implementing the GE program accountability framework, the Department is protecting students from attending programs that leave students with unaffordable debt or earnings not more than comparable high school graduates. As explained further above, we do not believe such programs meet the HEA requirements for participating in title IV, HEA as GE programs. Those programs must prepare students for gainful employment in a recognized occupation or profession, and the accountability framework adopted here is designed to implement the applicable statutory provisions with clear and administrable rules that test for earnings enhancements and affordable debt. In addition, the GE program accountability framework, rather than limiting school choice, will improve the choices available to students and, at the same time, protect the interests of taxpayers and the Federal Government.

For several reasons, the Department does not agree that the rule will cause increases in tuition by reducing the number of educational options available to students. The GE accountability provisions of the rule, in part, target programs with high debt relative to earnings. We expect the primary impacts of the rule to be (1) encouraging institutions with high D/E programs to reduce their tuition or arrange for their students to receive greater grant support to reduce borrowing, and (2) making ineligible for participation in title IV, HEA student aid those GE programs that have particularly high costs to students, leaving more affordable options in other programs with better outcome measures. More generally, the fact that so much variation in debt exists across programs that are in similar fields with similar earnings levels suggests strongly that competition across such programs for students may play a limited role in keeping tuition low.

We expect that programs that are low performing under the framework will take steps to improve, to avoid a loss of title IV, HEA eligibility. As shown in the RIA (see Tables 4.25 and 4.26), most students who enroll in a GE program projected to fail the D/E rates or EP measure have better options available to them in a similar field nearby or, possibly, at the same institution. On average, these alternative options leave graduates with 43 percent higher earnings and 21 percent less debt. Accordingly, rather than restricting the educational and professional choices of those considering career-focused programs and causing cost increases due to reduced competition, we believe the GE program accountability framework will lead to overall improvement in the career program options available to students and in the financial outcomes for those students.

See the section in the RIA titled “Alternative Options Exist for Students to Enroll in High-Value Programs.”

Nor has the Department ignored the value of student choice. The financial value transparency framework will provide average education debt and earnings information about degree programs offered at nonprofit and public institutions to help students and families make informed choices, while the GE program accountability framework will ensure that GE programs are meeting eligibility thresholds in accord with applicable statutes. Again, the GE program accountability framework is based on the GE provisions of the HEA that differentiate between career training programs and other eligible programs by conditioning the title IV eligibility of career training programs on their meeting the gainful employment requirement. We believe it is appropriate to set eligibility thresholds for these programs to ensure they meet the HEA requirements, and that these thresholds will promote better outcomes for students and encourage institutions to improve the outcome measures for marginal programs. By providing equivalent information about programs not subject to the GE eligibility requirements, the financial value transparency framework will promote better comparisons of comparable programs offered at different institutions for students looking at multiple institutions.

We also disagree with suggestions by commenters to adopt measures such as graduation or placement rates instead of the D/E rates and EP measures or to create stronger conditions around cohort default rates. While we agree that graduation rates are an important piece of information, they are insufficient for ensuring that programs prepare students for gainful employment in a recognized occupation. The measures in the GE program accountability framework are based upon students who graduate and received title IV, HEA aid, and the data included in the NPRM and this final rule show that even when looking only at graduates, there are too many programs that leave students in a situation where they are no better off than if they had never attended postsecondary education or they have debt that they cannot afford to repay. Restricting our analysis to graduation rates would overlook these concerning results. Broadly, we do not view a high completion rate as evidence that a program prepares its students for gainful employment if most graduates struggle in the labor market or cannot afford their debt.

Placement rates exhibit similar shortfalls. While they can be useful indicators of results, not every program is directly tied to a specific set of occupations and, thus, such measures may not always be appropriate. Moreover, calculating placement rates is burdensome and time consuming for institutions compared to the GE program accountability metrics. Further, we do not believe that job placement is proof that a program is preparing students for gainful employment in a recognized occupation, if graduate earnings are no better than if they had never attended postsecondary education or if they nonetheless have debts they cannot afford.

Regarding default rates, the Department is concerned about the negative effects of default on borrowers, so we are taking steps to lessen the likelihood of default, even if the institution does nothing to improve its offerings. For instance, in the final rule improving income-driven repayment, we instituted regulatory provisions that would allow for the automatic enrollment into income-driven repayment of borrowers who go at least 75 days without making their scheduled payment and who have granted us the approval for the disclosure of their Federal tax information from the IRS. We have also created the new Saving on a Valuable Education (SAVE) plan, which increases the amount of income protected from payments, which will give more at-risk borrowers a $0 payment and prevent many from defaulting. While these provisions provide critical benefits for borrowers, they underscore the importance of additional measures of program outcomes beyond default rates to assess whether programs are preparing students for gainful employment.

88 FR 43820 (July 10, 2023).

Changes: None.

Demographics and Outcomes

Comments: Many commenters raised concerns about how the demographics of students at programs could lead to unfairness in the calculation of earnings or debt at programs with diverse student bodies. For example, several commenters raised the issue of wage discrimination that affects the earnings of racial and ethnic minority students and women. Because of this labor market discrimination, some commenters argued that programs that serve widely discriminated-against students and communities will be disadvantaged in the calculation of earnings relative to programs that serve fewer students from communities facing discrimination. Several commenters also claimed that the high school earnings threshold reflects in large part the gender composition of the high school completer workforce in each State, which, if largely male, may not be an appropriate comparator for postsecondary programs that predominantly graduate women. Many commenters argued that schools that educate a large population of low-income or low-wealth students will have higher debt-to-earnings ratios, since such students are more likely to borrow. Another commenter suggested that the Department should apply a “Pell Premium” to institutions with high populations of low-wealth students. However, several commenters also suggested that institutions play a strong role in the job opportunities their graduates can obtain, even if student demographics can have some role in the outcomes across programs.

Discussion: We agree that systemic discrimination may affect the need for some groups of students to borrow and may affect their earnings after graduation. Still, we do not believe that the demographic makeup of a program's students sufficiently influences whether the program meets this final rule's minimal thresholds for financial value such that the Department should alter or abandon the regulations that we adopt here.

The Department addresses this concern in the RIA, the basic points of which we reiterate and discuss here. In the RIA, the Department provides evidence indicating that programs and institutions play an important causal role in determining student outcomes, more so than student demographics. We first present regression analysis (Tables 4.22 and 4.23) showing that institutional and program factors (credential level, control, institution fixed effects) explain a great deal of the variation in program outcomes. Adding student demographics on top of these variables does not explain much additional variation in outcome (as measured by increase in R-squared) (Tables 4.22–4.23). Second, we show that program-level differences in students' family income background is only modestly correlated with the EP measure, and that there are many programs that pass at every level of family income (Figure 4.3). The same is true among programs with similar gender and racial composition (Table 4.24). Third, evidence from our compliance oversight activities indicates that some institutions aggressively recruit women or students of color into programs of substandard quality and claim that the resulting poor outcomes are because of the alleged “access” the program provides to their students. Finally, the closure of a poor-performing program is not likely to affect students' access to a similar program with better outcomes. More than 90 percent of students have at least one transfer option within the same two-digit CIP code, credential level, and geographic area (Table 4.25). We also note that the research literature on this topic likewise concludes that factors related to institutions and programs are stronger predictors of student outcomes than the demographic characteristics of students. On that score, please consult the numerous citations to this literature in the “Need for Regulatory Action” section of the RIA.

Furthermore, in designing the D/E rates and EP measures, the Department included several features to limit the influence of student demographics on these financial value metrics. In the measurement of program debt under § 668.401(b)(1)(i), for example, we cap individual student borrowing at the direct costs charged by the program excluding borrowing for living costs. Low-income students tend to borrow more for non-tuition and fee expenses than do high-income students; therefore, this cap at the total cost for tuition, fees, and books should mitigate concerns that programs will be penalized for enrolling large numbers of low-income students. Further, an analysis by New America suggests that capping debt at the total cost for tuition, fees, and books will have a particularly large impact for programs at Historically Black Colleges and Universities (HBCUs), Hispanic Serving Institutions, Tribal Colleges and Universities, and other Minority Serving Institutions (MSIs), in terms of increasing the number of programs at these institutions that pass the metrics.

See, for example, Dancy, Kim & Barrett, Ben (2018). Living on Credit? An Overview of Student Borrowing for Non-Tuition Expenses. New America ( https://www.newamerica.org/education-policy/reports/living-credit/ ).

See Caldwell, Tia & Garza, Roxanne (2023). Previous Projections Overestimated Gainful Employment Failures: Almost All HBCUs & MSI Graduate Programs Pass. New America ( https://www.newamerica.org/education-policy/edcentral/ge-failures-overestimated/ ).

Even using the data in the 2022 PPD, which does not have that cap applied (since the cap will rely on institution-level reporting not yet available to the Department), programs with small proportions of students who receive Pell Grants (which proxies for socioeconomic status) have median student debt levels that are similar to programs serving large shares of Pell students. In Figure 1.1, we show the relationship between median program debt and the share of Pell students using the PPD. As the share of Pell students increases (moving from left to right on the graph), the average median program debt does not increase (the average of the individual programs' median debt levels is shown in the dark line); rather, it remains similar. To illustrate that institutions do influence borrowing levels, in the same figure we show the average median debt levels for institutions with higher tuition levels (the highest quartile of tuition, with the average depicted by the dotted line) versus those with lower levels of tuition (those in the lowest quartile of tuition, depicted by the dashed line). The figure shows that tuition levels affect borrowing levels substantially, whereas the family income background (proxied by the percent of student receiving Pell grants) of students does not.

Related to potential issues raised about differences in the gender compositions of programs and high school graduates in the State, adjusting thresholds poses several challenges, including practical feasibility. As described in more detail below, attempting to create program-specific metrics would be very complex and lead to inconsistent standards across programs. As well, standards might need to continually change as the gender composition of programs change, potentially adding undesirable volatility to program outcomes.

Changes: None.

Comments: Working from concerns about the role of demographics in the comparison of metrics across programs, commenters suggested a number of potential solutions. One commenter suggested that the earnings information provided on the Department's program information website should note salary discrepancies by gender and race. One commenter recommended the Department disaggregate high school earnings data by demographic characteristics when an institution can demonstrate a predominate demographic or population being served by its programs or field of study. A few other commenters, relying on an estimate of return on investment from a think tank analysis, suggested adjusting the threshold down by 15 percent to account for variances in earnings levels due to demographic differences. A few commenters suggested using demographic adjustments for labor market discrimination, similar to those used in the Bipartisan Policy Center's (BPC) methodology for estimating the return on investment (ROI) for college enrollment.

Discussion: We appreciate the suggestions provided by commenters. For website disclosures, the Department is interested in providing data to students that will help them make informed decisions and to institutions that will help them identify and remove the potential barriers to opportunities for all students to achieve success. The Department will carefully consider the best way of providing this information to students and institutions, including contextual information about the influence of factors such as race and gender discrimination on earnings levels, taking into account the results of consumer testing.

Related to high school earnings, the EP threshold is based on an estimate of State-level median earnings of individuals aged 25 to 34 who have only a high school diploma or GED. Further adjustment to this threshold, such as using a program-specific statistical adjustment to better match the demographics of students completing a given program to the composition of high school graduates in a given State, poses several challenges. An important constraint on this approach is its practical feasibility. To implement the approach, one would need to measure high school median earnings separately for each demographic subgroup of interest. If we only started with the five race and ethnicity groups on which the Office of Management and Budget (OMB) requires reporting and added two sex-at-birth categories, we would need to estimate median earnings for ten subgroups within each State. In many States there would be too few individuals in ACS data to produce a reliable measure, so different groups would need to be combined or other methods of adjustment would need to be employed, thereby requiring potentially arbitrary methodological choices. To compute a program-specific threshold, presumably one would create a weighted average of these subgroups, where the weights would correspond to the share of completers in the program. Again, this could be quite complex and create different standards that programs must meet for eligibility. Especially in small programs, changes in the demographic composition of programs could result in different earnings thresholds from year to year. This could add undesirable volatility to program outcomes under the rule.

With respect to establishing a 15 percent variance to account for disadvantaged groups, we appreciate the suggestion, but there are numerous issues with the commenter's methodology that preclude a sound basis for adjusting the rule by an amount generated by that analysis. This includes several self-acknowledged reasons why the commenter's methodology systematically overestimates or underestimates ROI for different types of programs, and makes assumptions that students' earnings trajectories relative to their peers do not change over time. In addition, the commenter's attempt to create counterfactual wages relies on adjustments made on very broad educational credential by field of study groups that do not reflect specific programs well.

The Department has considered different methodologies for calculating a median high school earnings threshold in each State, including an option (using only those individuals with a high school degree working year-round) that would have used an earnings threshold approximately 20 percent higher.

See “Alternative Earnings Threshold” in the “Alternatives Considered” section of the RIA.

The BPC's ROI model includes a “discrimination adjustment” based on earnings gaps in the overall population of college graduates. Earnings of female graduates, and graduates from underrepresented minority racial or ethnic groups, are adjusted upward to match the earnings of white male college graduates. If applied to a program's earnings outcome measure, this statistical adjustment would misrepresent the true median earnings of graduates from a given program by inflating the median salary for programs enrolling large shares of women and underrepresented minorities. Such an adjustment could potentially misrepresent a student's potential earnings, and ability to repay their debt, for a given program, which are important datapoints within the financial value transparency framework. If applied to State-level EP thresholds of median high school earnings, this statistical adjustment is again likely to cause more year-over-year uncertainty for programs serving a demographic population that is dissimilar from the State-level population of high school graduates in the labor force, due to small n-sizes of these groups.

Finally, we note again that as shown in Tables 4.22 and 4.23 of the RIA and elsewhere in this rule, program demographics do not play an outsized role in influencing the debt and earnings-based outcomes measured in the final rule. In light of these factors, we believe the methodology for setting thresholds based on State-level high school earnings described in this rule is better than alternative approaches and sets a reasonable benchmark for the earnings outcomes of all programs.

Changes: None.

Comments: Several commenters suggested that the Department should include separate provisions for underserved and under-resourced institutions such as HBCUs and other MSIs. These commenters contended that the unique circumstances of HBCUs and MSIs should be considered important factors in assisting both students and institutions. The commenters stated that the Department can do this by providing technical assistance to these schools instead of loss of eligibility if programs fail the D/E rates or EP measure, helping to achieve compliance.

Discussion: While we are sensitive to the additional burden associated with implementing these regulations, we do not believe an exception should be made for HBCUs and other MSIs. As for the financial value transparency framework and the acknowledgment provisions therein, we believe the students at HBCUs and other MSIs are just as deserving of access to useful and comparable information about programs, including information that may be necessary to prevent them from accumulating unaffordable debt. As for the GE program accountability framework, we similarly believe that consumer protection and providing information to highlight the value of programs is important for all students who attend GE programs. As stated above, we maintain that any burden on institutions to meet the reporting requirements is outweighed by the benefits of the transparency and accountability frameworks of the regulations to students, prospective students, their families, taxpayers, and the public at large.

Changes: None.

Comments: Many commenters expressed additional concerns about the impact of the rules on institutions that educate large numbers of low-income and minority students. For example, several commenters equated the student acknowledgment requirements to public shaming of institutions that educate such students. Several other commenters contended that, as a result of the rules, institutions will discriminate against students with lower incomes who do not have the capacity to pay for their program with their own money. These commenters believed that schools are likely to admit students who can be persuaded to borrow private student loans, who do not require accommodations for disabilities, and who enroll in training for fields that are likely to result in higher incomes. This means, according to these commenters, that women, people of color, people with disabilities, and LGBTQ+ individuals will be less likely to gain access to these higher education programs.

Discussion: We do not agree that the student acknowledgment requirements constitute a public shaming of institutions that serve low-income and minority students. The acknowledgments are delivered to the Department through its website, and they are obtained from individual students with respect to particular programs—more specifically, title IV eligible programs that do not lead to an undergraduate degree and that are associated with high debt burden, as well as GE programs that are at risk of losing title IV, HEA eligibility based on measures of high debt burden or no enhanced earnings. The acknowledgments are not obtained from the public at large nor are they associated with the institution as a whole. Moreover, as further discussed in response to a comment above, our analysis of the PPD shows that programs with small proportions of students who receive Pell Grants (which proxies for socioeconomic status) have similar median student debt as programs serving large shares of Pell students.

Moreover, the Department believes that the GE program accountability framework will help protect all individuals including women, people of color, people with disabilities, and LGBTQ+ individuals from entering programs that do not prepare students for gainful employment. The lack of title IV, HEA aid at such programs will help students to avoid failing GE programs, which will ultimately help maximize their educational investment. To help prevent institutions from encouraging students to substitute private loans for Federal loans, the D/E rates measure counts all student borrowing including institutional and private loans in the median debt measure. In effect, then, institutions do not receive an advantage on that metric for concentrating on students with access to private lending, which was a matter of concern to some commenters.

Changes: None.

Alternative Accountability Metrics

Comments: One commenter proposed that the Department use repayment rates as an alternative accountability metric to monitor debt affordability. This commenter noted that in their analysis of College Scorecard data, they identified many online schools where less than 20 percent of borrowers make any progress in lowering their loan principal; however, these programs pass the D/E rates and EP metrics. This commenter recommended penalties for programs where many students do not make progress paying down their principal. Specifically, the commenter suggested the Department consider mandatory disbursement delays, mandatory reduced loan maximums ( e.g., 20 percent less annual loan maximums), or limiting borrowing for one category of costs.

Discussion: The Department agrees that measuring the realized repayment rates of borrower cohorts from particular programs may provide valuable information on borrower outcomes. As provided in § 668.43(d)(1)(vii), through the program information website, we will provide the loan repayment rate for students or graduates who entered repayment on Direct Loans. The Department currently lacks sufficient evidence, however, to design accountability thresholds that would tie eligibility to whether a program's repayment rate exceeded a particular threshold.

Changes: None.

Comments: A few commenters suggested that we assess programs based on a tuition-to-earnings ratio rather than a debt-to-earnings ratio. These commenters believed this approach would treat programs with similar prices and earnings outcomes comparably, regardless of the share of students with debt.

Discussion: We believe it is reasonable to consider whether students' labor market outcomes justify the amount they borrow, as well as any educational expenses they pay using other funds. This rule will generate new program-level data that captures the total debt students borrow to attend programs, which will provide students with relevant information about program outcomes. Since no data on program-level tuition exists, we are not able to calculate a tuition-to-earnings ratio. We focus instead on the direct costs to attend a program that students finance with student loans. This approach reflects the Department's natural interest in Federal loans being repaid, and its concerns that excessive borrowing to attend postsecondary education may lead to financial consequences including default that undermine the goals of title IV, HEA programs in promoting economic mobility.

Changes: None.

Comments: One commenter noted that nursing education is composed of various programs and specializations ranging from practical nursing degrees to doctoral degrees. The current GE metrics may not differentiate between the levels of nursing education and varying incomes. For example, the employment outcomes and debt-to-earnings ratio for a nursing assistant program may differ significantly from those of a four-year Bachelor of Science in nursing program. According to the commenter, incomes vary widely in individual fields in the nursing profession and a rigid formulaic measure may result in unfair and inconsistent outcomes. The commenter further stated that GE metrics prioritize financial indicators, such as earnings and debt, while overlooking other valuable outcomes specific to nursing. The commenter contended that the Department should consider factors like patient outcomes, job satisfaction, and advancement opportunities. The commenter believed that these aspects are also important in assessing the overall quality and value of nursing programs.

Discussion: The EP and D/E metrics are measured for programs that are defined based on credential level and CIP codes. We expect these measures will indeed differentiate between programs that train nurse assistants and BS programs in nursing, unless the BS program graduates end up finding employment as nurse assistants. Regardless, the GE measures are meant to determine whether graduates of career training programs leave their students with enhanced earnings or affordable debt. These are minimum standards to ensure students are not financially harmed by completing an education program. The additional factors specified by the commenter are important but not measured by or reported to the Department Therefore, we are unable to report on these measures.

Changes: None.

Other Comments

Comments: A commenter expressed concern that if we promulgate these GE regulations, there is nothing to stop the Department from enacting more restrictive metrics for all programs.

Discussion: Although D/E rates and the EP measure will be calculated for informational purposes for all programs, we note that the use of the D/E rates and EP measures in this final rule to determine continuing title IV, HEA eligibility for GE programs is pursuant to the statutory authority specific to those programs.

Changes: None.

Comments: Several commenters noted that proprietary schools provide value and economic strength to the country even though they do not receive the State and Federal support provided to public and nonprofit institutions that subsidize the education costs for students. The commenters said that students taking programs at trade schools should have the same opportunities to obtain Federal loans as students attending other institutions of higher education. Commenters also questioned whether programs offered at public and nonprofit institutions in fields such as performing arts, education, leisure, and hospitality provided gainful employment compared to the lower program costs and many jobs available to graduates from cosmetology programs.

Discussion: We agree that many factors go into program costs and post-graduate earnings for the choices students make when selecting institutions, programs, and careers. The regulations measure education debt and earnings for the student graduates, and the education debt itself is tied to the program costs that might or might not be subsidized from other sources. Other factors such as program length also impact those measures. Regardless of those factors, the average education debt for a program is relevant because it reflects the direct obligation that the student is expected to pay, while the average earnings provides some measure of the graduate's ability to do so.

Changes: None.

Comments: Some commenters noted that many graduates of the shorter programs offered at proprietary schools can get licensed in professions with work that provides those graduates and society with immediate benefits. One commenter acknowledged that some for-profit beauty schools may underperform, but surmised that students take cosmetology programs with different goals, plans and ambitions, such as working part-time instead of full time. A number of commenters criticized the eligibility outcome measures as being targeted to cosmetology programs and asserted that the proposed regulations are intended to drive student enrollments away from cosmetology programs and into other fields such as medical and dental. Commenters strongly objected to measures where Department estimates show the regulations could eliminate two-thirds of the cosmetology programs offered at proprietary institutions. Some commenters noted that institutions have little voice in factors that may be reflected in the lower earnings for cosmetology programs such as part time work or unreported income. Some commenters cautioned that programs failing the earnings tests may close and students may face limited choices to enroll in more expensive degree programs or find comparable cosmetology programs in less convenient locations. Other commenters said that many cosmetology graduates seeking full time careers easily get well-paying jobs even before they develop dedicated clientele, while others may do little beyond maintaining their licenses.

Discussion: These measures for debt and earnings are comparable for all programs under the transparency framework and eligibility measures. In general, this means that to keep the education debt affordable for the graduates, programs with lower earnings will have lower costs. Graduates choosing not to work full-time or providing volunteer services in addition to working part-time still are faced with the obligation to repay the education debt associated with their program. The regulations provide the average education debt and average earnings for program graduates without adjustments for any part-time work, and students should consider that information when evaluating career options. Institutions offering GE programs that do not meet the eligibility thresholds may search for better options for their students that effectively reduce the education loan debt or lead to better earnings outcomes. A more detailed discussion about unreported income from cosmetology program graduates is addressed separately in the “Tipped Income” sections here and in the NPRM.

Changes: None.

Comments: Some commenters suggested earnings outcomes could be impacted due to student athletes who might underperform in academic engagement, impact retention and graduation rates, and not be gainfully employed.

Discussion: The Department has no information that suggests the commenters' assertions that student athletes are likely to have lower academic engagement and thus lower earnings might be correct. The metrics of the rule are based on students that complete a program, however, so the commenters' concerns about retention and completion are not likely to be relevant. Regardless, the Department expects institutions to serve all of its students well and to meet the minimal standards set by the rule.

Changes: None.

Definitions—§ 668.2

General Comments

Comments: Several commenters stated that the definitions are unclear and do not adequately define terms in ways that can be operationalized by institutions. Commenters contended that previous iterations of the GE rule have shown that many definitions are so confusing that implementation for schools became overwhelming. These were general assertions, and no examples were given to the extent comments addressed specific definitions, they are addressed in the corresponding section.

Discussion: We believe the definitions are clear. We have taken care to define terms precisely in this final rule and do not anticipate widespread confusion. In addition, as we did when issuing the 2014 Prior Rule, we will again provide clear guidance and training to assist postsecondary institutions in complying with the new regulations.

Changes: None.

Classification of Instructional Program (CIP) Code

Comments: Many commenters asserted that the proposed regulation's definition of the CIP Code to consist of six-digits is not appropriate for the purposes of the transparency and accountability regulations. Commenters offered several at times conflicting reasons for using alternative approaches. One commenter noted that the six-digit CIP code does not adequately distinguish among different levels of program success at different locations of the institution. Another commenter cautioned that the four-digit CIP code captured several different six-digit programs offered at a school, and that if the program defined at a four-digit CIP level failed then all the programs at the school would fail and the school might need to close.

On the other hand, other commenters suggested the definition of a CIP code should consist of four-digits to increase the number of students covered by metrics under the rule, or alternatively to use the six-digit CIP but to “roll-up” programs to the four-digit level when doing so would avoid too few students at the six-digit level programs. Some commenters noted that few four-digit programs had multiple six-digit programs within them, and in those cases, the different six-digit programs rarely had different financial value outcomes. This, they said, suggested there would be little granularity lost in using the four-digit CIP level to define programs, and would increase coverage of the rates. Finally, one commenter expressed appreciation for the Department's decision to use 6-digit CIP codes and requested the Department to re-release the dataset included with the NPRM with a 6-digit CIP code versus the currently published 4-digit CIP code data to aid in understanding institutions' performance with these new measures.

Discussion: We appreciate commenters' views on both sides of this issue. There is a tradeoff between granularity of how specifically programs' performances are measured, and the coverage of metrics due to minimum n-size restrictions discussed elsewhere. As we note in the RIA, we estimate that metrics using a 6-digit CIP with the 4-year completion cohort roll-up for programs with few completers over 2 years will be available for programs enrolling over 80 percent of title IV, HEA recipients. While also rolling up programs to the four-digit level could allow even greater coverage, the potential gains are small, and it is possible that some programs (measured at the six-digit level) that should be deemed passing are combined with larger failing programs and end up failing. We put more weight on avoiding an inappropriate sanction on a passing program, and so prefer to define programs at the six-digit level.

Although the Department considered treating each additional location offering the same combination of six-digit CIP code and credential level as a separate program, we determined that doing so would further reduce the number of programs with a sufficient number of completers to be evaluated, and the gains in granular coverage may not be justified. This is, in part, due to an added dimension of complexity that not all locations are well aligned with the organizational units of institutions with which students engage in pursuing an education, and the mapping between locations and such units differs widely across States. The Department might revisit the issue of program classification in the future, for example to assess student outcomes more granularly across different campuses in some State systems or in online programs.

The Department does not anticipate being able to rerelease the information published with the NPRM at the six-digit CIP level due to constraints in our ability to obtain earnings data.

Changes: None.

Office of Postsecondary Education Identification (OPEID) Code Level

Comments: A few commenters argued that, in defining a “program”, the Department should use the eight-digit Office of Postsecondary Education identification number (OPEID) since it because it more granularly identifies the institution where a student receives an education. The commenter asserted that disaggregated data would afford students a clearer understanding of the quality of their specific institution. Also, the commenter stated that accreditors and State regulators view institutions with distinct 8-digit OPEID numbers separately and so using the 8-digit OPEID would align data across the triad.

Discussion: The Department agrees with these commenters that it would be desirable to be able to track program performance at separate locations of colleges with multiple locations rather than reporting them together under a single six-digit OPEID campus. Currently, however, eight-digit OPEID locations do not correspond neatly to the separate components of an institution that students interact with to participate in their education programs. Moreover, the Department must balance the competing interests of specificity of data and having enough completers in a cohort group to calculate rates. Additional sub-division of completer groups would lead to some programs falling short of 30 students in the 4-year cohort, resulting in rates and data being unavailable for those programs. We believe that variation in the same program offered by the same institution at different locations would be too small to justify the loss of rates for programs that fall short of the 30 completer n-size requirement.

Changes: None.

Cohort Period

Comments: One commenter stated that, for programs that prepare pilots, student outcomes should be measured under the GE regulations after students have completed the credential and worked for the airlines at least 2 to 3 years. The commenter noted that the proposed GE outcomes measures could negatively impact flight schools.

The commenter proposed adding a new paragraph to the definition of “cohort period” that reads: “For a program whose students are required to complete post-graduation flight hours pursuant to the Federal Aviation Administration (FAA) standards to qualify as an Airline Transport Pilot (ATP) and where a majority of the graduates are pursuing an FAA ATP certification, the sixth and seventh award years prior to the award year for which the most recent data are available from the Federal agency with earnings data at the time the D/E rates and earnings threshold measure are calculated. For this purpose, the institution must provide a certification that a majority of its graduates pursue completion of the required FAA certified flight hours to work as an FAA Certified ATP.”

The commenter also recommended adding another paragraph to the same definition of “cohort period” that reads: “For a program whose students are required to complete post-graduation flight hours pursuant to the Federal Aviation Administration standards to qualify as an Airline Transport Pilot (`ATP') and where a majority of the graduates are pursuing an FAA ATP certification, the sixth, seventh, eighth, and ninth award years prior to the award year for which the most recent data are available from the Federal agency with earnings data at the time the D/E rates and earnings threshold measure are calculated. For this purpose, the institution must provide a certification that a majority of its graduates pursue completion of the required FAA certified flight hours to work as an FAA Certified ATP.”

Discussion: The Department declines to add the proposed language. We are committed to reviewing our own internal data and processes to collect, analyze, and make program eligibility determinations based on the soundest data available to us. We are concerned that providing program specific carve-outs that have not been evaluated using the Department's internal data and processes would cause the GE metrics to be inconsistent and ineffective.

Changes: None.

Earnings Threshold

Comments: None.

Discussion: The proposed definition of “earnings threshold” referred to a “Federal agency with earnings data” as the basis for determining median earnings for purposes of calculating the earnings threshold, however our proposed description of the provision in explained that “[u]sing data from the U.S. Census Bureau, the Department would also calculate an earnings threshold. . . .”

88 FR 32300, 32332 (May 19, 2023).

Change: We have clarified the definition of “earnings threshold” to provide that median earnings are determined based on data from the Census Bureau.

Institutional Grants and Scholarships

Comments: One commenter stated that the definition is not grammatically correct and should be improved through technical, non-substantive edits.

Discussion: The Department agrees with the commenter.

Changes: The Department has updated the definition to read: “Assistance that the institution or its affiliate controls or directs to reduce or offset the original amount of a student's institutional costs and that does not have to be repaid. Typically, an institutional grant or scholarship includes a grant, scholarship, fellowship, discount, or fee waiver.”

Student

Comments: Several commenters believed that defining “student,” for purposes of these regulations, to include only title IV, HEA recipients, would undermine the quality of data that the Department would use to calculate the D/E rates and EP measures for programs with significant numbers of students who did not receive Federal student aid. One commenter proposed to expand the definition of “student” to include graduates who have not received any title IV, HEA assistance for enrolling in a program, noting that in some years, 10 to 20 percent of the commenter's institution's graduates do not receive title IV, HEA funds. The commenter contended that it is unfair that a measure based on graduates' median debt excludes graduates who did not receive title IV, HEA assistance. One commenter suggested that, given the reporting proposed, logistical hurdles in adding these graduates to the cohorts are easily overcome.

Discussion: These rules provide a framework to provide financial value transparency information to students and to determine the eligibility for students to receive Federal student aid at career training programs. It is reasonable to base this eligibility on measures of the outcomes of students who receive that aid. Similarly, for non-GE programs the Department seeks to provide relevant information to students regarding the outcomes of programs for students receiving title IV, HEA assistance. This will help students who need to borrow to attend non-GE programs to make an informed decision and, where applicable, hold GE programs accountable to increased oversight and guardrails.

Changes: None.

Title IV Loan

Comments: One commenter recommended that the Department omit the “title IV loan” definition or, if the Department believes that it is crucial to define the term for these regulations, use the existing defined term of “Direct Loan Program loan” at § 668.2(b). The commenter contended that the proposed definition is incomplete and not aligned with actual statutory provisions, which could be misleading and confusing. The commenter noted that, although new Federal Family Education Loan Program (FFELP) and Federal Perkins (Perkins) Loan Program loans are no longer being originated, these loans still exist and should not be excluded from the definition of “title IV loan.” The commenter cited, as examples, §§ 668.403(e)(1) and 668.404(c)(1), in which the Department refers to “title IV loans” as including Perkins and FFELP.

Under 34 CFR 668.2(b), a “Direct Loan Program loan” is a loan made under the William D. Ford Federal Direct Loan Program.

Discussion: The Department agrees with the commenter. We can rely on the definition of Direct Loan Program loan in preexisting regulations, and we agree that, to avoid confusion, it is helpful to use consistent terminology in our regulations.

Changes: The Department has revised references to “title IV loan” to “Direct Loan Program” loan throughout the final rule's regulatory text.

Comments: One commenter suggested that, in calculating administrative burden, the Department should consider the administrative burden of all the proposed rules together, not individually.

Discussion: The Department took great care to analyze the impact of the proposed regulations. The Department has separated the GE and Financial Value Transparency Framework topics from the other rules covered in the NPRM. We, therefore, updated the RIA to reflect that, as well as to reflect changes we made from the proposed rules to these final rules.

Changes: None.

Measurement of Earnings

Timing of Earnings Measurement

Comments: One commenter supported the Department's proposal to measure students' earnings for the calendar year three years after graduation, observing that the proposed interval will give students time to establish normal earning levels and will allow for meaningful comparisons of debt and earnings outcomes between programs.

Discussion: We thank the commenter for their support.

Changes: None.

Comments: Many commenters expressed concerns over the timing of earnings measurement. First, many expressed concerns that three years is too little time from graduation to allow for earnings to grow enough to be a fair representation of the earnings return to pursuing a degree in their field of study. Commenters noted that, in some cases, fields with lower initial earnings can end up having higher lifetime earnings. Others believed that we should account for the full lifetime earnings that flow from the benefit of a degree. Some commenters suggested that students without family members to advise them to consider other factors might be more swayed by the short-term earnings information provided as part of the financial value transparency framework.

By contrast, others argued that this three-year lag between when students graduate and when their earnings are measured is too long to fairly characterize the current quality of the program at the moment any sanctions might be levied.

Discussion: Because the benefit of some educational investments may take time to manifest, real-time assessments of educational program performance face a tradeoff between allowing enough time to pass to produce an accurate measure of the benefits and assessing those outcomes quickly enough that they are likely to reflect the current performance of a program. We agree that trusted resources such as family members can provide important assistance in college decisions, and we believe that the information produced from this rule will aid the decision making of students and their families. We are not aware of evidence that supports the argument that students without family members on which to rely will systematically make differential decisions in the way suggested by the commenter.

We believe a three-year lag in measuring earnings, with longer periods for programs documented to have exceptionally high earnings growth due to government-imposed limits on early career earnings capacity, strikes this balance. Data from the Census' Postsecondary Employment Outcomes (PSEO) project shows that earnings levels measured shortly after graduation are very highly correlated with longer term measures. The correlations of programs' 1-year and 5-year post-graduation earnings measures with 10-year program median earnings are 72 and 89 percent, respectively (a 3-year earnings measure is not available in the PSEO, but it is reasonable to expect its correlation with longer term earnings to be between the 1- and 5-year measures). Moreover, according to administrative Department data on median debt levels for each program, programs' median debt levels evolve relatively slowly—the correlation of program median debt levels for the 2016–2017 and 2021–2022 cohorts is about 0.96. In general, then, information on past cohorts' debt and earnings outcomes are likely to be highly relevant for predicting outcomes of future cohorts.

Changes: None.

Post-Graduate Training Requirements

Comments: Several commenters noted that recent graduates who engage in apprenticeships and other types of probationary or training periods, often required by the State before students can practice independently, earn lower wages in those initial years as compared to later years. The specific programs that commenters pointed to include clinical psychologists; marriage and family therapists; clinical counselors; social workers; and veterinarians. Other programs, especially in medicine, have residency requirements. In other cases, commenters noted that careers in their field often involve graduates running their own business, which requires time to build out a steady clientele and suppresses initial earnings.

One commenter suggested that, in determining which programs should be eligible for a longer earnings horizon, the Department should consider whether (1) the relevant field requires multiyear post-degree supervision for licensure (noting the possibility of creating competing State and Federal regulatory frameworks); and (2) a large increase in the earnings of program graduates follows licensure.

Discussion: Both the D/E rates and EP measures are based on the earnings of graduates after three years. For example, for students graduating between July 1, 2018, and June 30, 2019 (the 2019 award year), their earnings would be measured in calendar year 2022. In most cases this should give students enough time to settle into stable employment, and after that transition the Department believes it is reasonable to expect students to be able to meet the minimum standards of this rule to be able to afford their debt payments and for a gain in earnings beyond what they might have earned in high school to be realized.

Moreover, we note that a student's earnings three years after graduation might govern their loan payments for up to five years after the student graduates if they enroll in income driven repayment plans. That is between 20 and 25 percent of the full time that students will be required to make payments on such plans, so the Department has a responsibility to taxpayers to hold institutions accountable in providing quality programs that produce graduates that earn enough to repay their loans at that point.

The Department is sympathetic to the argument that some programs may have lower earnings three years after graduation due to government-imposed post-graduate training requirements necessary to earn a license before an individual can practice independently. To assess the commenters' claims that these programs see substantial earnings gains just outside the measurement window used in the rule, we used program-level PSEO data. These administrative data are based on individual records that match program graduates to their annual earnings from the U.S. Census Bureau's Longitudinal Employer-Household Dynamics program at one, five, and 10 years after completion. The PSEO reports program-level median earnings at these three intervals, linked to 2-digit or 4-digit Classification of Instructional Program (CIP) codes for a large number of institutions and State public higher education systems throughout the United States. This is the only dataset we know of that currently includes program-level earnings for programs from a broad selection of institutions, credential levels, and fields of study with such long follow-up.

We limited the dataset to programs and cohorts that had non-missing median earnings at all three intervals. We then grouped programs by credential level and focused here on graduate programs, where commenters noted post-graduate training requirements.

The PSEO data do have some important limitations. First, they cover a subset of States and not all sectors within each State ( e.g., in many States, only public institutions report data). For privacy reasons, data are not reported at the finest CIP level. For example, the PSEO data reports earnings for professional doctoral programs, such as MDs, at the 4-digit CIP level. These programs comprise about 10 percent of the programs that are in the data we analyze. However, the PSEO reports master's and doctoral research/scholarship degrees, which account for about 90 percent of the graduate programs in the data we use, at the 2-digit CIP level. For many programs, 2-digit CIP groups can include a wide range of programs. Still, this is the only dataset that allows us to measure program-level earnings for a wide range of programs across the country at multiple time intervals that include earnings outcomes at least five years after students graduate. Ultimately, we observe median earnings for 7,856 graduate programs for the graduating cohorts of 2001, 2004, 2006, and 2007.

The commenters raise the concern that some programs will have particularly fast earnings growth after the third year after completion, suggesting that prior to earning their independent license their earnings three years after graduation were suppressed by the government-imposed requirement. In the PSEO data, we estimate 3-year median earnings as the average of the 1-year and 5-year median earnings available in PSEO. Figure 1.2 below compares these estimated 3-year median earnings (on the x-axis) to the 10-year median earnings (on the y-axis), focusing on all graduate programs with available data. The figure shows that, in general, early career earnings are highly correlated with later career earnings: the correlation in the 3 vs. 10-year post-graduation median earnings is 0.74. The “best-fit line” in the figure (fit with a simple ordinary least-squares regression) illustrates the estimated linear relationship between the average 10-year measure and the estimated 3-year measure. Most programs have higher earnings when measured 10 years from graduation than 3 years after graduation, reflecting the fact that earnings tend to grow with experience for most workers. While most programs are centered around the best-fit line, there is an obvious cluster of graduate programs that have much higher 10-year median earnings than would be expected based on their 3-year earnings. The professional programs in Medicine, are all in the outlier group in the figure. Within the 2-digit CIP code of “Health Professions and Related,” there are some programs within the group of outliers, as well as programs that are not outliers in terms of their earnings growth. Though we do not show the relationship here, there is no similar group of outliers for BA programs evident in the PSEO data.

We replicated these analyses focusing on earnings growth from 1 year after graduation to 5 years after graduation and found qualitatively similar results.

Some commenters pointed to programs that prepare students to become mental health clinicians, including Clinical Psychology and Marriage and Family Counseling, which require post-graduate work to obtain a license. We have limited ability to analyze these programs in the PSEO data since the master's and doctoral research and scholarship programs for these fields are lumped with other health and psychology programs in those broader 2-digit CIP categories. The PSEO data does have data for Clinical, Counseling, and Applied Psychology professional doctorate programs in the PSEO data, but there are only a very small number of these programs in the data, preventing a robust view of the earnings growth of these programs.

Social Work is somewhat different from the other programs in that graduates with a master's in Social Work (MSW) pursue a variety of fields, and not all of them require a clinical license. The first column of Table 1.3 below shows the number of graduates with an MSW each year, based on an annual census of social work programs by the Council on Social Work Education. The second column shows the number of first-time licensing exam takers, based on data from the Association of Social Work Boards. Under the assumption that MSW graduates take their exam three years later, this leads to an estimate of approximately 60 to 70 percent of graduates taking the exam. Using a 6-year cohort period for all MSW graduates may not therefore be appropriate.

See, for example, Salsberg et al. (2020). The Social Work Profession: Findings from Three Years of Surveys of New Social Workers.

See, for example, Council on Social Work Education (2022). Annual Statistics on Social Work Education in the United States.

See, for example, Association of Social Work Boards (2022). 2022 ASWB Exam Pass Rate Analysis Final Report.

Table 1.3—MSW Graduates and First Time LCSW Exam Takers, by Year

MSW graduates First-time LCSW exam takers
2011 20,573 9,100
2012 22,441 9,604
2013 22,677 10,879
2014 25,018 12,217
2015 25,883 13,044
2016 27,659 14,007
2017 27,270 16,095
2018 27,296 16,022
2019 29,546 17,207
2020 31,750 16,801
2021 20,657

In summary, there appears to be some possibility that, similar to programs in medicine, some other programs that provide training to licensed mental health professions may also generate significant earnings growth following a post-graduate training period. At present, detailed data do not exist to evaluate which groups of programs by credential and CIP code are likely to have outlier earnings growth, but over time such data will become available in the College Scorecard. For example, program median earnings measured five years after completion should be available by early 2024. One area of complication is that the career paths of graduates of some mental health training programs are more diverse, and not all graduates might seek to become licensed.

In light of the evidence presented by commenters and the Department's analyses, we adopt a data driven process to identify qualifying graduate programs where we will use a longer cohort period to measure the earnings of graduates six years, rather than three, after they graduate. The Department selected an initial set of these fields based on evidence currently available to the Department suggesting that graduates of such programs may have constrained earnings three years after graduation as a result of government imposed postgraduation training requirements. Data in the College Scorecard will eventually allow more accurate assessments of which programs experience atypically high growth in graduates' earnings that are potentially due to postgraduation training requirements. Going forward, the Department will use these data, combined with an information request to the field to identify groups of programs (at the credential level and CIP code level) where A) state or other government postgraduation requirements exist that are likely to lead to delays in program graduates being able to practice independently; and B) programs are outliers with regard to their earnings growth relative to programs at the same credential level.

The Department will use a standard statistical procedure to determine whether groups of programs (graduate fields of study, defined by their credential level and CIP codes) are outliers with regard to their earnings growth. The Department will use College Scorecard measures to calculate the percent growth in the median earnings of program graduates between one- (or three-) and five-years (or ten-years) postgraduation. Lastly, a qualifying graduate program must have at least half of its graduates obtain licensure in a State where the postgraduation requirements apply. Since the rule is based on measuring the earnings of the median graduate, this requirement means that the student with median level of earnings is likely to have their earnings outcomes influenced by the training requirement.

Changes: We modify the definition of “cohort period” in § 668.2 so that earnings for the 2-year cohort period are measured six years after graduation for completers in “qualifying graduate programs,” rather than “a program where students are required to complete a medical or dental internship or residency.” Similarly, we modify the definition of “cohort period” so that earnings of completers of a qualifying graduate program for the 4-year cohort period are measured the sixth, seventh, eighth, and ninth award years prior to the year for which the most recent earnings data are available from the Federal agency with earnings data at the time the D/E rates and earnings premium measure are calculated.

We then add to § 668.2 and define a “qualifying graduate program,” which (a) establishes an initial list of graduate degree fields (defined by their credential level and CIP code) that potentially qualify for this longer cohort period used for earnings measurement for the first three years after the effective date of this rule; (b) establishes a regular data driven process the Department will use to update that list after the initial period; and (c) specifies further criteria that institutions must attest apply to a program to deem it a qualifying graduate program.

We define an initial list of potentially qualifying graduate programs whose students are generally required to complete a postgraduation training program to obtain a license to practice independently in the following fields: medicine, osteopathy, dentistry, clinical psychology, marriage and family therapy, clinical social work, and clinical counseling. These fields were selected based on credible evidence presented to the Department that program graduates are subject to lengthy, government-imposed, postgraduation training requirements; and graduates' earnings may be constrained by these requirements for at least three years after they graduate from a program.

A program is considered to be an outlier in terms of its earnings growth if its growth is more than two standard deviations higher than the average earnings growth among programs with the same credential level. A graduate degree field (defined by credential level and CIP code) will be considered to have outlier earnings growth if at least half of the individual programs in the field have outlier earnings growth.

In using the College Scorecard data to determine which graduate fields are outliers in terms of earnings growth, we seek to identify programs that have atypically high earnings growth between the first three years after they graduate, and subsequent years. In practice, the College Scorecard measures earnings 1-, 3-, 5-, and 10-years (the 5- and 10-year measures are planned, but not yet available, though will be after the initial period) after graduation. Accordingly, to measure whether programs have outlier earnings growth we will base our assessment on the comparisons available in these data. Defining a program as an outlier based on whether its earnings growth is two standard deviations above the mean is rooted in a common statistical approach for defining outliers.

There are several common ways of defining statistical outliers in a distribution, including by measuring how many standard deviations an observation's value is from the mean or by measuring the distance of a value from the 25th or 75th percentile of a distribution in terms of multiples of the interquartile range. In defining a single observation as an outlier it is more common to use a threshold of three standard deviations away from the mean. We use a more lenient two standard deviation standard for any single program, in part because we require that a majority of programs in a graduate field are outliers in order for that field to meet the outlier earnings test to be on the list of potentially qualifying programs.

We will conduct this process every three years to balance a desire to stay up to date with current practices around licensure and training requirements, while ensuring institutions have stability in how the metrics of the rule will be calculated for their programs. In identifying postgraduate training requirements, we limit the rule to those that typically take at least three years to complete. This accommodation is meant to apply to programs where graduates' earnings capacity three years after graduation is constrained due to not yet having a required license. If training requirements took only one or two years to complete, graduates' earnings would not be constrained at the point when earnings are typically measured three years after graduation and the accommodation would not be necessary.

Programs with a credential level and CIP code included in the list of potentially qualifying graduate degree fields are eligible to have their earnings calculated under the extended cohort period (with a six-year lag before earnings are measured) if the institution attests that A) if necessary for the license for which the postgraduate training is necessary, that it is accredited by an agency that meets State requirements; and B) at least half of the program's graduates obtain licensure in a State where the postgraduation requirements apply.

We have also made conforming changes to refer to a “qualifying graduate program” in § 668.408.

Comments: One commenter mentioned that medical residency length varies by specialty, so the D/E rates calculation should allow for individualized time to license for programs with medical residency, not just an overall extension that is the same for all programs.

Discussion: We acknowledge that different medical specialties have different residency lengths. It is not feasible, however, to adapt different cohort periods for every student depending on the type of residency they pursue. We believe that establishing a 6-year lag before earnings are measured gives the vast majority of students in such programs time to complete residency requirements and measure their early career earnings.

Changes: None.

Tipped Income

Comments: Many commenters expressed concerns about our ability to fully capture earnings in sectors where gratuities play an important role in the compensation structure of employees, such as many jobs associated with cosmetology. These commenters lamented the widespread underreporting of income of this form to tax authorities, but claimed it posed a major obstacle to the Department's ability to capture the complete earnings picture for workers in such situations. These commenters also argued that this phenomenon of tax evasion was not the fault of institutions, and they should not face sanctions as a consequence. Several other commenters pointed to past Department statements about the prevalence of the underreporting of tipped income. These commenters believed that the estimates expressed in those statements support modifying our earnings measurement methodology.

Discussion: In the NPRM, the Department addressed its views on the challenges posed by unreported income of any sort. In the NPRM section titled “Process for Obtaining Data and Calculating D/E Rates and Earnings Premium Measure (§ 668.405),” we explained the rationale for relying on administrative income data collected by a partner Federal agency. There are several reinforcing reasons why we choose to rely on reported income to the Federal Government. These reasons include: individuals are legally required to report their income subject to Federal taxation; the Department relies on reported income in its administration of the title IV, HEA programs, including with respect to Pell grant eligibility, subsidized loan eligibility, and income-driven repayment payment determinations; past experiences with the earnings appeals process suggests it does not improve the quality of information available to assess program performance; and new research on the prevalence and scope of unreported income and its effects on the accuracy of earnings measures.

As the Department explained in the NPRM, individuals who fail to report taxable income in a manner consistent with Federal law are subject to considerable legal penalties. In an increasingly digitized economy, new Federal law in the American Rescue Plan Act lowered to $600 the reporting threshold for when a 1099–K is issued, which will result in more third-party settlement organizations issuing these forms. Relatedly, the increasing prevalence of electronic payment methods and the decline in cash transactions should lessen the concern of tax evasion as a source of error in our measurement of graduates' earnings. The anonymity of cash transactions makes it possible for the exchange of goods and services to take place without a record, facilitating evasion. With digital transactions, however, records of the transactions are kept, not only by business owners but also by the payment processers. This record of payments exposes would-be evaders to elevated risk of apprehension in the case of an audit. Consequently, there are now greater practical hurdles to evading Federal tax reporting since the Department last regulated GE programs with respect to D/E rates. As we noted in the NPRM, this is not to deny that some fraction of income will be unreported despite legal duties to report, but instead to recognize as well that legal demands, technology, payment practices, and other relevant circumstances have changed.

88 FR 32300, 32335 (May 29, 2023).

The 1099–K form reports payments from payment card companies, payment apps, and online marketplaces and is required to be filed with the IRS by these third-party settlement organizations. In 2021, a statute was enacted that reduced the threshold for reporting to $600, as opposed to $20,000 in years prior. This lower reporting threshold means that settlement organizations will likely have to file 1099–K forms for a greater number of sellers and transactions. See Public Law 117–2 (2021) ( govinfo.gov/content/pkg/PLAW-117publ2/html/PLAW-117publ2.htm).

Indeed, commenters frequently cited the fact that graduates from fields such as cosmetology often operate cash businesses as a reason to suspect such proprietors of tax evasion. The economics literature also has cited a concern over tax evasion as a drawback of paper currency. See, for example, Rogoff, Kenneth (2015). Costs and Benefits to Phasing Out Paper Currency. NBER Macroeconomics Annual, 29.1: 445–456.

88 FR 32300, 32335 (May 19, 2023).

In the NPRM, the Department also explained that administrative earnings data from the IRS play a crucial role in the HEA framework for determining Pell grant and other aid eligibility, as well as monthly loan payments on income-driven repayment plans. Income information provided from official filings to the IRS are one of the primary ways that borrowers document their income to the Department to qualify for critical student or borrower benefits. It would be inconsistent and imprudent for the Department to use different earnings data for similar purposes related to the administration of title IV, HEA student aid. In these regulations, earnings data are employed so that students might avoid programs that leave them with very low earnings or unaffordable debt, in part to protect taxpayer investments in the title IV, HEA programs. More specifically, these regulations represent front-end safeguards on the use of title IV, HEA support, which will reduce Federal investments in ineffectual programs through loans and other student aid and, likewise, will reduce back-end liabilities for the Department and taxpayers when program completers default or make reduced Federal loan payments. It would undermine the goals of taxpayer protection if we allow borrowers to qualify for lower or zero loan payments due to low reported earnings to the IRS, but ignore these low reported earnings when providing students with information or determining whether a program prepares students for gainful employment.

The Department's experience with the earnings appeal process also cautions against making accommodations for the possibility of income underreporting. Because institutions were permitted to offer alternative measures of earnings through an appeals process under the 2014 Prior Rule, the Department has direct experience with the challenge of trying to measure earnings more accurately than the information available through administrative wage records. As the Department noted in the NPRM, the goal of more accurate earnings data through the earnings appeal process in the 2014 Prior Rule was ultimately frustrated by implausibly high earnings reported through the survey measures. Problems of accurate recall and selection bias ( i.e., only higher earners were sampled, or they were differentially likely to respond) among survey respondents likely impacted that earnings appeal process and make it unlikely that a similar process would yield improved information on a program's earnings outcomes.

The Department notes that commenters' concerns with earnings reporting ( e.g., misreporting or mismeasurement, classification of small business income, ability to observe all earners) would be more likely to occur in survey measurements of income than in administrative records. First, the definitions of different types of income are complicated and would require survey respondents to recall not only those definitions but also the amount of earnings that fit into each category. By contrast, administrative records contain this information for all earners, often prepared by tax professionals who are well aware of the proper definitions. To the extent that commenters are concerned about tax evasion in reporting to the IRS, it is hard to see why program graduates would be more forthcoming about the true nature of their earnings on a survey, where they have no legal obligation to report accurately, especially if such reporting would implicate them in tax crimes. Survey data are also hard to collect accurately, with a great deal of scholarly work in survey methodology devoted to handling biases produced by common biases of respondents and the difficulty in collecting representative, truthful data on all types of individuals of interest. Given these challenges, lessons from prior experience, and the incentives for institutions to find a sample of students whose aggregated earnings would allow their program to continue operating, the Department does not believe that surveys would prove a reliable measure of earnings.

Finally, as we explained in the NPRM, new research is now available. A 2022 study shows that earnings underreporting is likely to be small—about 8 percent—in contrast to previous estimates that formed part of the record for the 2014 GE rule and was a basis for arguments in litigation over that rule. The Department's goal is a reasonable assessment of available evidence overall, and the Department has taken care not to rely unduly on any one study. At the same time, the Department has accounted for evidence that puts into perspective the low magnitude of possible underreporting that is relevant to these rules.

See Am. Ass'n of Cosmetology Sch. v. Devos, 258 F. Supp. 3d 50, 59–60 (D.D.C. 2017) (stating that “[a] report by Stanford professor Dr. Eric Bettinger, which was submitted to the agency during the notice-and-comment period, found that both tip income and self-employment income are, on average, underreported by around 60 [percent]”). The report referenced by the court is Bettinger, Eric (May 26, 2014). Imputation of Income Under Gainful Employment. We have reviewed that report again during this rulemaking.

The recent study that we reference in the text of this final rule and that we discussed in the 2023 NPRM is Cellini, Stephanie Riegg & Blanchard, Kathryn J. (2022). Hair and Taxes: Cosmetology Programs, Accountability Policy, and the Problem of Underreported Income. Geo. Wash. Univ. ( www.peerresearchproject.org/peer/research/body/PEER_HairTaxes-Final.pdf ).

The 2022 Cellini and Blanchard study critiques the earlier May 26, 2014, study by Bettinger, which had estimated a much higher level of underreported earnings for cosmetologists. See id. at 11 n. 14 (discussing Bettinger (May 26, 2014). Imputation of Income Under Gainful Employment). See also our discussion in the NPRM, 88 FR 32300, 32336, 32346 (May 19, 2023). We independently reviewed the Bettinger report during this rulemaking, as well as Cellini and Blanchard's critique of it. We concur with Cellini and Blanchard that the May 26, 2014, Bettinger report appears to include an unrealistic overestimate of underreported total income. The Bettinger report inflates total income by 50 percent, and the adjustment appears to be based on an assumption about the share of underreported tips; however, tipped income is only a portion of total income.

We further observe that, according to a report sponsored by Wella Company and others—with listed supporters including John Paul Mitchell Systems, the Professional Beauty Systems, and others, and submitted or referenced by numerous commenters during the public comment period for this final rule, including AACS-salon owners reported a “high rate of tip compliance.” Qnity Institute (2023). A Career in Pro Beauty, at 8 ( https://www.reginfo.gov/public/do/eoDownloadDocument?pubId=&eodoc=true&documentID=216592 ). Specifically, that source indicates that 4 percent of salons reported not allowing their employees to receive tips, 87 percent of salons surveyed reported that tips were included on the W2 for all employees, and another 5 percent of salons reported tips on the W2 for some employees; meaning that just 4 percent of salons did not report tips for employees on W2s. See id. This report also relied on the Cellini & Blanchard (2022) estimate of 8 percent tip underreporting for the report's estimate of annualized earnings. See id.

Finally, we note again that tips included on credit card payments to a business are more likely to be reported, as we have discussed above in the text, and it is reasonable to expect that many workers are complying with the law to include tips in their reported income.

In addition, as we emphasized in the NPRM, the timing for measuring earnings in this final rule differs from the timing in the 2014 Prior Rule. This change in timing, where graduates' earnings will be measured longer after when they graduate, will tend to increase the measured earnings of all programs. Based on our analyses of program median earnings estimates under the 2014 Prior Rule and those released in the PPD, we estimate that such increases are likely to be much higher than the 8 percent estimate of underreporting from the Cellini and Blanchard research. Therefore, the rule already includes safeguards against potential underestimates of earnings.

88 FR 32300, 32329–35 (May 19, 2023).

We also seek to avoid the perverse incentives that would be created by making the rule's application more lenient for programs in proportion to how commonly their graduates unlawfully underreport their incomes. We do not believe that taxpayer-supported educational programs where benefits are provided based on reported income to the IRS should, in effect, receive credit when their graduates fail to report income for tax purposes. All things equal, earnings underreporting will tend to have borrowers repay less of their loans under income driven repayment plans. If the Department ignores lower reported earnings among some programs, it would effectively be supporting greater taxpayer investments in those programs. Even if that position were fiscally sustainable, it would incentivize institutions to discourage accurate reporting of earnings among program graduates—at the ultimate expense of taxpayers. It could also potentially invite private investment in training programs aimed at exploiting this weakness in accountability for student loans that are unlikely to have to be repaid, thereby increasing the amount of Federal funds going to programs like these.

Given these considerations, the Department reaffirms its decision to rely on administrative earnings reported to a Federal agency, comparable in quality to earnings data from the IRS, without an opportunity to appeal these earnings estimates or accommodation for the possibility of income underreporting. To the extent that institutions believe that underreporting is negatively affecting their program's performance on the D/E rates and EP metrics, the Department continues to believe that institutions are well positioned to counsel their students on the importance of tax compliance. Indeed, many commenters noted the role that cosmetology programs play in training their students to run their own small businesses, including managing their finances. Though individuals are certainly the most responsible party for decisions about tax compliance, programs are as well positioned as any party to inform students about the requirements and benefits of tax compliance. Therefore, it is also important in the Department's view to maintain incentives for programs to deliver this message as effectively as possible.

Changes: None.

Comments: Many commenters expressed suspicion about the quality of our earnings data based on their own knowledge of earnings level in their industry. In some cases, this knowledge came from employing people in the field and marshalling evidence from the W–2 wage records of their employees, while others provided anecdotal reports of their own earnings or those of people they know working in the field.

Discussion: While we value the input of commenters who wish to alert us to a mismatch between their industry experience and the earnings reflected in the 2022 PPD released with the NPRM, we remain confident in the comprehensiveness of the data we use to assess the earnings of program graduates. IRS earnings data are the most comprehensive source of income available for individuals in the United States and are legally required to be reported by all individuals who have income above a minimum earnings level. The measures provided in the PPD come from the College Scorecard and contain both total wages and deferred compensation from W–2 forms, as well as positive self-employment earnings from 1040–SE IRS forms for each completer. Only Federal administrative sources contain such a comprehensive view of earned income. The quality and reliability of this data is reinforced by the many commenters who cited their own business's W–2 earnings as evidence of typical earnings in their industry. Indeed, one commenter conducted (and some others cited) a study of earnings in a segment of the beauty industry by compiling W2 records for a sample of independently owned salon businesses with 1–10 locations. These attempts to estimate earnings underscore the advantages of Federal administrative data, as it provides a comprehensive repository of the records commenters put a great deal of effort into collecting. However, whereas commenters report information from only W–2 records they have immediate access to through their own businesses, or through surveys of a convenience sample of employees with response rates of 11 percent, IRS administrative records have no such gaps in data collection or limitations in coverage to individuals in a particular set of employers. What is more, the data available to the Department through its data match with the IRS allows it to observe self-employment income through the 1040–SE records it has access to, a source of earnings not available to commenters.

Changes: None.

Comments: Some commenters argued that in lieu of constructing an accountability framework based on reported earnings, the Department should focus its efforts on encouraging or requiring tax compliance among employers in industries where cash tips are prevalent.

Discussion: Though the Department fully endorses tax compliance for all legally obligated parties, it recognizes that enforcement of those rules is under the purview of the IRS. In addition, as outlined in the NPRM and the Department's above responses about unreported income, the Department does not believe there are strong reasons to make accommodations for the possibility of income underreporting.

Changes: None.

Comments: Some commenters noted recent changes in tax law requiring electronic third-party payment processors to issue a 1099–K for dollar amounts as low as $600, a fact relevant to the ability of workers who use such electronic transfer payments to have those payments go undetected. One commenter noted that because this change will likely increase tax compliance and mitigate any underreporting issue, the Department should delay implementation of the regulations until the earnings years used in the rule were covered by this change, which was first applied to the 2022 tax year.

Discussion: As the Department explained in the NPRM and its response to commenters with regard to the underreporting of income, the changes to 1099–K reporting requirements for third party settlement organizations is an important change in the landscape of tax compliance since the last time the Department expressed a view on the extent of underreported income in administrative earnings data. However, while this change certainly buttresses the Department's confidence that currently there is not a more reliable source of earnings information for all occupations, it is not the decisive factor, and therefore the Department does not view the delay of the law's implementation as grounds to delay implementation of either the Transparency Framework or the GE standards.

Changes: None.

Unearned and Self-Employment Income

Comments: Some commenters noted that self-employment is common for some fields and that accurate income measurement could be difficult for individuals in such circumstances because individuals often choose to keep income in their business or may be able to count business expenses against their total income to reduce their taxable income. In particular, one commenter expressed concern that earnings captured on form 1040 schedule SE would not be included in graduates' incomes. One commenter asserted that the Department has acknowledged limitations in its ability to capture self-employment earnings in the Master Earnings File and claims no adequate remedy has been proposed.

Discussion: The earnings data in the PPD used to conduct the Regulatory Impact Analysis come from the College Scorecard data, which matches title IV, HEA recipient data for completer cohorts to three-year earnings information from the IRS. As the technical documentation for the College Scorecard explains, these data contain “the sum of wages and deferred compensation from all non-duplicate W–2 forms and positive self-employment earnings from IRS Form 1040 Schedules SE (Self-Employment Tax) for each student measured.” As noted elsewhere, the Department believes these are data are well-suited for the purposes of these regulations.

Changes: None.

Inclusion of Non-Completers

Comments: Several commenters provided feedback about our choice to exclude non-completers from our calculation of official measures of program performance, including the D/E rates and EP measures. Some mentioned the possibility of including non-completers in the information provided to students through the financial value transparency framework. One commenter supported including non-completers because they represent such a large share (the majority) of students in higher education. Another recognized the value of including non-completers but argued against it for the purposes of constructing a consumer information tool. The remaining commenters opposed the use of non-completers for these measures, arguing that most students were concerned with results for students who complete their programs.

Discussion: Though the Department recognizes the importance of considering the experiences of students who do not complete a program for understanding student success in any field, we believe that tracking results for completers is the most practical approach to assessing outcomes. That approach bases the median earnings measure on students who have had the full benefit of the educational experience at the institution, and that measured debt levels reflect the cost of obtaining the credential. While we agree that institutions should be accountable for helping their students attain a degree, these regulations focus primarily on promoting a balance between financial costs and benefits to students of different credentials. Still, the rule includes completion rates at the institution or program level among a set of supplemental performance metrics that may be included in the program information website to provide this added context to students.

Changes: None.

Median and Mean—§§ 668.403 and 668.404

Comments: A number of commenters disagreed with the Department's proposal in the NPRM to use the median earnings amount for the D/E rates measure and the EP measure. Many commenters noted that in the 2011 and 2014 Prior Rules, the Department used the higher of the mean and median earnings amount as the denominator for the debt-to-earnings rate and these commenters suggested that approach should be applied to calculate earnings for the D/E and EP metrics in this rule as well. One commenter noted that the Department's rationale in the text of the 2014 final rule for using the higher of mean and median earnings was grounded in a concern about the impact of a large number of zero earnings individuals in a completer cohort. In general, quantile statistics such as the median have the drawback of instability if there is a large dispersion of the data near a given quantile point.

One commenter presented a simple example, if a program had five earners (putting to one side the fact that such a program's earnings would be privacy suppressed) whose earnings were $0, $0, $0, $50,000, and $50,000, their median earnings would be $0. However, if just one of those $0 estimates switched to $50,000, the median would switch to $50,000 as well. The question presented by such a case is whether the mean earnings ($20,000 in the first case, $30,000 in the second) better conveys what graduates typically earn at such a program than the $0 median.

The 2014 Prior Rule argued that in such cases the mean is the better reflection of what students can expect than the median. It concluded that in cases where the median is the higher of the two statistics, the mean should be preferred because it reflects high levels of employment in higher earning jobs. Such an example is evident in our second case above, where the median earnings would be $50,000, but the mean is $30,000.

Discussion: As the Department explained in the 2023 NPRM's Background Section, the Department has changed its view on the tradeoffs presented by the advantages and disadvantages of these two measures of central tendency and has concluded that the median is the correct measure. This view is grounded in the fact that the median reflects the minimum earnings level achieved by at least half of a program's graduates, a meaningful measure of student earnings that reflects the experience of the majority of students. Based on data released in the 2014 rule, the median and mean earnings of programs are often very similar. Mean earnings are most commonly higher than median earnings of program completers at programs with very low earnings levels. In such programs, most graduates may have earnings close to minimum wage earnings, but there may be some outlier observations with higher earnings—leading the mean to be higher. Again, we believe it is more appropriate to base the rule on the median earnings, since it indicates the amount of earnings that half of graduates exceed, and it is not as sensitive to outlier observations.

88 FR 32300, 32311 (May 19, 2023).

The Department notes that the commenter's example with just five earnings estimates provides some useful insight into potential limitations of the use of median earnings, but gives an overly dramatic sense of the stakes between the mean and median in the context of the rule. Under these rules, the Department only calculates earnings when there is a minimum of 30 completers in a cohort. With more observations, the difference in earnings among observations near the median is likely to be much smaller than in the commenter's example and so additions of one higher or lower earner will tend to change the median only slightly. On the other hand, an addition of a single extremely high earner could influence the mean substantially, even though outcomes for nearly all students are left unchanged. We view the potential of this latter type of distortion as much more likely and therefore prefer the median.

The Department also believes it is important to be consistent across measures by using same statistic to measure both program graduates' earnings and to construct the earnings thresholds to calculate the earnings premium. The Department cited evidence in the NPRM that mean earnings levels among high school graduates in a State are always higher than median earnings levels because of the large rightward skew of the earnings distribution created by very high earners in income distributions. Using the higher of mean and median earnings in the construction of each State's high school earnings threshold would thus result in a much higher EP threshold for programs to meet. Given our concerns with the representativeness of the mean in the earnings context, we believe such a standard would be an inappropriate comparator for programs. Taken as a whole, we believe the correct choice for both setting an earnings threshold and measuring program graduates' typical earnings against that threshold is to use median earnings.

Changes: None.

Part-Time Employment

Comments: Many commenters mentioned that workers often choose fields such as cosmetology for their flexible work schedules, allowing them to combine part-time work with other valuable activities such as childcare. Working fewer hours means lower annual earnings, they say, but that hourly rates remain very strong and show that many jobs are still lucrative given the number of hours employees in these sectors are working.

Discussion: We acknowledge that many workers may choose to pursue occupations with work schedules that suit their lives. Regardless of the hours that individuals choose to work, we believe it is important that students who borrow earn enough in total to be able to afford their debt payments. For the earnings premium metric, we do not condition on full-time employment in measuring the median high school earnings of individuals in the same State. We therefore compare the earnings of program graduates to high school degree earners in the same State, some of whom are also making similar choices to work part-time.

Changes: None.

Graduates Who Earn Higher Degrees

Comments: One commenter expressed concern about the exclusion of graduates who earn higher degrees from a program's data, since these students may ultimately have higher earnings.

Discussion: In measuring median earnings under the rule, we exclude program completers who are enrolled full-time in a postsecondary program in the year their earnings are measured. Otherwise, however, we will not exclude individuals who may subsequently have gone on to earn a higher credential. As a result, if one program helps students attain higher credentials and thereby higher earnings, that will be reflected in the programs outcomes.

Changes: None.

Earnings Data

Comments: Some commenters expressed suspicion whether the IRS data sources were accurate, with concerns often centering around differences between the incomes reported in the Program Performance and other government sources such as the Bureau of Labor Statistics. As a result, some commenters argued, schools should have the ability to examine earnings data.

Discussion: The disparities between the earnings data in the PPD and the Bureau of Labor Statistics (BLS) in particular stem from a difference in what these two sources attempt to measure. Whereas the PPD measures earnings for all individuals who graduate from specific programs, regardless of the industry they enter (or whether they find any formal employment at all) 3 years after completion, the BLS data cited by the commenters measures the distribution of earnings for individuals who successfully work in a given industry, irrespective of their path into the industry or the stage of their career. It is, therefore, not surprising that these two data sources would differ in the earnings they observe; they estimate a different value for a different population. As we explained in the NPRM and elsewhere in this preamble, we believe that administrative earnings records from the Federal Government matched to the specific students who graduated from a given program is the correct way to measure program earnings outcomes. We believe it is much more appropriate for its purpose than aggregated statistics for whole sectors of the economy, which do not have any necessary relationship to the outcomes of graduates of particular programs.

Changes: None.

Comments: One commenter noted that there is no provision for adjusting the 2021 and 2022 earnings for inflation, in contrast to earnings data provided on the College Scorecard. The commenter noted that we did not explain was given in the NPRM about the rationale for this difference, even though it could affect earnings measurements.

Discussion: The D/E rates metric is a ratio of debt payments divided by earnings or discretionary earnings. For presentation purposes, debt and income numbers from previous years may be translated into more current year dollars on the program information website to facilitate interpretation. But outcomes under the D/E rates metric would not be affected if we do so since both the numerator and denominator would be subject to the same inflation adjustment. For the EP metric, again since both program earnings and the earnings threshold would be adjusted by inflation, the pass/fail outcome of each program is not influenced by the adjustment. Still, the Department may present the EP with such an adjustment on the Department's website and in other communications to facilitate interpretation.

Changes: None.

Completers With No Income

Comments: One commenter recommended that the Department change its calculation of median earnings for programs by excluding individuals with no reported income and then also removing the same number of individuals from the debt cohort, where those individuals are selected for having the highest debt burdens out of the cohort for that program. The rationale, they explained, was that it is unfair to assume zero earnings reflects inability to find work.

Discussion: While the Department recognizes that often individuals choose to leave the labor force for reasons that do not reflect their ability to find a job, we believe that, especially with respect to the career training programs covered by the accountability provisions of the regulations, students typically have a strong interest in being employed in the three-year window directly after graduation. As a result, we believe measuring median earnings, and including those with zero earnings, among completers is the best way to capture the labor market outcomes of program graduates, including both the likelihood that they find employment and the earnings among those who are employed.

Changes: None.

Individuals in Comprehensive Transition and Postsecondary (CTP) Programs

Comments: One commenter indicated that the Department should not exclude students enrolled in CTP programs from GE requirements, arguing that such students were particularly vulnerable and, despite being ineligible for Direct Loans, could exhaust their Pell Grant eligibility while enrolled in poor-performing CTP programs. The commenter asked the Department to consider other options to ensure the quality of CTP programs.

Discussion: Although we agree with the commenter that it is important that CTP programs are of adequate quality, we do not believe that applying the Financial Transparency metrics to CTP programs is the appropriate method of ensuring program quality. As stated in the NPRM, the Department does not believe it is appropriate to apply either the earnings premium or D/E metric to CTP programs. Since students in CTP programs are not required to have a high school credential, it would be inappropriate to judge a CTP program's earnings outcomes against the outcomes of individuals with a high school diploma or the equivalent. And, since these students also are not eligible to obtain Federal student loans, debt-to-earnings rates would be meaningless for these programs.

Changes: None.

Data Sources

Comments: Some commenters expressed concern that the Department has not definitively determined the Federal data source that will provide the earnings data used to calculate the D/E rates and EP measures. These commenters further argued that this indeterminacy does not allow the public adequate opportunity to comment on their choice of data source.

Discussion: The Department provided an adequate notice and opportunity to comment on the proposed rules regarding earnings data, as well as the subjects and issues involved in choosing among data sources. Although the Department has not finalized its data source for the administration of these rules, we have confidence in the reliability of all Federal agency sources under consideration. We believe it is prudent for the long-term efficacy of the rules to retain the flexibility to change data sources if future changes in law or data collection practices and availability make impracticable the use of whichever source might be best to use today. At the same time, the Department's NPRM informed the public about the kind of data needed for the rules, as well as the sources from which those data might be drawn. Indeed, in the NPRM, the Department expressed its current preference for the use of the IRS data that already forms the basis of the earnings measures in the Department's College Scorecard data, and that is used for the Regulatory Impact Analysis in this rule. Comments were welcome on the data types and data sources that we could use in the final rule, including any specific concerns about the Department's preferred options. The Department did, in fact, receive a number of comments regarding those issues—for example, on whether administrative data capture self-employment earnings or whether other survey-based sources of earnings might be appropriate substitutes—and we have responded to those comments elsewhere in this document.

Changes: None.

Comments: Several commenters pointed to salary aggregation websites such as salary.com and ZipRecruiter as alternative data sources, either to support claims about the pay increases their students would see after an initial supervisory or apprenticeship period post-graduation or to dispute the facial validity of the Department's earnings estimates for some types of programs.

Discussion: As with other data sources provided by commenters to challenge the accuracy of the data provided through the PPD, the Department would like to emphasize the comprehensiveness of its Federal administrative data and the reasons that it should be used instead of external sources that do not have a census of earnings records directly matched to the individuals who complete a given program of study.

Websites such as those mentioned by commenters use a variety of methods to estimate earnings for a field, but none of these methods come close to the coverage of the IRS data used to obtain program-level earnings. Instead, they rely on sources such as job listings or self-reported income from website users or other survey sources. By their nature, these methods try to estimate the data we directly obtain from Federal administrative sources. In addition, these external sources provide industry-wide estimates of earnings, regardless of worker experience or background, and often miss the earnings of program graduates who work in a different occupation than that the program intends to train students for, as well as students who may not find work altogether. We do not believe that these sources provide any reason to doubt the accuracy of Federal administrative data, and more broadly believe they are not an appropriate data source to assess the performance of particular programs for our present purposes.

Changes: None.

Comments: One commenter expressed concern that institutions would not be able to collect income information from their students, because it would be a large burden and because students would be unwilling to (and should not have to share) personal income information. This commenter also suggested that the State should collect such information.

Discussion: The regulations in this rulemaking do not require institutions to collect earnings information for their students. The Department will obtain the relevant earnings information through a Federal agency with administrative earnings records.

Changes: None.

Minimum N-Size for Earnings and Debt Metrics

Comments: One commenter noted that they interpreted the remarks of the Department as implying that we would consider a look-back period of 2 to 6 years to develop a cohort of a minimum of 30 students. The commenter objected to the longer look-back period, arguing that such a long period cannot account for any improvements in policy that a program may have made in more recent years.

Discussion: The Department will use a 4-year cohort ( i.e., combining completers who graduate over 4 consecutive award years) when a 2-year cohort is insufficient for a n-size of 30. The Department has not considered a period that is broader than 4 years. The use of a 4-year cohort, when needed, will enable the Department to include data from more programs in the D/E and EP measures.

We note that some lag in the metrics between when students complete a program and when the data is produced is inevitable if we wait several years to measure the earnings of program completers. As discussed elsewhere we believe the 3-year lag to measure earnings is appropriate to allow graduates a period to find employment and settle into their early careers, and the broader lag stems from this choice.

For a period after the effective date of the rule, however, institutions can choose to report data for transitional rates on more recent cohorts' information for calculating median debt levels. During this transition period, changes to programs' borrowing outcomes will be reflected more rapidly in the D/E rates published by the Department.

Changes: None.

Comments: One commenter suggested analysis of additional n-sizes beyond the assessment of 10 and 30 completers, as we discussed in the NPRM. They suggest allowing the minimum n-size to vary by program depending on the need for privacy considerations, or for the rule to include flexibility in the determination of n-size.

Discussion: An n-size of 30 is consistent with past Department practices, including the policy governing the development of cohort default rates, as well as IRS data policy. We recognize that a lower n-size would include more programs, but we believe the n-size of 30 completers over a four-year period is appropriate to protect the privacy of individuals who complete smaller programs, and we project will result in coverage of over 80 percent of students receiving Federal student aid (as documented in the RIA).

Changes: None.

Comments: A few commenters posited that excluding D/E rates for programs with fewer than 30 students completing during a 2- or 4-cohort period rewards public and private nonprofit programs with poor graduation rates.

Discussion: As detailed in the RIA, many programs have very few completers in any given year, and such programs are indeed more prevalent among public and private nonprofit institutions. Still, the more relevant measure of coverage of the rule is the share of students covered. As we explain in the RIA, with these privacy safeguards in place we expect to be able to publish metrics for programs that enroll over 80 percent of federally aided students in both the GE and non-GE programs.

Changes: None.

Comments: One commenter supported the approach to calculate median debt based on at least 30 completers in an applicable cohort.

Discussion: We thank the commenter for their support.

Changes: None.

Measurement of Debt

General Opposition

Comments: Several commenters argued that the rule is too lenient because of reasons such as: it does not include all types of debt in the calculation of D/E, does not take into account other debt metrics such as repayment rates, and because graduate student have longer amortization periods. One commenter argued that the leniency leads only a small subset of programs to be subject to the metrics and that many programs are immune from the accountability metrics.

Discussion: The regulations will provide stronger protections for students of programs where typical students have high debt burdens or low earnings. The share of student enrollment that is covered under the rule is much higher than the share of programs that is covered because there are many very small programs with only a few students enrolled each year. As discussed in the RIA, we estimate that more than half of all programs have fewer than five students completing per year and about 20 percent have fewer than five students enrolled each year. The Department believes that the coverage of students based on enrollment is more than sufficiently high to generate substantial net benefits from the policy. We believe that the number of students, rather than programs, covered by the rule is the more important consideration because the benefits, costs, and transfers associated with the policy almost all scale with the number of students (enrollment or completions) rather than the number of programs.

We do not agree that the Department arbitrarily chose which types of debt to include in the D/E rates calculation. For most borrowers, we measure substantially all of their debt, including private and institutional loans. We exclude parent PLUS loans because parents—and not the students—are responsible for repaying those loans. Finally, we cap this debt at the net direct costs charged to a student in deference to consistent concerns from institutions that they cannot directly control students' borrowing for living expenses.

Changes: None.

Comments: Several commenters criticized the Department for only applying GE rules to the for-profit sector. The commenters argued that 4-year degree programs (administered at private nonprofit and public institutions) saddle students with more debt than shorter programs; however, these programs are not subject to accountability under GE. These commenters argued that the notion that for-profit institutions saddle students with debt at the taxpayers' expense is misguided and not the source of the affordability problems in higher education.

Discussion: The GE regulatory provisions do not measure total debt in isolation. Rather, the regulations hold programs accountable for the ratio of debt to earnings. Although debt may be higher for graduates of some 4-year programs (at private and public institutions), it is reasonable to expect typical earnings to also be higher at programs that lead to students borrowing large amounts. The rule will require 4-year programs at for-profit institutions to pass the D/E and EP metrics, and the rule includes transparency provisions for non-GE programs, including 4-year degree programs, that fail D/E metrics to provide information about the program. Further, GE provisions in the HEA apply only to GE programs.

Changes: None.

Comments: One commenter does not believe institutions should be held accountable for student borrowing because institutions' financial aid departments do not have control over how much students borrow. Specifically, the commenter noted that institutions are required to offer students loans up to what they are offered, even if that exceeds the cost of tuition and fees.

Discussion: Under § 668.403, we cap the debt counted for institutions at the costs of tuition and fees and books and supplies. Institutions have a role in how much they charge to attend programs and in the earnings of their students. These regulations encourage students to attend programs where their debt levels are not likely to be burdensome relative to their earnings.

Changes: None.

Comments: One commenter questioned whether large loan balances are the primary reason for default, as opposed to students' choice or preference to not repay loans or changes in financial and repayment circumstances. The same commenter questioned the use of default rates while the Department is pursuing Fresh Start.

Discussion: This rule focuses on the ratio of debt to earnings and an earnings premium, not on default rates. The Department will use the D/E rates measure to assess the affordability of the debt students incur to pay for their educational program. Regardless of students' decision to make loan payments, a program's D/E rates will be the same.

Changes: None.

Debt Capped at Net Direct Costs

Comments: Several commenters supported the modification to cap the median loan debt at tuition and fees net of institutional grants rather than the amount assessed.

Discussion: We thank the commenters for their support.

Changes: None.

Comments: Many commenters argued that the Department should reduce the total debt number by the amount of any Federal or State grant funds that the student received and used to pay tuition and fee costs. These commenters argued that some students borrow to cover living expenses even when they have received State and Federal aid to cover tuition and fees. These commenters suggested that to ensure that institutions are not held accountable for funds borrowed in excess of what is required to pay for tuition and fees, the Department should reduce the total debt number by the amount of any Federal or State grant funds that the student received and used to pay tuition and fee costs.

Two other commenters suggested that the Department deduct “outside scholarships and grants intended for direct costs from the capped tuition and fees” in the D/E metrics, recommending that the Department net-out both institutional and external grant aid.

Discussion: The Department will deduct only grant controlled by the institution from the estimate of charges for direct costs used to cap individual borrowers' debts. The institution controls institutional grants but would typically not control State grants or external scholarships.

Additionally, under § 668.403, median debt is calculated by capping the total amount of each student's borrowing at the charges for direct costs (tuition, fees, books, and supplies), minus any institutional grant aid the student receives. Therefore, the Department does not hold institutions accountable for loans taken out in excess of direct costs as the commenters suggest. One way that programs can lower their D/E metric is by controlling their net direct program costs—that is, by lowering tuition or providing greater institutional aid.

Changes: None.

Comments: Several commenters suggested that the Department include all student debt (not just debt for tuition, fees, books, equipment, and supplies) in the measurement of debt. A few commenters argued that until the Department restricts borrowing to course delivery, the Department should count all debt regardless of what it is used for.

Discussion: The measurement of debt will cap each student's amount borrowed at the total net direct costs charged to a student. This is in part in deference to institutions' concerns that borrowing for the cost of living is not directly under the control of the institution, whereas institutions can exercise more control over the direct costs charged to students.

Another reason to cap the measurement of debt at direct charges is that it mitigates the influence of differences in students' family income background on measured median debt levels across programs, since some of the additional borrowing of low-income students relative to higher income students is due to borrowing for living costs.

Changes: None.

Comments: One commenter stated that the Department should not remove institutional grant aid from cost of attendance in the measurement of program debt.

Discussion: This rule departs from the 2014 Prior Rule in subtracting institutional grants and scholarships from the measure of direct costs. This change, as described in the NPRM, was in the interest of fairness to institutions that provide substantial assistance to students. Since this type of aid is more common among non-GE programs than GE programs, this change in approach is related to the fact that under subpart Q, the D/E rates will be computed for all types of programs rather than only GE programs as was the case in the 2014 Prior Rule.

Changes: None.

Comments: One commenter suggested that the Department exclude loans borrowed for programs at the institution—other than the one from which the student graduated. The commenter contended that, to establish a true estimate of debt associated with the program a student completes, the attribution provisions should only apply to debt associated with credits from a non-completed program that transfer into the student's ultimate program or that share the same CIP code, or career programs completed at the institution, or both.

Another commenter noted that when students transfer between programs, or when a student enters an institution and does not declare a major, attributing debt to a particular program becomes complex.

A few commenters suggested that the Department include all student debt incurred as of graduation, not just debt incurred for a particular program. These commenters recommended that we hold institutions accountable for the overall financial well-being of their students. The commenters also noted that many programs admit students knowing that they incurred debt from other programs at the same institution or at other institutions. The commenters also highlighted the relevance of the inclusion of all debt for stackable credentials.

Discussion: The Department excludes loan debt incurred by the student for enrollment in programs at other institutions (with the potential exception of when institutions are under common ownership or control). We do not believe it would be fair to hold institutions accountable for debt incurred at other institutions not under their control. We agree that attributing debt to programs within institutions is complex and believe the most reasonable way to do so is to assign it to the highest credentialed program subsequently completed by the student at the institution (within undergraduate and graduate levels). The measurement of debt is based on program completers.

Changes: None.

Parent PLUS Loans

Comments: Many commenters supported exclusion of parent PLUS loans from the median debt calculation. Commenters noted that parent PLUS loans are serviced by parents' earnings, so these loans should not be included in a measure of the student's debt service obligations. Commenters also noted that the inclusion of parent PLUS loans in debt service might logically suggest also including parental earnings in D/E rates calculations.

Discussion: We agree with commenters in support of exclusion of parent PLUS loans. We exclude parent PLUS loans because parents are responsible for repaying those loans, and treating the debt service associated with those loans as a burden to be paid out of the students' earnings may not be appropriate for many students.

Changes: None.

Comments: Several commenters suggested that the Department include parent PLUS loans in calculation of debt for D/E ratios. One commenter argued that excluding parent PLUS loans benefits programs serving mostly dependent students. The commenter also contended that since independent students are ineligible for parent PLUS loans, excluding these loans increases debt for programs serving primarily independent students. The commenter claimed that while the Department states that students are not responsible for repaying parent PLUS loans taken out by a family member, many students nevertheless assist their parents with repayment of these loans. Another commenter argued that the exclusion of parent PLUS loans fails to account for the true amount of debt and unreasonably benefits degree-granting programs at public institutions. Several other commenters claimed that by excluding parent PLUS loans, the Department is undercounting debt obligations and creating a loophole for institutions. Institutions could shift the financial burden of financing higher education from the institution or the student to the parents. One commenter suggested that the Department exclude Direct PLUS loans from measure of debt.

Discussion: The primary purpose of the D/E rates is to indicate whether graduates of the program can afford to repay their educational debt. Repayment of parent PLUS is ultimately the responsibility of the parent borrower, not the student. Moreover, the ability to repay parent PLUS loans depends largely upon the income of the parent borrower, who did not attend the program. We believe that including in a program's D/E rates the parent PLUS debt obtained on behalf of dependent students would cloud the meaning of the D/E rates and would ultimately render them less useful to students and families.

The commenter contended that not including parent PLUS loans increases debt for programs serving primarily independent students. This statement is not accurate, because including parent Plus loans would not impact (positively or negatively) the median debt for a program that serves predominantly independent students who are ineligible for parent PLUS loans. By not including parent PLUS loans, the median debt is not increased as the commenter suggests. Rather, exclusion of parent PLUS loans creates an accurate assessment of the student's ability to repay loans as discussed above.

We remain concerned, however, about the potential for an institution to steer families away from less costly Direct Subsidized and Unsubsidized Loans towards parent PLUS in an attempt to manipulate its D/E rates. We have addressed this concern, in part, by proposing changes to the administrative capability regulations at § 668.16(h), which would require institutions to adequately counsel students and families about the most favorable aid options available to them.

While distinct from the rationale for excluding parent PLUS loans, we note that, for the vast majority of programs, a minority of students are recipients of parent PLUS loans and so their inclusion would affect the median debt of a program only infrequently.

Changes: None.

Comments: A commenter stated that loan debt from parent PLUS loans disproportionately impacts low-income and Black and Hispanic families and contributes to the Black-White racial wealth gap. This commenter suggested that the Department either include parent PLUS loans in the debt measure or impose restrictions on the use of parent PLUS loans that would make it harder for institutions to “game the system.” Specifically, the commenter offered as an example, that the Department could set limits on the percentage of a school's funding that comes from parent PLUS loans or require that students exhaust their title IV, HEA borrowing options before taking out parent PLUS loans.

Discussion: The Department shares the commenter's broad concerns about parent PLUS loans. As explained above, however, the Department does not believe that this rule is the appropriate vehicle to address these concerns.

Changes: None.

Cancelled Debt

Comments: One commenter proposed that the Department remove any student debt discharged or cancelled, including as the result of a national emergency, from the D/E rates calculations.

Discussion: The Department may discharge or cancel debt for a variety of reasons, including if a student becomes totally and permanently disabled, if a student completed 10 years of payments while working for an eligible public service employer, and in circumstances where an institution may have made misrepresentations to students, among other reasons. These actions to discharge or cancel loans do not absolve or change an institution's obligation under the GE regulation to offer programs that provide graduates with earnings sufficient to repay their education debt. For instance, discharges through borrower defense to repayment are due to acts or omissions by the institution. Excluding such discharges from the GE program accountability framework would create a situation where an institution that is found to have engaged in substantial misrepresentations ends up with reduced debt amounts for GE purposes. A similar rationale applies for false certification discharges. In addition, were we to exclude closed school discharges, an institution at risk of failure would have incentives to close some locations to improve their performance on metrics under the GE program accountability framework. Other discharges, such as those tied to Public Service Loan Forgiveness or income-driven repayment are unlikely to be relevant for consideration here because they take at least 10 years for forgiveness, which is longer than the timeframes under consideration for the GE program accountability framework.

However, consistent with the 2014 GE rule, the Department will exclude students with one or more loans discharged or under consideration for discharge based on the borrower's total and permanent disability or if the borrower dies. We exclude these students (from both the numerator and denominator of the D/E and EP measures) because under the HEA a student with a total and permanent disability is unable to engage in substantial gainful activity for a period of at least 60 consecutive months and thus their ability to work and have earnings or repay a loan could be diminished under these circumstances, which could adversely affect a program's results, even though the circumstances are the result of student events that have nothing to do with program performance. Similarly, an institution would not be able to anticipate if a borrower passes away.

Changes: None.

Reduced Program Hours

Comments: One commenter proposed that the Department create a process for schools to report on programs where they reduced the hours and, therefore, student debt in recent years. The commenter contended that this will allow institutions to correct the debt of previous years that did not reflect the current program using the same CIP code.

Discussion: The Department acknowledges that institutions may attempt to improve their program outcomes following the introduction of rates. The transitional D/E rates discussed in the NPRM allow non-GE programs to report information to calculate debts for the most recent 2 award-years, rather than for the same completer cohorts (who generally graduated about 5 years earlier) as used to measure earnings outcomes. Based on comments received, we have modified the final rule to extend this option to all programs. This will allow improvements in borrowing outcomes to be reflected in the D/E rates.

Changes: We have extended the option to report transitional rates information necessary to compute median debt for more recent cohorts to GE programs.

High Debt Holders Eliminated Based on Data Limits

Comments: Many commenters questioned eliminating the highest debt holders based on the number of students without earnings data and believes the Department's basis for doing so is arbitrary and unspecified.

Discussion: The Department is subject to limitations in data access that necessitate our approach. When the Federal agency with earnings data provides the Department with the median earnings of students who complete a program, it will also provide an estimated count of the number of students whose earnings information could not be matched or who died. We remove that number of the highest loan debts before calculating the median debt for each program. Since we do not have individual-level information on which students did not match to the earnings data, we remove those with the highest loan debts to provide a conservative estimate of median loan debt so that we do not overestimate the typical loan debts of students who were successfully matched to earnings data.

Changes: None.

Debt Service Payments Calculations

Comments: A few commenters expressed concerns with the calculation of the annual debt service amounts for a typical borrower at a program that serve as the basis for the debt-to-earnings ratios. The commenters disapproved of amortizing the median program debt balance according to the method described in the regulation rather than calculating the actual annual debt service levels observed for program graduates under the terms of their loans and chosen repayment plan.

A couple of commenters noted that the interest rates used to calculate D/E rates do not correlate with the actual interest rates of the student loan portfolio. The commenters recommended that the Department revise the annual loan payment calculation to reflect the actual repayment terms of the individual student, including the amortization period and interest rate.

Discussion: Actual loan payments depend on a variety of factors, including which repayment plans borrowers elect. Programs with the same levels of borrowing and the same earnings outcomes could have median graduates with different realized loan payments, then, depending on the share enrolled in various plans. Similarly, changes in the set of plans available might lead actual loan payments to change even with no changes in borrowing or labor market outcomes. Using estimated yearly debt payments that are a function of how much students borrow should focus institutions on the goal of ensuring that their programs are ex ante not requiring students to take on unaffordable debt, given the expected earnings of their graduates. The Department disagrees that the interest rates used to calculate D/E rates do not relate to the actual rates of the student loan portfolio. We do not attempt to average the interest rates of the actual loans of student in the completion cohort, but rather take a simpler approach of taking an average of the interest rates on Direct loans over a span of years when completers were likely to borrow. This simpler approach yields much greater transparency and predictability to institutions in how their D/E rates will be determined, while still being likely to accurately reflect borrowing costs in most cases.

Changes: None.

Comments: Commenters suggested that the Department use the same amortization period for all programs. These commenters argued that when borrowers repay over a longer period, this is a sign that the debt is less affordable. Specifically, commenters argued that the 10-year standard should be used across programs regardless of level.

Discussion: Section 668.403(b), provides for three different amortization periods, based on the credential level of the program for determining a program's annual loan payment amount. This schedule will account for the fact that borrowers who enrolled in higher-credentialed programs ( e.g., bachelor's and graduate degree programs) are likely to have incurred more loan debt than borrowers who enrolled in lower-credentialed programs and, as a result, are more likely to select a repayment plan that would allow for a longer repayment period. The longer periods for higher level programs also correspond empirically with the fact that borrowers in longer programs tend to take more time to repay. A further benefit of the longer amortization period for longer programs is that it provides some adjustment for the fact that longer programs often have higher earnings growth beyond the 3-year period used to measure earnings for most programs. As noted above, waiting longer to measure earnings results in the data being more backward looking and less recent. The longer amortization period provides some adjustment without sacrificing the recency of the metric's availability.

Changes: None.

Comments: One commenter proposed that the Department use a fixed interest rate to calculate median debt for the D/E rates. The commenter noted that interest rates are out of the control of the institution and not an indicator of education quality. The commenter proposed that a fixed interest rate be used with the most generous loan payment option available to students in the cohort.

Discussion: The D/E rates are designed to indicate whether graduates can afford to repay their educational debt. Therefore, the calculation uses interest rates over the years that students were likely to have borrowed to calculate median debt, since those interest rates affect the debt service costs that students will need to pay.

Changes: None.

IDR and Debt Payment Calculations

Comments: Several commenters argued that the Department should consider income-based repayment options available to students in the D/E rates calculation. A few commenters noted the loan payment calculation used for the D/E rates is substantially higher than the real monthly payments that borrowers are subject to because of these repayment programs. To improve accuracy of this estimate, and fairness of the regulation, these commenters suggested the Department use expected payments under an income-driven repayment (IDR) plan for D/E rates calculations. By not including repayment plans, these commenters asserted that there is a misconception about the ability of an institutions' graduates to satisfactorily make their loan payments.

A few other commenters argued that the availability of income-based and income-driven repayment programs makes all student debt affordable. The same commenters argued that as long as these programs exist (and students enroll in these programs) the D/E metric is not necessary because all student debt is affordable to students through these repayment plans. One of these commenters argued that use of the D/E rates to indicate affordability is therefore arbitrary and capricious because loan payments for students in repayment plans do not the measures of debt used in the D/E metric. Several commenters noted that the availability of the Revised Pay as You Earn (REPAYE) program renders the D/E rates misleading since no borrower is actually required to pay off loans under a standard repayment plan.

Similarly, another commenter suggested that the D/E measure should incorporate loan repayment programs such as the National Health Service Corps Loan Repayment Program (LRP), Indian Health Service LRP, Health Professions LRP, and the Veterans Affairs Specialty Education LRP. According to this commenter, failure to consider these repayment programs may adversely affect medical schools whose students commit to public service.

Discussion: As we noted in the NPRM, income-based and income-driven repayment programs partially shield borrowers from the risks of not being able to repay their loans. However, such after-the-fact protections do not address underlying program failures to prepare students for gainful employment in the first place, and they exacerbate the impact of such failures on taxpayers as a whole when borrowers are unable to pay. Not all borrowers participate in these repayment plans; where they do, the risks of nonpayment shift to taxpayers when borrowers' payments are not sufficient to fully pay back the loans they borrowed. This is because borrowers with persistently low incomes who enroll in IDR—and thereby make payments based on a share of their income that can be as low as $0—will see their remaining balances forgiven at taxpayer expense after a specified number of years ( e.g., 20 or 25) in repayment. For these reasons, the Department disagrees with the commenters who believe that no debt limit should matter for the D/E metric to make the program affordable to students.

As explained in the NPRM, the purpose of the D/E rates is to assess whether program completers are able to afford their debt, including program completers who do not enroll in IDR or other repayment plans intended to help protect students from excessive payments. The Department recognizes that some repayment plans we offer allow borrowers to repay their loans as a fraction of their income, and that this fraction is lower for some plans than the rate used to calculate the D/E rates. However, we decline to set acceptable program standards at a rate that would allow institutions to encumber students with even more debt while expecting taxpayers to pay more for poor outcomes related to the educational programs offered by institutions. Instead, we view the D/E rates as an appropriate measure of what students can borrow and feasibly repay. Put another way, under the D/E rates calculation, the maximum amount of borrowing is a function of students' earnings that would leave the typical program graduate in a position to pay off their debt without having to rely on payment programs like income-driven repayment plans.

The Department understands that other debt repayment plans for particular fields exist as well, but views these analogously to the Department's own IDR plans. Moreover, these loan repayment programs, while generous, affect only a small fraction of borrowers. For example, in fiscal year 2021, the National Health Service Corps made fewer than 7,000 new Loan Repayment Program awards and the Nurse Corps made about 1,600 LRP awards. The Association of American Medical Colleges estimates that there were about 21,000 graduates of US medical schools in per year in the most recent few academic years, and during the same time period, the number of first time candidates taking the national Nurse Licensing Exam (NCLEX–RN) has totaled over 160,000 annually. This means that these loan repayment programs are used by only a fraction of students.

The NHSC Loan Repayment Program (LRP) currently includes LRP programs for clinicians working at Indian Health Services facilities. See Indian Health Service (n.d.). NHSC Loan Repayment Program. U.S. Department of Health and Human Services Indian Health Service (retrieved from https://www.ihs.gov/loanrepayment/nhsc-loan-repayment-program/ ). U.S. Department of Health and Human Services, Health Resources and Services Administration (2021). Report to Congress: National Health Service Corps for the Year 2021 (available at https://bhw.hrsa.gov/sites/default/files/bureau-health-workforce/about-us/reports-to-congress/report-congress-nhsc-2021.pdf ).

See Association of American Medical Colleges (2022). 2022 FACTS: Enrollment, Graduates, and MD-Ph.D. Data ( https://www.aamc.org/data-reports/students-residents/data/2022-facts-enrollment-graduates-and-md-Ph.D.-data ). National Council of State Boards of Nursing (2023). 2022 NCLEX® Examination Statistics (Vol. 86). National Council of State Boards of Nursing, Inc. ISBN 979–8–9854828–2–9 (retrieved from www.ncsbn.org/public-files/2022_NCLEXExamStats-final.pdf ).

Changes: None.

D/E Metric

Support

Comments: Two commenters noted that the D/E metric is a critical means to identify programs that do not serve students. According to these commenters, it will help protect students, particularly students from marginalized communities, from entering low-value programs.

Discussion: We thank commenters for their support.

Changes: None.

Comments: One commenter noted that D/E rates can be accurately and rapidly calculated using data available to the Department, are easy for students and institutions to understand, and are hard for institutions to manipulate or circumvent.

Discussion: We thank the commenter for their support.

Changes: None.

General Opposition

Comments: One commenter noted that graduate students are sophisticated and should be able to make decisions on their own based on evaluating costs and benefits. Allowing the Federal Government to signal its opinion or remove funding unfairly limits a student's right to choose the program according to this commenter.

Another commenter suggested that the D/E measure should not apply to graduate programs, since their undergraduate experiences affect future earnings.

Discussion: Graduate debt is growing as a share of Federal borrowing. While we might hope that graduate students' relative sophistication would result in fewer students taking on unaffordable debt, the data described in the RIA show that many graduate programs still lead to unaffordable debt. This problem may partially be addressed by the transparency provisions in subpart Q of these final regulations, which would for the first time produce accurate information on the net prices of graduate degree programs to better inform students about costs. Given the very high debt levels associated with some graduate programs, however, we seek to protect borrowers and taxpayers from all programs that consistently leave most of their graduates with unaffordable debts. Among non-GE programs, we will provide D/E and EP information to students and require acknowledgments at high-debt-burden programs to make sure students have this information when they make their choices. GE programs that consistently leave students with high debt-burdens will lose eligibility to participate in the title IV, HEA programs.

With respect to the influence of undergraduate experiences, students pursue graduate education expecting that they will benefit from additional education. The rule requires measurement only of the debt students acquire at the graduate level when measuring the D/E rates of graduate programs yet credits the program with the entirety of a students' earnings (as opposed to the increment to those earnings added by attending the graduate program). Regardless of the extent to which students' undergraduate experience influences their earnings, their graduate debt should be affordable given what they can earn following program completion.

Changes: None.

Comments: One commenter contended that the rule rewards low graduation rate programs with higher typical salaries than would be the case with an acceptable graduation rate. According to this commenter, the Department should downward adjust earnings levels for low graduation rate programs and upward for higher graduation rate programs.

Discussion: The median debt and earnings information underlying the metrics in the rule are based on completers. For debt, the goal is to capture the full amount students need to borrow to obtain a credential. For earnings, we use completers' median earnings to better reflect the value of fully completing the program. While we agree in principle that accounting for completion rates may be additionally useful, in practice it is infeasible to measure program level completion outcomes given that students often do not enroll in a specific program at entry ( i.e., students enrolling in longer programs with overlapping general education requirements often begin undeclared), making it impossible to define completion cohorts. More generally, we believe the measures as defined are a reasonable compromise in measuring the debt and labor market costs of students who complete a program—a group of students where there can be less debate about whether the program should be responsible for their outcomes.

Changes: None.

Comments: One commenter proposed that D/E should include other types of debt, such as automobile loans and credit cards.

Discussion: The Department cannot definitively tie non-student loan debt that students acquire, such as automobile loans and credit card debt, to the student's pursuit of a degree. The D/E metric aims to measure how well a GE program prepares students for gainful employment in a recognized occupation. Data on the other debt students might incur is not readily available to us and, more importantly, is outside of the scope of our regulatory authority.

Changes: None.

Comments: A few commenters warned that it is unclear how D/E is calculated for undeclared students.

Discussion: The D/E rates are calculated based only on students who graduate from a program. Students initially undeclared are counted in the program where they graduate at a given credential level, and the debt they accumulate at that credential level is included in their total debt.

Changes: None.

Comments: Several commenters contended that the D/E metric prevents institutions from developing new programs, because an institution that offers a new program will not have students completing within 6 years.

Discussion: In instances where a program does not have data to calculate the D/E rates, such as for a new program, there would simply be no D/E metric available. There are no eligibility consequences for a program with no D/E or EP rates available. Additionally, we do not believe the rule would discourage an institution from creating new programs unless the institution expected the program to eventually lose eligibility due to high-debt burdens or low-earnings.

Changes: None.

Comments: Two commenters argued that it is unfair to not allow programs to improve or reintroduce a program once it has failed.

Another commenter contended that the Department should not penalize an institution if it responsibly ends a program that produces failing D/E rates in its final years.

Discussion: The rule allows institution to report transitional D/E rates based on median debt outcomes for completers in the two most recent award years for a temporary period. This affords institutions the opportunity to improve their programs in response to the metrics produced for their programs. After this transitional period where institutions can improve their measures, the metrics become more backward-looking, so this opportunity is diminished.

If a program loses eligibility under the rule or if an institution voluntarily discontinues a failing program, the institution may not launch a similar program for 3 years. As we discussed in the NPRM, we intend for this waiting period to protect the interests of students and taxpayers by requiring that institutions with failing GE programs take meaningful corrective actions to improve program outcomes before reintroducing a similar program with Federal support. The 3-year period of ineligibility closely aligns with the ineligibility period associated with failing the CDR, which is the Department's longstanding primary outcomes-based accountability metric on an institution-wide level.

Changes: None.

Comments: One commenter expressed concern about how D/E will be calculated for colleges and programs that do not participate in the Direct Loan program due to the low cost of tuition and fees.

Discussion: The median debt for programs whose students receive no Direct Loans will be zero. This means that these programs will pass D/E.

Changes: None.

Comments: One commenter suggested that students already enrolled in a failing program should be allowed to receive title IV, HEA aid until they complete the program.

Discussion: The Department is sympathetic to the potential disruption for students who may continue to be enrolled in a program that loses title IV, HEA eligibility. Institutions must issue warnings to any student in or interested in a program if the program fails one of the GE metrics and, therefore, faces a potential loss of Title IV, HEA eligibility if it fails again. Hopefully this will both allow students a chance to finish their studies, at least in shorter programs, or to make plans to transfer if the program loses funding.

The Department believes, however that most students will be better served by transferring to a better performing program rather than further accumulating debt or spending time in a program where they will be unlikely to earn enough to manage it, or not accumulate skills to earn more than a high school graduate. Analyses presented in the RIA suggest that most students will have other better options to which to transfer.

Changes: None.

Comments: Several commenters contended that the GE rule should allow for transitional D/E rates for GE programs for a multiyear period after the regulation takes effect.

Discussion: All programs will have transitional rates that will be based on the debt of completers in more recent years for 6 years.

Changes: We have modified § 668.408(c) to give all programs the option to report transitional rates for the first six years after the rule is in effect. While we believe that most institutions with GE programs have experience reporting similar information under the 2014 Prior Rule, this change offers flexibility and alleviates burden for some institutions to avoid reporting on cohorts that completed six years or more previously.

Comments: One commenter recommended that since the 2014 GE rule only included the D/E metric, passage of either D/E or EP should be sufficient for establishing that a program prepares students for gainful employment. Other commenters suggested that we require all programs to pass both measures, instead of some being required to just pass one.

Discussion: As we explain in the NPRM and elaborate upon above, the EP measure captures distinct aspects of how programs prepare students for gainful employment. The EP is based in part on statutory provisions ensuring that postsecondary programs build on the skills learned in high school and enhance a students' earnings capacity regardless of how much they borrow. Whatever students' post-college earnings are, it is important that their debt levels are affordable and in reasonable proportion to their earnings. GE programs must pass both metrics to avoid consequences. Career training programs that fail either or both metrics in a single year will be required to provide warnings to students that the programs could be at risk of losing eligibility for title IV, HEA funds in subsequent years. Programs that fail the same metric in two of three consecutive years would have lose their eligibility. The two metrics together create the strongest framework for protecting students and taxpayers.

88 FR 32300, 32325 (May 19, 2023).

Comments: One commenter raised concerns that institutions cannot compel graduates to seek occupations in the field for which they train.

Discussion: The purpose of these regulations is to increase the likelihood that students entering career training programs are given the skills and credentials to repay their student loans and earn more than they would have had they not attended a postsecondary program. Many students may find employment in an occupation that differs from what the program prepared them for, and we do not penalize programs for that.

Changes: None.

Exclusion or Inclusion of Certain Student Populations

Comments: One commenter contended that the earnings component of the D/E rates calculation should exclude students who have a title IV, HEA loan in military-related deferment status. The commenter believed that including outcomes for such students in the D/E rates would be arbitrary and exceed the Department's statutory authority, because such students' military earnings provide no information about the quality of the program. The commenter recommended that the Department adopt the approach in the 2014 Rule and exclude such students.

Discussion: The Department disagrees. As we acknowledged in the NPRM, the D/E rates calculation in these regulations differs from the 2014 Rule in certain respects. In the 2014 Prior Rule, the Department reasoned that students with military deferments should be excluded from the D/E rates calculations because they could have less earnings than if they had chosen to work in the occupation for which they received training. The final rule went on to state a student's decision to enlist in the military is likely unrelated to whether a program prepares students for gainful employment, that it would be unfair to assess a program's performance based on the outcomes of such students, and that the Department believed that this interest in fairness outweighed potential impact on the earnings calculations and the number of students in the cohort period.

79 FR 64889, 64944–45 (Oct. 31, 2014).

However, we cannot now conclude with confidence that the earnings of military personnel are unrelated to the postsecondary programs that they completed. First, the latest Quadrennial Review of Military Compensation (QRMC) shows how strongly correlated educational attainment is with pay grade for both enlisted personnel and officers. For example, in 2017 while none of the enlisted personnel at the lowest reported pay grade (E–2) had a bachelor's degree or more, 55 percent of those in the highest pay grade for enlisted personnel had at least a B.A. Similarly, virtually all officers (91 percent) at the lowest pay grade had a bachelor's degree, while 80–100 percent of the officers in the top pay grades had an advanced degree, with that share increasing with the pay grade. Educational attainment is clearly a key component of pay grade in the military, and program quality is a key factor in attainment.

See tables 2.1 and 2.1 in Department of Defense (2020). Report of the Thirteenth Quadrennial Review of Military Compensation, Volume I, Main Report ( https://militarypay.defense.gov/Portals/3/QRMC-Vol_1_final_web.pdf ).

More broadly, program quality determines the skills a student will receive and have available to them on the job. Whether that job is in the military or in some other field with a step-and-lane-style pay schedule, skill is still an important determinant of job success and pay, if for no other reason than more skilled employees (or military personnel) have more opportunities for advancement. That can be as simple as promotion to Officer, but it also includes opportunities such as the military's opportunities for service members to be trained in designated military skills or career fields, which require special advanced training or educational credentials in key fields that military seeks to promote. Training in these fields can earn personnel a bonus upon completion of their role, plus whatever career advancement comes from a military career in those valued fields.

Department of Defense, Under Secretary of Defense (Comptroller) (n.d.). DoD 7000.14—R: Military Pay Policy—Active Duty and Reserve Pay, Volume 7A ( https://comptroller.defense.gov/Portals/45/documents/fmr/Volume_07a.pdf ).

Furthermore, including these earners would likely raise the median income measured for their particular program because this group of program completers are demonstrably employed, and because, as the latest QRMC demonstrates, the military has long sought to (and surpassed) a goal of paying service members at a level equivalent to the 70th percentile of comparably educated and experienced civilians. Nevertheless, there is still a possibility that this group of program completers may have earnings that do not otherwise support the debt they incurred. Servicemembers should receive the same consumer protections afforded to other student borrowers from their GE program completer cohort. Accordingly, the Department has concluded that their earnings should be reflected in the data that we use to provide information about and evaluate GE programs supported by title IV, HEA student assistance. This conclusion is reasonable and, as we explained in the “Reliance Interests” section of the NPRM, this approach does not implicate any significant reliance interests.

Changes: None.

Comments: One commenter suggested that the Department should consider programs with fewer than 30 students as “passing due to insufficient data.” The commenter contended that this label may help to mitigate the incentive for schools to cap program enrollment at 29 students.

Discussion: In principle, the Department agrees that “passing due to insufficient data” is one appropriate label for programs that have too few completers in the applicable cohort for metrics to be issued. That label conveys potentially helpful information, and we may use that or similar language to describe programs in the future. We note that these rules specify the conditions under which programs pass or fail the D/E and EP metrics (§ 668.402), along with the conditions under which the Department does not issue the D/E rates or the EP measure because of an insufficient number of completers (§§ 668.403(f) and 668.404(d)). Those rules do not require the Department to use particular labels to describe programs that are subject to these metrics. At the appropriate times and consistent with these rules, the Department will make the necessary choices regarding the details of the Department's program information website, through which student acknowledgments will be administered (§§ 668.407(b) and 668.605(c)(3), (g)), as well as the warnings with respect to GE programs (§ 668.605).

Changes: None.

Comments: One comment expressed concern about how to calculate the data for students that do not complete their program of study because they choose to enter the workforce once they gain a certification in a program.

Discussion: Students who do not earn a credential are not counted in the earnings or debt metrics for a program. If a student does not complete an associate degree after obtaining a certificate, that student would be counted in the completer cohort for the certificate program. We may expect that student's earnings would be less than their earnings would have been if they completed the associate program, but so, too, would their debt. Regardless, we expect the majority of students completing a certificate to out-earn individuals with only a high-school diploma and to not have a high debt-burden.

Changes: None.

Discretionary D/E Measures

Comments: One commenter posited that D/E has a low correlation with a measure of return on investment (ROI) that the commenter themself created. The commenter then compares pass/fail under GE to pass/fail under their personal formula to assign whether they think a program “correctly” or “incorrectly” passes or fails. The commenter uses such comparisons to recommend changing amortization periods for graduate students and that the D/E rate should be assessed on the basis of the annual earnings rate alone.

Discussion: We appreciate the commenter's suggestions, and analysis of how this rule's parameters could be modified to better align its pass/fail outcomes with the commenter's own estimates of program-level ROI. However, there are numerous issues with the commenter's methodology that do not make it an appropriate standard for judging whether the metrics used and pass/fail outcomes in GE are “correct” or “incorrect.” This includes several self-acknowledged reasons why the methodology systematically overestimates or underestimates ROI for different types of programs, and assumptions that students' earnings trajectories relative to their peers do not change over time. In addition, the commenter's attempt to create counterfactual wages relies on adjustments made on very broad educational credential by field of study groups that do not reflect specific programs well.

Changes: None.

Comments: Several commenters argued that the evidence cited for the use of the 20 percent discretionary income threshold is not strong. Several commenters note that the 20 percent discretionary D/E threshold can be traced back to a 2006 report from Economists Sandy Baum and Saul Schwartz. The commenters asserted that discretionary income is always defined arbitrarily ( i.e., attempts to draw distinctions between discretionary and nondiscretionary expenditures are fraught with difficulty). Other commenters contended that the (annual) D/E threshold is based on affordability of mortgage rates and should not be used for student debt.

Discussion: As the commenters noted, the 20 percent discretionary D/E threshold is based on research conducted by Sandy Baum and Saul Schwartz. Their research proposed benchmarks for manageable debt levels, and the authors' research suggested that no student should have loan payments exceeding 20 percent of their discretionary income. In subsequent commentary one of the authors argued that, if anything, a 20 percent discretionary threshold for the median borrower is too permissive and a stricter standard would be justified. Although the starting point for their research was in the context of the affordability of mortgage rates, their overall point stands—that it would not be affordable for borrowers to have student debt-service ratios beyond what is in the GE rule.

Changes: None.

Comments: One commenter asked how a school could pass the discretionary debt-to-earnings rate and not the annual debt to earnings measure. According to this commenter, if reasonable scenarios do not exist, this ratio is irrelevant and does not provide a reasonable additional option to schools.

Discussion: We carefully explain the relationship between the two rates in the NPRM (see Figure 1 from the NPRM and the surrounding text). Many programs with higher levels of earnings pass the discretionary D/E measure but not the annual D/E measure.

Changes: None.

D/E Rates Thresholds

Comments: A few commenters argued that the thresholds align with other measures of hardship: Borrowers with student loan payments above 8 percent of income or 20 percent of discretionary income experienced greater hardship than those with payments below these thresholds.

Discussion: We thank the commenters for their support.

Changes: None.

Comments: Many commenters requested that the Department return to the D/E rate thresholds of 12 percent annual D/E and 30 percent annual discretionary D/E that were used in the 2011 and 2014 Prior Rules. Some of these commenters posited that the changes from those thresholds to the D/E rate threshold in the NPRM is arbitrary and capricious.

Several other commenters objected to the lack of inclusion of the “zone” as in the 2014 Prior Rule, asserting that without the zone, programs could fail because of fractions of a dollar in the GE calculation or that programs do not have the space to make necessary program changes.

Discussion: The Department considered these concerns and decided to base the thresholds upon expert recommendations and mortgage industry practice—that is, the 8 and 20 percent thresholds for annual and discretionary D/E, respectively. The 12 and 30 percent thresholds used in the “zone” were selected by adding a 50 percent buffer to these evidence-based thresholds, so as to give institutions that were “close” to the D/E thresholds an additional year to potentially improve their performance.

In the final rule, the Department has adopted a transition period where institutions can report debt information for more recent completion cohorts. This provision is similar to a transition provision that was included in the 2014 Prior Rule under 34 CFR 668.404(g) that permitted institutions to use updated program costs in the outcome calculations for 5 to 7 award years, depending upon the length of the program. The transition period for these regulations will allow any improvements in the cost structure of programs to more rapidly be reflected in institutions' D/E rates.

Changes: None.

Comments: A few commenters stated that the 8 percent annual D/E threshold would preclude for-profits from offering BAs and eliminate many Associate of Arts (AA) programs. The commenters believe these institutions will be forced to lower tuition; therefore, this imposes a price cap on for-profit and vocational institutions.

Discussion: Programs must pass either the annual D/E threshold of 8 percent or the discretionary D/E threshold of 20 percent. For programs with higher income levels, the discretionary rate is more likely to apply, which allows median debt levels to be higher relative to median earnings levels. The RIA shows that the majority of proprietary associate and bachelor's programs do not fail the D/E metrics. We disagree with the commenters' assertion that institutions will be forced to lower tuition to pass the D/E rates, as the final rule allows institutions to set tuition or find additional student resources so that students' borrowing levels are reasonable in light of their typical earnings outcomes and so that students do not take on more debt than they can reasonably manage.

Changes: None.

Programs With Low Borrowing Rates

Comments: Some commenters suggested that the Department should not subject programs with only a few borrowers to the D/E metric or should use a different metric for them. According to this commenter, a program with a small percentage of borrowers overall that does not meet the debt to earnings ratio would jeopardize the Pell Grant eligibility for the entire program.

Discussion: Programs with few borrowers are very unlikely to fail the D/E rates measure. We calculate median debt among all title IV, HEA recipients, including those who receive only Pell grants. As a result, if the majority of program completers do not borrow, the median debt of program completers will be zero. The program will, therefore, pass the D/E metric. This acknowledges the affordability of programs where many or most students do not need to borrow to attend the program. As a result, we see no risk that programs with few borrowers will lose title IV, HEA eligibility as a result of the D/E provisions of rule.

Changes: None.

Comments: One commenter believed that non-borrowers will not look at the D/E ratios because they are not relevant to them.

Discussion: The D/E metric is primarily a measure of debt affordability, capturing the share of a typical graduate's annual earnings that will need to be devoted to loan payments. Under the transparency provisions in § 668.407, only prospective students will provide acknowledgments prior to enrolling in an institution. While ultimately those with no intention of borrowing may not be concerned with potential loan payments, prospective students may find information about the D/E rates of different programs helpful as an indicator of the labor market success of those programs' graduates, the costs of the programs, or both. More importantly, the information may inform their choice of whether to enroll in the program, and if so whether to borrow to attend. The rule will create more transparency on earnings outcomes and the net price of programs, however, and we expect that non-borrowers will find that information most salient. Moreover, we also expect the D/E ratios to be relevant to borrowers.

Changes: None.

Earnings Premium Metric

General

Comments: Many commenters expressed support for the EP measure as a “common sense” threshold to measure completer earnings against.

Discussion: We thank commenters for their support.

Changes: None.

Comments: Many commenters suggested that the EP measure is arbitrary, not sufficiently studied, and not backed by research evidence.

Discussion: The Department believes that the EP threshold, which uses the median State-level earnings of high school graduates in the labor force, is an intuitive benchmark for both policymakers and prospective students. Comparison to the earnings of those with only a high school diploma has long been a measure of the effectiveness or value of completing a given post-secondary credential in research literature.

See for example, see Goldin, Claudia & Katz, Lawrence F. (2010). The Race Between Education and Technology. Cambridge: Harvard Univ. Press. Baum, Sandy (2014). The Higher Education Earnings Premium. Urban Institute ( www.urban.org/sites/default/files/publication/22316/413033-Higher-Education-Earnings-Premium-Value-Variation-and-Trends.PDF )—among other numerous examples.

Changes: None.

Comments: One commenter suggested that the EP threshold should be higher to account for a student's need to repay the loan debt incurred in connection with the credential.

Discussion: The Department recognizes that calculating a “net earnings premium” that subtracts from the EP some measure of the (amortized yearly) costs of college or debt service payments may provide a reasonable measure of the financial gain to completing a program in some contexts. However, under the rule, we will use the EP measure to assess whether students who complete a program are better off, strictly in terms of their earnings, than individuals who never attended a postsecondary program. The calculation of this measure is unaffected by the costs students might incur to attend the program. The measure applies even for a student whose education expenses might be entirely covered by grant aid. We note that the D/E rates are intended to assess a cohort's ability to afford the debt they borrow to pay the direct costs of attending the program, so we do not additionally account for program costs in the EP measure.

Changes: None.

Earnings and Location

Comments: Many commenters suggested that earnings vary substantially within a given State by urbanicity. These commenters suggested that we adjust the D/E rates or EP calculations for programs serving students in rural areas. Some other commenters suggested using metropolitan or micropolitan statistical areas (MSAs) to better distinguish between earnings potential for completers within a given State.

Discussion: Though many commenters expressed concerns about urban/rural divides in economic opportunity, their proposed solutions often involved calculating earnings premiums at the metropolitan area level. There are a few reasons the Department sees this as a flawed approach. First, as Office of Management and Budget (OMB) Bulletin No. 23–01 outlines, Core Based Statistical Areas, such as Metropolitan Statistical Areas (MSAs) “do not equate to an urban-rural classification; many counties and county-equivalents included in Metropolitan and Micropolitan Statistical Areas, and many other counties, contain both urban and rural territory and populations.” There is plenty of variety in the urban character of local areas even within area designations as small as the MSA, and so calculating earnings estimates at that level may not capture differences in labor market opportunities by population density or other characteristics of an area often associated with the urban/rural divide.

Executive Office of the President, Office of Management and Budget (2023). Revised Delineations of Metropolitan Statistical Areas, Micropolitan Statistical Areas, and Combined Statistical Areas, and Guidance on Uses of the Delineations of These Areas (OMB Bulletin No. 23–01). Washington, DC.

The same OMB bulletin further warns that, in keeping with the Metropolitan Areas Protection and Standardization (MAPS) Act of 2021, agencies should be hesitant to use CBSA designations for the administration or regulation of non-statistical programs and policies. Our view is that while MSAs provide a useful approximation to major and minor urban centers in a State, they do not measure a relevant unit for the purposes of this regulation. This is especially true in the context of postsecondary education, where students often travel outside of their home MSA to attend school and, as a result, are likely to have considerable cross-MSA mobility after graduation.

Our view is informed by an analysis the Department conducted to assess the viability of measuring earnings at the metropolitan area level. To understand the implications of such a change, we first examined how the earnings threshold would vary across each State if it varied for metropolitan and non-metropolitan areas. The IPUMS USA version of the ACS 5-year sample for 2019 adds the necessary information to the PUMS data to divide households into different geographic classifications based on the metropolitan status of the area they live in, which the IPUMS USA describes in this way: “[the relevant field] indicates whether the household resided within a metropolitan area and, for households in metropolitan areas, whether the household resided within or outside of a central/principal city.” Table 1.4 below shows how earnings thresholds would vary if they were set at the median earnings for the same population (high school graduates aged 25–34 who were in the labor force in the previous year), divided by which type of metropolitan area those individuals live in.

Table 1.4—Median Income for HS Grads 25–34 in Labor Force, by State and Metro Status

Metropolitan status
Mixed met. status Not in met. area In met. area: central city In met. area: not central city Met. area: mixed central city status Overall
Alabama 21,582 23,000 21,177 29,202 22,445 22,602
Alaska 30,000 21,307 29,675 27,489
Arizona 21,582 18,111 26,000 26,471 25,453 25,453
Arkansas 22,527 21,902 30,000 25,569 24,000
California 25,000 26,073 26,178 26,073 26,073
Colorado 27,500 30,000 27,000 30,107 29,322 29,000
Connecticut 31,961 22,000 29,202 25,899 26,634
Delaware 26,634 25,453 26,471
District Of Columbia 21,582 21,582
Florida 22,373 21,582 22,445 24,819 24,000 24,000
Georgia 24,000 22,700 24,000 25,030 23,000 24,435
Hawaii 30,000 26,330 26,978 30,245 31,288 30,000
Idaho 23,883 28,000 28,600 25,453 26,073
Illinois 25,036 26,073 22,297 26,634 25,000 25,030
Indiana 27,000 27,699 24,503 28,000 24,842 26,073
Iowa 30,000 26,073 29,202 28,000 28,507
Kansas 25,569 24,819 23,438 30,544 26,073 25,899
Kentucky 26,073 22,945 20,221 25,359 23,012 24,397
Louisiana 26,073 26,500 20,024 26,386 21,000 24,290
Maine 25,453 29,830 21,798 26,073
Maryland 26,634 22,900 29,136 26,500 26,978
Massachusetts 26,073 28,000 30,000 30,349 29,830
Michigan 23,988 23,740 17,000 25,030 24,000 23,438
Minnesota 30,000 27,116 25,569 31,154 27,116 29,136
Mississippi 21,000 20,562 17,613 25,569 19,963 20,859
Missouri 25,000 23,988 21,307 25,575 26,471 25,000
Montana 25,030 25,453 28,159 25,453
Nebraska 29,783 29,800 21,307 34,092 25,782 27,000
Nevada 23,417 31,961 25,030 27,489 27,387 27,387
New Hampshire 31,961 28,057 28,057 36,652 32,373 30,215
New Jersey 23,438 27,325 23,620 26,222
New Mexico 19,548 26,741 20,400 20,859 25,453 24,503
New York 26,000 24,405 24,700 26,978 25,000 25,453
North Carolina 23,000 22,661 22,399 23,417 23,417 23,300
North Dakota 33,598 27,116 27,116 31,294
Ohio 24,435 25,569 18,326 26,073 23,000 24,000
Oklahoma 25,030 25,453 25,453 27,800 26,000 25,569
Oregon 23,988 23,000 25,569 29,800 24,435 25,030
Pennsylvania 25,453 26,073 21,307 27,806 25,030 25,569
Rhode Island 23,417 26,978 30,000 26,634
South Carolina 24,718 20,362 25,860 22,900 23,438
South Dakota 30,000 25,030 29,202 28,000
Tennessee 23,438 22,900 19,500 26,438 23,824 23,438
Texas 25,899 25,000 24,405 28,000 25,899 25,899
Utah 26,471 30,215 19,709 29,202 28,765 28,507
Vermont 25,000 30,215 26,200
Virginia 25,453 20,566 25,000 27,699 24,435 25,569
Washington 27,534 25,300 30,000 31,961 29,202 29,525
West Virginia 21,582 22,661 30,544 24,196 23,438
Wisconsin 30,000 29,617 22,160 27,116 28,507 27,699
Wyoming 27,082 31,961 30,544
Total 25,453 25,000 24,280 26,654 25,453 25,453

Table 1.4 illustrates the challenge of this approach. To the extent that the commenters' main concern about State-level earnings thresholds is that institutions located outside of metropolitan areas would be disadvantaged, the data does not bear this out. In many instances, such as Alabama, Colorado, and Illinois, the earnings threshold outside of metropolitan areas would be higher than the current statewide standard (displayed in the “Overall” column). Because many low-income people live in cities, it is not consistently the case that metropolitan areas or central cities have higher median incomes for high school graduates than non-metropolitan areas. What is more, this pattern is not consistent across States, suggesting there is not a systematic disadvantage for non-metropolitan areas that would justify switching to another standard that would have its own disadvantages.

Changes: None.

Comments: Several commenters suggested using a school's location in a Persistent Poverty County as an additional EP consideration. These commenters proposed that we could exclude schools located in these counties prior to the effective date of the GE rule from application of the EP measure, or we could adjust the EP threshold for programs in such counties downward by 20 percent.

Discussion: To understand the implications of this proposal, we assessed whether each program would be exempt based on being located in a Persistent Poverty County. To do this, we assigned each program to a county based on the location of its main campus and then determined whether that county was one of the 341 the Census Bureau determined to be persistently poor. We then examined which institutions, and which major cities housed institutions that would be exempt from the EP measure if we modified the rule in this way. Below is a list of the 15 largest institutions located in a county that is Persistently Poor under the Census's definition:

Largest Institutions With Main Campuses in Persistent Poverty Counties in Terms of Enrollment

Institution name 6-Digit OPEID Total enrollment Number of programs Location
University of Florida 1535 45,996 324 Gainesville, FL.
Temple University 3371 40,537 255 Philadelphia, PA.
Fresno City College 1307 40,431 114 Fresno, CA.
University of Georgia 1598 35,589 296 Athens, GA.
Texas A&M University 3632 34,089 252 College Station, TX.
Ohio University 3100 33,722 190 Athens, OH.
El Paso Community College 10387 31,413 81 El Paso, TX.
University of Texas Rio Grande Valley 3599 30,710 121 Edinburg, TX.
West Virginia University 3827 30,592 192 Morgantown, WV.
Georgia Southern University 1572 30,141 111 Statesboro, GA.
East Carolina University 2923 30,021 172 Greenville, NC.
Brigham Young University—Idaho 1625 29,243 84 Rexburg, ID.
Central Michigan University 2243 28,126 150 Mt Pleasant, MI.
University of Texas at El Paso 3661 27,759 141 El Paso, TX.

This list is a clear signal that the Persistent Poverty County exemption would be poorly targeted from the perspective of identifying institutions facing insurmountable economic conditions that would merit exemption from the general standard laid out in the NPRM. A number of the institutions on this list are major State flagship institutions with a strong track record of graduating large numbers of students into stable and well-remunerated employment, suggesting that being located in these counties is not in fact outcome determinative for students in such institutions. The exercise reveals a limitation of the approach more generally, which is that these institutions draw on students from a variety of different locations, and their graduates go on to work in many different places outside the county where the institution is located.

An additional datapoint that reveals that this measure of county poverty may not well capture economic conditions that dramatically impede labor market success for college graduates is the list of the 15 cities in Persistent Poverty Counties with the largest enrollment across all institutions and programs located there:

Top Cities in Persistent Poverty Counties in Terms of Enrollment

City Total enrollment Total number of programs
Philadelphia, PA 147,782 1,300
Fresno, CA 74,385 352
Brooklyn, NY 72,679 340
El Paso, TX 64,957 254
New Orleans, LA 58,608 532
Gainesville, FL 57,652 379
Bronx, NY 57,528 301
Baltimore, MD 51,202 542
Athens, GA 40,123 363
College Station, TX 34,089 252
Athens, OH 33,722 190
Richmond, VA 33,323 257
Statesboro, GA 32,570 163
Morgantown, WV 30,824 201
Edinburg, TX 30,710 121

This list includes a number of the country's largest cities, as well as a number of college towns. This gives us pause for two reasons: first, the inclusion of major cities with both a high incidence of poverty and vibrant economies suggests that the Persistent Poverty County construct is not designed to capture the kind of within-county inequality that allows deep poverty to coexist with strong labor markets for college graduates. Second, the existence of so many college towns suggests that the measurement of Persistent Poverty Counties may partly be picking up places where a large fraction of the area's residents are students who are in school and therefore not in the labor force or working only part time, perhaps exaggerating the true extent of poverty in the area, or at least not reflecting its likely transience for the individuals being measured, who can expect a significant increase in their standard of living once they graduate from college. Additionally, in such cases we would not expect this more transient poverty measured in college towns to be an impediment to the earnings trajectory of students after college.

See the Census's own analysis of poverty measurement in college towns here: www.census.gov/library/stories/2018/10/off-campus-college-students-poverty.html.

Changes: None.

Economic Swings

Comments: Several commenters expressed concern about how earnings data would be affected by rapid downturns in the economy. Their concerns largely regarded the lag between the economic conditions at the time students incur their debts and when the earnings are assessed. Other commenters argued that the EP threshold could not accurately account for the labor market impact of national events, such as a pandemic, or for more localized labor market events, such as a natural disaster.

Discussion: The Department recognizes that economic conditions can change rapidly, that the earnings premium for a program during a booming economy may differ from that premium during a downturn, and that students often make decisions about their educational investments without a full picture of the economy they will graduate into. Nonetheless, we believe the uncertainty around the broader economic conditions provides more reason to monitor and enforce rules around the economic outcomes for students who graduate from a given program through the EP measure. One benefit of a college education is some degree of insulation from economic downturns, and an important measure of program quality is the robustness of its graduates' employment outcomes to economic shocks.

The EP threshold is well suited to adjust to State or national disruptions to the labor market. The earnings of high school graduates tend to be much more pro-cyclical than those of college graduates. That suggests that the EP threshold will tend to fall more in economic downturns than will the median earnings of college graduates, therefore buffering the impact on program outcomes. It is possible that the EP threshold may not adjust for more localized labor market shocks at the sub-State level. The Secretary may, however, have authority under statute to waive or modify regulatory provisions that apply to institutions in disaster areas or that are significantly affected by disasters. The Department is not convinced that the rules here should be further adapted to address such exceptional circumstances.

See, for example, 20 U.S.C. 1098bb(a)(2)(E).

Changes: None.

Earnings Threshold for Graduate Programs

Comments: A few commenters suggested using a different EP threshold for programs that issue graduate degrees. One suggestion was that we use the median earnings of bachelor's degree recipients who majored in the same field as the graduate degree.

Discussion: The 2019 5-year American Community Survey (ACS) contains information on bachelor's degree fields for survey respondents. These data are available in broad categories that generally align with similar CIP categories. The median earnings for those age 25–34 in the labor force with a bachelor's degree and a recorded major category is around $46,000, reported in 2019 dollars. The range of median earnings by degree field is substantial, ranging from around $28,000 to $71,000.

The Department recognizes the logic of this approach, but also has identified some substantial disadvantages. For example, the data do not have enough individuals in the sample to provide robust State-level estimates of median earnings for all fields of study. Further, the use of comparable undergraduate earnings relies on the assumption that those who seek a post-baccalaureate credential have a bachelor's degree in a similar field. This may not be the case, however, particularly for degrees that are less reliant on the attainment of a specific set of undergraduate prerequisites. We currently lack comprehensive information on the bachelor's degrees typically obtained by graduate students in each field. The Department believes that using the same standard for the EP for graduate programs provides some degree of protection from programs not meeting even this low bar.

Changes: None.

ACS Earnings Measures

Comments: At least one commenter suggested that because the ACS relies on self-reported earnings, rather than on administrative data, these earnings metrics are not comparable.

Discussion: The ACS is a commonly used source of data on the experiences of a representative sample of Americans and a provider of many key economic indicators used by governments and researchers throughout the country. The Census Bureau regularly reviews the accuracy of the data. The survey relies on decades of experience from nationally recognized experts to develop and constantly improve the quality of the information provided through these surveys. The U.S. Census Bureau has researched the accuracy of ACS income data and found that income data from the ACS corresponds well with administratively reported earnings measures ( e.g., via employer provided W2 forms) in IRS records. The ACS is the best available data to measure the State-level earnings by education level used in the construction of the earnings threshold and the commenter did not provide an alternative source for comparable data.

Changes: None.

Comments: One commenter noted that recent earnings gains have been largely among those in the labor force without a post-secondary credential. When more recent years are used as the basis for the EP threshold, this could raise the bar such that more programs fail.

Discussion: The Department believes that this comment highlights the value of using a dynamic measure from concurrent survey data, rather than a static benchmark. In cases where the economy improves for those without a post-secondary credential, the EP threshold could increase. If so, it appropriately sets a higher bar for college programs' performance.

Changes: None.

State and National Benchmarks

Comments: One commenter argued that standards for aid programs are set nationally—for example, a single maximum Pell grant amount, and standard national limits for undergraduate debt by level and dependency status. The commenter maintained that instituting different State-level thresholds for the EP by program location runs counter to this national framework.

Discussion: The earnings threshold is meant to proxy for the earnings levels that a typical student might obtain if they did not earn a postsecondary credential. As shown in the NPRM, these earnings vary across States for a variety of reasons related to local economic conditions, of the policies of States, Tribes, and Territories, and other factors. For example, States establish requirements for programs, licensing, or both. States, Tribes, and Territories also establish requirements for earning a high school diploma and its equivalency. Additionally, because State policy can have a substantial impact on both aid and on local labor market conditions, the Department believes that a State-level EP threshold is appropriate since the EP threshold is meant to measure the earnings that a student might have obtained had they not attended college.

Changes: None.

Comments: Some commenters thought that the proposed regulations needed to make more distinctions in outcomes based on the sizes of the institutions as well as the type of educational program and said the Department should consider the differences in the variety of jobs that students pursue from programs that are not specialized to lead into careers. Some concern was also expressed that there would be national earnings for programs compared to regional earnings information for high school graduates, as well as noting that many small programs would not be captured under the proposed regulations.

Discussion: The financial value transparency framework is intended to provide information to students and families about average educational debt and average program earnings using the CIP codes for those programs. This provides students and families with useful information not only about different programs offered at one institution, but also to compare comparable programs offered at different institutions. Institutions are in the best position to determine what additional information will provide context about the impact the size of an institution may have on the educational experience and the job opportunities that may be available to program graduates. We note that the average earnings provided for a program are based upon that program's graduates and therefore have some direct connection to the institution whose programs are at issue. This provides a reasonable comparison with the earnings for high school graduates in that region.

Changes: None.

Comments: One commenter suggested that, in place of the State-level median earnings on ACS, the Department should use BLS data on the lower end of earnings for a given career path. For example, the EP threshold could be the 10th percentile of earnings for those who are employed in a given occupation.

Discussion: BLS's Occupational Employment and Wage Statistics contain national-level data on annual wages at the 10th, 25th, 50th, 75th, and 90th percentile, by industry code (North American Industry Classification System) and by occupational code (Standard Occupational Classification System). Across roughly 450 broad occupational codes, about 11 percent of occupational codes had 10th percentile earnings of less than $25,000 (roughly the EP threshold). Using the BLS threshold would mean that most programs would likely be held to a higher threshold than they would under the ACS measure, and that the threshold would have no adjustment for geography. The Department intends the earnings threshold to represent a benchmark level of earnings that students would obtain had they not pursued a post-secondary credential. As the comparison to BLS benchmarks suggest, this is a more conservative minimum bar on which to hold programs accountable. In our view it is the more appropriate threshold to determine whether career training programs are preparing their students for gainful employment.

Changes: None.

Comments: Two commenters suggested that students who earned higher-level credentials (such as a bachelor's degree or a graduate degree) were more likely to seek employment out of State.

Discussion: The earnings threshold is meant as a proxy for what students would earn had they not attended college, not to put graduates' earnings in context based on where they work after college. Accordingly, the high school earnings levels in the states where students come from is more relevant. We have clarified in the final rule that if fewer than 50 percent of the students in the program come from the State where the institution is located, the program would be subject to a national EP benchmark, rather than a State-level benchmark.

Changes: We revised the definition of “earnings threshold” at § 668.2 to clarify that national earnings are used if fewer than 50 percent of the students in the program come from the State where the institution is located, rather than where the students are located while enrolled.

Growth Measure for Earnings Premium

Comments: Many commenters suggested using earnings growth or an economic mobility measure, rather than an EP threshold. Commenters suggested that pre-enrollment earnings could be compared to post-enrollment earnings. If the post-enrollment earnings were higher (some comments suggested by 20 percent), then the program would pass the earnings test.

A couple of commenters also suggested that the programs could choose between being measured on the EP threshold or on the growth measure. Other commenters noted that students in cosmetology programs are often coming from very low wage jobs before entering school, so such a pre-post comparison would reflect favorably on these programs.

Discussion: The Department agrees that pre- and post-earnings comparisons are a theoretically attractive way to assess how well programs boost students' earnings potential. In practice, however, such a metric is infeasible to operationalize for the majority of programs.

For many programs, a large number of students have low pre-period earnings because, for example, they either do not work or work a limited number of hours, often because many are still enrolled in high school, prior to enrollment. All else equal, programs that enroll larger numbers of students without substantial prior attachment to the labor force ( e.g., younger students) will have calculated earnings gains that are larger than programs with a smaller share of students without significant prior work histories. Using administrative Department data on undergraduate certificate programs eligible for title IV, HEA programs, we show in Figure 1.3 that (a) the estimated earnings gains using simple pre- post-earnings comparisons are unrealistically large; and (b) the proportion of younger students enrolled in the program predicts earnings gains. The estimated earnings gains using data where many students do not have pre-enrollment data tend to be illogically large, with the typical program having earnings gains estimates over 10 times what is commonly found in the research literature. While some of this relationship could be because of differences across programs, the figure demonstrates that because younger students having no or less robust earnings records, they will mechanically have lower pre-period earnings and higher calculated earnings gains. The earnings gain metrics, therefore, yield heavily biased estimates that are meaningless in assessing program quality, and the bias greatly disadvantages programs serving older students.

For a summary of results from selected studies related to returns to certificates, see Table 1 from Darolia, Guo, & Kim (2023). The Labor Market Returns to Very Short Postsecondary Certificates. IZA Discussion Paper 16081 ( https://docs.iza.org/dp16081.pdf ).

One way to address this would be to measure earnings gains only for workers who appear to have high labor force attachment in the pre-period, as evident by exceeding some minimum earnings threshold. In practice, however, this would result in dramatically smaller numbers of completers that could be used to measure earnings gains, and dramatic reductions in the share of programs and enrollment covered by an earnings gain metric. Based on analysis of administrative data, we approximate that at least half of programs that had sufficient student volume to calculate median student earnings would no longer have sufficient data if students without labor force attachment were excluded. These limitations make an earnings-gain measure infeasible, at least give current enrollment patterns.

Changes: None.

Age Range for Measuring Earnings

Comments: Several commenters raised reservations about the timing of earnings measurement for the high school graduates to which each program's completers would be compared. These commenters worried that the 25 to 34-year-old demographic used to calculate median earnings for high school graduates was inappropriately old for comparison to recent program completers and would put their programs at a disadvantage because their program completers were younger and earning less.

Discussion: The preamble in the NPRM discussed the motivation for choosing the 25 to 34-year-old age range. Across all credential levels, the average age three years after graduation is 30 years old, and the range from 25th to 75th percentile of program age (the interquartile range) is 27 to 34 years old. In other words, the typical graduate from most credential programs is within the comparison EP age range three years after graduation. Because of this, the Department declines to consider additional adjustments to the age cohort selected for the EP.

Changes: None.

Comments: A few commenters suggested using years of work experience, rather than age, as the measure for selecting a comparable sample of high school graduates for the EP.

Discussion: This approach is generally infeasible since detailed information on workers' years of experience is not available in the ACS, which is the source for the EP threshold. Moreover, it is unclear whether and how a comparable years of experience variable could be generated for graduates from a given program, especially for those who started a program of study mid-career.

Changes: None.

Comments: One commenter noted that some of their students enroll through an early college option. As a result, these students tend to be even younger than a typical cohort with a given credential.

Discussion: Students enrolled through a dual enrollment or early college program are typically not eligible for title IV, HEA assistance, and would not be included in an earnings or debt measure unless they obtained Federal financial aid after their high school graduation, or as part of a pilot program ( i.e., the Department's Experimental Sites program). The Department reiterates that most programs have a typical graduate whose age is within the age range used in the EP threshold.

Changes: None.

Demographics and the Earnings Threshold

Comments: Many commenters noted that program completers who are disabled, are incarcerated, or choose not to seek employment are included in the program's earnings data but would not be considered part of the labor force in the ACS, and therefore are not part of the EP threshold calculation.

Discussion: Individuals who are not seeking employment, or who are unable to find employment over a full year due to disability or incarceration or for other reasons, are not included in the calculation of the earnings threshold using ACS data. To the extent possible with administrative data, the Department also excludes those who are unable to work due to disability, as borrowers who have been identified as having a total and permanent disability are not included in the D/E or EP measure earnings. Further, individuals who are incarcerated and are enrolled in an approved prison education program are also excluded. The Department believes that those who enroll in a GE program are doing so with the intent of seeking employment after completing the program. This assumption is borne out by the fact that a much higher share of program graduates have positive earnings reported to the IRS than is true among individuals in a similar age range and with a college education in the ACS data.

Changes: None.

Comments: A few commenters contended that the median wage for high school graduates should sample everyone who meets the age and credential criteria, including those who no longer participate in the workforce.

Discussion: The median high school earnings threshold includes those in the labor force (who have a job or report being available and looking for a job). As noted in the NPRM, the Department believes that most graduates of postsecondary programs, particularly those graduating from career training programs, are likely to seek work or be employed three years after graduation. A comparison to those who cannot work, or who have chosen not to work, is not appropriate in this case.

Changes: None.

Reporting—§ 668.408

General Support

Comments: A few commenters praised the Department for requiring reporting for both GE and non-GE programs, noting that doing so will make more information about educational programs available to the public regardless of institution type. Another commenter expressed support for extending financial value transparency reporting requirements to graduate-level programs, which account for a substantial portion of student borrowing.

Discussion: We appreciate the commenters' support.

Changes: None.

Benefits and Burdens

Comments: One commenter stated that they expect the long-lasting and regularly accruing benefits of the new rule, including better earnings and employment opportunities, lower student loan burden, and reduced taxpayer costs, will dwarf the reporting costs to institutions. The commenter also maintained that most of the compliance costs will be one-time investments to adapt to new reporting requirements, while the benefits will be persistent.

Discussion: We agree that the costs associated with the institutional reporting requirements in § 668.408 will be outweighed by the benefits of the financial value transparency framework, as well as the benefits of the GE program accountability framework.

Changes: None.

Comments: Many commenters opined that the proposed reporting requirements would be costly, time consuming, and burdensome for institutions, especially HBCUs, community colleges, rural institutions, and small institutions which operate with budgetary and staffing limitations. One commenter urged the Department to limit new reporting requirements to the greatest extent possible. Another commenter highlighted the need to balance the interests of accountability and practicality to achieve desired outcomes while minimizing reporting burden. Some commenters note that, because the proposed transparency framework applies to all programs, and not just GE programs, it represents a large increase in reporting burden for institutions.

Discussion: We understand the commenters' concerns about limiting reporting requirements and recognize the need to appropriately balance the interests of accountability and practicality. The Department requires the reporting under the regulations to calculate the D/E rates and EP measure, as provided in §§ 668.403 and 668.404, and to calculate or determine many of the disclosure items, as provided in § 668.43(d).

We have carefully reviewed all of the required reporting elements and have determined that the benefits of the transparency and accountability frameworks made possible through the reported data sufficiently justify the associated reporting costs and burden for institutions. We further note that institutions will benefit from the reporting because the information will allow them to make targeted changes to improve their program offerings, benchmark their tuition pricing against similar programs at other institutions, and better promote their positive outcomes to potential students.

In terms of staffing limitations, we have not estimated whether or how many new personnel may be needed to comply with the reporting requirements. Allocating resources to meet the reporting requirements is an individual institution's administrative decision. Some institutions may need to hire new staff, others will redirect existing staff, and still others will not need to make staffing changes because they have highly automated reporting systems. We expect these costs to be modest since, as noted in the RIA, most institutions have experience with the data reporting for the rule for at least some of their programs under the 2014 Prior Rule or in responding to recent NCES surveys.

Changes: None.

Comments: One commenter opined that it is unclear what mechanism and process institutions would use to provide the large amount of data necessary to calculate D/E and EP metrics for nearly all eligible programs to the Department. Some commenters said that this additional burden and cost of complying would be complex and require meticulous coordination, particularly to create the reporting process for the first year the regulations would go into effect. Several commenters cautioned that the regulations the Department proposed to improve institution accountability will have the unintended consequences of imposing significant reporting burdens on many institutions that provide strong outcomes for students who readily find good jobs in high demand fields.

Discussion: While we acknowledge that the overall number of programs will increase from those reported under the 2014 Prior Rule, we anticipate the process will largely remain similar. We also expect to add additional fields as appropriate to existing Departmental systems including the Common Origination and Disbursement (COD) system and the National Student Loan Data System (NSLDS).

The Department will provide institutions with guidance and training on the new reporting requirements, provide a format for reporting, and enable our systems to accept reporting from institutions beginning several months prior to the July 31, 2024, deadline so that institutions have sufficient time to submit their data for the first reporting period. The Department will also continue to look at ways this information can be routinely updated in the systems to reduce separate reporting burdens on institutions and will consider additional ways to simplify our reporting systems, as appropriate.

We are also exempting from these regulations, including the reporting requirements, institutions offering any group of substantially similar programs, defined as all programs in the same four-digit CIP code at an institution with less than 30 completers in total during the four most recently completed award years. While these metrics are calculated at the six-digit CIP code level, for the purposes of qualifying for this exemption, we measure completers among all such programs at the four-digit CIP code level to avoid incentives for institutions to create new, smaller programs that are substantially similar in order to avoid being covered by these rules. Although this change will result in the loss of some beneficial information from these institutions independent of the D/E rates and earnings premium metrics, such as net pricing at specific credential levels, we believe this loss is acceptable when balanced against the alleviated reporting burden for many institutions. Approximately 700 institutions will benefit from this exemption, including about 85 percent of participating foreign institutions and a diverse group of other institutions. This reduction of burden is achieved without diminishing the impact of the D/E rates or EP measure, as institutions exempted from the reporting requirement would not have sufficient numbers of completers to calculate those measures for any program. Moreover, the overall impact to students is minimal because institutions affected by this exemption constitute less than one percent of total title IV, HEA student enrollment and less than one percent of total title IV, HEA disbursement volume.

Changes: We have modified the exemptions under §§ 668.401(b) and 668.601(b) to exempt institutions that do not have any group of programs that share the same four-digit CIP code with 30 or more completers in total over the most recent four award years from these regulations, as described above.

Comments: A few commenters claimed that new reporting requirements would overly tax institutional financial aid and information technology staff who are already tasked with implementing and adapting to significant changes to Federal Student Aid processes and systems for the upcoming 2024–25 award year. One commenter noted that the 2014 Prior Rule presented technical difficulties in report coding for students enrolled concurrently in multiple GE programs and anticipated these challenges to be more significant with the potential for students to now simultaneously enroll in GE and non-GE programs. One commenter indicated that the proposed rule did not clearly explain how to handle reporting requirements for a student enrolled simultaneously in a GE program and an eligible non-GE degree program, recommending that the eligible non-GE degree program should take precedence for reporting because funds received by the student would be primarily used for that program.

A few commenters recommended that the data reported under § 668.408 be open, interoperable, and available for integration into State longitudinal data systems. One commenter noted that additional investments in State data systems will be necessary to ensure accurate reporting on the proposed metrics and requested that the Department encourage States to invest more resources into linked and integrated longitudinal data systems to reduce reporting burdens on institutions.

Discussion: We acknowledge that the reporting requirements in § 668.408 may, in some cases, increase the demands on an institution's information technology staff and resources. We also recognize that institutions must adjust for technical and system changes under the Free Application for Federal Student Aid (FAFSA) Simplification Act and Fostering Undergraduate Talent by Unlocking Resources for Education (FUTURE) Act, effective for the 2024–2025 award year. The Department has provided, and will continue to provide, training and technical resources in advance of the implementation of the FAFSA Simplification Act and Future Act provisions.

We will also provide training and technical resources prior to the implementation of the Financial Value Transparency and Gainful Employment frameworks set forth in this final rule, which will address the handling of situations involving students simultaneously enrolled in multiple GE programs. We appreciate the request for a clearer explanation of how institutions should handle reporting requirements for a student enrolled simultaneously in a GE program and an eligible non-GE degree program. We will provide further clarification in sub-regulatory guidance and training in advance of the effective date of the reporting requirements under this final rule, and we will consider the request that eligible non-GE degree programs take precedence.

The Department agrees that data published under these provisions should be as transparent and interoperable as possible, while recognizing the necessary constraints to protect student privacy. We will continue to evaluate ways to make the published data as valuable as possible to researchers and State policymakers. We also agree that wise investments in State data systems may increase the value of data reporting requirements, and we encourage States to support linked and integrated longitudinal data systems as appropriate.

Changes: None.

Comments: One commenter noted that the proposed reporting requirements appear unnecessarily burdensome for institutions that do not participate in the Direct Loan program and whose graduates are therefore unburdened with student debt.

Discussion: The Department disagrees with the assertion that the reporting requirements are unnecessarily burdensome for institutions that do not participate in the Direct Loan program. A program should not be exempt from the reporting requirements because it has a low borrowing rate or a low institutional cohort default rate. The information that institutions must report is necessary to calculate not only the D/E rates, but also to calculate the EP measure and to determine many of the disclosure items as provided in § 668.43(d). Exempting some institutions from the reporting requirements, whether partially or fully, would undermine the effectiveness of both the accountability and transparency frameworks of the regulations because the Department would be unable to assess the outcomes of those programs. In addition, students would not be able to access relevant information about these programs and compare outcomes across institutions. We also note that D/E rates calculations would likely be favorable for institutions with low rates of borrowing.

Changes: None.

Comments: One commenter noted that reporting requirements constitute administrative work that does not serve students in a direct manner. Several commenters noted that the costs of the new reporting requirements will inevitably transfer to the student.

Discussion: We do not agree that the efforts institutions will need to invest in to comply with reporting requirements do not directly serve students. The financial value transparency metrics calculated using the reported data will provide valuable information directly to current and prospective students, who can use that information to better inform critical enrollment and borrowing decisions. Moreover, the GE accountability framework will directly protect students, prospective students, families, and the public by ending title IV, HEA participation for the poorest performing programs.

While we acknowledge that institutions may pass administrative costs on to students through increased tuition and fees, we note that the transparency framework will increase the availability of cost information available to students and prospective students in comparing programs and institutions, and we expect that market forces will mitigate this practice to some extent through increased pricing competitiveness among institutions.

Changes: None.

Specificity

Comments: One commenter argued that proposed § 668.408(a)(4), which would allow the Department to specify additional reporting requirements in a future Federal Register notice, is vague and overly broad to such an extent as to provide us with unlimited discretion in imposing additional reporting requirements. This commenter contended that proposed § 668.408(a)(4) did not provide sufficient notice concerning the types of information that institutions may be required to report or disclose. The commenter requested that the Department either provide further information about the types of reporting that may be required under § 668.408(a)(4) or remove this provision. Another commenter expressed concern that the public would lack a mechanism to engage the Department prior to the addition of any further reporting requirements through a future Federal Register notice.

Discussion: We believe that the Department needs the discretion to reasonably modify future reporting requirements to adapt to unforeseen changes in the postsecondary ecosystem, including to eliminate unnecessary or duplicative reporting requirements. Examples of such potential developments that might be relevant to students could include more reliable and consistent job placement rates, new types of financial assistance available to students in addition to the title IV, HEA programs, or other such information. Retaining the flexibility to efficiently modify future reporting requirements is necessary to support our goal to provide the students, families, and the public with relevant information to make better informed postsecondary choices.

We note that any future modifications to reporting requirements in the Federal Register would be published well in advance of the effective date of such modified requirements and would provide a contact for questions about the new requirements.

Changes: None.

Timeframe

Comments: One commenter expressed support for the proposed reporting timeline and urged the Department to aggressively prioritize the development of data systems and other related tools. This commenter further noted that such reporting requirements are not new because institutions with GE programs have previously implemented many aspects of the proposed reporting requirements, and we already require all institutions to report many of the proposed data points.

Discussion: We appreciate the commenter's support, and we affirm our intent to prioritize the development of the systems and tools necessary to facilitate the reporting requirements. We agree that the reporting requirements set forth in this final rule are not without precedent, and many of them should already be familiar to institutions.

Changes: None.

Comments: Many commenters noted that the proposed reporting provisions would require institutions to report multiple years of initial data with only a 30-day window from the effective date of this final rule and urged the Department to allow institutions adequate time to prepare and report any required information, particularly in light of other high-priority work competing for institutions' limited resources. One example provided was implementing sweeping FAFSA simplification changes for the 2024–2025 award year.

A few commenters remarked that efforts necessary to comply with the initial reporting deadline for the 2014 Prior Rule were harmful to other institutional operations that had to be postponed. These commenters suggested revising the initial reporting deadline from July 31, 2024, to October 1, 2024, which would be consistent with the reporting deadline for all subsequent years. Several commenters more broadly suggested that the initial reporting deadline should be a minimum of 90 to 120 days after the later of the effective date of the final rule or the date that the Department makes available the full reporting format and process. These commenters recommended further extensions if we modify or supplement reporting guidance after releasing it.

Discussion: We believe that the July 31, 2024, deadline for initial reporting is reasonable and appropriate. While this reporting period ends one month from the effective date of the final rule, institutions will have over nine months from the publication of the final rule to plan and prepare for the required reporting. With regard to alleged harm to other institutional operations caused by efforts to meet the initial reporting deadline, we note that under the existing administrative capability provisions at § 668.16(b)(2), institutions are required to maintain an adequate number of qualified staff to administer the title IV, HEA programs, and part of an institution's responsibility is to comply with reporting requirements. The Department will provide training in advance to institutions on the new reporting requirements, provide a format for reporting, and enable the Department's relevant systems to accept optional early reporting from institutions beginning several months prior to the July 31, 2024, deadline. We are not persuaded by commenters' arguments that the implementation of changes for the 2024–25 award year under the FAFSA Simplification Act and FUTURE Act would necessitate extending the initial reporting timeline because most institutions will have already made the necessary operational and procedural adjustments much sooner than July 2024. We note that the new FAFSA system and associated processes will become operational and available to institutions in December 2023.

We respectfully decline the commenters' suggestions to extend the initial reporting period through October 1, 2024, or for an initial reporting deadline 90 to 120 days after the effective date of this final rule. As discussed above, we maintain that institutions have sufficient advance notice between the publication of this final rule and the initial reporting deadline of July 31, 2024, to comply, especially given the anticipated option for advanced reporting. If the Department significantly modifies or supplements the reporting requirements after the effective date of this rule, we will consider further extending the deadline.

Changes: None.

Reporting Period

Comments: Many commenters noted that the requirement to report certain information for students who enrolled in the previous seven award years (and, in some cases, up to nine) would consume significant institutional time and resources. These commenters explained that this would especially burden under-resourced institutions. One such commenter postulated that requiring institutions to report data from prior award years could lead to a widespread exodus of institutional financial aid staff. Some commenters noted that reporting for more than three to five past award years would exceed existing record retention requirements and, as a result, this historical data requested by the Department would be incomplete. Several commenters urged the Department not to impose sanctions for metrics calculated using data from past years that exceed applicable record retention requirements.

Discussion: We believe that the initial reporting requirements are reasonable for most institutions and programs, including under-resourced institutions. Nearly all proprietary institutions are already familiar with the previous reporting requirements under the 2014 Prior Rule, and significant portions of public and private nonprofit institutions were also required to report for one or more GE certificate programs under those previous requirements. We remain skeptical that the initial reporting requirements would lead to significant departures of institutional financial aid professionals, in part because at most institutions, reporting responsibilities falls primarily on specific financial aid staff, and in many cases reporting is handled through automated processing systems or dedicated reporting staff outside the financial aid office. Furthermore, most of the records institutions must report fall within the record retention timeframe required under § 668.24(e), even if the data are maintained in multiple systems or formats. In addition, institutions may have a policy of retaining student records for longer periods; or a State or accrediting agencies or both may require them to do so.

Nonetheless, we are sensitive to institutions' concerns about the initial reporting burden. To address these concerns, we have extended the transitional reporting period option initially proposed for non-GE programs to GE programs as well, as further discussed under “Transitional Period” below.

Changes: We have revised the transitional reporting option at § 668.408(c)(1) to now apply both to GE and non-GE programs.

Comments: A few commenters noted that the Department would better promote a cooperative and supportive relationship with institutions by including an opportunity for institutions to explain any failure to comply with reporting requirements. Another commenter suggested the Department further explain the provision at proposed § 668.408(b)(2) that would allow an institution to provide an explanation acceptable to the Secretary of why the institution failed to comply with any of the reporting requirements. A few commenters argued that the Department should hold an institution harmless for failing to report data it is no longer required to retain. These commenters suggested that, if a material number of institutions fall into this category, the Department should not calculate D/E or EP metrics for the impacted years.

Discussion: We concur with commenters that a process is necessary for institutions to explain to the Department any failure to comply with reporting requirements. This process would be appropriate, for example, in instances in which a disaster, emergency, or attack results in the loss or destruction of data the institution must otherwise report. We expect to provide additional information regarding the manner and circumstances in which institutions could employ this provision in future sub-regulatory guidance and training. In such instances where institutions are unable to comply with these reporting requirements because the institution was not required to retain the records, § 668.408(b)(2) will allow an institution to explain its inability to comply with part of the reporting requirements. The Department will review an institution's explanation and may provide relief from the consequences of the rule if sufficiently supported by the circumstances and evidence provided. We believe this approach provides the needed flexibility to accommodate limited circumstances in which institutions may be unable to report, including exceptional circumstances that are difficult or impossible to foresee at this time, without unduly delaying or compromising the transparency and accountability benefits of the rule.

Changes: None.

Comments: One commenter noted that the Department and other regulators encourage institutions to limit the volume of data they store, further noting that our data destruction guidance encourages institutions to minimize the amount of data they retain by destroying them when no longer needed, identifying this as a best practice for protecting individuals' privacy and for limiting the potential impact of a data breach.

Discussion: We do not believe the proposed reporting requirements inherently conflict with the record retention requirements at § 668.24(e), nor with the Department's guidance pertaining to the destruction of records. The record retention provisions at § 668.24(e) were never intended to shield institutions from complying with the Department's legitimate program oversight activities. For example, § 668.24(e)(3) requires institutions to retain applicable program records relating to costs questioned in an audit or program review, indefinitely and beyond the prescribed three-year retention period, until resolution of such audit or program review. In addition, many institutions retain student records for longer periods than required by § 668.24(e), either as a matter of institutional policy or as a result of State or accrediting agency requirements. As noted in the Department's data destruction guidance cited by the commenter, some data may need to be preserved indefinitely, while other student information will need to be preserved for a prescribed period of time to comply with legal or policy requirements. The reporting requirements established under this rule constitute such a requirement that necessitates the retention of relevant records, potentially beyond the three-year periods referenced in § 668.24(e).

studentprivacy.ed.gov/sites/default/files/resource_document/file/Best%20Practices%20for%20Data%20Destruction%20%282019-3-26%29.pdf.

Changes: None.

Comments: One commenter expressed concern that the proposed reporting period may inadvertently identify medical programs as low financial value, lessening their ability to recruit students and exacerbating the Nation's physician workforce shortage, because a program's current metrics would be calculated based on the outcomes of students from nearly a decade ago, long before the institution would know what metrics the Department would eventually consider to constitute good financial value in 2024.

Discussion: Our Regulatory Impact Analysis in the NPRM showed that certain undergraduate health professions programs, particularly certificate programs in medical assisting and medical administration, would fail the GE accountability measures at higher-than-average rates. We do not, however, expect that programs leading to a terminal medical degree will fail the D/E rates or EP measure in significant numbers. We further note that the cohort period defined at § 668.2 for doctoral medical and dental programs that require students to complete a residency provides additional time, relative to other programs, before graduate earnings will be measured. This provides additional reassurance that reported earnings will accurately and positively reflect physicians' and dentists' ability to exceed the high school earnings threshold and capacity to repay their educational debts. In summary, we do not expect that the regulations will deter aspiring physicians and dentists from pursuing their chosen field, and we do not believe that they will substantially negatively impact the Nation's physician workforce.

See, for example, 88 FR 32427.

Changes: None.

Comments: One commenter posited that a more practical and less burdensome reporting process might focus on forward-looking reporting rather than data from past award years, arguing that such an approach would better accommodate institutions' need for time to adapt to new reporting requirements, and that current and future data would be more relevant for evaluating program effectiveness.

Discussion: Although we appreciate the commenter's suggestion, as discussed in the “Background” section of the NPRM, we perceive that the need for these financial value transparency measures and the GE accountability framework is too urgent to justify further delay in calculating and publishing the D/E rates and EP measures. The Department believes that the regulations provide institutions sufficient time and flexibility to adapt to any new reporting requirements, and that historical data can provide helpful insight into an established program's performance over time. Students, families, and the public deserve to benefit from improved transparency and accountability as swiftly as possible.

88 FR 32300, 32306 (May 19, 2023).

Changes: None.

Comments: Several commenters noted that some of the required data would be associated with years in which institutions and students were impacted by the COVID–19 national emergency and that this pre-pandemic environment may no longer exist for many students.

One commenter suggested that the Department postpone any sanctions where data prior to 2022 is used in determination of eligibility, due to the broad impact of the COVID–19 pandemic on workers, graduates, and the postsecondary education industry. A commenter suggested extending the initial reporting requirements by one to two years to better account for the economic effects of the pandemic.

Discussion: The Department recognizes that data from some years included in the initial reporting period were impacted by the COVID–19 pandemic and national emergency. However, postponing calculating the outcome measures until such time as no earnings data through 2022 is included in D/E rate or EP calculations would delay the benefits of the rule until at least the 2026–2027 award year. Extending the initial reporting timeframe by one to two years would produce a similar result. As discussed above, we believe the need for the transparency and accountability measures is too urgent to postpone any of their primary components to such an extent, and to do so would abdicate our responsibility to provide effective program oversight.

Additionally, we are unconvinced by arguments that data from prior to 2020 represent a pre-pandemic reality that no longer exists. Recent data show that overall labor force participation is back to its pre-pandemic forecasted level, and the prime-age (25–54) labor force participation rate is now slightly above pre-pandemic levels. We consider and further discuss comments pertaining to the COVID–19 pandemic below under “Other Accommodations and Special Circumstances.”

Changes: None.

Transitional Period

Comments: A few commenters expressed appreciation for the transitional reporting offered at proposed § 668.408(c)(1) for eligible non-GE programs.

Discussion: We appreciate the commenters' support.

Changes: None.

Comments: Several commenters requested that we offer GE programs the same reporting options as non-GE programs in the interests of fairness, reduced burden, and consistent comparison among all types of programs. One commenter opined that the proposed transitional reporting period option would unfairly hold GE program to a more difficult standard. This commenter argued that the reporting burden offered by the Department as reasoning for the transitional reporting period for non-GE programs holds equally true for GE programs.

A few commenters requested further explanation of the Department's reasoning for the difference in initial reporting requirements.

A few commenters recommended extending the transitional reporting period option to GE programs that do not offer loans. These commenters noted that many GE programs—particularly at community colleges—do not offer loans, yet we would require them to report seven years of institutional data to facilitate D/E rates that we would ultimately not calculate for those programs.

Discussion: Our reasoning for offering the transitional reporting and rates option only to non-GE programs was to lighten the initial reporting burden for institutions offering only non-GE programs which they were not required to report under the 2014 Prior Rule. Given that the financial value transparency metrics do not impact program eligibility for non-GE programs, we believed that alleviating some of the initial reporting burden would justify a temporary sacrifice in the quality and comparability of the D/E data reported during the transition period.

With regard to concerns about reporting requirements for institutions and programs that do not offer loans, we note that the Department would nonetheless calculate the EP measure for such institutions and programs.

While we maintain that the initial reporting requirements are reasonable, in the interests of more equitable treatment of programs and institutions, and to facilitate smoother and less burdensome implementation for institutions, we extend the transitional reporting option to all programs in this final rule. We believe that this change will alleviate many commenters' concerns about fairness, cost, and burden, and that these considerations justify the brief period for which the D/E rate data will be impacted.

Changes: We have revised the transitional reporting option at § 668.408(c)(1) to now apply both to GE and non-GE programs.

Comments: One commenter suggested that the Department use only the transitional reporting and calculation methodology, abandoning any requirements to report for periods older than the preceding two award years.

Discussion: The Department considered permanently adopting the transition period's structure of calculating D/E rates for all programs. While this approach would result in a mismatch between borrowing and earnings cohorts, it would use the most recently available debt and earnings data to determine program D/E outcomes. Such an approach would also increase institutions' ability to affect their students' borrowing levels in response to adverse D/E outcomes before losing eligibility. While this approach could make the D/E rates more forward-looking, we decided against it as a permanent measure because the earnings and debt measures would reflect the outcomes of different students. We believe the D/E rates will be more meaningful and informative to most students if completers' earnings outcomes are matched with the debt incurred by the same group of borrowers.

Changes: None.

Comments: One commenter posited that because the 2014 Prior Rule used a different methodology to calculate D/E rates, such as not considering scholarships and grants in capping loan debt, it would be inappropriate to use those earlier data to calculate D/E rates under this final rule.

Discussion: In writing the NPRM, we did not envision using previously reported data to calculate D/E rates. Instead, we will require reporting of new information for past completer cohorts to construct the rates as set forth in the final rule. Since we have extended the transitional reporting option to both GE and non-GE programs, institutions will have the choice to report these additional data elements, such as private loans, institutional scholarships, and grants, starting with the most recent completer cohorts, or for the historical cohorts matching those for whom we measure median earnings.

Changes: None.

Redundancy

Comments: Several commenters urged the Department to avoid imposing duplicative reporting requirements, asserting that institutions already report some data elements at proposed § 668.408 (such as CIP code, credential level, program name, program length, enrollment status, attendance and graduation dates, disbursement amounts, and income once IRS Direct Data Exchange is in place) to other Department-maintained websites such as NSLDS, COD, and Integrated Postsecondary Education Data System (IPEDS). These commenters further suggested that the Department should share data it controls between systems and processes to relieve administrative burden for institutions. A few commenters further noted that duplicative reporting requirements increase institutional burden yet provide little added value to students because much of the information is already available.

Several commenters noted that institutions are already required to publish graduation and placement rates through accrediting agency requirements. A few commenters opined that it is difficult for career training programs to comply with overlapping transparency requirements. These commenters suggested that the Department thoroughly review the annual requirements for reporting, accountability, and transparency.

Discussion: Although there is some overlap with the Department's current enrollment reporting and disbursement reporting requirements, those data do not include several key elements required for the calculation of D/E rates, such as debt students owe directly to the institution, other private education loan debt, tuition and fees, and allowance for books and supplies. As discussed under “Burden” above, we believe that the transparency and accountability benefits outweigh any burden of reporting. We further note that various factors, such as the sophistication of an institution's systems, the size of the institution and the number of programs that it has, whether or not the institution's operations are centralized, and whether the institution can update existing systems to meet the reporting requirements will affect the level of burden for any particular institution.

With regard to accrediting agency requirements concerning the publishing of graduation and placement rates, we remind commenters that we do not include placement rates among the reporting requirements in this rule. Accrediting agency requirements and methodologies vary, and inconsistencies in how institutions currently calculate job placement rates limit their usefulness in comparing institutions and programs.

As previously noted, the Department has carefully considered the reporting requirements that support the transparency and accountability frameworks of this rule. We believe them to provide the most appropriate and helpful information for students, families, and the public at this time balanced with the needs of institutions. The Department will nonetheless review the data institutions currently report and will work to mitigate duplicative reporting to the greatest extent possible.

Changes: None.

Data Elements

Comments: One commenter suggested that, in addition to the data elements identified in the NPRM, the Department require institutions to report the distance education status of their students ( i.e., entirely online, entirely on-campus, or hybrid). This commenter reasoned that doing so would enable useful insights about the outcomes of online and hybrid programs and would allow a more targeted comparison of earnings between completers and high school graduates for the EP measure.

Discussion: We appreciate this suggestion, and we concur that more granular data on students' distance education status could yield useful and better targeted program information. We do not currently gather this information on the individual student level. We considered strategies for obtaining such information, such as creating and assigning virtual OPEID numbers to represent an institution's online-only programs. Upon further consideration, we believe that such changes could have wider ranging impacts and would be best addressed by including them in a broader discussion of distance education issues in our upcoming negotiated rulemaking.

See 88 FR 17777 (Mar. 24, 2023).

Changes: None.

Comments: One commenter suggested removing reporting requirements for non-Federal sources of aid, particularly private loans and institutional grants, noting that institutions are only aware of private loans if lenders or students disclose them. The commenter further noted that gathering and reporting private loan information is burdensome for institutions.

One commenter proposed removing the requirement to report institutional debt. This commenter argued that the institutions collect these debts directly from the student, they are not tied to Federal investment, and they typically result from student withdrawals. As an alternative, this commenter suggested using return of title IV, HEA funds (R2T4) record submission to estimate the average institutional debt.

Another commenter noted that reporting debt due at time of exit from the program presents unique programming challenges that would require manually fixing a significant portion of records, suggesting that institutions be exempted from reporting this data element if the median value is less than $200.

Discussion: The reporting of non-Federal sources of aid—including institutional grants and scholarships; State, Tribal, or private funding; and the private education loans of which the institution is aware (including those made by an institution) is necessary to accurately determine educational debt for purposes of calculating and providing D/E rates. Omitting private education loan debt, including institutional loan debt, would harmfully diminish the usefulness of the information by providing an inaccurate estimate of the true costs typically incurred by students to enroll in a program. Regardless of any associated burden, reporting non-Federal grants and scholarships ultimately benefits institutions because, as provided under § 668.403, in determining a program's median loan amount each student's loan debt would be capped at the lesser of the loan debt or the program costs, less any institutional grants and scholarships. Some institutions with higher overall tuition costs offer significant institutional financial assistance or discounts that reduce the net cost for students to enroll in their programs. Requiring institutions to report institutional grants and scholarships allows the Department to take such financial assistance into consideration when measuring debt outcomes, will encourage institutions to provide financial assistance to students, and will ultimately result in a fairer metric and more consistent comparisons of the actual debt burdens associated with different programs.

While we appreciate the suggestion to use R2T4 reporting as a proxy to estimate institutional debt, doing so would overlook other sources of institutional debt such as gap loans, emergency loans, and payment plans. We believe it is necessary to capture all such sources of educational debt to calculate and provide D/E rates that are sufficiently accurate.

We also appreciate the commenter's suggestion that institutions be exempted from reporting institutional debt if the median value is less than $200. While we recognize the technical concerns, we believe that this burden is outweighed by the benefit of accurate debt information. While $200 may appear to be a reasonable de minimus amount of debt for institutions not to report, it is unclear what data would support this threshold or some other particular amount. Additionally, we do not believe a threshold to be appropriate, because to many current and prospective students even a modest amount could make the difference in covering critical indirect costs such as housing, food, or transportation, or going forward with those needs unfulfilled.

Changes: None.

Comments: Regarding the requirement to report licensure information (including whether the program meets licensure requirements for all States in the institution's area and the number of graduates attempting and completing licensure exams), one commenter noted that licensure requirements and oversight bodies vary by State and suggested that the Department investigate other, more accurate sources of licensing, certification, and workforce data, such as BLS Occupation and Wage Statistics or Employment Projections data.

One commenter opined that reporting State-specific licensure preparation requirements exceeds the limits of what institutions can reasonably accomplish.

One commenter noted that the Florida Education & Training Place Information Program does not disaggregate wage and employment data for private nonprofit institutions, further noting that student and employer surveys are unreliable and suffer from poor response rates.

One commenter posited that reporting program costs including books, supplies, and equipment would be burdensome for community colleges because those elements can frequently change. This commenter instead suggested that we require institutions to report a good-faith estimate.

Discussion: We are aware that licensure oversight bodies, processes, and requirements vary from State to State, and we acknowledge that institutions must commit sufficient time and resources to adequately navigate those requirements. Notwithstanding the complexities of the State licensing landscape, we remind commenters that accurate information about whether a program meets State licensure requirements is of paramount importance to students. Reporting whether a program meets relevant licensure requirements for the States in the institution's metropolitan statistical area or whether it prepares students to sit for a licensure examination in a particular occupation allows the Department to provide current and prospective students with invaluable information about the career outcomes for graduates of the program and supports informed enrollment decisions. In recent years, some institutions have misrepresented the career and employment outcomes of programs, including the eligibility of program graduates to sit for licensure examinations, resulting in borrower defense claims. Reporting information about a program's licensure outcomes—such as share of recent program graduates that sit for and pass licensure exams will help to reduce the number of future borrower defense claims that are approved.

With regard to the request to consider BLS data, we do not believe that BLS data reflect program-level student outcomes. The average or percentile earnings gathered and reported by BLS for an occupation include all earnings gathered by BLS in its survey, but do not show the specific earnings of the individuals who completed a particular program at an institution and, therefore, would not provide useful information about whether the program prepared students for gainful employment in that occupation.

With regard to concern about the disaggregated Florida earnings data, we note that institutions do not report wage and employment data under this rule. A Federal agency with earnings data provides aggregate earnings data directly to the Department.

We believe that institutions are capable of collecting and reporting State licensure information, and the importance of State licensure information to students justifies any burden to institutions in collecting and reporting such data. We do not believe that allowing institutions to report a good-faith estimate would result in accurate and comparable information, in part because whether an estimate was provided in good faith would be subjective and difficult if not impossible to define.

Changes: None.

Comments: One commenter suggested that the Department require institutions to report additional data elements, including (1) whether a program graduates commonly are subject to a postgraduate training period, similar to a medical or dental program internship or residency, that could impact their early career postgraduate earnings; (2) the amount of title IV, HEA funds obtained by the student for housing; and (3) whether graduates obtain employment that is unpaid or subsidized through a government program with housing, meal, or other non-income benefits.

Discussion: We appreciate the commenter's suggestions. With regard to postgraduate training requirements that could impact immediate postgraduate earnings, we include this information among requirements that institutions must report to the Department, and include it on the list of elements the Secretary may include on the program information website described in § 668.43. Our analysis, however, revealed that those particular disciplines demonstrate significantly more meaningful gains with an extended earnings measurement period than any other program categories. As further explained in our earlier discussion under “Measurement of Earnings,” we determined that reporting postgraduate internship or residency requirements is properly targeted to medical and dental programs, as initially proposed.

We believe it is more appropriate for institutions to report the annual allowance for housing, rather than the amount of title IV, HEA funds a student obtained specifically for housing. Not all institutions offer institutional housing, nor do all students partake of institutional housings at institutions that offer it. It would be both burdensome and unreliable to require institutions to divine which specific educationally related indirect costs each student covers using title IV, HEA credit balances.

While we recognize that some students obtain employment that is unpaid or subsidized through a government program with housing, meal, or other non-income benefits, we believe this would apply to only a small portion of postsecondary graduates. While unpaid or subsidized programs may provide meaningful personal fulfilment and valuable societal benefits, financial concerns weigh more heavily in most students' decision to go to college, with the top three reasons identified being “to improve my employment opportunities,” “to make more money,” and “to get a good job.” We believe it would be unnecessarily burdensome to require institutions to report this supplementary information, and that such burden would outweigh the benefits to students.

Rachel Fishman (2015). 2015 College Decisions Survey: Part I Deciding To Go To College. New America ( static.newamerica.org/attachments/3248-deciding-to-go-to-college/CollegeDecisions_PartI.148dcab30a0e414ea2a52f0d8fb04e7b.pdf).

Changes: None.

Alternative Approaches

Comments: One commenter urged the Department to consider alternative approaches to increase transparency without increasing costs to institutions.

Discussion: The Department is always interested in exploring new approaches to deliver improved outcomes while minimizing costs and burden. Nonetheless, among the options available at this time, we believe the approach set forth in this rule will provide the optimal achievable balance between costs and benefits. Further discussion is provided under “Discussion of Costs and Benefits” below.

Changes: None.

Other

Comments: One commenter opined that the Department did not discuss the collection of such a large amount of data and information during negotiated rulemaking sessions.

Discussion: The Department disagrees with the commenter's assertion that the reporting requirements were not discussed during negotiated rulemaking. Preliminary language in the GE issue papers for weeks two and three of negotiations provided potential reporting requirements for consideration and discussion by the committee. Because the committee did not reach consensus, the Department is neither limited nor bound to the specific regulatory language discussed in negotiated rulemaking. Moreover, the reporting requirements were published in the NPRM, and the Department provided the public—including the negotiators—a reasonable opportunity to provide feedback to the Department through the public comment period.

Changes: None.

Program Information Website—§ 668.43

General Support

Comments: Several commenters voiced general support for the proposed program information website and requirements, noting that programmatic information should be more publicly available to support students in making informed decisions.

The commenters further noted that this information may help to prevent harm to vulnerable populations. Additionally, these commenters suggested that this information can encourage schools to operate more efficiently and devote more resources to providing career services and job development resources to students. The commenters further highlighted that the program information website provides other State, local, and Federal stakeholders with information to monitor and guide the improvement of student outcomes.

One commenter noted that borrowers with defaulted loans interviewed in focus groups expressed a desire for more information about loans and college outcomes.

One commenter observed that financial value transparency information relating to cost of attendance, majors of interest, residence, and post-graduation earnings can impact a student's enrollment decisions.

Discussion: We thank the commenters for their support.

Changes: None.

General Opposition

Comments: One commenter opined that institutions, not the government, are best positioned to advise and inform students and families.

Discussion: We remind the commenter that nothing in this rule prohibits an institution from providing information to students and families. We of course welcome and encourage institutions to provide any reliable supplemental and contextual information to students that they may wish to provide in addition to the information we make available through the program information website. We believe, however, that both institutions and the government have important roles to play in this regard. We believe that relying solely on institutional efforts and resources would result in inconsistent information that would make comparing different institutions and programs more challenging and confusing for students, would increase the risk of misrepresentation and abuse leading to costly borrower defense claims, and would unfairly disadvantage smaller and under-resourced institutions without large marketing departments and budgets. The financial value transparency information we have chosen provides more consistent information to students and the public, more equitable treatment of institutions and programs, and better serves the needs of the public and the mission of the Department.

Changes: None.

Comments: Several commenters questioned how many students would carefully view the proposed program information website, opining that excessive consumer information risks obscuring the information and overwhelming students.

Another commenter cited the Department's Direct Loan entrance counseling as an example of consumer information transparency where the organization, length, and language impede students' interest and understanding of the information, leading students to only skim the material to meet the requirement to enable disbursement of pending loan funds.

Discussion: The purpose of Direct Loan entrance counseling and the financial value transparency information materially differ. Entrance counseling is intended to make borrowers aware of their rights, responsibilities, and resources available to them. The financial value transparency information provides information about the debt and earnings outcomes of a program intended to aid students in making informed enrollment decisions. We believe that all of the required information would be useful and relevant to prospective and enrolled students. We, however, concur with the commenters that it is critical to provide prospective and enrolled students with the information that they would find most helpful in evaluating a program when determining whether to enroll or to continue in the program. We note that § 668.43(d)(1) allows us to use consumer testing to identify additional information that will be most meaningful for students, and § 668.408(a)(4) permits us to modify future reporting requirements as necessary to support improved transparency.

Changes: None.

Comments: One commenter opined that the requirements in proposed § 668.43(d)(1)(ii), (v), (vi), (vii), (x), and (xi) to report a program's completion and withdrawal rates, D/E rates, EP measure, loan repayment rates, median loan debt, and median earnings would violate institutions' constitutional rights under the First Amendment. The commenter argued it is not clear that the information required to be reported would be purely factual and uncontroversial because institutions would not have an opportunity to review, challenge, or appeal the Department's data or calculations before the information is made public. This commenter further posited that the proposed requirements do not advance a significant government interest in preventing deceptive advertising and providing consumer information about program benefits and outcomes because the information is made public before institutions have an opportunity to review, challenge, or appeal the information. As a result, according to the commenter, the Department could inadvertently provide deceptive or confusing information. This commenter additionally noted that, in response to similar objections under the 2014 Prior Rule, the Department cited that the disclosures in that rule were purely factual and uncontroversial in part because institutions were given an opportunity to challenge the data and calculations, which is absent in the proposed regulations.

Discussion: The Department disagrees that the requirements related to the program information website violate institutions' First Amendment rights to the freedom of speech. As an initial matter, the rules do not require institutions to disclose the information in § 668.43(d)(1) to students because that information will be posted on the Department's website, not the website of an institution or program. In order to clarify the nature of the reporting requirements in § 668.43(d), we are replacing references to the Department's “disclosure” website with “program information” website and making related conforming changes to better clarify the distinction between this website hosted by the Department and the institutional disclosure requirements in § 668.43(a) through (c). Section 668.43(d)(1) does not require institutions to make disclosures to students, as the 2014 Prior Rule did, and we are changing the terminology to avoid any confusion about the nature of these requirements.

Section 668.43(d)(2) through (4) (regarding links to the Department's program information website) is addressed below in this section, as well as in a separate discussion that covers public comments on that section that are not directly related to the freedom of speech under the First Amendment.

Additionally, the rules aim to protect the use of taxpayer funds and facilitate program innovation, not only to enhance informed student choice and public information more generally. To the extent some commenters suggest the rules will require institutions or programs to include such information on their own websites, they are incorrect. To clarify, the Department will collect information and data from institutions and other sources, conduct certain calculations in accordance with the rules, and post results on the Department's website. The material posted on the Department's website will be the government's speech, and clearly so, not any institution or program's speech, and will impose no burden on the content choices of institutions. To the extent that commenters suggest that private parties have free speech rights to control the content of an agency website under these circumstances, or that institutions have a free speech right to regulate communications between the Department and students receiving Federal aid, the Department disagrees with the conclusion. That view of the First Amendment would implicate a broad range of government communications that rely in part on information collections from private parties.

See Walker v. Texas Div., Sons of Confederate Veterans, Inc., 576 U.S. 200, 207 (2015) (“When government speaks, it is not barred by the Free Speech Clause from determining the content of what it says.”).

Moreover, the information available on the Department's program information website will consist of accurate factual, uncontroversial information regarding an institution's programs. Courts have upheld the provision of factual information against First Amendment challenge even when, unlike the situation here, the government has required disclosures to be made by private parties. Indeed, a district court rejected First Amendment and other challenges to a disclosure provision in the 2014 Prior Rule, which required institutions to make disclosures directly to prospective and enrolled students. We point out that, in this final rule, § 668.43(d)(2) through (4) merely require schools to inform students of and direct them to the Department's program information website, which will contain purely factual, uncontroversial information. Such website links and access information are not the kind of “compelled speech” that has raised serious concerns in the past.

See, e.g., Recht v. Morrisey, 32 F.4th 398, 419 (4th Cir.) (involving required insertions into attorney advertisements regarding certain drugs and their approval by the Food and Drug Administration), cert. denied, 143 S. Ct. 527 (2022); Am. Hosp. Ass'n v. Azar, 983 F.3d 528, 540 (D.C. Cir. 2020) (involving required disclosures of hospital pricing information to reduce confusion); CTIA—The Wireless Ass'n v. City of Berkeley, 928 F.3d 832, 849 (9th Cir. 2019) (involving required retail information regarding cellular phone carriage and Federal Communications Commission standards); Spirit Airlines, Inc. v. U.S. Dep't of Transp., 687 F.3d 403, 414–15 (D.C. Cir. 2012) (involving the required prominent display of total prices on airline websites); Am. Meat Inst. v. U.S. Dep't of Agric., 76 F.3d 18, 26–27 (D.C. Cir. 2014) (involving required country-of-origin labeling); New York State Restaurant Ass'n v. New York City Bd. of Health, 556 F.3d 114, 131 (2d Cir. 2009) (regarding required disclosure of calorie information in connection with the sale of restaurant meals). This list is not intended to be an exhaustive collection of relevant sources, but instead an instructive list of court decisions that upheld regulations even when government subsidies were not at issue. For a readily distinguishable case that found a constitutional violation, see Nat'l Inst. of Family & Life Associates v. Becerra, 138 S. Ct. 2361, 2371 (2018) (regarding crisis pregnancy centers). Note further that, below, we address the freedom of speech and warnings about GE programs.

See Ass'n of Priv. Sector Colleges & Universities v. Duncan, 110 F. Supp. 3d 176, 198–200 (D.D.C. 2015) (alternative holdings) (involving required disclosures including total costs or estimated costs of completing a program), aff'd, 640 F. App'x 5, 6 (D.C. Cir. 2016) (noting that, on appeal, the Association no longer challenged the disclosure rules).

See Rumsfeld v. Forum for Acad. & Institutional Rts., Inc., 547 U.S. 47, 61–62 (2006) (distinguishing government-mandated pledges and mottos from a requirement that law schools include notices regarding recruitment on behalf of the U.S. Military when the schools offer such assistance to other recruiters).

As for the rules adopted here regarding the Department's program information website and the institutional reporting of information on which it will be based, we believe the rules will directly advance important government interests in informed student choice and protection of tax-financed resources, as well as innovation in educational programs, by making comparable information on program features and results readily available. Moreover, the rules are crafted to serve the Department's goals and do not impose burdens on the speech rights of institutions. The final rules will make available objective, factual, uncontroversial, and commonsense information about programs and their track records. Those outcomes include clearly defined measures of affordable debt and adequate earnings. As we discuss elsewhere in this document, institutions may correct errors in certain calculations.

See Zauderer v. Office of Disciplinary Couns. of Supreme Ct. of Ohio, 471 U.S. 626, 651 (1985) (testing advertiser disclosure requirements for a reasonable relationship to a governmental interest in preventing deception, and for whether the requirements are unduly burdensome to speech); Milavetz, Gallop & Milavetz, P.A. v. United States, 559 U.S. 229, 259–53 (2010) (following Zauderer); Am. Hosp. Ass'n, 983 F.3d at 540–42 (same).

Contrast the dictum in Ass'n of Priv. Colleges & Universities v. Duncan, 870 F. Supp. 2d 133, 154 n.7 (D.D.C. 2012), which expressed concern about a “statement that every student in a program `should expect to have difficulty repaying his or her student loans.' ” The requirements related to the program information website adopted here do not require any such message.

Furthermore, the rules will not interfere with institutions' ability to convey their own messages about program performance and much else. Students and others will be free to evaluate the content of the Department's website as they make educational decisions. And we emphasize that the rules apply only to institutions that participate in title IV, HEA programs. Only institutions seeking to gain or maintain title IV, HEA eligibility will have to report the information at issue.

Therefore, the program information website directly advances compelling government interests—preventing deceptive advertising about postsecondary programs, providing consumers information about an institution's educational benefits and the outcomes of its programs, protecting taxpayer interests in the careful use of title IV, HEA funds, and improving program performance, which often comes from better and more accessible information about results. Furthermore, as we noted in the preamble to the 2014 Prior Rule, the program information website builds on significant Federal interests in consumer information that are evidenced in decades of statutory disclosure requirements for institutions that receive title IV, HEA program funds. Contrary to the commenter's opinion, the information provided under § 668.43(d) is purely factual and will not be controversial, in part because the underlying information is either directly reported to the Department by the institution or, in the case of earnings data, is the highest quality data available and provided directly to the Department by a Federal agency with earnings data. As for concerns related to institutional data challenges, we address them below under “Challenges, Hearings, and Appeals.”

79 FR 64890, 64967 (Oct. 31, 2014).

The Department is confident in the quality of information to be presented on the Department's program information website, and confident that it will significantly improve what is easily available today. The individual items of information listed in § 668.43—including completion and withdrawal rates, D/E rates, EP measure, loan repayment rates, median loan debt, and median earnings—have been narrowly tailored to provide students and prospective students with the information the Department considers most critical in their educational decision making and in protecting taxpayer interests in the use of title IV, HEA aid, and in promoting improvement in education programs. Moreover, the Department intends to use consumer testing to further inform its determination of any additional items it will include on the program information website. We expect that this consumer testing will highlight the information that students find particularly critical in helping them make informed choices, which will in turn help the Department protect tax-financed resources.

Changes: We have revised § 668.43 to refer to the Department's website as the “program information website” rather than the “disclosure website.” We have also made conforming revisions to § 668.605(c)(2) and (3) by changing the reference from “disclosure website” to “program information website.”

Mechanism for Providing Transparency

Comments: Several commenters generally supported the proposed requirements but suggested that the Department provide the information via a single centralized website such as the College Scorecard rather than develop a separate website for the proposed metrics. These commenters noted that the College Scorecard is an established and well-known comparison tool and that adding the financial value transparency information to it would give students and families a better-rounded assessment of program value.

One commenter argued that developing a separate program information website would be duplicative, confusing to students, and increase costs to taxpayers when the College Scorecard is already available.

Discussion: We agree that the College Scorecard is a well-established and beneficial tool for providing information about postsecondary outcomes. The Department, however, also recognizes that merely posting the information on the College Scorecard website has had a limited impact on student choice. For example, a randomized controlled trial inviting high school students to examine program-level data on costs and earnings outcomes had little effect on students' college choices, possibly due to the fact that few students accessed the information outside of school-led sessions. Similarly, one study found the College Scorecard influenced the college search behavior of some higher income students but had little effect on lower income students.

Blagg, Kristin, Matthew M. Chingos, Claire Graves, and Anna Nicotera. “Rethinking consumer information in higher education.” (2017) Urban Institute, Washington DC. www.urban.org/research/publication/rethinking-consumer-information-higher-education.

Hurwitz, Michael, and Jonathan Smith. “Student responsiveness to earnings data in the College Scorecard.” Economic Inquiry 56, no. 2 (2018): 1220–1243. Also, Huntington-Klein 2017. nickchk.com/Huntington-Klein_2017_The_Search.pdf.

Consumer information is most likely to impact choice when tailored to the applicant's personal context. We seek to improve the information available to students with several refinements relative to information available on the College Scorecard, including debt measures that are inclusive of private education loans and other institutional loans (including income sharing agreements or tuition payment plans), as well as measures of institutional, State, and private grant aid. This information will enable the calculation of both the net price to students as well as total amounts paid from all sources. We believe these improvements will better capture the program's costs to students, families, and taxpayers, and we maintain that these benefits sufficiently outweigh the costs of developing the new program information website.

Changes: None.

Comments: One commenter encouraged the Department to consider whether requiring institutions to provide disclosures directly to students could be more efficient than creating a new website.

Another commenter requested that the Department consider a disclosure template similar to the GE disclosure template featured in the 2014 Prior Rule, noting that it would provide clear, concise, and uniform information from institutions to students.

Discussion: We believe that providing financial value transparency information through a centralized website maintained by the Department will make this information more convenient because it allows students, families, institutions, and the public to more easily compare programs than direct institutional disclosure would allow. In addition, requiring institutions to complete and post disclosure templates, or to directly distribute the information to students, would be more burdensome and costly to institutions than the Department's hosting the program information website. We of course welcome and encourage institutions to provide any reliable supplemental and contextual information to students that they may wish to provide in addition to the information we make available through the program information website.

Changes: None.

Comments: One commenter expressed support for a comprehensive postsecondary education data system which would provide academic, debt, and earnings information beyond the institutional or programmatic level down to the individual student level, and which would follow individual students across institutions, ultimately providing more complete and accurate post-graduation debt and earnings information. This commenter expressed support for the system proposed in this rule as a workaround, given that the Department is currently prohibited from establishing a unit record system of this nature, and noted that in the absence of such a system the approach proposed in this rule represents a generally positive workaround.

Discussion: We appreciate the commenter's support. While HEA section 134 prohibits the creation of new student unit record databases, any earnings data provided to the Department by the Federal agency with earnings data will be at the aggregate level. In the absence of such a granular system of records, we believe the transparency and accountability frameworks will provide program-level information that will exceed the quality and utility of currently existing information and oversight mechanisms.

Changes: None.

Comments: One commenter urged the Department to conduct user testing on its program information website before it launches.

Discussion: We appreciate the commenter's suggestion. The Department recognizes the value of consumer testing, and to this end we deliberately affirm in § 668.43(d)(1) the Secretary's authority to conduct consumer testing to inform the design of the program information website, if we determine that such input would likely enhance the implementation of the transparency framework.

Changes: None.

Scope

Comments: A few commenters expressed support for applying financial value transparency to both GE and non-GE programs to increase access to meaningful information about program performance. The commenters believed this approach addresses concerns about the growing presence at public and nonprofit institution of certain predatory and wasteful practices more prevalent in the proprietary sector, such as incentive-based compensation for online program managers and aggressive marketing of costly online graduate programs. Another commenter expressed support for requiring the calculation of meaningful metrics and providing this information to all students in all eligible programs. One commenter noted that this information is especially important for graduate programs.

Discussion: We thank the commenters for their support.

Changes: None.

Comments: A few commenters opined that any substantive language on the Department's program information website describing whether a program has met the standards and its presentation should be consistent for both GE and non-GE programs. However, these commenters acknowledged that language regarding potential loss of title IV, HEA program eligibility would not be relevant to non-GE programs.

Discussion: The commenter correctly noted that any language relating directly or indirectly to the loss of title IV, HEA program eligibility must be limited to GE programs, as non-GE programs are not included in the GE program eligibility framework. In crafting any other language, we will attempt to deliver relevant content using language that best serves the needs of students, and we will consider the commenter's suggestion as we develop that content.

Changes: None.

Comments: One commenter argued that the requirements proposed at § 668.43(d)(1)(vii) to provide loan repayment rates for students or graduates who entered repayment, at § 668.43(d)(1)(x) to provide median loan debt of students who completed or withdrew from the program, and at § 668.43(d)(1)(xi) to provide median earnings of students who completed or withdrew from the program are inappropriate. This commenter noted that information would capture students who did not complete the program, further claiming that loan repayment rates, median loan debt, and median earnings for students who did not complete a program are unrelated to the quality of the program.

Several additional commenters opined that the information should not include median loan debt and median earnings for non-completers because it would have no bearing on the expected earnings of a student who completes the program.

Discussion: While the D/E rates and EP measure are specific to graduates of a program, the Department disagrees with the commenters' assertion that other information such as loan repayment rates, median loan debt, and median earnings for non-completers is unrelated to the quality of a program. Graduation is, unfortunately, not the only possible outcome of even the most effective and well-administered postsecondary programs. We believe that students and prospective students have a legitimate interest in knowing the median amount students borrow when enrolling in a given program and their likelihood of being able to repay that debt—whether or not those students ultimately graduate from the program. We contend that such information will assist students in making better informed enrollment and borrowing decisions.

We further note that the outcomes of students who do not complete a program nonetheless reflect, at least to some extent, upon the quality of the program. It can be reasonably inferred that the capability of an institution to recruit students likely to succeed, to support and retain those students once enrolled, and to provide outreach and support (such as career services and information about loan repayment) to students who withdraw is indeed related to the overall quality of the program.

Changes: None.

Content

Comments: One commenter noted that proposed § 668.43(d)(1) provides that the program information website may include certain items, but does not actually require any of the listed items to appear on the new program information website. The commenter further noted that courts have held that such language would not require the Department to include any of the listed items. This commenter speculated that a future Secretary could effectively rescind the financial value transparency requirements without rulemaking. The commenter added that by providing students a regulatory right to specific information (beyond a right to a website, without any particular content) the Department would clarify that, should it later opt to remove the information, students would suffer an Article III injury-in-fact sufficient to confer legal standing.

Discussion: We share this commenter's concerns and appreciate the suggestion. We concur that proposed § 668.43(d)(1) would have established access to a Department website without guaranteeing access to any specific information. Upon further consideration, we have concluded that some of the listed items of information constitute a minimum of financial value transparency information that should be available to students, and that to remove any of those elements would harm students in the sense of receiving less than that minimum of important and useful information. We have reviewed the list of items in proposed § 668.43(d)(1) as well as data that we can foresee being available to the Department when these rules are implemented, in order to identify information that is feasible and especially important to post. Based on that review we have concluded that, to adequately safeguard students' access to the financial value transparency information otherwise provided under this rule, proposed § 668.43(d)(1) should be revised to require the Secretary to include certain listed items of information on the Department's program information website when applicable, while retaining the flexibility to add additional items. In our judgment and based on available evidence, the required list of items represents core program features and matters of special importance to students, institutions, and others who are interested in evaluating and comparing postsecondary education programs. These elements are all key pieces of information that are likely relevant to all students to understand basic facts about how much the program costs, how long it takes to complete, the amounts students borrow, their typical earnings after graduating, and the D/E and EP measures for the program. The elements we mention as optional may have more or less relevance to some students and to some programs than others.

Changes: We have revised § 668.43(d)(1)(i) to require the Secretary to include certain items of information on the Department's program information website when applicable, including the published length of the program; the program total enrollment during the most recently completed award year; the total cost of tuition, fees, books, supplies, and equipment that a student would incur for completing within the published length of the program; the percentage of students who received a Direct Loan, a private loan, or both for enrollment in the program; the programs median loan debt and median earnings; whether the program is programmatically accredited and the name of the accrediting agency; the program's debt-to-earnings rates; and the program's earnings premium measure. The Department reserves the flexibility to add additional items, and retains the proposed data items at § 668.43(d)(1)(ii) as examples of such supplemental data items.

Comments: One commenter suggested revising the list of information items in § 668.43(d)(1) to remove redundant information. This commenter opined that a regulatory requirement for linking to the College Navigator is unnecessary because the College Navigator is not user-friendly for a typical student. The commenter also noted that we could choose to include a link if warranted, since the new program information website would be under the Department's control.

Discussion: We appreciate the commenter's suggestion, and we agree that the Department could include a link to the College Navigator website without specifying it in the list of elements at § 668.43(d)(1).

Changes: We have removed the link to the College Navigator website from the list of required information items at § 668.43(d)(1).

Comments: Several commenters recommended that the Department provide generalized program level on-time graduation rates, as well as program level on-time graduation rates for Pell-eligible students and for women and for Black, Hispanic, and other students of color.

Discussion: The Department thanks the commenters for these suggestions. We recognize that this information could be useful to students and others, and we may consider adding it to the program information website in the future, particularly if such a change is supported by consumer testing.

Changes: None.

Comments: A few commenters suggested that the program information website should identify institutions that serve a high proportion of low-income students. These commenters argued that a nonprofit institution enrolling 5 percent Pell-eligible students and graduating 95 percent of students does less to improve social mobility than a proprietary institution enrolling 80 percent Pell-eligible students and graduating 60 percent of students.

Discussion: We appreciate the commenters' suggestion, and we might consider adding to the program information website in the future some designation of institutional mission or of programs that serve a high proportion of students with low income. We note, however, that the supporting argument made by these commenters is speculative and appears to understate the emphasis different institutions across all sectors and credential levels in higher education give to diversity in their students and the demographics they serve.

Changes: None.

Comments: One commenter identified loan repayment rates as important information for students, particularly those in GE programs.

Discussion: We agree that a program's loan repayment rate may be important information for students and other stakeholders, and this information is included in the list of information items under § 668.43(d)(1).

Changes: None.

Comments: A few commenters expressed concern that D/E rate information and the high debt burden and low earnings labels could confuse or mislead students, particularly first-generation and disadvantaged students, and could negatively impact underfunded and under-resourced institutions in regions experiencing persistent poverty. A few commenters opined that labeling programs as high debt burden or low earnings would discourage students from pursuing majors, such as teaching, which suffer from low wages and staffing shortages.

Discussion: We do not agree that the high-debt-burden or low-earnings label on the program information website will be confusing or misleading to students. These designations stem from a program's D/E rate or EP measure outcomes, which in turn rely upon factual data provided by institutions themselves and by Federal agencies with the best available data. Additionally, the meaning of the designations comports with a plain reading of each respective phrase.

The Department disagrees with the commenters' assertion that labeling programs as high debt burden or low earnings would discourage students from pursuing fields such as teaching. While we expect that the high-debt-burden and low-earnings labels will discourage enrollment in particular programs at particular institutions that lead to poor outcomes, we do not expect the financial value transparency framework to discourage enrollment more broadly in those fields of study. With regard to the field of education cited by commenters as an area of concern, as further discussed under “Impact on Enrollment in Lower Earning Fields” above, our analysis reveals that education training programs are less likely to fail the D/E rates or EP measure than other programs. Although a career in education may be less lucrative than other professions within the same credential level, evidence suggests that programs that prepare graduates for a career in teaching easily pass the EP threshold for earnings, and even States with lower salaries have average starting salaries well above the State's EP threshold.

As discussed under “Geographic Variation in Earnings” above, our analysis suggests that being located in persistent poverty counties is not outcome determinative for students at such institutions.

Changes: None.

Comments: Several commenters recommended that information about low-earning programs should also include information about Public Service Loan Forgiveness, as well as other loan forgiveness programs available through the Department of Health and Human Services and the Department of Veteran Affairs, so students can make better informed enrollment and career decisions. One commenter added that information about Public Service Loan Forgiveness and other relevant assistance programs would particularly benefit those entering the education profession.

One commenter posited that the Department should provide disclaimers and supplemental information where appropriate, such as a disclaimer if a program is disproportionally affected by unreported income. One additional commenter recommended including a disclaimer addressing programs with small cohort sizes.

Discussion: We appreciate the commenters' suggestions and concur that much of this information would be useful to students. We, however, also note that other commenters expressed concerns that the anticipated list of information items could confuse or overwhelm students. These conflicting perspectives demonstrate that we must seek an optimal balance of providing information of the most benefit to students without unduly distracting from the most salient information. We will carefully consider what supplemental information to convey on the program information website, taking into account consumer testing. We note that the list of required disclosure information items at § 668.43(d)(1) does not preclude the Department from adding additional information in the future. We further note that nothing would prohibit institutions from providing supplemental information directly to their students. Lastly, the final rule excludes programs with fewer than 30 completers in substantially similar programs over the previous four award years from reporting requirements of the rule, and therefore their D/E rates and the EP measure will not be available to publish.

Changes: We have revised § 668.408(a) to limit the reporting requirements to institutions offering any program with at least 30 total completers during the four most recently completed award years.

Comments: One commenter suggested that students and taxpayers would benefit from information about completion and placement rates; the existence of academic and related supports; and transfer and persistence rates.

Another commenter asserted that information such as licensure passage rates and residency placement rates are necessary to guard against deceptive recruitment tactics.

One commenter expressed support for providing the typical employment outcomes for a program.

Another commenter opined that the Department should not only require job placement rates to be provided, but also regulate how such placement rates are calculated, citing the collapse of Corinthian as one example of why providing consistently calculated placement rates is essential to protect students and the public. This commenter contended that in the 2014 Prior Rule preamble, the Department cited a 2011 technical review panel, which concluded a uniform job placement methodology could not be developed without further study because of data limitations. The commenter noted that the NPRM preceding this final rule did not mention this study or discuss whether it should be updated in light of any advances in the available data systems since 2011. The commenter further questioned why the Department's policies requiring placement rates for certain short-term programs under § 668.8(g) could not be applied for purposes of financial value transparency.

Discussion: We agree that students will benefit from knowing completion rates and note that the program's or institution's completion rates are included among the list of information items at § 668.43(d)(1).

Though we agree that licensure passage and residency placement rates would be useful to students, a substantial portion of postsecondary programs do not prepare students to enter a field requiring licensure, and many programs do not entail any residency requirements. In the interest of focusing on the most relevant, comparable, and broadly applicable information, we do not anticipate including licensure passage and residency placement rates on the program information website at this time. We note that the list of information items at § 668.43(d)(1) is not all-inclusive and the Department could add these additional items in the future, particularly if consumer testing supports doing so.

We note that providing the “typical employment outcomes” for a program could mean a variety of things depending upon the audience—for example, the number of graduates who find employment in a specific field, the number of graduates who find employment in any field, the number of graduates who remain employed for a specific length of time, the job satisfaction of graduates, or any number of other measurements related in some way to employment. We therefore believe the suggestion to provide typical employment outcomes is too broad and imprecise to implement.

While we concur that job placement rates would be beneficial to most students, we note that accrediting agency methodologies and requirements for placement rates vary, and inconsistencies in how institutions currently calculate job placement rates limit their usefulness in comparing institutions and programs. The placement rate requirement for short-term programs under § 668.8(g) relies upon auditor attestations of institutional calculations, which again can vary amongst institutions and auditors. Developing a uniform Federal standard for the calculation of placement rates would be a complex and extensive undertaking surpassing the scope of this rulemaking. Nonetheless, should the Department introduce such a standard through future rulemaking, we could add placement rates to the program information website in the future.

Changes: None.

Comments: A few commenters suggested that any median earnings data provided under proposed § 668.43(d)(1)(xi) should be based on the same time periods as those used for the D/E rates and EP measure.

Discussion: We appreciate the commenter's suggestion. While in general we anticipate providing earnings data for the same time periods as those used for calculating the D/E rates and EP measure, we retain the flexibility to provide median earnings during a period determined by the Secretary. For example, if an institution uses the transitional reporting option and transitional metrics are calculated then the cohorts used for determining median debt may differ from the cohorts used for determining median earnings.

Changes: None.

Comments: Several commenters urged the Department to explain that the D/E rates exclude funding from State and local governments and only measure debt burden relative to students, not to taxpayers. One commenter noted that in the 2019–20 award year, public degree-granting institutions received 76.6 billion in State appropriations and 14.5 billion in local appropriations.

Several commenters suggested that the Department explore including an estimate of State and local taxpayer support for programs at public institutions, arguing that doing so would provide the public and policymakers a more accurate understanding of program cost, with one commenter noting that the Department has access to such information through The Digest of Higher Education Statistics.

Discussion: The Department disagrees with the commenters' suggestion that the regulations unfairly assess for-profit institutions because programs operated by for-profit institutions are in fact less expensive than programs operated by public institutions, once State and local subsidies are taken into account. While some for-profit institutions may need to charge more than some public institutions because they do not have State and local appropriation dollars and must pass the educational cost onto the student, there is some indication that even when controlling for government subsidies, for-profit institutions charge more than their public counterparts. Research has found that the primary costs to students at for-profit institutions, including foregone earnings, tuition, and loan interest, amounted to $51,600 per year on average, as compared with $32,200 for the same primary costs at community colleges. This analysis estimated taxpayer contributions, such as government grants, of $7,600 per year for for-profit institutions and $11,400 for community colleges.

Cellini, S.R. (2012). For Profit Higher Education: An Assessment of Costs and Benefits. National Tax Journal, 65 (1):153–180.

The goals of this rule are to provide increased transparency of program outcomes and improved oversight of Federal taxpayer funds. While public institutions often benefit from State and local appropriations, we maintain that monitoring, providing, and otherwise overseeing such sources of institutional revenue falls outside the scope of this rule. We further note that non-Federal funding is not exclusive to public institutions and could include any number of sources such as endowments, research grants, charitable donations, private equity, fees from publicly offered services, and so forth. Requiring institutions to report all such sources of funding would be unduly burdensome, and the inclusion of all such sources of funding on the Department's website would likely overwhelm many students and distract from the core information provided under these regulations.

Changes: None.

Comments: One commenter urged the Department to clarify that the financial value transparency information does not measure academic quality ( e.g., skill of faculty, learning outcomes, quality of facilities) or the lifetime earnings of graduates.

Discussion: The Financial Value Transparency and Gainful Employment regulations are intended to establish an accountability and transparency framework to encourage eligible postsecondary programs to produce acceptable debt and earnings outcomes, apprise current and prospective students of those outcomes, and provide better information about program price. Other factors such as those mentioned by the commenter may contribute to these financial outcomes, but we do not believe that students would mistake the financial value transparency information that the Department proposes to present in a straightforward manner on its website as for a direct measurement of academic quality. While the Department believes that students should be informed about the debt and earnings consequences of their postsecondary choices, we may consider adding language to the student program information website noting that the debt and earnings outcomes of programs are a subset of the myriad factors students may consider important in deciding where to attend, particularly if such language is supported by consumer testing.

Changes: None.

Comments: For public and nonprofit institutions, one commenter recommended that the Department additionally identify whether all revenues of the institution are committed to its educational and charitable mission and whether the majority of net tuition revenues in the program are used for post-enrollment instruction and student support. The commenter further suggested that such information should be affirmed in a footnote on the institution's audited financial statement. The commenter opined that this additional information would promote the legitimate nonprofit operation of institutions and shield students from incorrect assumptions that tuition dollars will be used to support their success in cases where the institution diverts funds to recruitment or other purposes. This commenter also suggested initially making this additional information a voluntary option, to accommodate institutions which may need time to add those measure to their internal accounting.

Discussion: While we share the commenter's concern about some nonprofit institutions' use of title IV, HEA revenue for marketing, recruitment, and other pre-enrollment functions unrelated to academic instruction and student support, we do not believe that the financial value transparency website is the best vehicle to address that concern. The Department also received comments related to this issue on both the Financial Responsibility and the Certification Procedures regulations proposed in the NPRM. Those issues will be discussed in a separate forthcoming final rule.

Changes: None.

Comments: A few commenters encouraged the Department to provide disaggregated data whenever possible.

Discussion: We thank the commenters for that suggestion. The metrics in the rule currently focus on whether a program is leading to high-debt-burdens or enhanced earnings for the majority of its completers. We will carefully consider what additional information might feasibly and usefully be added to give students more tailored information on program performance for students in their own demographic group, particularly in light of consumer testing and privacy safeguards.

Changes: None.

Distribution and Linking Requirements

Comments: Several commenters voiced general support for requiring institutions to provide current and prospective students with a link to the Department's program information website and urged the Department to preserve this component of the proposed rule. One commenter argued that students enrolling in postsecondary programs are sufficiently mature to be expected to review the information available to them without requiring institutions to actively distribute a link to the material.

A few commenters expressed concern about requiring institutions to post a link to the Department's program information website on every institutional web page containing information about a program or institution's academics, cost, financial aid, or admissions. One commenter likened this requirement to the requirement in the FAFSA Simplification Act for institutions to provide all elements of the cost of attendance on any portion of the institution's website that describes tuition and fees. This commenter noted that while it appears to be a simple requirement, it has already generated numerous inquiries from institutions about how to comply.

Several commenters noted that although adding links to the Department's program information website to institutions' websites would be a one-time cost and burden, large institutions may have hundreds of web pages requiring these links. These commenters advised that such a requirement could lead to compliance issues if such an institution inadvertently neglected to post the required link on one or a few web pages.

One commenter further noted that monitoring and enforcing such a broad requirement could divert the Department's resources away from more impactful issues and urged the Department to require institutions to link to the program information website only on their main website and on each individual program's landing pages.

Discussion: We thank those commenters for their support. The Department disagrees with the commenter who suggested relying on students to find the Department's website on their own because students enrolling in postsecondary programs vary widely in life experience and financial literacy. For many students, selecting an institution and program of study is likely to be one of the most financially significant decisions of their life. While some students may possess the financial savvy and inclination to independently research and compare institutions and programs, others may not. We believe that requiring institutions to inform students about the Department's program information website under § 668.43(d)(3) and (4) would benefit students by informing them about the existence of information that could aid in their decision making, without unduly burdening institutions.

Furthermore, we do not believe the requirement for institutions to post a link to the Department's program information website on every institutional web page containing information about a program or institution's academic, cost, financial aid, or admissions is confusing or unclear. The requirements pertaining to the posting of Cost of Attendance information under the FAFSA Simplification Act are unrelated to the financial value transparency information established under this rule, and many of the inquiries concerning those Cost of Attendance posting requirements were about the specific content of the information that must be posted to meet FAFSA Simplification Act requirements. We note that for the required financial value transparency information, institutions must post the link to the Department's program information website on all relevant web pages. We believe that institutions can reasonably meet this requirement and, as noted in the RIA, we believe that this activity will require an estimated 50 hours per institution. We expect to provide sub-regulatory guidance and training to institutions in advance of the effective date of these provisions to minimize this burden. With regard to the argument about the potential for inadvertent noncompliance with the posting requirements, we note that an institution could inadvertently fail to comply with any of our regulatory provisions, and it remains the institution's responsibility to have the necessary staff, systems and processes to be able to comply with all of our regulatory requirements. We do not expect that monitoring and enforcing this requirement will require significant resources and hinder the Department's other compliance monitoring and enforcement efforts.

Changes: None.

Comments: One commenter suggested that publicizing information and directing students to it during their senior year in high school or earlier could better impact enrollment decisions.

Another commenter expressed support for ensuring students receive the information before enrolling or making a financial commitment, agreeing with the Department that information on program value should be provided at relevant points of entry. This commenter further suggested that the Department consider providing access to this information through the FAFSA portal to provide the information to students earlier in the decision-making process in a manner that would not rely on institutional compliance.

Discussion: The timing of when applicants receive information about institutions and programs is critical. Data should be available at key points during the college search process, and applicants should have sufficient time and resources to process new information. Informational interventions work best when they arrive at the right moment and are offered with additional guidance and support.

Carrel, S. & Sacerdote, B. (2017). Why Do College-Going Interventions Work? American Economic Journal; Applied Economics. 1(3) 124–151.

We do not agree that providing information to prospective students during high school or earlier would be more beneficial than providing it closer to when the student makes the decision to enroll. We, however, appreciate the commenter's suggestion to provide information about the program information website to students through the FAFSA portal. While it would not be possible to incorporate this change to the 2024–25 FAFSA portal at this stage of development, we will consider adding it in a future award year.

Changes: None.

Comments: A few commenters opined that the requirements would present obstacles to serving the basic needs of enrolled students by delaying title IV, HEA disbursements. These commenters also opined that the information would arrive too late in the admissions process to affect college enrollment decisions.

Discussion: We do not agree that the requirement to distribute information about the program information website would disrupt the basic needs of students. We note that the distribution requirements at § 668.43(d)(3) and (4) are not directly tied to the disbursement of title IV, HEA funds. We also disagree that the distribution requirement would arrive too late to affect enrollment decisions. The institution must distribute information about the program information website to any prospective student before the student signs an enrollment agreement, completes registration, or makes a financial commitment to the institution. If the student is considering enrolling in a risky program, the acknowledgment or warning requirements at §§ 668.407 and 668.605 provide additional information and protection.

Changes: None.

Comment s: One commenter requested we clarify whether or how the definition of “student” in § 668.2 applies to the new program information website.

Discussion: The definition of “student” in § 668.2 applies specifically to subparts Q and S. The requirements related to the program information website in § 668.43 exist outside of subparts Q and S. Rather than relying upon the definition of “student” in § 668.2, § 668.43(d)(4) requires an institution to provide information to access the program information website to any enrolled title IV, HEA recipient prior to the start date of the first payment period associated with each subsequent award year in which the student continues enrollment at the institution.

Changes: None.

Cooling-Off Period

Comments: One commenter noted that the NPRM preamble text suggests that a three-day “cooling off” period after distributing information about the program information website is required for all enrollments, not just those where warnings are required, while the regulatory text of proposed § 668.43(d)(4) does not include such a requirement. This commenter asked that the Department clarify in the final rule that no pre-enrollment cooling-off period is required except when a warning requirement is in place for the intended program of study.

Discussion: We thank the commenter for alerting us to the discrepancy between the proposed regulatory text and the preamble discussion in the NPRM. We confirm that the three-day cooling off period in § 668.605(f)(2) only applies when a warning requirement is in place for a GE program and does not apply to the distribution of information about the Department's program information website under § 668.43(d).

Changes: None.

Student Acknowledgments and GE Warnings—§§ 668.407 and 668.605

General Support

Comments: Several commenters expressed support for the proposed requirement in § 668.407 of the financial value transparency framework for students enrolling in a high-debt program to acknowledge viewing financial value information before the institution may enter an enrollment agreement with the student. One commenter further noted that information and market forces alone are insufficient without an acknowledgment requirement. One commenter expressed support for requiring acknowledgments prior to aid disbursement for poor-performing programs as an effective approach to improving the outcomes of students and encouraging the use of Federal aid at better-performing institutions.

Discussion: We thank the commenters for their support. We have retained the student acknowledgment provision in § 668.407 of the financial value transparency framework, with certain modifications that we explain below. Core features mentioned by these commenters remain the same compared to the proposed rule. Among those features are, for example, that the acknowledgments will not be limited to information about gainful employment programs but instead will extend to certain other postsecondary education programs; that the acknowledgments will be submitted by certain students to the Department through its program information website; and that the students will acknowledge having viewed information on the Department's website regarding particular programs that have substandard results on the D/E rates measure. As the commenters understood, the acknowledgments will help make salient to students, at important junctures in their decision-making processes, certain debt-related and other information about title IV, HEA eligible programs, and thereby assist students in making informed choices about their postsecondary education. Such informed decisions may benefit not only these students but also the Federal Government and others to the extent that title IV, HEA support is channeled, through informed student choices, toward programs that are not leaving graduates with unaffordable debt. Whatever is the full array of values that people pursue through higher education and training, including nonpecuniary goals involving service to others, unaffordable debt can obstruct the achievement of all those goals.

Changes: None.

General Opposition

Comments: One commenter suggested that requiring acknowledgment of the program information website before disbursement creates a barrier to receiving title IV, HEA funds, and that institutions are prevented from adding additional barriers to title IV, HEA aid by statute. Many commenters argued that requiring students to acknowledge having viewed program information on the Department's website prior to enrollment would delay course registration and impede the disbursement of aid to students in need of such funds to cover costs for housing, food, and other basic needs.

Discussion: The student acknowledgment requirement in § 668.407 of the financial value transparency framework does not conflict with HEA provisions intended to protect student access to title IV aid. Instead, this requirement will provide additional protection to students, as well as taxpayers, by providing certain information to students about programs before institutions enter into enrollment agreements with students.

Under the transparency framework's student acknowledgment rule, in certain circumstances the Department will require prospective students to acknowledge to the Department that they have viewed relevant information on the Department's program information website before signing an enrollment agreement with an institution regarding a certificate program or graduate degree program. The acknowledgment will be made electronically on the Department's website. In itself, this step toward enrollment and title IV, HEA aid is not onerous for students. Moreover, we will except undergraduate degree programs in this final rule (see § 668.407(a)), for reasons explained elsewhere in this document, thus avoiding undue burden for programs where prospective students may not generally apply to a particular major (but rather “declare” a major after being enrolled for some time in the institution). Furthermore, and also as explained below, this final rule states that only prospective students, not enrolled students, must give acknowledgments when the relevant program has substandard results regarding debt burdens under the debt-to-earnings (D/E) rates measure (see § 668.407(b) and (c)). That adjustment to the regulation relieves much of the commenters' concerns about disruptions of title IV, HEA student aid, and targets the requirement to a group of students most likely to act on the information in considering where to enroll.

In § 668.2 of these rules, “prospective student” is defined as an individual who has contacted an eligible institution for the purpose of requesting information about enrolling in a program or who has been contacted directly by the institution or by a third party on behalf of the institution about enrolling in a program. Potential transfer students are among those who may meet this definition of “prospective student.”

We explained in the NPRM our decision to limit the transparency framework's student acknowledgment requirement to programs with high debt burdens under the D/E rates measure, and we adopt that position again here. While many non-GE students surely care about earnings, non-GE programs are more likely to have nonpecuniary goals. Requiring students to acknowledge low-earning information as a condition of receiving aid might risk conveying that economic gain is more important than nonpecuniary considerations. In contrast, students' ability to pursue nonpecuniary goals is jeopardized and taxpayers bear additional costs if students enroll in high-debt burden programs. Requiring acknowledgment of the D/E rates ensures students are alerted to risk on that dimension.

88 FR 32300, 32336 (May 19, 2023).

We note as well that § 668.605 in subpart S of these regulations, which cover GE programs, includes warnings from institutions to prospective and enrolled students as well as acknowledgments from students to the Department through its website. Those GE warnings and acknowledgments will help inform students when GE programs are at risk of losing title IV eligibility in the following year. And those GE provisions in subpart S will complement the student acknowledgment provision in the transparency framework of subpart Q, the latter of which helps serve the interests of non-GE students where program eligibility based on performance metrics is not at issue.

Moreover, acknowledgments are a traditional, typical, and simple method of enhancing awareness of information before decisions are made. In this instance, the online mechanism for the acknowledgment will be relatively simple, and the decision in question involves both a student's education and Government support for that education. When programs fail certain performance metrics, the Department will protect prospective students and taxpayers by asking those students to pause and acknowledge information on the Department's program information website before they enter into an enrollment agreement for that program.

We agree that institutions may not add eligibility requirements that would prevent students or groups of students from receiving title IV, HEA aid for which they are otherwise eligible. But these student acknowledgment rules do not implicate those protections for students. Changes: None.

Comments: A few commenters urged the Department to ensure that institutions receive immediate confirmation when students complete any required acknowledgments through the Department's program information website, to ensure timely disbursement of title IV, HEA funds. One commenter noted that the system for providing D/E and EP metrics has not yet been developed and that, as a result, institutions will not be timely made aware of metric outcomes, causing a delay in disbursements of title IV, HEA funds. One commenter suggested that the Department instead administer financial value transparency acknowledgment requirements through the Free Application for Federal Student Aid (FAFSA), which would provide the relevant information to each student at an important stage in the student's decision process while also eliminating disbursement delays and relieving administrative burden on institutions.

Discussion: We understand the commenters' concerns and we have made certain modifications to § 668.407 as proposed. To begin, in this final rule the Department has decided to require student acknowledgments under that regulation before students enter into an enrollment agreement with the relevant institution (§ 668.407(c)(1)), rather than before an institution may disburse title IV, HEA aid. Pegging student acknowledgments to an enrollment agreement should reduce concerns about unjustified disruptions in title IV aid, while nonetheless enabling students to make informed choices at an adequately early stage in the decision-making process. In the final rule, we also clarify that the Department will monitor an institution's compliance with the pre-enrollment-agreement acknowledgment requirement through audits, program reviews, and other investigations (§ 668.407(c)(2)). Although the students will make acknowledgments to the Department and the Department will operate the acknowledgment process through its website, institutions will check whether the students whom they seek to enroll have completed the acknowledgment. As we have explained, an acknowledgment is a simple yet important step that students must take when § 668.407 applies due to substandard debt-to-earnings results for the relevant program. In addition, we reiterate here that § 668.407 will apply to prospective students (§ 668.407(b)), rather than enrolled students.

We recognize that requiring prospective students to acknowledge the program information prior to an enrollment agreement means that some students will have to take that step before course registration and disbursement of aid. We understand students' need for timely access to title IV, HEA funds not only to cover direct institutional costs but also to cover indirect educationally related expenses. We note again, however, that the acknowledgment process will not be lengthy or particularly burdensome to students. And the adjustments to the rule that we have made in light of commenter concerns should minimize disruption while enhancing informed choice. We believe that such information is necessary to make an informed decision about whether to enroll in a program, and that the urgency of a student's need for this information warrants the potential delay, which again should not be excessive or disruptive.

Moreover, in part to reduce burden for institutions and students, we will limit the acknowledgment requirement in § 668.407 to programs that do not lead to an undergraduate degree. We believe this change will better target the acknowledgment requirements to programs to which students tend to directly apply. In addition, our empirical analysis shows that high-debt-burden programs are relatively rare among undergraduate degree programs outside the proprietary sector.

Commenters are correct in observing that the website for delivering financial value transparency information and administering acknowledgments is not yet developed. As we develop the website and its underlying processes, we will consider ways to efficiently and timely transmit confirmation of completed acknowledgments to institutions. Nevertheless, we recognize the potential for delays and uncertainty as the Department designs and deploys new systems to implement these requirements. To minimize disruption and facilitate a smoother implementation of the Department's program information website and acknowledgment requirements, the Department has specified that the requirements under § 668.43(d) and the acknowledgment requirements under §§ 668.407 and 668.605 are not applicable until July 1, 2026.

We appreciate the commenter's suggestion to administer the acknowledgment requirements through the FAFSA. However, administering the acknowledgment process through the FAFSA would not reach prospective students who have not yet applied for title IV, HEA funds. The acknowledgment requirement in § 668.407 is limited to prospective students and does not apply to enrolled students. We believe that administering the acknowledgment process through the Department's program information website is the most efficient and effective approach, but we will continue to analyze ways of most seamlessly delivering information to students.

Changes: The Department has specified that the requirements under § 668.43(d) and the acknowledgment requirements under §§ 668.407 and 668.605 are not applicable until July 1, 2026. Furthermore, the Department requires student acknowledgments under § 668.407(c)(1) before students enter into an enrollment agreement with the relevant institution, and the Department will monitor an institution's compliance with the pre-enrollment-agreement acknowledgment requirement through audits, program reviews, and other investigations per § 668.407(c)(2). In addition, we exclude undergraduate degree programs from the acknowledgment requirements at § 668.407(a)(1).

Comments: One commenter suggested that the Department consider a two-year pilot study, during which the student acknowledgment and GE warning requirements would not be applied, to review the earnings and salaries of completers to enable a real-world comparison of costs and earnings.

Discussion: We appreciate the commenter's suggestion. Although we will certainly monitor the median earnings data obtained under these regulations, we believe that the need for the financial value transparency framework and GE accountability framework is too great to delay implementation for a two-year study. As noted above, however, we recognize the potential for delays and uncertainty as the Department designs and deploys new systems to implement these requirements. To minimize disruption and facilitate a smoother implementation of the program information website and acknowledgment requirements, the Department has specified that those requirements are not applicable until July 1, 2026.

Changes: The Department has specified that § 668.43(d) and the acknowledgment requirements under § 668.407 are not applicable until July 1, 2026. In addition, we exclude undergraduate degree programs from the acknowledgment requirements at § 668.407(a)(1).

Comments: Many commenters opined that the proposed warning requirements in § 668.605 of the GE accountability framework would irreparably harm programs, rendering ongoing recruitment impossible and leading to program teach-outs and closures after warnings were provided to students. Several commenters opined that requiring warnings after a single year of failing the D/E rates or EP measure would fail to account for market shifts, emergencies, disasters, or other unforeseen conditions, and would result in program closures precisely when they are most needed, such as during an economic downturn when many dislocated workers tend to seek retraining. Several commenters argued that such a swift warning requirement does not establish a pattern of poor performance and would offer institutions little or no opportunity to improve troubled programs. One commenter further noted that sudden changes to National or State licensure requirements could have far-reaching effects, causing more students than usual to fail licensure exams and delaying employment, causing programs to fail one or both metrics, and requiring warnings due to circumstances beyond an institution's control. One commenter predicted that these consequences would especially impact institutions that focus on a single program, such as cosmetology institutions, claiming that for such institutions a required warning would be tantamount to an accelerated school closure.

Discussion: We believe that enrolled students and prospective students should receive a warning when a GE program may lose eligibility in the following award year based on its D/E rates or EP measure. We recognize that a program's D/E rates and EP measure may be atypical in a particular year as a result of any number of factors and for that reason a GE program will not lose eligibility for failing the D/E rates or EP measure in a single year. However, a student enrolled in a GE program that loses its title IV, HEA program eligibility because of its D/E rates or earnings premium faces potentially serious consequences. If the program loses eligibility before the student completes the program, the student may need to transfer to an eligible program at the same or another institution to continue to receive title IV, HEA program funds. Even if the program does not lose eligibility before the student completes the program, the student could be, nonetheless, enrolled in a program consistently associated with poor earnings outcomes or unmanageable levels of debt. Accordingly, we believe it is essential that students be warned about a program's potential loss of eligibility based on its D/E rates or earnings premium.

The student warning will provide currently enrolled students with important information about program outcomes and the potential effect of those outcomes on the program's future eligibility for title IV, HEA program funds. This information will also help prospective students make informed decisions about where to pursue their postsecondary education. Some students who receive a warning may decide to transfer to another program or choose not to enroll in such a program. Other students may decide to continue or enroll even after being made aware of the program's poor performance. In either case, students will have received the information needed to make an informed decision.

We believe that ensuring that students have this information is necessary, even if it may be more difficult for programs that must issue student warnings to attract and retain students, and even in cases where an institution only offers a single program of study. Institutions may mitigate the impact of the warnings on student enrollment by offering meaningful assurances and alternatives to the students who enroll in, or remain enrolled in, a program subject to the student warning requirements.

We disagree with the arguments from commenters about the effects of licensing changes. The Department does not dictate how many hours States require for students to sit for licensing tests. And since States dictate the required program lengths for licensure or certification, we think it is reasonable to assume States have considered the hours needed for someone to then be able to pass any necessary tests. As noted already in this discussion, to the extent there are changes in passage rates, the fact that programs have to fail more than once will mitigate this issue by giving institutions time to improve. Commenters raised the issue of potential changes to the length of GE programs in a part of the NPRM that will be addressed in a separate final rule.

Changes: None.

Comments: One commenter expressed concern that the rule as proposed would require programs without aid to send letters to prospective students stating that their target occupation is a low-income profession.

Discussion: This is incorrect. The warning provision requires schools to distribute warnings to prospective students of GE programs that still are eligible for title IV, HEA aid but are at risk of losing it so that the prospective student can make an informed decision cognizant of the possibility that the program may lose title IV, HEA eligibility before the student has completed the program. The warning language does not identify any occupations as low-income professions, but rather alerts prospective students to the fact that the program in question has not passed standards established by the Department based on the amounts students borrow for enrollment in the program and their reported earnings, as applicable, and directs prospective students to the relevant program information web page so that they can explore more contextual information.

Changes: None.

Comments: One commenter objected to any warning requirements for GE programs under subpart S, opining that student acknowledgments under subpart Q are sufficient. Another commenter posited that neither the warning nor acknowledgment requirements are necessary because the requirement to post links to the Department's program information website would be sufficient.

One commenter maintained that establishing acceptable levels of performance regarding debt and earnings exceeds the role of government because the Department would substitute its own judgment of acceptability thresholds for those of prospective students whose risk tolerances could potentially differ. This commenter further postulated that some students could rely on the Department's assessment and still realize poor results, misinterpret “no results” as an absence of risk, or unnecessarily forego opportunities because the Department's information increased their risk aversion.

Discussion: The Department disagrees with the argument that the student acknowledgment requirements in § 668.407 under subpart Q obviate the need for GE program warning requirements in § 668.605 under subpart S. Those rules regard different programs, and they involve different information and circumstances. The student acknowledgment requirements under subpart Q are limited to prospective students, and they are limited to programs that do not lead to an undergraduate degree and that have high debt-burden results under the D/E rates measure. In contrast, the acknowledgment and warning requirements under subpart S apply to GE programs (including degree programs) that are at risk of losing title IV, HEA eligibility because of failing either the D/E rates or the EP measure, and include additional content designed to assist prospective students and enrolled students facing a potential loss of funds, such as information about the transferability of credit, availability of refunds, and continued availability of the program of study in the event of a loss of title IV, HEA eligibility. The rules for GE program warnings and acknowledgments are crafted for the special circumstances of GE programs. Hence the student acknowledgment requirements in § 668.407 do not duplicate the GE program warning and acknowledgment requirements in § 668.605. Although the two provisions serve some of the same general purposes, such as informing students who seek title IV, HEA aid about higher education programs, § 668.407 does not eliminate the need for § 668.605.

In § 668.2 of these rules, “prospective student” is defined as an individual who has contacted an eligible institution for the purpose of requesting information about enrolling in a program or who has been contacted directly by the institution or by a third party on behalf of the institution about enrolling in a program. And “student” is defined, for the purposes of subparts Q and S of this part and of § 668.43(d), as an individual who received title IV, HEA program funds for enrolling in the program.

We further disagree with the contention that the requirement in § 668.43(d)(2) for institutions to post links to the Department's program information website renders both the acknowledgment and warning requirements unnecessary. As discussed above, the timing of the delivery of relevant information significantly affects the impact of that information on students. Absent acknowledgment and warning requirements, even students who may have carefully reviewed information about their program of study on the Department's program information website before enrolling may be unaware of changes in that information that may have occurred since they first accessed the website. The Department seeks to require that, for programs where acknowledgments or warnings are required and before certain specified events such as the signing of an enrollment agreement, students have reviewed up-to-date information including information that may implicate the student's access to title IV, HEA funds in future years to complete the program.

With regard to the commenter's claim that establishing acceptable levels of performance regarding debt and earnings exceeds the role of government, the Department disagrees with the commenter's conclusions. As discussed in more detail under “Authority for this Regulatory Action” in this document, this framework is supported in principal part by the Secretary's generally applicable rulemaking authority, which includes provisions regarding data collection and dissemination, and which applies in part to title IV of the HEA, as well as authorizations and directives within title IV of the HEA regarding the collection and dissemination of potentially useful information about higher education programs. We also disagree with the notion that the Department may not seek to inform students about program outcomes as they evaluate programs within a lawful range of options for Federal Government support. Existing law and sensible policy indicate that the Department's role in supporting the interests of students, taxpayers, and others is more meaningful than some commenters suppose.

As further discussed above under “Statutory Authority for GE Framework,” the basic question of whether the HEA authorizes GE performance measures has been resolved repeatedly in the Department's favor. Questions of how exactly to specify the GE performance metrics involve matters of detail, which the Department is statutorily authorized and well-positioned to resolve. It is not only reasonable but also in accord with all indications of Congress's intent to conclude that a program does not prepare students for gainful employment in a recognized occupation if typical program graduates are left with unaffordable debt, or if they earn no more than comparable high school graduates. In addition, the Department is fully authorized to share information about the debt and earnings outcomes of a program with students, institutions, and the public to the extent that such information is available. In whatever manner the information is labeled, providing this information to students will allow them to make better informed enrollment and borrowing decisions.

Changes: As discussed in General Opposition under Program Information website above, we have revised the reference to the Department's website as the “program information website” rather than the “disclosure website.”

Scope of Acknowledgments

Comments: Many commenters expressed support for requiring acknowledgments from students entering high-debt-burden GE and non-GE programs, but opined that acknowledgments should also be required when students enter low-earning non-GE programs. Some such commenters further argued that: (1) the Department's analysis in the NPRM concluded that more students enrolled in failing non-GE programs than in failing GE programs; (2) earnings outcomes are important even to students in non-GE programs; (3) students do not differentiate programs by institution type; and (4) not applying acknowledgment requirements to non-GE programs that fail the EP measure would unfairly shield poor-performing programs at public and nonprofit institutions from any meaningful impact of poor performance.

In contrast, a few commenters urged the Department to exempt all non-GE programs from student acknowledgment requirements because of the time and burden associated with identifying relevant students and ensuring that they complete the acknowledgments, or because many non-GE programs are intended as only the first steps of a student's education and necessarily lead to graduate or doctoral studies or clinical work requirements. One commenter theorized that borrowers would likely ignore warnings associated with non-GE program as a result of the REPAYE income-driven repayment plan. One commenter suggested that the Department consider a tiered approach applying acknowledgment requirements to GE programs as well as a subset of low-earning non-GE programs, opining that such an approach would recognize the interests of students who prioritize earnings potential while reducing burden on institutions.

Discussion: We do not agree that students should be required to complete acknowledgments when enrolling in low-earning non-GE programs, nor do we agree that not applying acknowledgment requirements to non-GE programs that fail the EP measure would unfairly shield poor-performing programs at public and nonprofit institutions from meaningful impacts of poor performance. Public institutions are subject to additional layers of oversight and scrutiny at the State or local level, and nonprofit institutions typically are subject to oversight by a board of directors. We do anticipate that a considerable portion of non-GE programs lead to high debt burden or low earnings under the financial value transparency metrics, and we understand that many students seeking to enroll in non-GE programs may place high importance on improving their earnings. But we believe that students who enroll in non-GE programs are more likely to have nonpecuniary goals, and requiring students to acknowledge low-earning information as a condition of receiving aid might risk improperly conveying that economic gain is more important than those nonpecuniary considerations. We concur that most students likely compare programs rather than institution types, but we note that in many cases the types of programs offered across institutions significantly vary, and public and nonprofit institutions are less likely to predominately market their programs solely based on employment and earnings outcomes.

We also disagree with the requests to entirely exempt non-GE programs from student acknowledgment requirements. As further discussed under “Burden” below, we believe that the burden associated with identifying relevant students and ensuring that they complete the acknowledgments is reasonable considering the benefit of providing relevant and timely information to students who enroll or continue in non-GE programs that do not lead to an undergraduate degree and are associated with high debt burden. We concur that many non-GE programs are intended as the initial stage of a student's education leading to further graduate or doctoral studies or clinical work requirements, but that does not obviate the relevance of information about debt outcomes in better informing students' enrollment choices, nor does the possibility that borrowers might ignore warnings associated with non-GE program as a result of the REPAYE income-driven repayment plan take away the relevance of this information.

Changes: None.

Duration of Acknowledgments

Comments: One commenter indicated that the duration of the obligation to obtain acknowledgments under proposed § 668.407(a)(1) of the financial value transparency framework appeared to be unspecified. The commenter recommended that the duration mirror that of GE programs requiring warnings and acknowledgments—that is, until the program receives two consecutive passing outcomes.

Discussion: The Department appreciates the commenter's suggestion. We have made changes to § 668.407(b)(3) to specify the duration and frequency of the requirement. Under revised § 668.407(b)(3), prospective students must provide acknowledgments until the program has passing D/E rates or three years after the institution was last notified it had failing D/E rates, whichever is earlier. The three-year “look-back” period is relevant only in situations where a program might fail the D/E rates measure in one year, but then not have rates issued by the Secretary in the following year(s) due to the number of completers at that program falling below the minimum threshold necessary for the Secretary to issue the program's median debt and median earnings. In choosing to disregard rates over three years old, the Department is balancing the goals of making students aware of the financial risk involved in enrolling in the program and fairness.

A reduction in the number of completers at a program is very unlikely to be indicative of improvement in its performance. As a result, a program that fails the D/E rates measure in one year, and then experiences a decline in the number of completers leading its D/E rates not to be issued, is still likely to be failing the D/E rates measure. At the same time, we do not believe it fair to keep the acknowledgment requirement indefinitely if new rates are not calculated. After several years, continuing to base student acknowledgments on earlier calculated rates yet without confirmation of substandard program performance becomes less helpful to students and ultimately unreasonable. After considering the relevant factors and the importance of an administrable rule, we have chosen a period of three years as a reasonable and balanced intermediate option. That option falls between maintaining the student acknowledgment requirement for a single year (which is the minimum-length option and which would provide the least protection for students under the acknowledgment rule) and the lengthier five-year look-back period (which we will apply under § 668.602(c) for determining whether a GE program has failed a GE measure in two of the three most recent years when the GE measures were calculated). Since GE program eligibility is based on outcomes over three consecutive years in which metrics were calculated, the longer five-year period is apt for that purpose. We are not using the same duration set out in § 668.605 for GE student warnings and acknowledgments because the duration in § 668.605 is based on when an institution mitigates the risk of losing title IV, HEA eligibility for a GE program, which is not a factor for non-GE programs.

Changes: We have revised § 668.407(b)(3) to require acknowledgments annually until the program has passing D/E rates or three years after the institution was last notified that the program had failing D/E rates, whichever is earlier.

Comments: One commenter expressed appreciation for requiring subsequent acknowledgments for re-enrolling students after 12 months, as opposed to a 30-day window.

Discussion: We thank the commenter for their support. We believe that a 12-month window appropriately balances the need for subsequent acknowledgments for students who re-enroll well after providing an initial acknowledgment with the time and effort needed to secure the acknowledgment.

Changes: None.

Content of Acknowledgments and Warnings

Comments: A few commenters expressed concern about the Department's decision not to publish specific text for institutions to convey acknowledgment requirements to students. These commenters predicted that offering this discretion to institutions would risk a patchwork approach that could provide some students with more clarity about their debt prospects than others.

Discussion: We disagree with the commenters. While institutions may communicate acknowledgment requirements differently, the acknowledgment would be facilitated through the Department's program information website. The Department's website will present information to students in a clear and consistent way with the goal of ensuring students understand the risk of incurring high debt.

Changes: None.

Comments: One commenter noted that the Department makes GE program eligibility determinations, not institutions, and opined that the wording of student warnings regarding GE programs should convey that the Department has chosen to revoke eligibility based on its own criteria.

Discussion: We agree that the Department, rather than an institution, makes GE program eligibility determinations. We disagree, however, with the assertion that warnings to students enrolled in failing GE programs should convey that the Department has chosen to revoke eligibility based on its own criteria. Students must receive a warning when a GE program faces a potential loss of title IV, HEA eligibility after failing the D/E rates or EP measure, but that does not mean that a subsequent loss of eligibility is certain. The institution could take swift and appropriate action that would enable the program to pass the GE metrics in subsequent years, and the Department would encourage that outcome. Even if a program loses eligibility due to a subsequent failure of the relevant GE metric, it would be inaccurate to characterize that loss of eligibility as a choice on the part of the Department. As with other metrics that can result in the loss of title IV, HEA eligibility, such as failure to achieve acceptable cohort default rates under subpart N of part 668 or failure to comply with 90–10 requirements at § 668.28, the loss of eligibility is a predictable and consistent consequence reflecting the institution's failure to meet an established standard, not a matter of the Department's discretion.

Changes: None.

Comments: One commenter expressed support for retaining the warnings provision to require information about the academic and financial options to continue education at the same institution; whether the institution would refund tuition and fees; and whether students can transfer credits earned to another institution through articulation agreements or a teach-out.

Discussion: We thank the commenter for their support and will retain these components of the student warnings for GE programs.

Changes: None.

Burden of Acknowledgments and Warnings

Comments: A few commenters opined that the proposed requirement in the financial value transparency framework for students to acknowledge having seen information about a high-debt-burden program prior to disbursement of title IV, HEA funds resembles the Department's earlier efforts with the Annual Student Loan Acknowledgment (ASLA). These commenters suggested that, similar to the ASLA, the proposed acknowledgment requirements should be optional rather than required because of the burden to students and potential delays to title IV, HEA disbursements.

Discussion: The Department disagrees with this suggestion because the ASLA requirements serve a different purpose than the acknowledgment requirements of this rule. The Annual Student Loan Acknowledgment provides students an annual reminder of their individually accrued student debt amounts and expected repayment obligations, to enhance debt awareness and encourage students to limit borrowing. The acknowledgment requirements in the rule are targeted towards prospective students considering enrollment in a program that does not lead to an undergraduate degree that leaves students with a high debt-burden (§ 668.407), and current and prospective students of a GE program at risk of a loss of title IV, HEA eligibility (§ 668.605) because of failing either the EP or D/E measures. These acknowledgment requirements are intended to provide timely information to assist students in making informed decisions about whether to enroll or continue in the program and is targeted only to students enrolled or considering enrollment in programs where the Department has identified concerns with financial value. We believe that making this acknowledgment optional would result in students not viewing and benefiting from the information.

Changes: None.

Comments: A few commenters opined that requirements that institutions directly deliver GE warnings to students, and that students acknowledge having seen the information, would be inefficient and burdensome to students and institutions.

Discussion: While we are sensitive to the fiscal and logistical needs of institutions, we maintain that any burden on institutions to meet the warning and acknowledgment requirements is outweighed by the benefits of the debt and earnings outcomes information to students in making better informed enrollment and borrowing decisions. The Department will clearly notify institutions about any programs for which warnings or acknowledgments will be required. Although, as noted above, we offer institutions flexibility to tailor communications about acknowledgment requirements in a manner that best fits the needs of their students, the required text for warning notices for GE programs will be provided to institutions. We therefore expect that the burden to institutions in administering the warning and acknowledgment requirements to be manageable.

Changes: None.

Comments: Another commenter noted that for non-GE programs, it would be difficult to identify which students require acknowledgments, as students may initially be in an undeclared major, may enroll in multiple majors, or may change majors mid-term or mid-year.

Discussion: We acknowledge that it may seem unclear whether acknowledgment requirements would apply in the situations noted by the commenter. For this reason, as discussed above, we will limit the acknowledgment requirements of § 668.407 to eligible programs that do not lead to an undergraduate degree. We believe this change will better target the acknowledgment requirements to programs to which students tend to directly apply, and should eliminate most of the situations identified by the commenter including for undeclared majors, as an undeclared major would be within the undergraduate degree program for which an acknowledgment would not be required. Our analysis shows that high-debt-burden programs are relatively rare among certificate programs and graduate degree programs outside the proprietary sector, so we believe the impacts of this change on students will be minimal. To be clear the warnings and acknowledgment requirements in § 668.605 apply to all GE programs. Based on the Department's data and experience, it is extremely rare for students to enter such programs without a declared program major.

Students enrolled in multiple majors that do not lead to an undergraduate degree will complete acknowledgments for each program for which acknowledgment requirements would otherwise apply. For changes of program, acknowledgment requirements will begin when the student changes to a program for which acknowledgments are required. The Department intends to provide further sub-regulatory guidance and training prior to the effective date of the acknowledgment requirements.

Changes: None.

Comments: One commenter indicated that it would be burdensome and resource-intensive to require institutions to affirmatively provide students with transfer information in GE warnings and suggested that the Department instead only require institutions to provide a person for students to contact for questions about transfer eligibility.

Discussion: We do not agree that the requirement to provide transfer-related information to students in GE warnings is overly burdensome. The GE warning provisions generally require institutions to notify students about the transferability of credit to other programs offered by that institution. These warning provisions do not broadly require institutions to confirm the transferability of credit to other institutions, except in the case of an established articulation agreement or teach-out plan. We believe it is reasonable to expect an institution to be well aware of its own policies regarding transfers of credit amongst its own programs, and to communicate that information to students when required in a GE warning. It is equally reasonable to expect an institution to understand and communicate details about the transferability of credit in an established articulation or teach-out plan to which the institution is a party. With regard to the commenter's suggestion that the Department instead only require an institution to provide access to a person who students may contact with questions about transfer eligibility, we expect that institutions would already provide access to such a resource under the administrative capability requirements at § 668.16(h), as such information would comprise conditions that may alter the student's aid package.

Changes: None.

Timing of Warnings

Comments: One commenter claimed that the requirement to provide warnings to prospective GE students who have contacted or been contacted by an institution on a single occasion is premature, as there is no indication that a prospective student is seriously considering enrolling in the program at such an early point. Instead, this commenter suggested that the Department change the proposed requirement so that, instead of requiring warnings at the first contact about the program, warnings would be provided before the student signs an enrollment agreement or makes a financial commitment to the institution, consistent with the timing of the requirement at proposed § 668.43(d)(3) to provide information about the Department's program information website. This commenter also argued that a requirement to provide warnings any time before the GE program loses eligibility is premature, because changes made by the institution to the program or changes in external forces such as the labor market could cause the program to pass the D/E rates and EP measure and remain eligible.

Discussion: We do not agree that a requirement for an institution to provide a GE warning to prospective students who have initially contacted or been contacted by an institution is premature, nor do we agree that it would be more appropriate to provide the GE warning before the student signs an enrollment agreement or makes a financial commitment to the institution. We believe it is important that prospective students have this critical program information early in the decision-making process, when students may be comparing many institutions and programs, so that students have the benefit of understanding the debt and earnings risks of the GE program before investing significant time into investigating it.

Additionally, we disagree that a requirement to provide GE warnings any time before the GE program loses eligibility is premature. A GE program that has failed the D/E rates or EP measure is at risk for loss of title IV, HEA eligibility. Such a loss of eligibility would significantly impact students, who may be unable to complete their program of study and may need to transfer to another program or institution. Given the seriousness of these consequences to students, we believe it is imperative that students are alerted without delay and provided information to better inform their decision making.

Changes: None.

Comments: One commenter recommended that we should extend the deadline to provide warnings to enrolled students from 30 to 60 days after the date of the notice of determination, to provide institutions the time necessary to identify the appropriate students and accurately issue the warnings, while still allowing institutions to perform other necessary functions.

Discussion: We believe that 30 days from the date the Department issues a notice of determination that a GE program has failed the D/E rates or EP measure is a reasonable period of time for institutions to identify and distribute warnings to students enrolled in that GE program. We note that institutions should generally be well aware of which students are enrolled in each of the institution's programs. The Department further notes that the administrative capability regulations at § 668.16(b)(2) require an institution to use an adequate number of qualified staff to administer the title IV, HEA programs. The Department considers those requirements to include the distribution of required GE warnings to students. Moreover, § 668.16(b)(3) requires institutions to have a system in place to communicate to the financial aid administrator all information maintained by any institutional office that impacts students' title IV, HEA eligibility, including information about which students are enrolled in a particular program of study.

Changes: None.

Cooling-Off Period After Warnings

Comments: One commenter expressed support for the three-day cooling-off period after institutions deliver GE warnings to students, as prescribed in § 668.407(f)(2). The commenter encouraged the Department to consider additional guidance concerning the type of communication allowed between the institution and the student during the cooling-off period, such as stipulating that only students can initiate contact with the institution or communication from the institution may only occur via email.

Discussion: We thank the commenter for their support, and we appreciate the suggestion to provide additional guidance on allowable types of communication during the cooling-off period. Although we do not believe that this level of specificity is required in the regulation, we expect to provide additional sub-regulatory guidance and training prior to the effective date of the rule.

Changes: None.

Comments: One commenter supported the Department's decision not to consider a student acknowledgment or GE warning as evidence against a borrower's loan discharge application, but expressed concern that institutions could exploit the warnings and acknowledgment requirements to try to insulate themselves from legal liability for misconduct and recommended that the Department include language providing that neither the warnings nor the acknowledgments can be used by an institution as a defense to deceptive practices claims brought by students or government agencies in administrative or judicial proceedings.

Discussion: The Department thanks the commenter for their support. While we share the commenter's concern, we are not changing the regulatory language because we believe that categorically limiting the defenses institutions can raise in the types of litigation noted by the commenter would extend beyond the scope of the Department's authority.

Changes: None.

Alternative Languages for Warnings

Comments: Several commenters opined that the requirement in § 668.605(d) to deliver warnings in alternative languages is overly vague, would be burdensome for institutions to administer, and could result in discrimination claims. Commenters suggested that the Department produce a template format and content that can be used unilaterally for consistency across institutions; specify the minimum required languages for translation; only require that warnings be available in English and in any other language in which the program offers instruction; or allow the warning to be posted as a disclaimer on admissions and enrollment materials.

Discussion: The Department disagrees that that the requirement to deliver GE warnings in alternative languages is overly vague, burdensome, or would result in discrimination claims. The Department expects an institution to be reasonably aware if it admits and enrolls students with limited proficiency in English and expects institutions to provide required GE warnings in a language relevant to the student. Translation tools and services are available to institutions to aid them in meeting this requirement. We believe that a warning template would be of limited use given the variety of potential information related to transferability of credit, written arrangements, and teach- outs, and we further note that the regulation provides a helpful framework from which to craft the relevant GE warning language. Specifying the particular languages required for translation or only requiring that GE warnings be available in English and in the languages in which the program offers instruction would exclude some students from benefiting from content of the GE warnings.

The Department disagrees with the suggestion to allow the GE warning to merely be posted as a general disclaimer on admissions and enrollment materials. We want students to view any required GE warnings and have the opportunity to act upon the information. The timing and manner of information delivery can greatly affect whether the information is received and understood, such that audiences may use the information in their decisions. We believe the GE warning must be distributed directly to students, not provided as a general disclaimer. As discussed further below, the information at issue is critical for students when a GE program is at risk of losing eligibility to participate in title IV, HEA.

Changes: None.

The First Amendment and Warnings

Comments: A few commenters argued that a required warning under § 668.605 of the GE accountability framework, particularly a warning rule using prescribed language, may constitute compelled speech that may violate an institution's constitutional rights under the First Amendment. A few such commenters noted that the First Amendment extends to people and corporations alike, covers all types of lawful speech including factual disclosures, and protects the right to refrain from speaking at all. One commenter further opined that to survive legal scrutiny, a regulation must be narrowly tailored to promote a compelling government interest and suggested that the Department already has a narrowly tailored solution in the College Scorecard, which includes average student debt and average earnings. Another commenter posited that the warning provisions would require institutions to parrot the Department's determination of the program's value without regard for the reliability of the underlying data or the non-pecuniary value of the program to students.

Discussion: The Department disagrees. The relevant provisions of the GE program accountability framework will provide students with a straightforward, purely factual, and uncontroversial warning when there is a serious risk that title IV, HEA aid will not be available at a given GE program. These provisions will require institutions that operate these at-risk GE programs to deliver a one-time warning to students with whom they already have a relationship, through enrollment or outreach and contact as prospective students.

In § 668.2 of these rules, “prospective student” is defined as an individual who has contacted an eligible institution for the purpose of requesting information about enrolling in a program or who has been contacted directly by the institution or by a third party on behalf of the institution about enrolling in a program. And “student” is defined, for the purposes of subparts Q and S and of § 668.43(d), as an individual who received title IV, HEA program funds for enrolling in the program.

As discussed above, the unavailability of title IV, HEA assistance is an undeniably serious consequence for students who are enrolled in or considering whether to enroll in a GE program. In addition, the Department has an overwhelming interest in enabling informed student decisions before government resources are directed toward at-risk programs. And the communicative burden on institutions will be minor at worst, given that they will remain free to deliver their own messages to students. A responsible institution would strive to warn students of the potential loss of eligibility in these circumstances, and the rule aims to require participating institutions to act responsibly. The GE warning rule is an entirely reasonable and constitutional requirement for institutions that benefit from title IV, HEA aid to students. Such rules are consistent with the First Amendment's guarantee of the freedom of speech.

The justifications for a warning are especially strong in these circumstances—situations involving the need to inform students about the risk to student aid before Federal funds are used in programs that are supposed to train and prepare students for gainful employment in a recognized occupation or profession—not education of all kinds. In commercial speech cases, courts have asked whether a regulation directly advances a significant government interest and is a reasonable fit between means and ends. Courts also have recognized broader government authority to require disclosure of accurate information about services and products, allowing for the preservation of various consumer protection laws. Furthermore, the GE warning rule involves participants in Federal funding programs, rather than the regulation of private parties who are not seeking government support. Whatever the applicable test, the GE warning rule will satisfy it.

See, for example, Central Hudson Gas & Elec. Corp. v. Public Serv. Comm'n of N.Y., 447 U.S. 557, 564 (1980); Bd. of Trustees of State Univ. of N.Y. v. Fox, 492 U.S. 469, 480 (1989) (stating that the test involves reasonable fit).

See, for example, Zauderer v. Office of Disciplinary Couns. of Supreme Ct. of Ohio, 471 U.S. 626, 651 (1985) (testing advertiser disclosure requirements for a reasonable relationship to a governmental interest in preventing deception, and for whether the requirements are unduly burdensome to speech); Milavetz, Gallop & Milavetz, P.A. v. United States, 559 U.S. 229, 259–53 (2010) (following Zauderer); Am. Hosp. Ass'n v. Azar, 983 F.3d 528, 540–42 (D.C. Cir. 2020) (same). Other First Amendment cases regarding disclosures are collected in note 165, and we further discuss the freedom of speech in that discussion of the Department's program information website.

See generally United States v. American Library Ass'n, 539 U.S. 194 (2003) (addressing Federal assistance for internet access and a condition on assistance involving internet filters); United States v. Aguilar, 515 U.S. 593, 606 (1995) (recognizing that private parties may voluntarily agree to assume an enforceable duty not to disclose information).

The Department's interests in informed student decisions and protection of tax-supported government resources are obviously important, and warnings will directly advance those interests. The rule applies to institutions that operate at-risk GE programs and that have established relationships with their enrolled students, and that have contact with prospective students. The Department understands the obvious threat to students and taxpayers when the former enroll in programs that turn out losing eligibility under title IV, HEA. But the Department does not have the advantages of institutions in their ability to deliver necessary warnings to both enrolled and prospective students, who are in the process of making decisions about higher education. And institutions should understand why students need to obtain the information at issue. Given the stakes for students and taxpayers, the College Scorecard does not provide a direct warning to students and, therefore, is not an adequate substitute for warnings from participating institutions that their GE programs are at risk.

In addition, the GE warning rule is carefully tailored to the Department's interests, while the burden on participating institutions' speech will be minimal. As described in § 668.605(a) and (b), the warning is a one-time obligation, with a narrow exception for students who seek to enroll 12 months after a warning. Furthermore, § 668.605(e) and (f) allows institution to choose among more than one method of delivering the warning, including an email or other electronic means. It is true that, when a warning is delivered in a written form, § 668.605(e) and (f) indicates that the warning must be separate from other communications from the institution. That provision advances the Department's interests in an effectively communicated warning and does not prohibit other messages from the institution such as a separate email or electronic communication. In this rule, moreover, the Department chose not to ask institutions to deliver continuous warnings such as by posting messages on their own websites or incorporating warnings into their promotional materials. In our judgment, the warning rule in § 668.605 is necessary and adequate based on the Department's experience and available information. As a consequence, the burden on institutions will be minimized.

See CTIA—The Wireless Ass'n v. City of Berkeley, 928 F.3d 832, 849 (9th Cir. 2019) (observing that the regulation at issue permitted retailers to add information if the information was distinct).

Other features of this GE warning rule likewise moderate any burden on participating institutions' preferred messages. In § 668.605(c), the Department selected carefully a list of factual, objective, and commonsense items to include in warnings to students when their GE programs are at risk: notification that the GE program has not passed the Department's standards, and that the program could lose access to Federal grants and loans when the next round of results are available; a link to the Department's program information website along with notification that the student must acknowledge having viewed the warning through the Department's website before disbursement of title IV, HEA funds; and, in the event that the program does lose eligibility to participate in the title IV, HEA programs, a description of options within the institution, an indication of what the institution plans to do regarding teaching and refunds, and an explanation of whether students may transfer credits to other institutions. Each of these items is independently valuable. Notably, however, the rules do not require participating institutions to adopt the Department's view on program value, as one commenter feared.

Certain details for warnings will be specified in a future notice in the Federal Register , consistent with the terms of § 668.605. But the rule clearly does not require any script that would compel any participating institution to misrepresent its views about what is a high-value program, low-value program, or any other topic. The Department does want students to be warned effectively and accurately but respects the legitimate interests of participating institutions to maintain their own views and to communicate those views. We will avoid language in the GE warnings that may be unduly controversial, misleading, or distracting. As we discuss elsewhere in this document, institutions can correct errors in certain calculations to increase the accuracy of the outcome measures. That process is part of the Department's effort to make available factual information about programs that is readily comparable and easily understood by students and the general public. At the same time, institutions will remain free to hold and express their own views on which if any program metrics are best through their own channels of communication.

Contrast the warning that was criticized in a dictum in Ass'n of Priv. Colleges & Universities v. Duncan, 870 F. Supp. 2d 133, 154 n.7 (D.D.C. 2012), which expressed concern about a “statement that every student in a program `should expect to have difficulty repaying his or her student loans.' ” This rule does not require such a message.

This is not the first instance in which regulations have required individual, direct communication by institutions with consumers about Federal aid. Apart from the 2014 Prior Rule, section 454(a)(2) of the HEA authorizes the Department to require institutions to make disclosures of information about Direct Loans, and Direct Loan regulations require detailed explanations of terms and conditions that apply to borrowing and repaying Direct Loans. The institution must provide this information in loan counseling given to every new Direct Loan borrower in an in-person entrance counseling session, on a separate form that must be signed and returned to the institution by the borrower, or by online or interactive electronic delivery with the borrower acknowledging receipt of the message. Like the GE warning rule adopted here, under the loan counseling rules, institutions must provide warnings directly to the affected consumers.

Although we thoroughly considered the commenters' concerns regarding the First Amendment, we are convinced that the final regulations are constitutional. Additionally, we took into account a range of concerns expressed by commenters regarding disclosures and warnings, along with the Government interests in providing students an effective warning regarding a program's performance and eligibility status. Our judgment, in sum, is that the GE warning rule is both sound policy and constitutional.

Finally, the Department disagrees with a commenter's suggestion that the final rules are impermissible because any regulation of GE programs is content-based and subject to strict judicial scrutiny. The commenter's source of concern appears to be the GE statutes that create the distinctions between types of institutions and programs that prepare students for gainful employment. Regardless, we reiterate that the D/E rates and EP metrics focus on completer outcomes rather than program curriculum. We also observe that institutions have the option of not participating in title IV, HEA student aid programs. Title IV offers eligible institutions the option to participate in student aid programs. It does not compel institutions to prefer one curriculum over another.

Changes: None.

Students Switching Programs

Comments: A few commenters recommended that the Department exempt from the acknowledgment requirements in § 668.407 all students who transfer from one program to another within an institution or who have not declared a major. For undeclared majors, a few commenters suggested that the acknowledgment requirement apply once the student selects a major.

A few other commenters suggested instead that the Department address program transfers and undeclared majors by listing all of a school's programs on the program information website, with failing programs in the credential level of the student at the top of the list, and clearly marking all programs as passing or failing, or noting where no information is available. One commenter added that we could use the College Scorecard for this purpose, provided it included the relevant information.

Discussion: As noted above, the student acknowledgment requirements in § 668.407 are aimed at providing information to prospective students before they enter into enrollment agreements with an institution. While we agree with commenters' arguments that this information would be valuable to already enrolled students who are considering changing their major, we do not believe the benefit of requiring acknowledgments to such students would outweigh the administrative burden of requiring students to provide such information prior to switching or declaring majors. Students' educational pathways are complex, and they may form their preferences about an ultimate field of study course-by-course or class-by-class as they progress. There may therefore be no obvious time to trigger a requirement that they view the program information website, and students may effectively have already made their decisions prior to being prompted to view the information. Accordingly, the Department believes it is best to rely on publicizing the availability of the information to all students to increase the odds students will have the relevant information available to them to inform choices in this situation. In this connection, we may consider listing links to information about all of a school's programs on the Department's program information website, with clear designations of each program's status under the financial value transparency metrics.

Changes: None.

Comments: One commenter urged the Department to ensure that transfer students from one institution to another acknowledge the information before receiving Federal aid for the receiving program.

Discussion: As noted above, transfer students to an institution are considered prospective students and so the acknowledgment requirements in § 668.407 apply.

Changes: None.

Impact on Loan Discharges

Comments: A few commenters recommended that we omit proposed §§ 668.407(d) and 668.605(h), which provide that the Department will not consider a student acknowledgment or GE warning as evidence against a borrower's loan discharge application. These commenters also opined that the proposed acknowledgment and warning provisions are underly nuanced and that the Department could not rule out in all cases the possibility that a warning or acknowledgment would be irrelevant. Additionally, the commenters noted that a final rule adopted by the Department in 2022 contained a provision requiring the Department to use all information in its possession when evaluating borrower defense claims. The commenters contended we should consider a warning or acknowledgment to constitute other relevant information about which the Department is aware.

87 FR 65904 (Nov. 1, 2022).

Discussion: The Department disagrees with the suggestion to omit §§ 668.407(d) and 668.605(h). Under the borrower defense provisions at § 685.401(b), actionable circumstances for a borrower defense claim include a substantial misrepresentation; a substantial omission of fact; an institution's failure to perform its contractual obligations to the student; aggressive and deceptive recruitment; or a State or Federal judgment against the institution, including an institution's termination or denial of recertification by the Department. The student acknowledgments provided under the financial value transparency framework regarding D/E rates, as well as the warnings and acknowledgments under the GE program accountability framework regarding D/E rates and the EP measure, pertain specifically to a program's outcomes that are provided for students and their family. The course of dealings and information shared between an institution and its students remain the focus of whether a student qualifies for a borrower defense discharge. The borrower defense regulations address the consideration of the relevant facts related to the borrower defense claim. A student's acknowledgment of a program's failing D/E rates would be one consideration but would not be dispositive. We anticipate that in acknowledging having viewed the financial value information on the Department's website, borrowers will consider this information in the context of other information they may receive, including from institutions.

Changes: We have revised §§ 668.407(d) and 668.605(h) to specify that the provision of an acknowledgement or warning will not be considered “dispositive” evidence in any borrower defense claim.

Comments: One commenter supported the Department's decision not to consider a student acknowledgment or GE warning as evidence against a borrower's loan discharge application, but expressed concern that institutions could exploit the warnings and acknowledgment requirements to try to insulate themselves from legal liability for misconduct and recommended that the Department include language providing that neither the warnings nor the acknowledgments can be used by an institution as a defense to deceptive practices claims brought by students or government agencies in administrative or judicial proceedings.

Discussion: The Department thanks the commenter for their support. While we share the commenter's concern, we are not changing the regulatory language because we believe that categorically limiting the defenses institutions can raise in the types of litigation noted by the commenter would extend beyond the scope of the Department's authority.

Changes: None.

Certification Requirements for GE Programs—§ 668.604

Comments: One commenter expressed concern that the timing of the requirement to certify GE programs may be overly burdensome for institutions, given the projected timing for institutional reporting and notification of D/E rates and EP measures. This commenter requested that the Department extend the certification deadline beyond December 31, 2024, to provide a more generous transition period.

Discussion: We do not anticipate the initial transitional certification requirements for GE programs to be particularly burdensome. Even institutions with many GE programs would generally submit a single transitional certification, likely through eligcert.ed.gov or its successor system. While some analysis is required on the part of institutions to know whether each GE program meets any applicable State licensure or accreditation requirements, the Department notes that, even in the absence of the GE certification requirements, institutions should be knowledgeable about the programs they offer. We reasonably expect institutions to keep their programs current and compliant with State and accrediting agency policies and requirements.

The December 31, 2024, deadline for GE program certification is entirely reasonable, especially given our decision to extend the transitional data reporting option to GE programs, as discussed under “Reporting” above, which already provides a more generous transition period.

Changes: None.

Ineligible GE Programs

Impact of Ineligibility

Comments: Two commenters voiced concern that a program's loss of eligibility to participate in the title IV, HEA programs will force many students to withdraw. According to these commenters, some students may abandon their education, others may struggle to find another institution willing to accept them, and others may have to retake some of their classes or restart their clinicals, thereby devaluing the taxpayer's investment in the student's education.

Another commenter discussed the lesser options for education in their field if their institution were to close, commenting that community colleges offer less in-depth programs in their field of study, located in areas with more limited housing options.

Discussion: As we illustrate in the RIA, most students in programs projected to fail the accountability metrics have alternatives with better student outcomes available to them. In most cases, then, where programs lose eligibility, we expect most students to reenroll in programs that result in higher earnings, less debt, or both. We acknowledge that a program's ineligibility may present some obstacles to some students' ability to complete their programs, but believe that these obstacles do not justify continuing to direct further taxpayer funds to programs that fail to meet standards. By providing prompt notice and an overview of options in student warnings, the GE framework will give students options to take action before sinking too much of their time, efforts, funds, and limited title IV, HEA aid into programs that do not lead to adequate student outcomes.

Changes: None.

Comments: Many commenters raised concerns about how the proposed rules would have disproportionate effects on cosmetology and massage therapy schools. Commenters said the rules would lead to the widespread closure of these schools. Commenters noted that many of these schools are also small businesses. Commenters further opined that these negative effects would be felt not just by supposedly bad cosmetology schools.

Commenters then proceeded to raise concerns about multiple follow-on negative effects from these closures. They raised the possibility of negative effects on students, including reduced opportunities for women, people of color, immigrants, persons with disabilities, and other groups that are traditionally underrepresented in postsecondary education. Commenters also raised concerns about students losing access to Federal aid in the middle of programs, which would discourage continued enrollment.

Commenters also argued that community colleges and high schools would not be able to accommodate the influx of students interested in attending cosmetology programs after many private cosmetology schools closed. They also claimed schools would not be able to meet the demand for massage therapists.

Commenters further cited the effects of closure on unemployment and local communities. Commenters particularly emphasized the effects of businesses hiring graduates of programs, and the inability to fill in-demand jobs if programs and institutions close. They also said unemployment would increase from students who would otherwise have found jobs after attending cosmetology schools. Others claimed thousands of employees from these schools would lose their jobs.

Commenters also expressed concern that closures would have negative effects on health, safety, and sanitary conditions as more services would be provided in homes and in unlicensed or uninspected facilities.

Discussion: We disagree with the commenters about the likelihood that closures would be widespread, as well as the negative effects that would come from any closures that might occur.

Regarding the extent of closures, commenters did not consider the large numbers of students attending cosmetology schools but not receiving Federal aid under title IV, HEA, as well as the significant number of cosmetology schools that do not participate in title IV at all. For example, across all institutions that participate in the title IV, HEA programs that award cosmetology certificate programs, we estimate the average institution awarded about 38 percent of its credentials to students who did not receive any Federal aid. Moreover, a review of licensure examination results from California suggests that only about one-third of schools with students taking the cosmetology licensure exam participate in the title IV, HEA programs. In a similar study cited in the RIA, Cellini and Onwukwe find the analogous share in Texas is about 14 percent. The same data used in these studies, along with more rigorous academic studies, suggest that loss of title IV, HEA eligibility among cosmetology schools results in schools adjusting their tuition downward (suggesting that students may not face higher costs of attendance despite losing access to title IV aid), and that their graduates still pass licensure exams at similar rates. These findings suggest that commenters' assertions that the loss of Federal aid eligibility would automatically lead to closure and a reduction of opportunities for students may not be correct. There is a difference between an institution losing access to title IV, HEA funds and closing—a distinction that is particularly evident in the cosmetology space.

This analysis compares data on the total number of awards granted during 2016 and 2017 reported by institutions in the Integrated Postsecondary Education Data System (IPEDS), which covers both federally aided students and not-federally aided students to the number of graduates in such programs reported to the National Student Loan Data System—covering only federally aided students.

California makes these data available at this website: https://www.barbercosmo.ca.gov/schools/schls_rslts.shtml .

Cellini, S.R. & Onwukwe, B. (2022). Cosmetology Schools Everywhere. Most Cosmetology Schools Exist Outside of the Federal Student Aid System. Postsecondary Equity & Economics Research Project working paper, August 2022.

See, for example, Cellini, S.R., & Goldin, C. (2014). Does Federal student aid raise tuition? New evidence on for-profit colleges. American Economic Journal: Economic Policy, 6(4), 174–206.

We also emphasize that the Federal financial aid programs are entitlements for students, not institutions of higher education. The GE accountability framework is designed to protect both Federal investment and student investment in programs of higher education. Students pursuing higher education are not just investing taxpayer and personal funds to attend a GE program, but are also incurring opportunity costs. The GE eligibility rules that we adopt here do not assess whether a program or a school is in some general sense “good” or “bad,” which are labels the commenters did not define. More concretely, a student directing their limited title IV, HEA aid to a GE program that does not prepare them for gainful employment in a recognized occupation has lost the opportunity to use those funds to attend a different educational program that would better serve their goals. The D/E rates and earnings premium measures provide objective and evidence-based metrics to direct Federal funds to programs that do not saddle students with more debt than they can afford or leave them with earnings prospects no better than they would have had with only a high school diploma.

We also disagree with the arguments from commenters about the effects of closures. First, as we note above, there is a possibility of enrollment moving into programs that are still eligible for title IV, HEA funds or those that operate solely on the private market. Second, commenters did not consider the potential responses from programs that do pass the GE program accountability framework. For instance, a passing program may choose to expand its enrollment and meet any excess demand. Students may also choose to enroll in different types of programs, which are likely to provide them better economic benefits since passing programs generally have a combination of higher earnings and lower debt. The Department thus believes commenters overstate the potential loss of postsecondary opportunities.

We also disagree with comments about the negative effects of closures on particular groups of students, such as women and students of color. The Department has already provided an extensive discussion of the effects of these rules on women and students of color, which can be found in the “Demographics and Outcomes” section of this final rule. Many of the other categories identified by commenters are not ones where there is any centralized data collection to identify them, such that there is no analysis of these populations that could be conducted. But we do not see a persuasive reason why the analysis conducted on women and students of color would not capture the largest demographic groups enrolling in cosmetology, massage therapy, and other beauty school programs. Given that cosmetology schools represent one of the largest areas of student enrollment in GE programs, we believe that analysis properly captures the consideration of the effects on these groups of students at beauty schools.

We also disagree with commenters' arguments about the effects of closure on local communities and businesses. The Department does not believe that a shortage of programs of study within a field is adequate justification for directing title IV, HEA funds to programs that do not lead to adequate student outcomes. If there is a shortage of eligible programs in a high-demand field, this provides an opening for institutions to expand the capacity of existing high-quality programs or to create new high-quality programs to meet that need. Moreover, employers also have tools available to them if they have jobs they cannot fill, such as increasing wages and benefits. Given that the beauty industry is predicated on charging clients for their services, they could also choose to either reduce their profit margins or pass some of these increased costs on to their clientele. We also reiterate that commenters have not considered the presence of a significant number of schools in these areas that do not participate in the title IV, HEA programs.

Finally, regarding concerns about the effects of the rules on health and safety, we note that cosmetologist licensure and facility inspection are areas regulated and enforced at the State and local levels, not at the Federal level. The Department trusts the appropriate State and local entities to maintain appropriate standards for health and safety within their jurisdiction.

Changes: None.

Comments: A few commenters mentioned the potential impact of school closures contributing to a shortage of practicing veterinarians and the competitive nature of veterinary school seats, contending that the loss of program eligibility would reduce the number of future veterinarians. Other commenters suggested that the D/E metric would result in the closure of numerous Doctor of Veterinary Medicine programs.

Discussion: While a determination of ineligibility for title IV, HEA aid may lead to closure of programs in fields of high demand that do not produce adequate student outcomes, we believe that this does not justify continuing to steer students and funds to programs with inadequate student outcomes. It is also possible that the need for additional training opportunities in a particular field may lead to the establishment of new programs or the expansion of existing programs that lead to better student outcomes.

Changes: None.

Comments: Some commenters raised concerns about how the GE accountability framework and program ineligibility stemming from it could create challenges for businesses trying to hire in the allied health, business, and nursing spaces.

Discussion: We disagree with the commenters. Regarding nursing and business, we do not see evidence of high rates of ineligibility. As shown in Table 4.18, these two programs have the smallest number of students in failing programs out of all the programs with the largest number of failures. But for these two areas as well as allied health, we do not think a shortage of programs of study within a field is adequate justification for directing title IV, HEA funds to programs that do not lead to adequate student outcomes. If there is a shortage of programs and excess demand by employers, then institutions would have an incentive to expand the capacity of passing programs or employers would need to raise wages. Either solution could help expand the number of offerings to what is needed.

Changes: None.

Comments: One commenter stated that cosmetology licensure requirements provide vital consumer protection and make any loss of funding to cosmetology programs unnecessary.

Discussion: The commenter conflates the protection clients of cosmetology program graduates receive from licensure requirements with the protection the Department seeks to establish for students themselves under the GE accountability framework. These are not equivalent and are not even protections for the same populations. The Department believes that both provide important protections.

Changes: None.

Alternatives to Ineligibility

Comments: One commenter suggested that title IV, HEA eligibility should be grandfathered for students who were already enrolled in a program at the time of its first fail rating. Two other commenters similarly suggested allowing students already enrolled in a program losing eligibility for title IV, HEA aid to continue receiving aid through completion of the program if they decided to continue with full knowledge that the program is failing. Many commenters voiced a belief that students already enrolled in a program that loses eligibility should be able to choose to continue in the program knowing the program's failing rates and continue to access Pell funds to complete the program since loans come with negative consequences if default occurs, while Pell Grants come without repayment obligations. One commenter suggested allowing students to continue to borrow title IV, HEA loans for programs that would lose eligibility, adjusting loan limits for those programs downward to amounts that would bring D/E rates to within amounts that would pass.

Discussion: More harm can come to students from continuing in a failing program than merely accruing additional loan debt. Students are limited in the amount of time for which they can receive Pell Grants. Continuing in a failing program and receiving a Pell Grant would exhaust some of their eligibility. Continuing in a program that produces inadequate student outcomes will also consume student time and effort. This invested time comes with more readily apparent costs, such as increased costs for childcare or lost opportunities for paid employment, but also with the loss of substitutes—with the time invested in a failing program, the student could have been pursuing a course of study that would have better advanced their career.

It is also possible that if the institution became ineligible to participate in the Direct Loan program, but Pell funding continued, students would merely replace their Federal student loans with private loans. Continuing in a failing program without Direct Loans would leave students in a worse position than if we took no action.

It would be mathematically unworkable to lower limits on Direct Loans to amounts that would cause a failing program to pass D/E rates. D/E rates are calculated across a student's entire enrollment in a program and different students may take a different number of years to complete a program, so annual borrowing could not be precisely adjusted. Additionally, since students could potentially replace lowered Direct Loan amounts with private loan debt, keeping their debt amount constant, it would be impossible to precisely lower D/E rates by lowering limits on title IV, HEA borrowing alone.

Changes: None.

Comments: One commenter suggested that the GE accountability metrics be paired with further reporting requirements but not tied to title IV, HEA eligibility. Another commenter recommended removing all references to the GE rule in the context of financial responsibility, administrative capability, and certification procedures, broadening the GE rule for uniform application across all program types.

Discussion: As further discussed in this document and in the NPRM, we believe that for GE programs, further steps beyond information provisions are necessary and appropriate. The Department intends to integrate the GE accountability metrics into all relevant aspects of Federal student aid administration covered by the final rule.

88 FR 32342.

Changes: None.

Timeframe for Warnings and Ineligibility

Comments: Several commenters suggested extending the timeframe for loss of title IV, HEA eligibility to failing in three out of any four consecutive award years for which metrics are calculated, with one of the commenters positing that allowing an additional year would limit loss of eligibility to programs truly demonstrating a pattern of poor performance versus merely experiencing a market shift or other unforeseen event. This commenter additionally suggested granting waiver authority to the Secretary for any program training students to be essential workers, for programs training students to enter professions experiencing critical national job shortages, or as a result of a national, State, or local emergency declared by the appropriate authority. Another commenter similarly suggested changing the provision for loss of eligibility to three consecutive fails.

Discussion: In the balance between gathering meaningful data and acting quickly enough to protect students and taxpayers from failing programs, an unavoidable amount of delay is already added to the rate and threshold calculation process for the time it takes for the data used in calculations to become available. The Department believes that allowing an additional year of failing GE metrics before a program becomes ineligible for title IV, HEA program participation would add too much risk for students in failing GE programs. We further note that the accountability framework already accounts for sudden market shifts in that a GE program will not lose eligibility based on failing the D/E rates or EP measure for a single year. Waiving ineligibility for GE programs designed to train students to be essential workers or to work in fields experiencing labor shortages could especially fall short of protecting students—if program graduates do not have sufficient earnings when the field is at peak demand, those students will be at an even greater disadvantage if demand goes down.

Changes: None.

Comments: One commenter mentioned that closures with little notice to students are already problematic. This commenter voiced concern that the rule as proposed will cause still more schools to close within two years.

Discussion: Under the GE accountability framework, institutions are required to issue warnings when a GE program is at risk of becoming title IV, HEA ineligible based on the next calculation of D/E rates or earnings premium measure. This would occur if the GE program had a failing D/E rate within its last two rate calculations or if the program failed the earnings threshold within the last two measurements. We believe these warnings will provide students adequate notice and information to decide how they wish to proceed.

Changes: None.

Comments: One commenter opined that if a GE program did not have metrics calculated for two years, the programmatic eligibility clock should restart, citing that programs and their students are continually evolving and that most community college GE programs will be one year or shorter in length, making a cumulative evaluation period that could last up to four years not a reasonable period.

Discussion: The Department acknowledges that programs and student populations may evolve over time at any institution, but this does not negate the importance of using the best available data to hold programs accountable for student outcomes.

Changes: None.

Period of Ineligibility and Substantially Similar New Programs

Comments: Several commenters expressed the opinion that an institution voluntarily discontinuing a program should not be penalized if it produces failing rates in its final years. Two of the commenters did not think it made sense to employ the three-year block on title IV, HEA eligibility for new programs substantially similar to programs voluntarily discontinued either before or after D/E rates or earnings premium measures are issued but allow eligibility for re-established programs that are discontinued before the metrics go into effect. One of these commenters expressed that they understood the need to prevent schools from using voluntary discontinuation to evade consequences, but that they believed the same goals could be achieved by limiting the block to programs that already had at least one failing accountability metric. A few commenters expressed the belief that CIP codes sharing the first four digits varied too greatly to be substantially similar, citing examples from the allied health fields and the cosmetology and related personal grooming fields, and that use of the six-digit CIP level would be sufficient to prevent manipulation. One commenter stated that this approach is problematic for institutions that provide specialized instruction in a narrow field such as cosmetology. Another of these commenters believed that the 3-year period was arbitrary and that its use in the rule on cohort default rates was not sufficient justification. Another commenter believed that the rule as proposed will block an institution from winding down a program based on market changes and reintroducing an improved version for three years, even if the newer program is designed to be shorter, less expensive, and more attractive to employers.

Discussion: As one of the commenters noted, this provision is designed to prevent institutions from evading consequences for programs producing inadequate student outcomes by voluntarily discontinuing a program before it could lose eligibility based on D/E rates or the earnings premium. Along those same lines, the period of ineligibility for new programs with substantial similarity would prevent institutions from bringing back a program that is failing or at risk of failing under a similar CIP code with few changes. While 6-digit CIP codes within some 4-digit CIP categories may have some more variation than others, there are still sufficient common elements to programs within a 4-digit CIP category to raise concerns that an institution with one failing program within the category should wait and reassess elements such as program design and market demand before establishing a new eligible program within the same category. The Department considers three years to be an appropriate waiting period. The Department selected a three-year period of ineligibility because it most closely aligns with the ineligibility period associated with failing the Cohort Default Rate, which is the Department's longstanding primary outcomes-based accountability metric at the institutional level. Under those requirements, an institution that becomes ineligible for title IV, HEA support due to high default rates cannot reapply for approximately three award years.

Changes: None.

Comments: One commenter suggested not imposing the three-year period of ineligibility for programs that have lost eligibility and allowing schools to reintroduce their programs redesigned to meet GE standards.

Discussion: The Department believes that omitting the period of ineligibility would provide inadequate protection for students against a program being quickly re-established with the same elements that led to its loss of eligibility in the first place. Since it would require several years of more data before debt and earnings outcomes could be determined for the “new” program, this would subject student futures to an unacceptable level of risk.

Changes: None.

Comments: One commenter suggested disregarding any fail rating more than four years old, providing an illustrative example of how under the rule as proposed in § 668.602(c) and (e), a program only large enough to receive rates in certain years could have failing rates in years one and seven and maintain eligibility (since the older rate would be disregarded under § 668.602(c) because the program had four or more consecutive award years without rates), while if the program had a passing rate in the interval, with failing rates in years one and seven and a passing rate in year four, it would lose eligibility for failing in two of the three consecutive years for which rates were calculated.

Discussion: The Department thanks the commenter for pointing out the potential for this unintended consequence. The Department agrees that the situation described by the commenter is undesirable. This provision of the rule is meant to avoid using measures of program performance too far in the past to determine program eligibility.

Changes: In response, we have modified this provision in § 668.602(c) and (e) to state that in determining a program's eligibility, the Secretary will disregard any D/E or EP measure that was calculated more than five years prior.

Comments: One commenter voiced a concern that loss of title IV, HEA eligibility for massage therapy programs would have a ripple effect on the industry, requiring current massage therapists to take the time to train new entry-level students.

Discussion: The Department best serves students and taxpayers by regulating the use of title IV, HEA funds so they support students in attending programs that lead to adequate outcomes. If the occupational licensure structure in a State or locality permits a training path outside of institutions of higher education, that is beyond the Department's jurisdiction.

Changes: None.

Other Concerns Related to Program Ineligibility Under the GE Framework

Comments: One commenter expressed the opinion that it was unfair to make program eligibility determinations based on data from years preceding the effective date of the final rule.

Discussion: The HEA requirement that gainful employment programs prepare students for gainful employment in a recognized occupation predates any years for which data will be gathered for the GE accountability framework.

Changes: None.

Comments: One commenter expressed the opinion that these will be the strictest debt-to-earnings metrics to date, making it increasingly difficult for programs to remain eligible.

Discussion: The Department is committed to protecting student and taxpayer resources with strong accountability metrics and, as noted in the RIA, we expect that most programs will pass the D/E rates metric.

Changes: None.

Challenges, Hearings, and Appeals

Comments: One commenter supported the Department's proposal in § 668.603 to provide an opportunity for institutions to appeal a determination that a program fails the D/E test on the grounds that the Department made an error in calculating the institution's D/E ratio. The commenter offered that this provision provides important due process protections to institutions.

In contrast, many commenters objected to the Department's decision not to include review, challenge, and appeal opportunities in the proposed rule that were present in the 2014 Prior Rule, primarily on the grounds of due process and fairness. These commenters maintained that the Department cannot reasonably remove the eligibility of a program, potentially resulting in the closure of an institution, based on calculations derived from certain data without providing institutions a mechanism to review or challenge the data and offer other evidence, as well as appeal D/E and EP outcomes.

Referencing language from the preamble to the notice of proposed rulemaking for the 2014 Prior Rule, in which the Department stated that “[t]he proposed regulations are intended to provide institutions, in the interest of fairness and due process, with an adequate opportunity to challenge the completion, withdrawal, and repayment rates and median loan debt determined by the Department,” one commenter asserted that the Department is not adhering to its previously acknowledged standard of due process. That commenter, as well as others, noted that the 2014 Prior Rule afforded institutions the opportunity to review and correct the list of students (with the Secretary determining in consideration of evidence submitted, whether to accept those corrections), challenge the accuracy of the loan debt information that the Secretary used to calculate the median loan debt for the program, and file an alternate earnings appeal to request recalculation of a failing or “zone” program's most recent final D/E rates using earnings data obtained from an institutional survey or State-sponsored data system. These commenters objected that the proposed rule does not offer those provisions, allowing only for provision of the student list to institutions (assertedly without the opportunity for review or correction) and an appeal where the Secretary has initiated a termination action of program eligibility under subpart G of part 668 (Student Assistance General Provisions).

79 FR 16426, 16485 (Mar. 25, 2014).

Discussion: The Department thanks the commenter who wrote in support of the appeal provisions in § 668.603. At the same time, we disagree with the commenters who asserted that the Department must include the same opportunities for appeals and challenges as those contained in the 2014 Prior Rule to afford institutions due process or fairness. We do not believe the appeal procedures urged by the commenters are required by the Due Process Clause of the Fifth Amendment or any applicable principle of fairness.

The threshold question for procedural due process purposes is whether a person has been or will be deprived of a property interest protected by the U.S. Constitution. But institutions lack such a protected interest in continued eligibility to participate in Federal student aid programs. A unilateral expectation of benefits is insufficient, and institutions are neither promised nor led to believe that they will receive a continuing stream of Federal support without change in student aid rules. In the context of title IV, HEA and GE programs, institutions and programs must satisfy a number of requirements for eligibility beyond the GE metrics in this rule, including standards related to administrative capability and financial responsibility. Moreover, neither institutions nor programs are direct beneficiaries of title IV, HEA aid to students. With respect to the GE accountability metrics, what will be at issue is specific program-level eligibility for Government support, not whether the institution and the other educational programs it offers may continue to participate in the Federal student aid programs. That indirect relationship to the benefit further weakens claims that institutions have a legitimate entitlement to continuing support from the Federal Government under title IV, HEA.

See Bd. of Regents of State Colls. v. Roth, 408 U.S. 564, 569 (1972); see also Assoc. of Private Colleges and Universities v. Duncan, 870 F. Supp. 2d 133, 154 n.7 (D.D.C. 2012) (“Without a property right in their participation in Title IV programs, schools cannot press a Fifth Amendment challenge to the regulation of those programs.”).

See Ass'n of Accredited Cosmetology Sch. v. Alexander, 979 F.2d 859, 864 (D.C. Cir. 1992); Dumas v. Kipp, 90 F.3d 386, 392 (9th Cir. 1996); Ass'n of Proprietary Colleges. v. Duncan, 107 F. Supp. 3d 332, 348–52 (S.D.N.Y. 2015) (rejecting procedural due process challenges to the 2014 Prior Rule based on asserted interests in property and liberty); Ass'n of Priv. Colleges & Universities v. Duncan, 870 F. Supp. 2d 133, 154 n.7 (D.D.C. 2012) (“Without a property right in their participation in Title IV programs, schools cannot press a Fifth Amendment challenge to the regulation of those programs.”).

See Ass'n of Accredited Cosmetology Sch. v. Alexander, 979 F.2d at 864 (concluding that “schools have no `vested right' to future eligibility to participate” in the Guaranteed Student Loan program).

See Dumas, 90 F.3d at 392.

Additionally, the final rule's appeal process is fair. The risk of error is low in the first place because the Department will use quality data on earnings from a Federal agency combined with other reliable information, including information supplied by institutions themselves. We have explained those choices at length in the NPRM and in this document. The calculations in question, moreover, are not fairly subject to open-ended debate or significant discretion. Regarding GE program accountability, the rules for calculating D/E and EP results specify clear formulas, thereby diminishing the value of additional procedures. On the flipside, and in view of the Department's experience with appeals under prior GE rules, we are convinced that adding such procedures will not improve decisions but will increase delays, expenditures, and other burdens. The rules will give adequate assurance of accurate decisions, while serving the Department's important interests in supporting career training that results in enhanced earnings and affordable debt.

Although the Department concluded that the alternate earnings appeals available under the 2014 Prior Rule were not effective, these rules will provide appeals that are meaningful and manageable. Section 668.603(b) states that if the Secretary terminates a program's eligibility, the institution may initiate an appeal under subpart G of this part if it believes the Secretary erred in the calculation of the program's D/E rates under § 668.403 or the earnings premium measure under § 668.404. Subpart G of part 668, specifically § 668.86(b), outlines the procedure for institutions to challenge decisions to limit or terminate a program. These procedures are designed to provide an opportunity to correct any errors in the calculation of a program's D/E rates under § 668.403 or the earnings premium measure under § 668.404. These procedures include issuance by a designated Department official of notice informing the institution of the intent to limit or terminate that institution's participation, through a possible appeal of the initial decision of the hearing official to the Secretary. In addition, under § 668.405, institutions will be provided a “completer list” of all students who completed each program during the cohort period and given an opportunity to correct the information about students on the list.

It is true that, unlike the 2014 Prior Rule, the rules adopted here will not allow for institution-by-institution challenges to draft D/E rates based on evidence provided by the institution that loan debt information used to calculate the median loan debt for a program is incorrect. However, median loan debt for a program is not a statistic that the Department creates on its own, but rather is derived from student enrollment, disbursement, and program data, or other data the institution is required to report to the Secretary to support its administration of, or participation in, title IV, HEA. We expect that institutions will review these data and confirm they are correct at the time of reporting. Should any reported data contain inaccuracies, the institution must timely correct that data. The Department provides ample opportunity for an institution to evaluate the accuracy of its data through reconciliation and closeout procedures at the end of each award year. Section 668.405 will require that, in accordance with procedures established by the Secretary, the institution update or otherwise correct any reported data no later than 60 days after the end of an award year. Inasmuch as participating institutions have access in real time to Department systems through which relevant data are reported—that is, COD and NSLDS—plus an appropriate period of time to correct any erroneous data, the presumption of accuracy with respect to such institution-provided information is fair and reasonable. Accordingly, these regulations do not establish a protocol for the publication of draft rates and an institutional challenge to those rates based on incorrect data being used to calculate median loan debt.

We acknowledge the references to fairness and due process in the preamble of the Department's 2014 Prior Rule. We remain committed to making decisions based on sufficiently reliable information that is relevant to the GE program accountability framework. We disagree, however, that due process or fairness requires the Department to adopt precisely the same appeals processes as in 2014, regardless of current circumstances and other rules that affect the reliability of the information needed to apply these rules. To the extent that constitutionally protected interests are implicated when institutions seek to benefit from government support, we observe that due process remains a flexible concept that accounts for considerations that include a relatively low probability of significant error and the Government's interest in reducing fiscal and administrative burdens.

See, for example, Mathews v. Eldridge, 424 U.S. 319, 334–35, 347 (1976); see also Jennings v. Rodriguez, 138 S. Ct. 830, 852 (2018) (reaffirming that due process is flexible).

As explained above, institutions with programs that are not eligible to participate in title IV, HEA as the result of failing GE rates can appeal under subpart G of part 668 if they believe the Secretary erred in the calculation of the program's D/E rates under § 668.403 or the earnings premium measure under § 668.404. We also note that some commenters mischaracterized these rules in asserting that the Department will limit institutions to a review of completer lists without an opportunity to make appropriate corrections. As previously discussed, § 668.405 will allow institutions to correct information about students on the list. Median loan debt challenges also are discussed above. Alternate earnings appeals are addressed in a separate discussion below.

Changes: None.

Comments: Several commenters, within the context of supporting the reintroduction of alternate earnings appeals, suggested the Department “cap” the number of programs at a given institution that can lose eligibility as a result of failing D/E rates or EP measures. One commenter broadly suggested a cap for the first year. However, commenters were not otherwise specific as to how such a cap might be applied.

Discussion: We are not convinced that a cap on the number of programs offered by a single institution that can lose eligibility is an appropriate or logical measure. Failing programs allowed to remain eligible as the result of such a cap would be no more successful than those that lost eligibility; however, institutions would still be able to enroll students in those programs, subjecting them to the potential harm these regulations are designed to prevent. Restricting a cap to the first year that an institution is subject to program sanctions in no way mitigates these concerns.

Changes: None.

Comments: Some commenters claimed that cosmetology programs have limited ability to improve or reform because of State requirements for minimum hours and curriculum, restrictions on offering programs substantially similar to failing programs, costs of opening or expanding new programs, and limits to their ability to offer distance education.

Discussion: The commenters' claim that State regulation prevents program improvement is not borne out by the data on the median debt of cosmetology programs within States. As Figure 1.4 shows, median debts for undergraduate certificate programs in cosmetology vary widely within all States. In Figure 1.4, each dot represents the median debt of a program, grouped by the State where the program is located using data from the 2022 PPD described in the RIA. This variation suggests that institutions can and do influence the amount of borrowing their students acquire and can therefore improve their outcomes. At a minimum, such varying program results within States are inconsistent with the theory that State regulation tightly restricts opportunities for program improvement. Furthermore, we note that, on its face, the restriction on offering programs that are substantially similar to failing programs does not prevent institutions from improving their existing programs. Rather, it plainly is a safeguard against institutions relabeling failing programs under different CIP codes without actually improving them.

Changes: None.

Comments: One commenter expressed the opinion that closures resulting from the absence of an appeal process will result in beauty professionals having no options for schooling and the displacement of thousands of employees. Another commenter listed negative effects that the COVID–19 pandemic had on the beauty industry, including the closure of salons and spas, the reluctance of clients to return, and the difficulty service providers experienced in reestablishing clientele, all of which reduced earnings. The commenter inquired how programs can accurately be measured without an appeal process for this time period. Another commenter posited that return on investment (ROI) should not be the only standard by which the value of an educational program is measured, and that there is inherent value in professions that help people, such as social worker, counselor, hairstylist, or esthetician. The commenter asked that due process in the form of an appeal on that basis be offered in final regulations.

Discussion: Regarding concerns about loss of educational opportunity for those seeking to enter the beauty profession and possible displacement of persons employed in the industry, the Department does not intend either of those results. We accept the need for quality programs in the fields of cosmetology and esthetics, as well as people to train those entering these occupations. However, those views do not obviate the importance of program outcomes that indicate completers have a reasonable expectation of reported, verifiable earnings exceeding those of a high school graduate and sufficient to service their education debt. Nor do predicted results for a given field of training establish any shortfall in the rules' procedures. Although some programs will not be eligible for title IV, HEA participation as the result of repeatedly failing D/E rates or EP measures, we are not convinced that opportunities for students who want to train for a career in the beauty industry will be materially circumscribed by the implementation of these rules, including the provisions for appeals. Moreover, we believe that the increased confidence students will have in the economic advantages of enrolling in programs that do establish passing D/E rates and EP measures outweigh the drawbacks associated with no longer being able to choose from among those programs that are not eligible under these rules.

We acknowledge that the COVID–19 pandemic likely affected the earnings of workers in salons, spas, the beauty industry, and many other industries besides. However, we do not find a basis for offering special appeals to any one field of programs or more broadly. As explained elsewhere in this document, the Department is not postponing action until such time as no earnings data through 2022 is included in D/E rate or EP calculations. Accordingly, and in consideration of the fact that most industries employing the graduates of GE programs were, to some extent, affected by the pandemic, permitting appeals based on this circumstance would effectively obviate the full effect of the rule until at least the 2026–2027 award year. We do not view the effects of the pandemic as being germane to the discussion of alternate earnings appeals.

We agree with the commenter who asserted that ROI is not the only standard by which the benefits of an education should be measured, and that professions that help people have value beyond any remuneration that can be expected. Elsewhere in this document and in the NPRM, we have affirmed that students rely on a variety of appropriate considerations in choosing among postsecondary education options and that postsecondary education programs may reflect and serve a range of values. However, having income sufficient to repay the debt incurred for a program is a commonsense and fundamental part of any assessment of whether the program prepares students for gainful employment in a recognized occupation. It is also reasonable in that assessment to expect that program graduates will, on average, earn more than a high school graduate. Last, we note that the GE program measures are not, strictly speaking, a determination of ROI, which is a formula for determining how well a particular investment has performed relative to others. As to the commenter's suggestion that the Department establish an appeal based on the extent to which a program's graduates help people or provide other societal benefits, we do not see how such an appeal could be anything other than entirely subjective and, therefore, lacking in fairness. Moreover, the suggestion seems to involve the commenter's preferred measures for program success, rather than statutory requirements or the adequacy of procedures used to determine program eligibility.

See, for example, 88 FR 32300, 32306, 32322 (May 19, 2023).

Changes: None.

Comments: Some commenters asserted that proposed § 668.603(b), which provides a basis for appeal if a program loses eligibility upon completion of a termination action of program eligibility, is a misapplication of the regulations applicable to limitation, suspension, and termination actions under subpart G, while still failing to give institutions adequate appeal rights. One commenter, while stressing the absence of challenges and appeals present in the 2014 Prior Rule and arguing for their reintroduction, noted that subpart G does provide institutions with notice and an opportunity to request a hearing prior to suspension, limitation, or termination of that institution's participation in the title IV, HEA programs and that no limitation, suspension, or termination occurs until after the requested hearing is held. Alternatively, an institution may submit written materials to the designated Department official, who is required to consider the materials before determining whether to limit, suspend, or terminate participation. The commenter further offered that, even after an initial decision, regulations allow that an institution may appeal the initial decision to the Secretary. Citing proposed § 668.91(a)(3)(vi), which stated, “In a termination action against a GE program based upon the program's failure to meet the requirements in § 668.403 or § 668.404, the hearing official must terminate the program's eligibility unless the hearing official concludes that the Secretary erred in the applicable calculation,” another commentor expressed concern that the provision improperly removes the official's discretion to make an eligibility determination based on the facts and circumstances before them. The commenter also contended that, because the rule requires the official to terminate a program's eligibility without the opportunity for presentation of the case before a hearing official, it violates the institution's due process rights. Other commenters expressed the opinion that limiting the basis for any appeal to a calculation error on the part of the Department unfairly denies institutions any opportunity to present data that are potentially more accurate than the data on which the Department based its calculations.

A number of commenters objected to the appeal process in subpart G being limited to fully certified institutions. Commenters acknowledged that procedural rights for provisionally certified institutions differ from those of fully certified institutions with respect to institutional eligibility but argued that (unlike for institutional eligibility) certification status has no bearing on program-level GE outcomes or the resulting eligibility status of those programs. The commenters further argued that inasmuch as fewer procedural protections would be accorded provisionally certified institutions and opportunities to challenge underlying data are absent, the proposed rules effectively create two separate sets of analysis for GE programs that share the same outcome.

Some commenters suggested the introduction of an appeal based on recalculating GE metrics using an eight-digit OPEID number. The commenters offered that alternate results calculated at the eight-digit level would indicate where, despite failing across all locations (presumably at the six-digit CIP level), a program is passing in specific markets and locations, preventing those successful programs from becoming “collateral damage.” Commenters added that the more specific rates and related information would have greater relevance to students attending individual locations.

Discussion: We disagree with the commenters who asserted that the basis for appeal in § 668.603(b) is a misapplication of the regulations in subpart G of part 668 and applicable to fine, limitation, suspension, and termination proceedings. Under the rules adopted here, a GE program that has failed the D/E rates measure or the earnings premium measure in § 668.402 in two out of any three consecutive award years is ineligible and its participation in the title IV, HEA programs ends upon the earliest of the issuance of a new Eligibility and Certification Approval Report (ECAR) that does not include that program, completion of a termination action of program eligibility, or revocation of program eligibility, if the institution is provisionally certified. Nothing in the regulations applicable to termination proceedings limits the Department in taking such action in circumstances where a GE program has failed the D/E rates measure or EP measure. Accordingly, we do not believe that any part of proposed § 668.603(b) is inconsistent with the provisions of subpart G or constitutes a misapplication of its provisions.

We agree with the commenter who noted that in taking an action to terminate the eligibility of a failing program, the Department is bound by all of the provisions of subpart G related to due process—that is, delivery of notice to the institution with an opportunity to request a hearing, as well as the opportunity to submit written materials to the designated Department official, and, finally, the institution's right to appeal the initial decision of the hearing officer to the Secretary. Section 668.91(a)(3)(vi) does, as noted by another commenter, require the hearing official to terminate the program's eligibility unless they conclude that the Secretary erred in the applicable calculation. However, we do not agree with that commenter that this provision either removes the official's discretion to make an eligibility determination based on the facts and circumstances before them or violates the institution's due process rights by requiring the Department official to terminate a program's eligibility without the opportunity for presentation of the case before a hearing official.

Unlike with a similar action taken as the result of serious program violations, termination proceedings to end the participation of a failing GE program would be based solely on the regulatory loss of eligibility prescribed in § 668.603. Such loss of eligibility can only result from failing D/E rates or EP measures as objectively calculated using the formulas prescribed in §§ 668.403 and 668.404, respectively. Therefore, a conclusion by the hearing official that the Department erred in the applicable calculation is, appropriately, the only basis on which that individual may decline to terminate the program's participation. However, within the context of determining whether errors were made in calculating the D/E rates or EP measures, the hearing official is not constrained when considering the facts and circumstances before them. It is also not the case that these rules will mandate that the Department official terminate a program's eligibility without the opportunity for the institution to present its case before a hearing official. Under § 668.86(b)(1)(iii), the Department official must inform the institution that termination will not be effective on the date specified in the notice if the designated Department official receives from the institution by that date a request for a hearing.

Regarding the objections of some commenters that limiting the basis for any appeal to a calculation error on the part of the Department unfairly denies institutions any opportunity to present data that are potentially more accurate than the data on which the Department based its calculations, we have addressed the substance of that concern in the NPRM and we elaborate on due process concerns elsewhere in this document. Here we reiterate that, earnings data notwithstanding, the information used by the Department to calculate D/E rates is reported by institutions and presumed to be accurate. As discussed above, moreover, institutions are provided an opportunity to correct completer lists and to update or otherwise correct any reported data. Finally, we believe that the question of whether to identify programs based on the six-digit CIP, six-digit OPEID, or eight-digit OPEID is most appropriately addressed in the discussion of the definition of a GE program and not germane to a discussion of appeals. We address the substance of that suggestion elsewhere in this document.

Changes: None.

Comments: Addressing the provision in proposed § 668.405, allowing an institution to update or otherwise correct any reported data no later than 60 days after the end of an award year, several commenters expressed confusion over and requested clarification from the Department on the required timeframe being tied to the end of an award year and suggested that the 60-day period be counted from the date the institution is provided with a completer list. An alternative offered by one commenter would bifurcate the process, giving institutions 60 days from the end of the award year to correct any self-reported data and an additional 60 days to respond to any subsequent completer list, the assumption being that the Department's intent is that any 60-day correction period would begin at a point where the institution has access to all data subject to correction. Additionally, commenters asserted that any correction opportunity should also extend to data the Department collects itself, such as Direct Loan Program loan debt, and that institutions should also have the opportunity to identify students whom the Department failed to exclude from the completer list, provided the institution has reliable evidence that the students should be excluded.

Discussion: We agree with the commenter who expressed confusion over the proposed timeframe for updating or otherwise correcting any reported data and suggested separating that process and corrections to the completer list. As noted by the commenter, an institution cannot review the completer list until it is received, a date which may not coincide with the end date of the academic year. Because the composition of completer lists is based on student enrollment information reported to NSLDS, we are not persuaded of the need for a process whereby an institution would identify to the Department students it (the institution) believes should be excluded from the list. Upon receipt of a completer list, the institution should correct any inaccurate enrollment data reported to NSLDS. Accordingly, we have revised § 668.405(b)(1)(iii) to allow the institution 60 days from the date the Secretary provides the list to make necessary corrections to underlying enrollment data in NSLDS. Subsequently, the Department will presume that all such data is correct and proceed with calculating D/E rates measures and EP measures. In response to the commenter who asserted that any correction opportunity should extend to data the Department collects itself ( e.g., Direct Loan Program loan debt), we note that median loan debt used in the D/E calculation is derived from information the institution is required to report to the Department and provision for the correction of that data already exists in § 668.405(a).

Changes: Section 668.405(b)(1)(iii) is revised to allow the institution to correct underlying enrollment information reported to NSLDS about the students on the completer list no later than 60 days after the date the Secretary provides the list to the institution.

Comments: We received a large number of comments objecting to the Department's decision not to include an alternate earnings appeal in these rules. Several of these commenters characterized the absence of an earnings appeal as a retraction of assurances made by the Department in the 2014 Prior Rule to provide an opportunity for institutions to demonstrate that actual earnings for a failing program are higher than those on which D/E rates calculations were based. These commenters cited the 2014 Prior Rule NPRM where the Department, in addressing what was then proposed § 668.406, stated, “[w]e recognize that this process must provide an institution an adequate opportunity to present and have considered rebuttal evidence of the earnings data, and the alternate earnings appeal process provides that opportunity,” and these commentators characterized the statement as evidence of a previous commitment to provide due process with respect to earnings that has been abrogated. Other commenters asserted that, inasmuch as a high potential for the underreporting of income to the IRS exists in “tipped” occupations and institutions have little or no control over whether graduates do report the portion of income derived from gratuities, it is unfair to predicate the loss of program eligibility on an incomplete earnings picture without providing an appeal based on earnings surveys such as existed in the 2014 Prior Rule. Still other commenters suggested the Department's stipulation in the preamble to the NPRM that earnings data obtained from the IRS contains “statistical noise” constitutes an admission that data are potentially flawed, further arguing the need for an earnings appeal process.

Many of the commenters writing in opposition to the lack of an earnings appeal objected to the Department's assertion (in the NPRM) that alternate earnings data for cosmetology schools filed under the previous earnings appeal (as permitted in the 2014 Prior Rule) were “implausibly high.” This statement was characterized by one commenter as implying that cosmetology schools altered or manipulated earnings data obtained from surveys to ensure D/E rates passed upon appeal. A few commenters questioned the Department's position expressed in the NPRM that it is unlikely any earnings appeal process would generate a better estimate of graduates' median earnings. One of those commenters offered that whether the alternate earnings appeal process would frequently change the estimate of median earnings at issue is irrelevant to whether the Department is providing institutions with due process as required by the Constitution. Another commenter added that the Department's conclusions regarding the likely merit of such appeals are based on a single round of alternate earnings appeals in which only institutions offering GE programs participated. Yet another commenter rejected the Department's assertion that, to date, it has identified no other data source that could be expected to yield data of higher quality and reliability than the data available from the IRS, inquiring why the Department asks for flexibility in seeking a source for earnings data, why any other source would be considered, and how the availability of appeals might be affected should the Department opt for an alternate source that is more available but less reliable.

Some commenters questioned the Department's lack of confidence in the results of earnings surveys, in view of the 2014 regulations then in effect requiring an attestation from the institution's chief operating officer, as well as an examination-level attestation engagement report prepared by an independent public accountant or independent government auditor that the survey was conducted in accordance with NCES. One commenter asked whether the Department has considered that perhaps the reported Social Security Administration (SSA) earnings data might be the data set that is suspect. Two more commenters related the success their respective institutions had in mounting successful alternate earnings appeals, with one example offered where average reported income was 65.5 percent higher than reported SSA earnings. Both commenters expressed confidence that the surveys were conducted in full compliance with applicable standards and produced accurate results. Finally, two commenters disputed the notion that an appeal process creates adverse incentives for programs to encourage underreporting, inasmuch as institutions do not instruct students on how to complete their taxes. These commenters also expressed the opinion that there would be no benefit in encouraging students to underreport their income since graduates' underreporting of tip and other income will always harm an institution that is subject to the GE rule.

These commenters contended that, despite expressing serious misgivings as to the veracity of earnings surveys, the Department presented no evidence of wrongdoing or overstating of income and displayed an unwarranted bias against the appeal process. One commenter summarized the Department's arguments as largely tracking those that were rejected by the district court in American Association of Cosmetology Schools v. DeVos ( AACS ). Commenters further criticized the Department's reference to the administrative burden resulting from the appeals structure under the 2014 Prior Rule, opining that easing burden on the Department is not a legitimate reason for denying institutions recourse to an earnings appeal as an essential part of ensuring due process.

258 F. Supp. 3d 50 (D.D.C. 2017).

Various commenters claimed that the decision of the district court in AACS constitutes an implied or even express mandate for the Department to offer an earnings appeal. Citing the court's conclusion regarding arbitrariness in making rebuttals of reported income data overly difficult, the commenters asserted that rather than modifying the alternate earnings appeal process to comply with the court's decision, the Department has proposed rules that ignore the court. One commenter added that the court ordered that the Department remove barriers to the appeal process in order to uphold the legality of the rule and, in doing so, signaled that it found value in the appeal process as an alternative means of measuring earnings data that was responsive to the problem but was constructed in a manner that was infeasible for certain programs to utilize the appeal.

Several of the commenters argued that the Department must, out of consideration for the district court's decision, principles of fairness, or both, restore the alternate earnings appeal contained in the 2014 Prior Rule (as modified by the court's order in AACS), or conduct a study of reasonable solutions for addressing the unreliability of reported earnings resulting from underreporting of tipped wages, independent employment tax treatment affecting net income, racial and gender wage discrimination, and other factors that may have a bearing on program graduates. One commenter offered that, while the district judge in the AACS case found that the specific earnings appeal mechanism in the prior rule was unworkable, it might be modified to comply with the law. The commenter suggested that the Department could use an earnings appeal that required schools to submit a statistically significant number of responders to the appeal cohort as opposed to requiring a 100-percent response rate, adding that changes such as this would allow for schools to have appropriate due process rights under the GE Rule.

Discussion: The Department shares the commitment to using reliable earnings data for the D/E and EP metrics, as expressed by many commenters. But the Department disagrees that relatively open-ended earnings appeals are the appropriate and sensible, let alone legally required, means of achieving that goal. We reach that conclusion for several reasons, many of them recounted in the NPRM. Among them are the Department's experience with earnings appeals after the 2014 Prior Rule went into effect, and the particular features of the rules that we adopt here. With the benefit of experience, other developments since 2014, and the inclusion in these rules of various safeguards against significantly inaccurate or underestimated completer earnings, we have concluded that alternate earnings appeals of the kind the commenters suggested would be unreasonable if not arbitrary. We have likewise concluded that those appeals are not mandated by the Due Process Clause of the Fifth Amendment.

We disagree, first of all, with suggestions that the Department's 2014 Prior Rule locked in a position on appeals today. We repeat that agencies may lawfully alter positions based on nonarbitrary grounds, which we supplied in the NPRM and further address in this document. Furthermore, we observe that the commenters who referenced the preamble to the 2014 Prior Rule NPRM do not appear to support the rules on earnings appeals that were proposed and adopted in 2014. Those provisions limited alternate earnings appeals to complaints that were supported by a State-sponsored earnings database or an earnings survey conducted in accordance with certain requirements established by NCES. Based on information that was available to the Department in 2014, and to adequately assure the reliability of results and fairness to all concerned, the Department favored a controlled form of alternate earnings appeals. Some commenters refer us back to 2014 but without endorsing the rules that were adopted then, and apparently without accepting that the Department may consider developments since then. We are not persuaded by those positions.

Formerly 34 CFR 668.406(b) through (d) (rescinded).

In any event, the reasons for alternate earnings appeals do not hold as they did in 2014. We have explained the Department's position in this document and in the NPRM. Now-familiar arguments about unreported income have become less persuasive based on further review and a number of considerations including: current Federal requirements for the accurate reporting of income and increased use of electronic transactions, which makes underreporting income more difficult; the fact that IRS income data are used without adjustment for determining student and family incomes for purposes of establishing student title IV, HEA eligibility, and determining loan payments under income-driven repayment plans; the relatively low quality of past data submitted by institutions in alternate earnings appeals, including submissions after litigation over the 2014 Prior Rule, along with the problems associated with processing those appeals; and new research on unreported income. We reiterate as well that we designed the metrics to be commonsense and modest standards of enhanced earnings and affordable debt, and that a GE program will have to fail the D/E or EP metric multiple times before the program is ineligible to participate in the title IV, HEA programs. Therefore, GE programs that are ineligible based on their repeated failure to meet the metrics will not be on the margin in a substantive sense, but instead will be demonstrably unable to satisfy modest expectations with a built-in margin for error. Moreover, compared to the 2014 Prior Rule, these rules allow additional time for program completers to establish earnings—effectively increasing program-level calculated earnings far beyond any estimated effects of statistical noise in privacy-protected data, and providing further assurance that programs will not inadvertently fail the D/E rates measure or the EP measure. As a result of the Department's thorough review and in light of the particular features of these rules, we conclude that it is neither necessary nor appropriate to include a similar alternate earnings appeal process. We respect the objections offered by commenters, but we are not persuaded to alter this position.

Regarding the argument made by some commenters that it would be unfair to determine program eligibility unless institutions may submit earnings surveys, again we refer to preamble language from the 2023 NPRM. There we explained that, to date, the Department has identified no other earnings data source that could be expected to yield higher quality and reliability than the data available to the Department from the IRS. We believe that alternative sources of earnings data such as graduate earnings surveys would be more prone to issues such as low or selective ( i.e., only higher earners are sampled, or are differentially likely to respond) response rates and inaccurate reporting, could more easily be manipulated to mask poor program outcomes, and would impose significant administrative burden on institutions, not only the Department. We add here that, in adopting these rules, the Department need not quantify the prevalence of self-interested or bad-faith earnings estimates. Inaccurate and unreliable earnings information in appeals is problematic whatever the explanations for its low quality. Furthermore, we lack a reasonable basis to conclude that subsets of institutions are likely to produce especially reliable or unreliable surveys on earnings. We, therefore, disagree with the commenter who suggested the Department's past experience with earnings appeals is irrelevant to evaluating rules that cover a different set of institutions compared to the 2014 Prior Rule. As to the influence of institutions on the degree of compliance exercised by their graduates with IRS reporting rules, that too is difficult to quantify with precision. But we offer our continued and logical belief that the potential influence of institutions on the ethical and lawful behavior of the students they educate is not insignificant. Regardless, we repeat that we do not believe that taxpayer-supported educational programs should effectively receive credit for earnings that their graduates fail to report.

Moreover, we have thoroughly considered the issue of statistical noise in IRS earnings data. As explained in the NPRM, we understand that the IRS would use a privacy-protective algorithm to add a small amount of statistical noise to its estimates before providing median earnings information to the Department. The Department recognizes this creates a small risk of inaccurate determinations, in both directions, including a very small likelihood that a failing program could have passed if its unadjusted median earnings data were used in calculating either D/E rates or the earnings premium. Using data on the distribution of noise in the IRS earnings figures used in the College Scorecard, however, we have estimated that the probability that a program could be erroneously declared ineligible (that is, fail in 2 of 3 years using adjusted data when unadjusted data would result in failure for 0 years or 1 year) is itself very small—less than 1 percent.

Assuming that such statistical noise would be introduced, the Department plans to counteract this already small risk of improper classification in several ways. First, we include a minimum n-size threshold as discussed under § 668.403 to avoid providing median earnings information for smaller cohorts, where statistical noise would have a greater impact on the earnings measure. The n-size threshold will effectively cap the influence of the noise on D/E and EP results. In addition, a program is not ineligible under the GE program accountability rules until that GE program fails the accountability measures multiple times. Furthermore, the rules will establish an earnings calculation methodology that is more generous to title IV, HEA supported programs than what the Department adopted in the 2014 Prior Rule for GE programs. The rules will measure the earnings of program completers approximately one year later (relative to when they complete their credential) than under the 2014 Prior Rule. This will yield substantially higher measured program earnings than under the Department's previous methodology—on the order of $4,000 (about 20 percent) higher for GE programs with earnings between $20,000 and $30,000, which are the programs most at risk for failing the earnings premium threshold. This will be more generous to programs under both the EP and D/E metrics because the higher measured program earnings will be used in both calculations. The increase in earnings from this later measurement of income will provide a buffer more than sufficient to counter possible error introduced by statistical noise added by the IRS. Together, these features of the rules safeguard against artificially low earnings results, and they do not suggest the need for further measures such as an earnings appeal process that would rely on survey earnings far less reliable than those provided by the IRS.

Although the Department currently prefers to rely on IRS earnings data, the rules also will allow the Department to obtain earnings data from another Federal agency if unforeseen circumstances arise. That provision of the rules will give the Department flexibility to work with another Federal agency to secure data of adequate quality and in a form that adequately protects the privacy of individual graduates. Despite suggestions by one commenter, the flexibility to use other data is no indication that the Department will use inferior data that are insufficiently accurate and reliable for purposes of these rules. We have confidence in the accuracy and reliability of all Federal agency sources under consideration. In any case, the Department's NPRM informed the public about the kind of data needed for the rules, as well as the sources from which those data might be drawn.

In response to those commenters who viewed as pejorative the Department's assertion that alternate earnings data for cosmetology schools filed under the 2014 Prior Rule were implausibly high, we intended no offense. This statement does not seek to imply that cosmetology schools altered or manipulated earnings data obtained from surveys to inflate D/E rates as to pass upon appeal. Rather, we sought to convey our misgivings over what appeared to have been an excessive amount of earnings reported by survey respondents. This may have resulted from a number of factors that are difficult to control when using such surveys. Those challenges in producing accurate and reliable survey results on completer earnings are not special to cosmetology schools.

Moreover, we disagree with some commenters' suggestions that infrequency of errors under the rules and administrative burdens from the alternatives that the commenters prefer are irrelevant to the Due Process Clause. Those assertions are incorrect. To the extent that constitutionally protected interests are even implicated when institutions seek to benefit from government support, we reiterate that due process remains a flexible concept that accounts for considerations that include a relatively low probability of significant error and the Government's interest in reducing fiscal and administrative burdens. We likewise disagree that the Department's experience with alternate earnings appeals is somehow irrelevant or inadequate to provide support for these rules. Those appeals were received and analyzed over an extended period of time during which the Department compiled more than sufficient data to show that the process contained serious flaws and failed to yield adequately reliable earnings data. The Department has no evidence to suggest that subsequent rounds of earnings appeals would have resolved the Department's misgivings about the accuracy and reliability of earnings data obtained through the use of earnings surveys, or about the various costs to all concerned in operating that process.

We further address due process in an above discussion of “Challenges, Hearings, and Appeals.”

We also disagree with the other arguments that commenters raised for creating an earnings appeal in these rules. The 2014 Prior Rule did allow for institution-sponsored surveys that met National Center for Education Statistics (NCES) standards. However, adherence to NCES standards in this context, even when confirmed by an examination-level attestation engagement report prepared by an independent auditor, does not mitigate the potential for misreporting of earnings by program graduates participating in the earnings survey. There are inherent biases for survey respondents to inflate their earnings and little incentive for institutions to encourage accurate survey responses. Additionally, the amounts reported on such instruments cannot be substantiated in any other way than to accept at face value the information supplied by a survey respondent. The Department's reservations about the use of earnings data surveys are already addressed above and discussed at greater length in the 2023 NPRM. As for whether the SSA earnings data used under the 2014 Prior Rule were “suspect,” we are aware of no evidence to suggest that was the case. We do not imply that the commenters who related their own success in alternate earnings appeals under the 2014 Prior Rule were noncompliant with NCES standards. Again, however, the degree to which any earnings survey was conducted in accordance with those standards is not responsive to the Department's reservations, given experience and new evidence, about the use of earnings data obtained in that way for calculating D/E rates and the EP metric.

In response to the commenters who maintained that institutions do not instruct students on how to complete their taxes, we have not suggested that institutions regularly offer students tax advice. In addition, we have concluded that the available evidence, taken as a whole, indicates that underreporting is modest in size for graduates of GE programs and other programs that are eligible to participate in the title IV, HEA programs. We do, however, believe that adding an earnings appeal process that is aimed at capturing unreported income could encourage a culture of underreporting. The practical concern is that a significant fraction of tax- supported programs may produce completers who do not report substantially all of their income to the Government at the front end, but that, at the back end, those programs will remain eligible for title IV, HEA support through institution-sponsored earnings surveys in which responses are costless to program completers. And in response to the commenters who asserted that there is no direct and immediate benefit that accrues to institutions when students underreport their income, the extent to which such practices will affect institutions through GE program accountability metrics would certainly be affected by earnings appeals that allow institutions to pitch estimates of income that has not been reported to the IRS as required by law. Finally, regarding evidence of wrongdoing or overstating of income intentionally by institutions, we repeat that, in adopting these rules, the Department need not quantify the prevalence of self-interested or bad-faith earnings estimates. Inaccurate and unreliable earnings information in appeals is problematic whatever the explanations for its low quality. With respect to institution-sponsored surveys, earnings estimates are entirely reflective of whatever figures respondents choose to report, unverifiable, and subject to several biases for which there are not adequate controls. Self-reported earnings on surveys are not an appropriate substitute for substantiated earnings reported to the IRS or another Federal agency with earnings data of comparable quality. Indeed, most research into the extent of misreporting of incomes in surveys take administrative data, including that provided to the IRS or SSA using the same information reports (W2 forms and schedule SE) we rely on to measure program graduates' earnings, as the “ground truth” with which to compare survey reported earnings.

See for example, Bollinger, Hirsch, Hokayem & Ziliak (2019). Trouble in the Tails? What We Know about Earnings Nonresponse Thirty Years after Lillard, Smith, and Welch. Journal of Political Economy, 127(5).

The Department disagrees with the commenters who argued that the decision of the district court in American Association of Cosmetology Schools v. DeVos, which addressed the 2014 Prior Rule, mandates that the Department offer an alternate earnings appeal in this final rule. There the district court rejected in part and accepted in part certain arbitrariness challenges to the 2014 Prior Rule. The court held that the Department had adequately explained why SSA earnings data were used and without an adjustment factor for unreported income, but the court also held that the Department had not justified certain limits on alternate earnings appeals. The court referred to evidence of unreported income in the 2014 rulemaking proceedings, and the court examined the Department's reasoning, focusing on then-current law regarding income reporting and on the earnings appeals in the 2014 Rule. In reviewing the prior rule's limits on those appeals, the court stated that the Department had not explained its assumptions. The court ultimately ordered that AACS member schools be allowed to pursue earnings appeals without meeting the numerical survey requirements in the rule. The court did observe that the notice-and-comment process failed to identify better data or a better methodology for calculating earnings for program completers, but, in fashioning a remedy, the court believed that each school should be allowed to offer something better, if it existed, during an appeal.

258 F. Supp. 3d 50 (D.D.C. 2017).

See id. at 75–76. We note here our disagreement with commentators' recommendations that the Department study the issue of unreported earnings even further, given our examination of the issue during this negotiated rulemaking process and the available research. See generally FCC v. Prometheus Radio Project, 141 S. Ct. 1150, 1160 (2021) (“In the absence of additional data from commenters, the FCC made a reasonable predictive judgment based on the evidence it had.”); Am. Hosp. Ass'n v. Azar, 983 F.3d 528, 539 (D.C. Cir. 2020) (“The Secretary . . . is not limited to relying only on definitive evidence. . . .”). We observe in this regard that the AACS district court concluded that the Department was not responsible for collecting earnings data on individual programs, see 258 F. Supp. 3d at 75 n.8, and the court indicated that the Department had no obligation to conduct independent studies under the applicable standard for use of data, see id. (quoting Sw. Ctr. for Biological Diversity v. Babbitt, 215 F.3d 58, 60 (D.C. Cir. 2000)). See also Prometheus Radio, 141 S. Ct. at 1160 (“The [Administrative Procedure Act] imposes no general obligation on agencies to conduct or commission their own empirical or statistical studies.”); District Hosp. Partners, L.P. v. Burwell, 786 F.3d 46, 56, 61 (D.C. Cir. 2015) (addressing standards for agency data use, and indicating that a dataset on which an agency relies need not be perfect).

Above in “Tipped Income,” we address such evidence of unreported earnings along with more recent findings.

See 258 F. Supp. 3d at 74 (discussing the prior rule's numerical response-rate requirements for earnings data from State-sponsored data systems and from institution-sponsored surveys).

See id. at 76–77 (severing part of the 2014 appeals rule from the remainder of the 2014 Prior Rule, and stating that the Department “will be able to decide, on a case-by-case basis, what modicum of evidence is enough”).

See id. at 63.

The Department followed the district court's opinion when the 2014 Prior Rule was in effect. The opportunity to submit a Notice of Intent to Appeal was re-opened and institutions were permitted to submit alternate earnings appeals for programs with overall “zone” or fail ratings regardless of whether the 50 percent minimum response rate or 30-response minimum were met, with the Department agreeing to review the earnings appeals on a case-by-case basis. Indeed, the Department allowed these case-by-case earnings appeals for all institutions, not only AACS members. And we have taken care to examine the court's opinion again during this rulemaking. We understand the concerns expressed in the opinion, as well as the hope for a workable even if open-ended earnings appeals process, given the record evidence that was available and the reasoning in the 2014 rulemaking proceedings. We appreciate as well that the court expressed concern for administrability. Of course, the district court's evaluation of the reasoning in the 2014 Prior Rule does not bind the Department in a subsequent rulemaking that considers new and different information, relies on a different set of reasons, and produces different final rules. Nonetheless, the Department has been mindful of the district court's review of the 2014 Prior Rule.

See id. at 73 (“[T]he [Department] has discretion to sacrifice some measure of fit for the sake of administrability.”); id. at 74 (“Nor did the commenters propose an alternative calculus to balance fit and administrability.”).

In this document and the accompanying NPRM, we have explained at length our rationale for relying on a Federal agency with earnings data as a source of reliable, verifiable, and accurate earnings information to use in the calculation of debt-to-earnings rates and the earnings premium. We have similarly explained the Department's decision not to include an alternate earnings appeal in this final rule. The Department's position here is not based on unexplained assumptions about tax law compliance or the value of certain survey response rates. Instead our conclusions are based on considerations such as new data on unreported income that indicate its modest size for the program graduates who are relevant to this rule; new laws on reported income and the increased use of electronic payments expected to further reduce underreporting; a longer earnings period in these rules that safeguards against programs failing the D/E or EP metrics in ways that concern various commenters; the use of reported income in other Department operations as well as the problematic incentives arising from crediting programs with unreported income; and the Department's hard-earned experience in conducting open-ended appeals and processing the surveys and other information that was submitted. The Department has concluded that AACS's previous estimates of up to 60 percent unreported income in that case were far too high to be plausible, are even less indicative of actual earnings under current circumstances, and are not a reasonable basis for adding earnings appeals now. That is not the quality of evidence on which the Department could rationally and fairly supersede earnings data from IRS or another Federal agency, nor should programs receive credit for such evidence of unreported earnings. Moreover, earnings appeals under the 2014 Rule were not only difficult to administer and burdensome for all involved but also, and crucially, they yielded low-value information overall. The district court in AACS could not have been aware of these developments when it evaluated the 2014 Prior Rule, and the Department's decision today obviously is no indication of disregard for the court. To the contrary, the Department's decisions in this final rule are importantly based on subsequent developments and insight gained from following the district court's judgment.

For additional detail, see the discussion above in “Tipped Income.”

Changes: None.

Program Application Requirements

Comments: One commenter voiced concern about certain portions of the requirements under § 600.21(a)(11) to update application information for GE programs. They described the difficulty of knowing when a change is considered to occur for the 10-day requirement to begin, citing lengthy approval processes sometimes involving a State and accrediting agency in addition to institutional academic governance structures. They also voiced concern at whether even potentially minor changes, such as a one-credit change in program length, or a minor change in words in a program name, would trigger reporting requirements. They recommended extending the reporting period to 30 or 60 days, and that we clarify that we require updates only for substantive items relative to program eligibility and misrepresentation, not to minor clerical changes not fundamental to eligibility.

Discussion: The 10-day period for reporting changes is consistent with the 10-day period for changes to GE programs institutions are currently required to report, as well as other eligibility changes ( e.g., change in institutional officials, change of address, etc.), and the Department believes that it is an appropriate reporting period. Changes to a GE program name were already reportable changes under § 600.21(a)(11)(v).

Changes: None.

Comments: One commenter sought to draw our attention to an inconsistency between the communicated intent in the preambulatory section to add a conforming change to acknowledge § 668.603 limitations on adding new programs and re-establishing programs after a loss in eligibility versus the language in proposed § 600.10(c)(1)(v), which would have required institutions to obtain Department approval before establishing or re-establishing any of these programs. They suggested repositioning that provision outside of § 600.10(c)(1) to correctly reflect the intention of a reporting requirement and not an approval requirement.

Discussion: The Department thanks the commenter for their observation. We agree that we are seeking to maintain the requirement to report new GE programs or changes to existing GE programs, and to add a requirement to report to the Department if a GE program is being established or re-established that would once have been ineligible to do so under § 668.403.

Changes: The provision was repositioned outside of § 600.10(c)(1), from § 600.10(c)(1)(v) to § 600.10(c)(3), with a slight rewording for additional clarity.

Comments: One commenter observed that while proposed § 668.604(c)(2) would prevent institutions from adding any new GE programs to their list of eligible programs if they are substantially similar to a failing program that became ineligible or was voluntarily discontinued, and while language in the preamble to the 2023 NPRM indicated an intent to use the same four-digit CIP prefix as under the 2014 rule, the rule as proposed did not contain a definition for “substantially similar.”

Discussion: The Department agrees with the commenter and thanks them for bringing this to our attention. We will adopt a similar definition of “substantially similar program” using the four-digit CIP prefix as was used in the 2014 Prior Rule.

We are establishing at § 668.2 that two programs are substantially similar to one another if they share the same four-digit CIP code. Institutions may not establish a new GE program that shares the same four-digit CIP code as a program that became ineligible or was voluntarily discontinued when it was failing within the last three years. An institution may establish a new GE program with a different four-digit CIP code that is not substantially similar to an ineligible or discontinued GE program and provide an explanation of how the new program is different when it submits the certification for the new program. We presume based on that submission that the new program is not substantially similar to the ineligible or discontinued program, but the information may be reviewed on a case-by-case basis so a new program is not substantially similar to the other program.

We believe that this revision strikes an appropriate balance between preventing institutions from closing and restarting a poorly performing program to avoid accountability and ensuring that institutions are not prevented from establishing different programs to provide training in fields where there is demand. We believe that it is appropriate to require an institution that is establishing a new program to provide a certification under § 668.604 that includes an explanation of how the new GE program is not substantially similar to each program offered by the institution that, in the prior three years, became ineligible under the regulations' accountability provisions or was voluntarily discontinued by the institution when the program was failing the D/E rates or EP measure. In the first instance, the institution will possess information on the programs in question, and the rule still will provide a safeguard in the form of an opportunity for the Department to evaluate such submissions when appropriate.

Changes: We have added a definition of “substantially similar program” under § 668.2.

Miscellaneous

Comments: One commenter recommended that the Department monitor the quality of education, or oversee curriculum, as the student progresses through their academic program, not just by using metrics established at the end of a program.

Discussion: The Department's authority in postsecondary education matters is limited to issues relating to Federal student aid, the use of Federal funds, and the specific programs administered by the Department. Further, under section 103 of the Department of Education Organization Act of 1979, the Department is generally prohibited from exercising any direction, supervision, or control over the curriculum, program of instruction, administration, or personnel of an educational institution, school, school system, or accrediting agency or association. Consequently, we do not have the authority—and are expressly prohibited from regulating—postsecondary institutions' curriculum.

Changes: None.

Comments: A few commenters suggested ways to properly identify GE programs and determine the most appropriate method and period to measure earnings. Suggested approaches included institutions self-certifying the existence of adequate mechanisms already in place, provided they point to a specific State legal requirement or process that justifies the extended time period, or the Department could periodically accept submissions from reliable authorities ( e.g., State regulatory bodies, accreditors or occupational industry groups) regarding covered occupations, and the Department could periodically publish resulting determinations in the Federal Register .

Discussion: We appreciate these suggestions. The methods for identifying GE programs and reporting earnings data included in § 668.405 allow for consistent calculations and data across states, programs, and institutions. We believe it is critical to provide students and families access to information that is comparable and consistently calculated.

Changes: None.

Other Accommodations and Special Circumstances

Comments: Many commenters argued that the Department must consider economic factors such as recessions and the COVID–19 pandemic. These commenters stressed that these events led, and could again lead in the future, to widespread unemployment and depressed earnings. These commenters further stated that it would unreasonably penalize institutions to use earnings data from periods of time that many graduates, particularly in the health and beauty industry, were prohibited from or otherwise unable to work.

Discussion: We believe the need for the financial value transparency and GE program accountability frameworks is too urgent to postpone any of their primary components to such an extent. The first official rates published under these regulations will, for most programs, be based on students who completed a program in award years 2018 and 2019, measuring their earnings outcomes in 2021 and 2022. The impact of the COVID–19 pandemic was most pronounced in 2020, and the labor market had largely recovered by 2022, with strong earnings growth particularly among lower income workers. While the unemployment rate for workers with some college or an associate degree overall was 6.6 percent in July of 2021, up from its rate in January of 2019 of 3.9 percent, this 2.7 percentage point difference in employment will have very little impact on median earnings—this is an additional benefit of using the median. And overall earnings growth among employed workers was very strong. By July of 2022, the unemployment rate had improved to 3.5 percent—tied for as low as it had ever been in the past 50 years. On balance, then, we do not expect the median earnings of most program graduates to have been distorted by the pandemic in the relevant years such that discarding the metrics based on these years is necessary.

The official monthly civilian unemployment rate data can be accessed here: https://www.bls.gov/charts/employment-situation/civilian-unemployment-rate.htm.

This assessment is bolstered by analysis of College Scorecard data. The Department does not have earnings measures for programs yet for 2021. But comparing College Scorecard earnings measures based on the year 2020—as noted above, by a large margin the year with the greatest elevation in unemployment due to the pandemic—suggests the pandemic may not have had a dramatic impact on measured earnings. Comparing 3-years earnings estimates based on earnings measured in 2018–2019 to those based on 2019–2020 (in real dollars), shows that the pandemic did not lead to systematically lower measured median earnings for all or even most programs. The middle 50 percent of programs ranged from a decline in earnings of 4.2 percent to an increase in earnings of 4.0 percent, with the median program experiencing no change in earnings across the two periods. Since the labor market had recovered considerably by 2021, we do not anticipate program earnings data based on earnings in 2021 and 2022 to be overly influenced by the pandemic for most programs.

Changes: None.

Comments: Several commenters stated that various State licensing boards were closed, behind, or backlogged by one to two years during the COVID–19 pandemic. These delays in State licensure substantially hindered job placements and earnings for graduates according to these commenters, who stated that many new graduates were not able to move forward and earn money until 2023.

Discussion: The Department recognizes that the COVID–19 pandemic and national emergency may have impacted data from some years included in the initial reporting period. But as noted above, available data suggest these impacts may be limited in scope even in 2020, the year when employment effects of the pandemic were most pronounced. Postponing sanctions until such time as no earnings data through 2022 is included in the D/E rate or EP calculations would delay the benefits of the rule until at least the 2026–2027 award year. To repeat, we believe the need for the transparency and accountability measures is too urgent to postpone any of the primary components to such an extent.

Changes: None.

Comments: One commenter asked for an exception in the final rule for barbering and cosmetology schools based on the unique circumstances of those schools. Specifically, the commenter suggested that the final rule should provide for (1) a proxy amount to account for unreported earnings that would be added to Federal agency earnings data for barbering/cosmetology programs; (2) an alternate earnings appeal as in the 2014 GE Rule; and (3) an exemption for institutions with revenues of $10 million or below.

Discussion: As stated above, we do not believe it is appropriate to make an exception for these institutions because we believe the students at these institutions are just as deserving of protection from accumulating unaffordable debt or experiencing no earnings gains from GE programs. We discuss the issues of tipped income and earnings appeals elsewhere in this final rule. Moreover, we do not believe there is a reasoned basis for an exception based upon revenue amounts, nor why such an exception should be only applied to cosmetology schools. Commenters did not supply any persuasive bases for those suggested carveouts. We believe the GE program accountability framework should be applied to the programs that are covered by the GE provisions of the HEA, which include cosmetology programs.

Changes: None.

Comments: Another commenter requested that we not make exceptions to the GE rules for some institutions, and we do not allow for “carve outs.” The commenter stated that allowing institutions to offer low earnings and low ROI programs without a program information website or student acknowledgments is harmful to prospective students seeking to attend these programs and cannot be justified.

Discussion: We appreciate the commenter's support.

Changes: None.

Financial Value Transparency and Gainful Employment (GE)

Executive Orders 12866 and 13563 and 14094

Regulatory Impact Analysis

Under Executive Order 12866, the Office of Management and Budget (OMB) must determine whether this regulatory action is “significant” and, therefore, subject to the requirements of the Executive order and subject to review by OMB. Section 3(f) of Executive Order 12866, as amended by Executive Order 14094, defines a “significant regulatory action” as an action likely to result in a rule that may—

(1) Have an annual effect on the economy of $200 million or more (adjusted every 3 years by the Administrator of the Office of Information and Regulatory Affairs (OIRA) for changes in gross domestic product), or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, territorial, or Tribal governments or communities;

(2) Create a serious inconsistency or otherwise interfere with an action taken or planned by another agency;

(3) Materially alter the budgetary impacts of entitlement grants, user fees, or loan programs or the rights and obligations of recipients thereof; or

(4) Raise novel legal or policy issues for which centralized review would meaningfully further the President's priorities, or the principles stated in the Executive order, as specifically authorized in a timely manner by the Administrator of OIRA in each case.

The Department estimates the quantified annualized economic and net budget impacts to be in excess of $200 million. Annualized transfers between institutions and the Federal Government through borrowers are estimated to be $1.2 billion at a 7 percent discount rate and $1.3 billion at a 3 percent discount rate in reduced Pell grants and loan volume. This analysis also estimates additional annualized transfers of $747 million (at a 3 percent discount rate; $732 million at 7 percent discount rate) among institutions as students shift programs and estimated annualized paperwork and compliance burden of $105.6 million (at a 3 percent discount rate; $109.5 million at a 7 percent discount rate) are also detailed in this analysis. Therefore, this final action is subject to review by OMB under section 3(f) of Executive Order 12866 (as amended by Executive Order 14094). Pursuant to the Congressional Review Act (5 U.S.C. 801 et seq.), the Office of Information and Regulatory Affairs designated this rule as covered by 5 U.S.C. 804(2). Notwithstanding this determination, based on our assessment of the potential costs and benefits (quantitative and qualitative), we have determined that the benefits of this regulatory action will justify the costs.

We have also reviewed these regulations under Executive Order 13563, which supplements and explicitly reaffirms the principles, structures, and definitions governing regulatory review established in Executive Order 12866. To the extent permitted by law, Executive Order 13563 requires that an agency—

(1) Propose or adopt regulations only on a reasoned determination that their benefits justify their costs (recognizing that some benefits and costs are difficult to quantify);

(2) Tailor its regulations to impose the least burden on society, consistent with obtaining regulatory objectives and taking into account—among other things and to the extent practicable—the costs of cumulative regulations;

(3) In choosing among alternative regulatory approaches, select those approaches that maximize net benefits (including potential economic, environmental, public health and safety, and other advantages; distributive impacts; and equity);

(4) To the extent feasible, specify performance objectives, rather than the behavior or manner of compliance a regulated entity must adopt; and

(5) Identify and assess available alternatives to direct regulation, including economic incentives—such as user fees or marketable permits—to encourage the desired behavior, or provide information that enables the public to make choices.

Executive Order 13563 also requires an agency “to use the best available techniques to quantify anticipated present and future benefits and costs as accurately as possible.” The Office of Information and Regulatory Affairs of OMB has emphasized that these techniques may include “identifying changing future compliance costs that might result from technological innovation or anticipated behavioral changes.”

We are issuing these final regulations to address inadequate protections for students and taxpayers in the current regulations and to implement recent changes to the HEA. In choosing among alternative regulatory approaches, we selected those approaches that maximize net benefits. Based on the analysis that follows, the Department believes that these regulations are consistent with the principles in Executive Order 13563.

We have also determined that this regulatory action would not unduly interfere with State, local, territorial, and Tribal governments in the exercise of their governmental functions.

As required by OMB Circular A–4, we compare these final regulations to the current regulations. In this regulatory impact analysis, we discuss the need for regulatory action, potential costs and benefits, net budget impacts, and the regulatory alternatives we considered.

1. Covered Rule Designation

Pursuant to Subtitle E of the Small Business Regulatory Enforcement Fairness Act of 1996, also known as the Congressional Review Act (5 U.S.C. 801 et seq.), the Office of Information and Regulatory Affairs designated that this rule is covered under 5 U.S.C. 804(2) and (3).

2. Need for Regulatory Action

Summary

The title IV, HEA student financial assistance programs are a significant annual expenditure by the Federal Government. When used well, Federal student aid for postsecondary education can help boost student outcomes and economic mobility. But the Department is concerned that there are too many instances in which the financial returns of programs leave students with debt they cannot afford or with earnings that leave students no better off than similarly aged students who never pursued a postsecondary education.

The final regulations will provide stronger protections for current and prospective students of programs that typically leave graduates with high debt burdens or low earnings. Under a program-level transparency and accountability framework, the Department will assess a program's debt and earnings outcomes based on debt-to-earnings (D/E) and earnings premium (EP) metrics. These regulations will require institutions to provide current and prospective students with a link to a Department website providing the debt and earnings outcomes of all programs. Students considering enrolling in all eligible programs, other than undergraduate degree programs, that have failed D/E metrics must acknowledge they have viewed the information prior to entering into an enrollment agreement with an institution. Students enrolled or considering enrollment in GE programs failing either the EP or D/E measures will receive warnings that must be acknowledged prior to receiving title IV, HEA funds. Finally, GE programs that consistently fail to meet the performance metrics will become ineligible for title IV, HEA funds.

The regulations will, therefore, increase transparency and strengthen accountability for postsecondary institutions and programs in several critical ways. All institutions will be required to provide students a link to access information about debt and earnings outcomes. Non-GE certificate and graduate programs not meeting the D/E standards will be required to have students acknowledge viewing this information before entering enrollment agreements, and career training programs failing either the D/E or EP metrics will need to warn students about the possibility that they would lose eligibility for Federal aid. Some institutions will have to improve their offerings or lose access to Federal aid. As a result, students and taxpayers will have greater assurances that their money is spent at institutions that deliver value and merit Federal support.

The Financial Value Transparency and GE eligibility provisions in subparts Q and S of the final regulations are intended to address the problem that many programs are not delivering sufficient financial value to students and taxpayers, and students and families often lack the information on the financial consequences of attending different programs needed to make informed decisions about where to attend. These issues are especially prevalent among programs that, as a condition of eligibility for title IV, HEA program funds, are required by statute to provide training that prepares students for gainful employment in a recognized occupation. Currently, many of these programs leave the typical graduate with unaffordable levels of loan debt in relation to their income, earnings that are no greater than what they would reasonably expect to receive if they had not attended the program, or both.

Through this regulatory action, the Department establishes: (1) A Financial Value Transparency framework that will increase the quality, availability, and salience of information about the outcomes of students enrolled in all title IV, HEA programs and (2) an accountability framework for GE programs that will define what it means to prepare students for gainful employment in a recognized occupation by establishing standards by which the Department would evaluate whether a GE program remains eligible for title IV, HEA program funds. As noted in the preamble to this regulation, there are different statutory grounds for the transparency and accountability frameworks.

The transparency framework (subpart Q and § 668.43) will establish reporting and program information website requirements that will increase the transparency of student outcomes for all programs. This will provide the most accurate and comparable information possible to students, prospective students, and their families to help them make better informed decisions about where to invest their time and money in pursuit of a postsecondary degree or credential. Institutions will be required to provide information about program characteristics, outcomes, and costs and the Department will assess a program's debt and earnings outcomes based on debt-to-earnings and earnings premium metrics, using information reported by institutions and information otherwise obtained by the Department. The final rule seeks to provide salient information to students by requiring that institutions provide current and prospective students with a link to view cost, debt, and earnings outcomes of their chosen program on the Department's website. For non-GE programs (excepting undergraduate degree programs where students commonly do not apply to a particular program) failing the debt-to-earnings metrics, the Department will require an acknowledgment that the enrolled or prospective student has viewed the information. Further, the website will provide the public, taxpayers, and the Government with relevant information to help understand the outcomes of these programs receiving Federal investment.

Finally, the transparency framework will provide institutions with meaningful information that they can use to improve the outcomes for students and guide their decisions about program offerings.

The accountability framework (subpart S) defines what it means to prepare students for gainful employment by establishing standards that assess whether typical students leave programs with reasonable debt burdens and earn more than the typical worker who completed no more education than a high school diploma or equivalent. GE programs that repeatedly fail to meet these criteria will lose eligibility to participate in title IV, HEA student aid programs.

Overview of Postsecondary Programs Supported by Title IV of the HEA

Under subpart Q, we will, among other things, assess debt and earnings outcomes for students in all programs participating in title IV, HEA programs, including both GE programs and eligible non-GE programs. Under subpart S, we will, among other things, establish title IV, HEA eligibility requirements for GE programs. In assessing the need for these regulatory actions, the Department analyzed program performance. The Department's analysis of program performance is based on data assembled for all title IV, HEA postsecondary programs operating as of March 2022 that also had completions reported in the 2015–16 and 2016–17 award years (AY). This data, referred to as the “2022 Program Performance Data (2022 PPD),” is described in detail in the “Data Used in this RIA” section below, though we draw on it in this section to describe outcome differences across programs.

Table 2.1 reports the number of programs and average title IV, HEA enrollment for all institutions in our data for AY 2016 and 2017. Throughout this RIA, we provide analysis separately for programs that will be affected only by subpart Q and those that will additionally be affected by subpart S (GE programs).

Table 2.1—Combined Number of Title IV Eligible Programs and Title IV Enrollment by Control and Credential Level Combining GE and Non-GE

Number of
Programs Enrollees
Public:
UG Certificates 18,971 869,600
Associate 27,312 5,496,800
Bachelor's 24,338 5,800,700
Post-BA Certs 872 12,600
Master's 14,582 760,500
Doctoral 5,724 145,200
Professional 568 127,500
Grad Certs 1,939 41,900
Total 94,306 13,254,700
Private, Nonprofit:
UG Certificates 1,387 77,900
Associate 2,321 266,900
Bachelor's 29,752 2,651,300
Post-BA Certs 629 7,900
Master's 10,362 796,100
Doctoral 2,854 142,900
Professional 493 130,400
Grad Certs 1,397 35,700
Total 49,195 4,109,300
Proprietary:
UG Certificates 3,218 549,900
Associate 1,720 326,800
Bachelor's 963 675,800
Post-BA Certs 52 800
Master's 478 240,000
Doctoral 122 54,000
Professional 32 12,100
Grad Certs 128 10,800
Total 6,713 1,870,100
Foreign Private:
UG Certificates 28 100
Associate 18 100
Bachelor's 1,228 5,500
Post-BA Certs 27 <50
Master's 3,075 9,000
Doctoral 793 2,800
Professional 104 1,500
Grad Certs 77 1,500
Total 5,350 20,400
Foreign For-Profit:
UG Certificates 1 <50
Master's 6 200
Doctoral 4 1,900
Professional 7 11,600
Total 18 13,700
Total:
UG Certificates 23,605 1,497,500
Associate 31,371 6,090,700
Bachelor's 56,281 9,133,200
Post-BA Certs 1,580 21,400
Master's 28,503 1,805,800
Doctoral 9,497 346,800
Professional 1,204 283,100
Grad Certs 3,541 89,900
Total 155,582 19,268,200
Note: Counts are rounded to the nearest 100.

There are 123,524 degree programs at public or private nonprofit institutions (hereafter, “eligible non-GE programs” or “non-GE programs”) in the 2022 PPD that will be subject to the transparency regulations in subpart Q but not the GE regulations in subpart S. These programs served approximately 16.3 million students annually who received title IV, HEA aid, totaling $25 billion in grants and $61 billion in loans. Table 2.2 displays the number of non-GE programs by two-digit CIP code, credential level, and institutional control in the 2022 PPD. Two-digit CIP codes aggregate programs by broad subject area. Table 2.3 displays enrollment of students receiving title IV, HEA program funds in non-GE programs in the same categories.

Throughout the RIA, “not-for-profit” and “nonprofit” are used interchangeably to refer to private nonprofit institutions.

Table 2.2—Number of Non-GE Programs by CIP2, Credential Level, and Control

Public Private, Nonprofit Foreign Total
Assoc. Bach. Master's Doct. Prof. Assoc. Bach. Master's Doct. Prof. Assoc. Bach. Master's Doct. Prof.
1: Agriculture & Related Sciences 693 507 267 143 1 20 95 14 5 10 27 6 1,788
3: Natural Resources & Conservation 260 433 219 114 2 10 445 67 8 12 80 9 1,659
4: Architecture & Related Services 91 216 224 43 6 4 102 117 13 4 14 54 12 2 902
5: Area, Ethnic, Cultural, Gender, & Group Studies 84 366 128 58 2 3 413 58 25 11 70 20 1,238
9: Communication 460 807 301 75 2 28 1,221 216 20 1 61 102 6 3,300
10: Communications Tech 312 63 9 10 97 16 6 7 520
11: Computer & Information Sciences & Support Services 1,986 857 460 126 1 127 1,051 297 59 2 1 36 59 11 5,073
12: Personal & Culinary Services 539 20 27 21 2 2 611
13: Education 975 1,158 2,204 641 36 94 1,725 2,103 299 25 1 32 111 29 5 9,438
14: Engineering 516 1,556 1,243 719 15 12 833 524 271 70 86 33 1 5,879
15: Engineering Tech 2,375 563 164 13 98 136 89 7 1 6 25 2 3,479
16: Foreign Languages 286 960 332 167 5 4 1,148 102 93 1 39 91 26 3,254
19: Family & Consumer Sciences/Human Sciences 586 368 182 59 2 13 178 48 12 1 6 24 1 1 1,481
22: Legal Professions & Studies 437 98 81 18 97 44 158 107 42 114 1 36 94 17 29 1,373
23: English Language 262 645 451 121 4 10 1,063 208 57 57 130 57 3 3,068
24: Liberal Arts 1,035 438 120 11 5 265 661 114 9 2 52 43 17 1 2,773
25: Library Science 33 7 57 12 2 2 16 2 1 1 14 2 149
26: Biological & Biomedical Sciences 370 1,222 894 793 15 28 1,678 389 349 7 75 171 58 6,049
27: Mathematics & Statistics 243 660 432 192 2 5 856 135 81 1 15 30 11 2,663
28: Military Science 5 1 2 1 1 3 13
29: Military Tech 8 2 3 1 9 9 1 33
30: Multi/Interdisciplinary Studies 440 716 372 115 6 33 1,023 259 52 4 2 45 139 27 1 3,234
31: Parks & Rec 341 474 253 53 3 18 571 103 6 1 9 21 6 1,859
32: Basic Skills & Developmental/Remedial Education 18 1 2 1 22
33: Citizenship Activities 1 2 3
34: Health-Related Knowledge & Skills 4 2 1 4 1 1 14 2 1 30
35: Interpersonal & Social Skills 1 1 2
36: Leisure & Recreational Activities 12 10 3 1 21 1 7 22 6 83
37: Personal Awareness & Self-Improvement 1 1
38: Philosophy & Religious Studies 76 435 117 72 1 20 980 161 80 8 17 43 26 1 2,037
39: Theology & Religious Vocations 2 1 144 861 567 167 60 3 16 42 26 1 1,890
40: Physical Sciences 440 1,262 604 418 3 10 1,232 176 167 1 33 67 41 1 4,455
41: Science Technologies/Technicians 171 11 7 1 3 9 1 7 15 5 230
42: Psychology 259 584 477 257 8 36 1,053 424 189 13 61 127 34 3 3,525
43: Homeland Security 1,253 392 195 25 106 476 161 4 2 20 3 1 2,638
44: Public Admin & Social Services 375 474 495 111 8 40 509 254 45 4 6 73 7 2 2,403
45: Social Sciences 734 2,092 826 400 13 27 2,391 276 158 4 1 142 385 122 2 7,573
46: Construction Trades 464 11 1 21 4 3 1 505
47: Mechanic & Repair Technologies/Technicians 1,059 19 41 8 1,127
48: Precision Production 433 2 1 13 5 2 456
49: Transportation & Materials Moving 114 57 7 1 10 35 5 2 1 2 234
50: Visual & Performing Arts 1,442 1,746 637 144 8 83 2,585 393 69 1 2 128 225 54 1 7,518
51: Health Professions & Related Programs 4,288 1,929 1,407 575 299 486 1,794 1,306 406 216 3 45 168 41 44 13,007
52: Business 3,669 2,688 1,131 143 18 415 3,556 1,554 109 24 1 129 387 25 3 13,852
53: High School/Secondary Diplomas 1 1 2 1 5
54: History 165 480 271 103 3 9 737 83 48 40 90 46 1 2,076
60: Residency Programs 1 4 1 1 1 6 2 16

Table 2.3—Title IV Enrollment of Non-GE Programs by CIP2, Credential Level, and Control

Public Private, nonprofit Foreign Total
Assoc. Bach. Master's Doct. Prof. Assoc. Bach. Master's Doct. Prof. Assoc. Bach. Master's Doct. Prof.
1: Agriculture & Related Sciences 24,100 65,500 5,300 1,300 <50 700 5,200 200 <50 <50 100 <50 102,500
3: Natural Resources & Conservation 10,200 50,800 5,300 1,400 <50 300 15,700 2,200 200 100 100 <50 86,300
4: Architecture & Related Services 5,300 24,000 8,400 500 300 100 7,700 4,300 100 100 <50 100 <50 <50 51,000
5: Area, Ethnic, Cultural, Gender, & Group Studies 2,700 21,100 2,100 900 <50 <50 7,700 1,100 600 <50 200 <50 36,500
9: Communication 40,900 228,200 8,400 1,500 <50 500 91,800 9,700 300 <50 200 300 <50 381,800
10: Communications Tech 22,200 7,600 100 300 7,600 500 <50 <50 38,400
11: Computer & Information Sciences & Support Services 200,300 210,200 18,000 1,500 200 10,000 89,200 14,400 700 <50 <50 100 100 <50 544,700
12: Personal & Culinary Services 47,900 1,000 9,700 6,900 100 <50 65,600
13: Education 140,600 318,400 195,800 29,700 1,800 4,500 147,400 175,600 27,500 1,900 0 100 200 100 <50 1,043,600
14: Engineering 73,900 352,200 26,400 8,100 100 300 85,200 10,500 3,100 200 100 <50 0 560,300
15: Engineering Tech 120,400 61,800 4,700 200 5,200 8,700 2,400 200 0 <50 <50 0 203,500
16: Foreign Languages 14,600 51,800 3,900 1,800 <50 100 20,900 1,000 700 <50 100 200 <50 95,100
19: Family & Consumer Sciences/Human Sciences 83,500 78,700 5,500 700 <50 1,900 18,900 2,500 100 <50 <50 100 <50 0 191,800
22: Legal Professions & Studies 33,700 13,200 2,700 3,900 30,900 2,900 7,200 5,400 9,200 48,200 0 100 200 <50 100 157,900
23: English Language 26,500 110,700 11,200 3,800 <50 100 45,800 8,400 1,000 200 300 100 <50 208,200
24: Liberal Arts 2,048,400 549,800 9,300 300 100 44,600 263,200 4,900 200 <50 900 400 100 <50 2,922,000
25: Library Science 900 300 11,000 100 100 <50 2,000 <50 100 <50 100 <50 14,600
26: Biological & Biomedical Sciences 94,700 419,700 17,400 11,000 100 800 163,100 11,000 5,100 200 200 400 100 724,000
27: Mathematics & Statistics 21,500 62,500 6,300 2,200 <50 <50 24,800 1,400 500 <50 <50 <50 <50 119,200
28: Military Science <50 <50 <50 <50 <50 <50 100
29: Military Tech 2,700 500 <50 <50 900 700 <50 4,800
30: Multi/Interdisciplinary Studies 147,300 185,400 10,400 1,600 <50 1,500 48,300 7,300 1,100 <50 <50 200 500 100 <50 403,800
31: Parks & Rec 43,100 170,200 12,300 1,000 <50 1,100 64,300 7,500 300 <50 <50 100 <50 300,000
32: Basic Skills & Developmental/Remedial Education 400 <50 200 100 600
33: Citizenship Activities <50 <50 <50
34: Health-Related Knowledge & Skills 700 500 <50 100 <50 <50 <50 <50 <50 1,400
35: Interpersonal & Social Skills <50 <50 <50
36: Leisure & Recreational Activities 600 700 <50 <50 700 <50 <50 <50 <50 2,100
37: Personal Awareness & Self-Improvement <50 <50
38: Philosophy & Religious Studies 2,100 18,400 1,100 1,000 <50 2,100 23,600 3,100 1,600 100 <50 100 100 <50 53,200
39: Theology & Religious Vocations <50 <50 5,700 51,800 38,100 4,500 2,300 <50 100 100 100 <50 102,800
40: Physical Sciences 44,300 114,300 7,000 7,500 <50 100 33,700 1,100 2,500 0 100 100 100 <50 210,700
41: Science Technologies/Technicians 16,300 1,500 100 <50 100 400 <50 <50 <50 <50 18,500
42: Psychology 81,000 330,000 24,900 9,700 100 3,100 157,300 49,200 16,100 500 300 300 100 <50 672,500
43: Homeland Security 218,200 167,500 13,100 500 12,500 84,800 12,000 100 <50 <50 <50 <50 508,700
44: Public Admin & Social Services 53,800 100,500 66,200 2,200 900 5,500 49,700 45,500 1,000 500 <50 100 <50 <50 326,100
45: Social Sciences 82,800 320,200 15,500 7,400 200 300 125,700 11,900 2,300 <50 0 800 1,700 300 <50 569,200
46: Construction Trades 18,300 1,100 <50 1,000 100 <50 <50 20,500
47: Mechanic & Repair Technologies/Technicians 71,000 700 7,700 1,200 80,700
48: Precision Production 23,700 <50 <50 600 100 <50 24,400
49: Transportation & Materials Moving 6,900 11,900 300 <50 1,300 9,800 1,400 <50 <50 <50 31,700
50: Visual & Performing Arts 118,600 215,900 14,300 3,400 <50 3,000 137,400 12,800 1,100 <50 <50 600 900 100 <50 508,200
51: Health Professions & Related Programs 902,300 591,600 123,300 37,800 91,500 98,700 328,300 154,900 54,800 75,400 <50 200 600 1,000 1,400 2,461,800
52: Business 641,600 876,800 124,200 2,000 1,000 40,500 490,100 190,400 6,700 1,100 0 600 1,200 <50 <50 2,376,100
53: High School/Secondary Diplomas <50 1,600 <50 <50 1,600
54: History 9,000 63,800 5,900 2,200 <50 100 25,700 2,400 1,000 100 300 100 0 110,500
60: Residency Programs 0 <50 <50 <50 <50 <50 <50 100
Note: Counts rounded to the nearest 100.

GE programs are non-degree programs, including diploma and certificate programs, at public and private nonprofit institutions and educational programs at for-profit institutions of higher education regardless of program length or credential level. Common GE programs provide training for occupations in fields such as cosmetology, business administration, medical assisting, dental assisting, nursing, and massage therapy. There were 32,058 GE programs in the 2022 PPD. About two-thirds of these programs are at public institutions, 11 percent at private nonprofit institutions, and 21 percent at for-profit institutions. In AY 2016 or 2017, these programs annually served approximately 2.9 million students who received title IV, HEA aid. The Federal investment in students attending GE programs is significant and growing. In AY 2022, students enrolled in GE programs received approximately $5 billion in Federal Pell grant funding and approximately $11 billion in Federal student loans. Table 2.4 displays the number of GE programs grouped by two-digit CIP code, credential level, and institutional control in the 2022 PPD. Table 2.5 displays enrollment of students receiving title IV, HEA program funds in GE programs in the same categories.

“For-profit” and “proprietary” are used interchangeably throughout this RIA. Foreign schools are schools located outside of the United States at which eligible US students can use Federal student aid.

Note that the 2022 PPD will differ from the universe of programs that are subject to the final GE regulations for the reasons described in more detail in the “Data Used in this RIA” section, including that the 2022 PPD includes programs defined by four-digit CIP code while the rule defines programs by six-digit CIP code.

Table 2.4—Number of GE Programs by CIP2, Credential Level, and Control

Public Private, nonprofit Proprietary Foreign Total
UG certs Post-BA cert Grad cert UG certs Post-BA cert Grad cert UG certs Assoc. Bach. Post-BA cert Master's Doct. Prof. Grad cert UG certs Post-BA cert Master's Doct. Prof. Grad cert
1: Agriculture & Related Sciences 375 4 3 7 2 11 4 1 1 1 409
3: Natural Resources & Conservation 91 10 21 8 1 2 2 5 1 1 1 143
4: Architecture & Related Services 29 10 10 4 1 8 1 4 3 2 1 1 74
5: Area, Ethnic, Cultural, Gender, & Group Studies 61 14 42 14 4 12 1 1 3 1 153
9: Communication 171 12 38 25 7 16 14 14 25 9 1 1 2 335
10: Communications Tech 272 2 2 3 3 3 24 23 24 1 3 1 361
11: Computer & Information Sciences & Support Services 1,479 28 64 51 31 36 140 168 110 1 41 4 8 1 2,162
12: Personal & Culinary Services 788 2 2 34 1 900 79 11 4 6 3 4 7 2 1,843
13: Education 461 222 494 62 134 406 35 20 33 8 63 23 1 29 1 2 5 1,999
14: Engineering 98 31 62 10 6 33 4 5 10 5 1 1 1 267
15: Engineering Tech 1,453 5 21 34 4 4 84 71 21 1 4 1 3 1,706
16: Foreign Languages 205 15 9 37 5 3 2 2 278
19: Family & Consumer Sciences/Human Sciences 530 7 23 18 5 7 10 8 11 1 2 1 2 625
22: Legal Professions & Studies 285 18 15 35 15 26 36 66 24 4 5 1 8 2 12 552
23: English Language 79 18 35 13 5 6 11 5 11 2 2 3 190
24: Liberal Arts 329 15 22 22 18 19 1 10 12 2 1 1 1 453
25: Library Science 22 7 16 1 5 1 52
26: Biological & Biomedical Sciences 69 22 61 22 14 25 2 1 8 1 2 1 1 3 2 234
27: Mathematics & Statistics 18 12 26 10 2 3 2 73
28: Military Science 1 1 1 1 1 5
29: Military Tech 6 1 1 3 1 2 1 1 16
30: Multi/Interdisciplinary Studies 156 51 105 26 23 36 5 4 14 2 6 5 2 435
31: Parks & Rec 145 7 15 14 3 9 25 25 8 2 1 1 1 1 257
32: Basic Skills & Developmental/Remedial Education 26 4 1 7 1 39
33: Citizenship Activities 1 1
34: Health-Related Knowledge & Skills 4 3 1 2 5 15
35: Interpersonal & Social Skills 1 1
36: Leisure & Recreational Activities 5 2 1 1 9
37: Personal Awareness & Self-Improvement 1 1 1 3
38: Philosophy & Religious Studies 15 1 7 23 6 7 3 1 1 64
39: Theology & Religious Vocations 1 60 49 50 1 5 7 1 1 1 176
40: Physical Sciences 41 7 16 15 5 1 1 3 1 90
41: Science Technologies/Technicians 75 2 3 1 1 1 1 84
42: Psychology 38 23 74 19 20 59 2 14 2 19 15 7 1 3 296
43: Homeland Security 747 15 32 42 8 30 31 74 58 1 23 4 6 1,071
44: Public Admin & Social Services 161 28 59 17 6 28 3 5 14 1 19 7 4 2 1 355
45: Social Sciences 164 30 79 44 11 29 1 15 5 1 3 3 5 390
46: Construction Trades 840 28 1 62 14 1 946
47: Mechanic & Repair Technologies/Technicians 1,469 1 1 42 188 65 1 1,767
48: Precision Production 751 18 51 13 833
49: Transportation & Materials Moving 187 2 2 11 32 5 1 240
50: Visual & Performing Arts 540 16 48 75 29 36 65 85 98 1 26 1 1 8 3 10 1,042
51: Health Professions & Related Programs 4,025 124 327 386 132 274 1,261 637 174 8 101 35 11 25 2 2 3 4 7 5 7,543
52: Business 2,733 100 189 140 83 208 198 308 233 15 117 23 4 27 2 2 14 4,396
53: High School/Secondary Diplomas 4 1 1 6
54: History 18 9 7 8 1 1 6 1 1 3 55
60: Residency Programs 3 1 3 1 1 2 2 1 14

Table 2.5—Title IV Enrollment of GE Programs by CIP2, Credential Level, and Control

Public Private, nonprofit Proprietary Foreign Total
UG certs Post-BA cert Grad cert UG certs Post-BA cert Grad cert UG certs Assoc. Bach. Post-BA cert Master's Doct. Prof. Grad cert UG certs Post-BA cert Master's Doct. Prof. Grad cert
1: Agriculture & Related Sciences 5,600 <50 <50 200 <50 300 <50 <50 <50 <50 6,200
3: Natural Resources & Conservation 1,200 <50 200 100 <50 <50 100 4,400 <50 400 <50 6,400
4: Architecture & Related Services 600 <50 <50 <50 <50 <50 <50 600 200 300 0 <50 1,700
5: Area, Ethnic, Cultural, Gender, & Group Studies 800 100 300 100 100 100 <50 <50 <50 0 1,500
9: Communication 3,700 100 400 300 <50 200 3,300 400 6,700 800 <50 <50 <50 15,800
10: Communications Tech 4,700 <50 <50 <50 <50 <50 3,200 2,700 7,300 <50 200 0 18,200
11: Computer & Information Sciences & Support Services 34,500 200 1,100 1,200 300 500 8,900 20,500 52,500 <50 6,400 800 300 <50 127,100
12: Personal & Culinary Services 31,000 <50 <50 3,200 <50 176,800 7,600 1,100 <50 200 <50 <50 100 <50 220,100
13: Education 16,100 4,500 16,000 1,700 2,400 14,100 800 6,700 33,500 100 37,000 15,800 1,100 2,100 0 <50 <50 152,000
14: Engineering 8,600 200 500 300 <50 200 200 500 1,500 100 0 <50 <50 11,900
15: Engineering Tech 22,500 <50 300 1,100 <50 <50 14,500 6,300 8,000 <50 1,400 <50 <50 54,100
16: Foreign Languages 4,600 <50 <50 400 <50 <50 300 <50 5,400
19: Family & Consumer Sciences/Human Sciences 22,100 <50 200 500 100 100 600 2,100 4,500 <50 1,000 300 100 31,600
22: Legal Professions & Studies 7,100 500 400 900 400 800 1,200 6,700 2,200 200 400 <50 1,700 <50 <50 22,600
23: English Language 3,900 100 300 1,600 100 <50 4,300 700 4,300 300 <50 <50 15,700
24: Liberal Arts 139,500 500 3,000 1,400 500 600 <50 2,300 3,800 200 100 <50 <50 151,900
25: Library Science 300 100 400 <50 100 300 1,100
26: Biological & Biomedical Sciences 2,700 100 600 300 100 200 <50 <50 2,700 <50 <50 <50 0 <50 <50 6,900
27: Mathematics & Statistics 400 200 100 100 <50 <50 400 1,300
28: Military Science <50 <50 <50 200 0 200
29: Military Tech 100 <50 <50 100 <50 200 100 <50 400
30: Multi/Interdisciplinary Studies 14,100 700 1,600 500 500 500 100 3,500 25,000 <50 1,200 300 <50 48,100
31: Parks & Rec 4,000 <50 200 500 <50 100 800 1,600 5,700 500 <50 <50 <50 <50 13,500
32: Basic Skills & Developmental/Remedial Education 600 <50 <50 500 <50 1,100
33: Citizenship Activities <50 <50
34: Health-Related Knowledge & Skills 100 <50 0 <50 100 200
35: Interpersonal & Social Skills 0 0
36: Leisure & Recreational Activities 200 <50 <50 <50 300
37: Personal Awareness & Self-Improvement 100 <50 500 600
38: Philosophy & Religious Studies 200 <50 <50 200 <50 200 500 100 <50 1,200
39: Theology & Religious Vocations <50 2,300 200 1,700 <50 3,200 900 300 300 0 8,900
40: Physical Sciences 900 <50 100 100 <50 0 <50 <50 <50 1,200
41: Science Technologies/Technicians 2,200 <50 <50 <50 <50 100 100 2,400
42: Psychology 2,700 300 1,400 400 200 2,200 <50 20,300 <50 17,800 10,100 2,200 <50 <50 57,500
43: Homeland Security 33,400 200 600 1,200 100 300 2,300 21,400 60,100 0 7,000 700 200 127,500
44: Public Admin & Social Services 6,500 700 800 100 100 400 200 4,300 22,500 <50 10,100 4,400 100 <50 <50 50,100
45: Social Sciences 3,200 400 700 500 100 500 <50 6,100 1,400 700 <50 <50 <50 13,600
46: Construction Trades 18,000 1,800 <50 8,300 900 <50 28,900
47: Mechanic & Repair Technologies/Technicians 48,800 0 <50 4,100 59,200 10,400 <50 122,600
48: Precision Production 34,100 2,500 13,000 1,000 50,700
49: Transportation & Materials Moving 4,900 <50 <50 700 9,500 200 <50 15,300
50: Visual & Performing Arts 15,000 100 300 2,100 200 400 2,600 7,700 29,700 0 3,100 <50 <50 <50 <50 <50 61,200
51: Health Professions & Related Programs 275,000 1,800 7,400 43,100 1,900 7,800 229,100 148,200 139,600 <50 74,200 11,700 8,800 2,200 <50 <50 200 1,900 11,600 1,300 965,700
52: Business 95,500 1,700 4,300 4,100 700 4,500 9,800 70,500 226,500 400 74,200 9,200 100 2,900 <50 <50 100 504,300
53: High School/Secondary Diplomas <50 <50 <50 100
54: History 400 <50 <50 100 0 200 2,200 900 100 <50 3,900
60: Residency Programs <50 <50 100 <50 <50 <50 100 <50 300

Tables 2.6 and 2.7 show the student characteristics of title IV, HEA students in non-GE and GE programs, respectively, by institutional control, predominant degree of the institution, and credential level. In all three types of institutional control, the majority of students served by the programs are female students. At public non-GE programs, out of all enrolled title IV, HEA students: 58 percent received a Pell grant, 31 percent are 24 years or older, 36 percent are independent, and 43 percent non-white. At non-GE programs at nonprofit private institutions, 43 percent of students received a Pell Grant, 37 percent are 24 years or older, 44 percent are independent, and 43 percent are non-white. Sixty-eight percent of students in the average public GE program ever received a Pell grant, 44 percent are 24 years or older, 50 percent are independent, and 46 percent are non-white. At for-profit GE programs, 67 percent of students received a Pell grant, 66 percent are 24 years or older, 72 percent are independent, and 59 percent are non-white.

Table 2.6—Characteristics of Non-GE Students by Control, Predominant Degree, and Credential Level

[Enrollment-weighted]

Average EFC Percent of students who are . . .
Age 24+ Male Pell Non-white Independent
Public
Less-Than 2-Year:
Associate 5,700 36.4 37.2 73.8 41.8 41.7
Bachelor's 10,600 59.4 40.6 54.0 37.4 62.6
Master's 8,700 71.8 34.7 36.1 27.7 81.5
2-Year:
Associate 5,800 29.6 37.5 74.1 49.3 34.8
Bachelor's 9,300 48.3 41.3 69.4 40.3 55.6
Master's 7,600 79.6 37.4 52.2 63.7 90.9
Professional 5,800 100.0 33.3 33.3 100.0
4-Year or Above:
Associate 7,600 36.5 37.8 67.0 39.7 42.2
Bachelor's 16,600 24.0 43.3 47.3 39.8 27.0
Master's 11,900 60.6 35.9 32.9 40.2 72.7
Doctoral 10,400 69.9 41.4 28.0 44.1 84.1
Professional 7,800 55.7 48.4 10.8 37.1 91.7
Total:
Total 11,300 30.5 40.2 57.8 43.2 35.6
Private, Nonprofit
Less-Than 2-Year:
Associate 2,600 64.6 33.8 89.7 65.9 74.8
Bachelor's 9,100 65.8 37.1 67.0 62.6 70.0
Master's 9,200 52.2 30.7 37.7 56.3 61.4
Doctoral 5,500 24.7 14.6 32.1 41.2 58.5
Professional 4,600 52.0 54.6 1.9 39.6 97.1
2-Year:
Associate 6,300 47.4 34.8 72.4 52.2 53.6
Bachelor's 8,300 60.7 40.7 68.3 51.4 64.8
Master's 9,600 86.5 34.0 28.9 69.9 89.2
Doctoral 9,600 81.3 26.4 14.6 62.5 100.0
4-Year or Above:
Associate 6,800 54.9 34.6 70.2 49.3 60.5
Bachelor's 17,600 23.2 39.9 48.9 40.2 26.1
Master's 13,100 67.3 35.3 25.0 45.9 78.0
Doctoral 12,200 69.4 41.1 17.7 49.7 87.1
Professional 9,200 57.2 48.8 10.1 43.0 89.1
Total:
Total 15,400 37.3 39.0 43.3 42.6 43.5
Note: Average EFC values rounded to the nearest 100. Credential levels with very few programs and most table elements missing are suppressed.

Table 2.7—Characteristics of GE Students by Control, Predominant Degree, and Credential Level

Average EFC Percent of students who are . . .
Age 24+ Male Pell Non-white Independent
Public
Less-Than 2-Year:
UG Certificates 4,500 45.5 37.5 76.5 42.4 53.1
Post-BA Certs 6,300 75.9 30.4 57.9 78.2
Grad Certs 8,100 57.1 16.7 57.5 32.1 65.2
2-Year:
UG Certificates 6,100 41.9 37.8 70.3 50.9 46.8
Post-BA Certs 10,800 47.2 23.7 58.4 59.5
Grad Certs 7,600 89.7 68.1 68.9 50.6 89.7
4-Year or Above:
UG Certificates 23,300 28.5 41.6 36.8 32.3 31.8
Post-BA Certs 11,500 60.5 31.6 35.9 71.3
Grad Certs 10,700 69.8 30.1 39.2 36.2 79.0
Total:
Total 7,100 43.7 37.6 68.3 45.7 49.8
Private, Nonprofit
Less-Than 2-Year:
UG Certificates 4,900 48.3 36.6 80.2 63.7 58.3
Post-BA Certs 15,600 51.0 59.2 3.3 65.3
Grad Certs 7,600 28.2 38.7 3.1 47.2 62.1
2-Year:
UG Certificates 3,300 61.0 21.1 83.2 56.3 73.8
Post-BA Certs 10,100 94.8 28.4 53.7 94.8
Grad Certs 26,700 89.5 10.5 19.3 100.0 100.0
4-Year or Above:
UG Certificates 10,500 37.4 35.8 66.4 65.8 42.1
Post-BA Certs 14,200 60.1 31.8 36.0 68.5
Grad Certs 11,500 70.8 32.8 29.8 44.5 80.3
Total:
Total 8,300 55.1 32.3 60.6 57.3 64.2
Proprietary
Less-Than 2-Year:
UG Certificates 3,900 45.7 31.5 82.4 63.0 56.5
Associate 5,900 56.6 32.2 80.6 63.2 63.7
Bachelor's 4,200 54.2 36.9 86.5 83.3 57.3
Post-BA Certs 9,100 70.7 44.7 36.8 77.2
Master's 9,200 85.4 26.7 32.2 62.1 90.4
Doctoral 9,800 98.6 19.2 32.0 47.6 99.7
Professional 14,100 84.7 19.5 30.5 54.2 100.0
Grad Certs 6,200 64.6 7.7 63.9 6.6 67.4
2-Year:
UG Certificates 4,800 48.4 39.8 77.8 64.2 57.1
Associate 5,700 51.8 33.3 77.8 60.6 58.1
Bachelor's 7,900 61.6 42.7 70.5 65.0 67.9
Post-BA Certs 13,400 86.4 25.0 39.4 86.4
Master's 7,100 82.3 42.1 31.0 65.1 89.5
Doctoral 0 0.0 0.0 100.0 0.0
Professional 5,700 71.6 46.0 14.6 36.7 99.0
Grad Certs 3,700 64.8 32.4 0.0 24.3 67.6
4-Year or Above:
UG Certificates 5,400 77.7 22.1 76.2 55.4 84.3
Associate 5,400 75.4 31.9 76.1 57.2 82.7
Bachelor's 9,700 75.2 40.7 64.2 54.6 78.8
Post-BA Certs 7,500 84.6 28.5 54.7 92.3
Master's 11,300 82.3 30.2 38.8 58.0 85.8
Doctoral 19,800 92.9 30.0 25.2 57.9 95.2
Professional 7,100 89.0 25.7 47.1 34.1 93.2
Grad Certs 11,900 88.6 27.1 38.2 63.2 90.7
Total:
Total 7,700 66.1 34.7 67.3 58.8 72.4
Note: EFC values rounded to the nearest 100.

Outcome Differences Across Programs

A large body of research provides strong evidence of the many significant benefits that postsecondary education and training confers, both private and social. Private pecuniary benefits include higher wages and lower risk of unemployment. Increased educational attainment also confers private nonpecuniary benefits, such as better health, job satisfaction, and overall happiness. Social benefits of higher or increased number of individuals with a postsecondary education include productivity spillovers from a better educated and more flexible workforce, increased civic participation, and improvements in health and well-being for the next generation. Improved productivity and earnings increase tax revenues from higher earnings and lower rates of reliance on social safety net programs. Even though the costs of postsecondary education have risen, there continues to be evidence that the average financial returns to graduates have also generally increased since at least the 1980s.

Barrow, L., & Malamud, O. (2015). Is College a Worthwhile Investment? Annual Review of Economics, 7(1), 519–555. Card, D. (1999). The causal effect of education on earnings. Handbook of labor economics, 3, 1801–1863.

Oreopoulos, P., & Salvanes, K.G. (2011). Priceless: The Nonpecuniary Benefits of Schooling. Journal of Economic Perspectives, 25(1), 159–184.

Moretti, E. (2004). Workers' Education, Spillovers, and Productivity: Evidence from Plant-Level Production Functions. American Economic Review, 94(3), 656–690.

Dee, T.S. (2004). Are There Civic Returns to Education? Journal of Public Economics, 88(9–10), 1697–1720.

Currie, J., & Moretti, E. (2003). Mother's Education and the Intergenerational Transmission of Human Capital: Evidence from College Openings. The Quarterly Journal of Economics, 118(4), 1495–1532.

Avery, C. & Turner, S. (2013). Student Loans: Do College Students Borrow Too Much-Or Not Enough? Journal of Economic Perspectives, 26(1), 165–192. Goldin, C. & Katz, L. (2008). The Race Between Education and Technology. Harvard University Press.

However, there is also substantial heterogeneity in earnings and other outcomes for students who graduate from different types of institutions and programs. Table 2.8 shows the enrollment-weighted average borrowing and default by control and credential level. Mean borrowing amounts are for title IV, HEA recipients who completed their program in AY 2016 or 2017, with students who did not borrow counting as having borrowed $0. For borrowing, our measure is the average for each institutional control type and credential level combination of program average debt. For default, our measure is, among borrowers (regardless of completion status) who entered repayment in 2017, the fraction of borrowers who have ever defaulted three years later. The cohort default rate measure follows the methodology for the official institutional cohort default rate measures calculated by the Department, except done at the program level. Though average debt tends to be higher for higher-level credential programs, default rates tend to be lower. At the undergraduate level, average debt is much lower for public programs than private nonprofit and for-profit programs and default rates are lower for public and nonprofit programs than those at for-profit institutions.

Table 2.8—Average Debt and Cohort Default Rate, by Control and Credential Level

[Enrollment-weighted]

Average debt Cohort default rate
Public:
UG Certificates 5,759 16.9
Associate 5,932 17.4
Bachelor's 17,935 7.6
Post-BA Certs 7,352 2.3
Master's 29,222 2.9
Doctoral 71,102 2.9
Professional 124,481 0.8
Grad Certs 24,883 2.5
Private, Nonprofit:
UG Certificates 9,367 12.0
Associate 16,445 14.9
Bachelor's 20,267 7.3
Post-BA Certs 9,497 2.8
Master's 40,272 2.9
Doctoral 128,998 2.3
Professional 151,473 1.3
Grad Certs 40,732 2.4
Proprietary:
UG Certificates 8,857 14.2
Associate 18,766 15.3
Bachelor's 29,038 12.4
Post-BA Certs 15,790 16.9
Master's 39,507 4.1
Doctoral 99,422 4.4
Professional 96,836 0.7
Grad Certs 47,803 3.9
Foreign Private:
UG Certificates (*) 0.0
Associate (*) (*)
Bachelor's 17,074 7.0
Post-BA Certs (*) (*)
Master's 40,432 2.0
Doctoral 22,600 3.5
Professional 247,269 3.1
Grad Certs 284,200 0.2
Foreign For-Profit:
Master's (*) 0.0
Doctoral 84,200 1.4
Professional 280,667 1.3
* Cell suppressed because it based on a population of fewer than 30.

Table 2.9 shows median earnings (in 2019 dollars) for graduates (whether or not they borrow) along these same dimensions. Similar patterns hold for earnings, with lower earnings in proprietary programs than in public and nonprofit programs for almost all types of credential level.

Table 2.9—Enrollment-Weighted Average of Program Median Earnings 3 Years After Program Completion, by Control and Credential Level

Median earnings 3 years after completion
Public:
UG Certificates 33,400
Associate 34,400
Bachelor's 46,100
Post-BA Certs 45,600
Master's 66,600
Doctoral 83,500
Professional 91,300
Grad Certs 71,500
Private, Nonprofit:
UG Certificates 26,200
Associate 35,700
Bachelor's 48,800
Post-BA Certs 61,600
Master's 68,600
Doctoral 86,200
Professional 88,200
Grad Certs 74,800
Proprietary:
UG Certificates 25,400
Associate 34,600
Bachelor's 45,600
Post-BA Certs 43,500
Master's 59,300
Doctoral 78,000
Professional 49,200
Grad Certs 52,200
Foreign Private:
UG Certificates
Associate
Bachelor's 8,200
Post-BA Certs
Master's 38,600
Doctoral
Professional 88,400
Grad Certs 15,100
Foreign For-Profit:
Master's
Doctoral 65,900
Professional 100,400
Note: Values rounded to the nearest 100.

A growing body of research, described below, shows that differences in institution and program quality are important contributors to the variation in borrowing and earnings outcomes described above. That is, differences in graduates' outcomes across programs are not fully (or primarily) explained by the characteristics of the students that attend. Differences in program quality—measured by the causal effect of attending the program on its students' outcomes—are important. It is, therefore, important to provide students with this information and to hold programs accountable for high levels of student debt and poor earnings outcomes. Research reviewed below also shows that GE programs are the programs least likely to reliably provide an adequate return on investment, from the perspective of both the student and society. These findings imply that aggregate student outcomes—including their earnings and likelihood of positive borrowing outcomes—would be improved by limiting student enrollment in low-quality programs.

Black, Dan A. & Smith, Jeffrey A. (2006). Estimating the Returns to College Quality with Multiple Proxies for Quality. Journal of labor Economics 24.3: 701–728. Cohodes, Sarah R. & Goodman, Joshua S. (2014). Merit Aid, College Quality, and College Completion: Massachusetts' Adams Scholarship as an In-Kind Subsidy. American Economic Journal: Applied Economics 6.4: 251–285. Andrews, Rodney J., Li, Jing & Lovenheim, Michael F. (2016). Quantile treatment effects of college quality on earnings. Journal of Human Resources 51.1: 200–238. Dillon, Eleanor Wiske & Smith, Jeffrey Andrew (2020). The Consequences of Academic Match Between Students and Colleges. Journal of Human Resources 55.3: 767–808.

A recent study computed productivity—value-added per dollar of social investment—for 6,700 undergraduate programs across the United States. In that study, productivity was measured using both private (individual earnings) and social (working in a public service job) notions of value. A main finding was that productivity varied widely even among institutions serving students of similar aptitude, especially at less selective institutions. That is, a dollar spent educating students does much more to increase lifetime earnings potential and public service at some programs than others. The author concludes that “market forces alone may be too weak to discipline productivity among these schools.”

Hoxby, C.M. (2019). The Productivity of US Postsecondary Institutions. In Productivity in Higher Education, Hoxby, C.M. & Stange, K.M. (eds). University of Chicago Press: Chicago.

The finding of substantial variation in student outcomes across programs serving similar students or at similar types of institutions or in similar fields has been documented in many other more specific contexts. These include community colleges in California, public two- and four-year programs in Texas, master's degree programs in Ohio, law and medical schools, and programs outside the United States. Variation in institutional and program performance is a dominant feature of postsecondary education in the United States.

Carrell, S.E. & Kurleander, M. (2019). Estimating the Productivity of Community Colleges in Paving the Road to Four-Year College Success. In Productivity in Higher Education, Hoxby, C.M. & Stange, K.M. (eds). University of Chicago Press: Chicago.

Andrews, R.J. & Stange, K.M. (2019). Price Regulation, Price Discrimination, and Equality of Opportunity in Higher Education: Evidence from Texas. American Economic Journal: Economic Policy, 11.4, 31–65. Andrews, R.J., Imberman, S.A., Lovenheim, M.F. & Stange, K.M. (2022). The Returns to College Major Choice: Average and Distributional Effects, Career Trajectories, and Earnings Variability. NBER Working Paper w30331.

Minaya, V., Scott-Clayton, J. & Zhou, R.Y. (2022). Heterogeneity in Labor Market Returns to Master's Degrees: Evidence from Ohio (EdWorkingPaper: 22–629). Retrieved from Annenberg Institute at Brown University: doi.org/10.26300/akgd<5011.

Hastings, J.S., Neilson, C.A. & Zimmerman, S.D. (2013). Are Some Degrees Worth More than Others? Evidence from College Admission Cutoffs in Chile. NBER Working Paper w19241.

A recent overview can be found in Lovenheim, M. & J. Smith (2023). Returns to Different Postsecondary Investments: Institution Type, Academic Programs, and Credentials. In Handbook of the Economics of Education Volume 6, E. Hanushek, L. Woessmann & S. Machin (eds). New Holland.

The wide range of performance across programs and institutions means that prospective students face a daunting information problem. The questions of where to go and what to study are key life choices with major consequences. But without a way to discern the differences between programs through comparable, reliably reported measures of quality, students may ultimately have to rely on crude signals about the caliber of education a school offers.

Recent evidence demonstrates that information about colleges, delivered in a timely and relevant way, can shape students' choices. Students at one large school district were 20 percent more likely to apply to colleges that have information listed on a popular college search tool, compared with colleges whose information is not displayed on the tool. A particularly important finding of the study is that for Black, Hispanic, and low-income students, access to information about local public four-year institutions increases overall attendance at such institutions. This, the author argues, suggests “that students may have been unaware of these nearby and inexpensive options with high admissions rates.”

Mulhern, Christine (2021). Changing College Choices with Personalized Admissions Information at Scale: Evidence on Naviance. Journal of Labor Economics 39.1: 219–262.

This evidence reveals both the power of information to shape student choices at critical moments in the decision process and how a patchwork of information about colleges may result in students missing out on opportunities. Given the variation in quality across programs apparent in the research evidence outlined above, these missed opportunities can be quite costly.

Unfortunately, the general availability of information does not always mean students are able to find and use it. Indeed, evidence on the initial impact of the Department's College Scorecard college comparison tool found minimal effects on students' college choices, with any possible effects concentrated among the highest achieving students. But the contrast between these two pieces of evidence, one where information affects college choices and one where it doesn't, is instructive: while students generally must seek out the College Scorecard during their college search process, the college search tool from the first study delivers information to students as they are taking other steps through the tool, from requesting transcripts and recommendation letters to submitting applications. It tailors that information to the student, providing information about where previous students from the same high school have enrolled and what their outcomes were. Accordingly, there is some basis to believe that personalized information delivered directly to students at key decision points from a credible source can have an impact.

Hurwitz, Michael & Smith, Jonathan (2018). Student Responsiveness to Earnings Data in the College Scorecard. Economic Inquiry 56.2: 1220–1243.

To that end, the transparency component of these regulations attempts to improve not only the quality of information available to students (by newly collecting key facts about colleges), but also its salience, relevance, and timing. Because this information will be delivered directly to students who are reviewing financial aid packages from colleges and programs which they are considering, students would be likely to see the information and understand its credibility at a time when they are likely to find it most useful for deciding if and where to attend. Better still, the information would not be ambiguous when the message is most critical: if a school is consistently failing to put graduates on better financial footing, students are informed of that fact before they make a financial commitment.

The Department has concluded that relying on just market-disciplining role of information is not sufficient, and that regulation beyond information provision alone is warranted. This conclusion is based on evidence, reviewed below, that such regulations could reduce the risk that students and taxpayers spend money toward programs that will leave them worse off. Program performance is particularly varied and concerning among the non-degree certificate programs offered by all types of institutions, as well as at proprietary degree programs. These are the programs where the Department's concerns about quality are at their height, especially given the narrower career-focused nature of the credentials offered in this part of the system.

Certificate programs are intended to prepare students for specific vocations and have, on average, positive returns relative to not attending college at all. Yet this aggregate performance masks considerable variability: certificate program outcomes vary greatly across programs, States, fields of study, and institutions, and even within the same narrow field and within the same institution. Qualitative research suggests some of this outcome difference stems from factors that providers directly control, such as how they engage with industry and employers in program design and whether they incorporate opportunities for students to gain relevant workforce experience during the program. Unfortunately, many of the most popular certificate programs do not result in returns on investment for students who complete the program. An analysis of programs included in the 2014 GE rule found that at 10 of the 15 certificate programs with the most graduates, graduates had typical earnings of $18,000 or less, well below what a typical high school graduate would earn.

Aspen Institute (2015). From College to Jobs: Making Sense of Labor Market Returns to Higher Education. Washington, DC ( www.aspeninstitute.org/publications/labormarketreturns/ ).

Much of the research is summarized in Ositelu, M.O., McCann, C. & Laitinen, A. (2021). The Short-Term Credential Landscape. New America: Washington, DC ( www.newamerica.org/education-policy/repoerts/the-short-term-credentials-landscape ).

Soliz, A. (2016). Preparing America's Labor Force: Workforce Development Programs in Public Community Colleges. Brookings: Washington, DC ( www.brookings.edu/research/preparing-americas-labor-force-workforce-development-programs-in-public-community-colleges/ ).

Aspen Institute (2015). From College to Jobs: Making Sense of Labor Market Returns to Higher Education. Washington, DC ( www.aspeninstitute.org/publications/labormarketreturns ).

In addition to non-degree programs at all types of institutions, the final rule will subject for-profit degree programs to the transparency framework in § 668.43 and subpart Q, and the GE program-specific eligibility requirements in subpart S. This additional scrutiny, based in the requirements of the HEA, is warranted because for-profit programs have demonstrated particularly poor outcomes, as was shown in Tables 2.8 and 2.9 above. A large body of research provides causal evidence on the many ways students at for-profit colleges are at an economic disadvantage upon exiting their institutions. This research base includes studies showing that students who attend for-profit programs are significantly more likely to suffer from poor employment prospects, low earnings, and loan repayment difficulties. Students who transfer into for-profit institutions instead of public or nonprofit institutions face significant wage penalties. In some cases, researchers find similar earnings or employment outcomes between for-profit and not-for-profit associate and bachelor's degree programs. However, students pay and borrow more to attend for-profit degree programs, on average. The result of higher debt levels paired with lower or equivalent earnings means students attending for-profit degree programs have a worse overall return on investment. This evidence of lackluster labor market outcomes accords with the growing evidence that many for-profit programs may not be preparing students for careers as effectively as comparable programs at public institutions. A 2011 GAO report found that, for nine out of 10 licensing exams in the largest fields of study, graduates of for-profit institutions had lower passage rates than graduates of public institutions. These comparatively poor outcomes may not be surprising, as many for-profit institutions devote more resources to recruiting and marketing than to instruction or student support services. A 2012 investigation by the U.S. Senate Committee on Health, Education, Labor, and Pensions (Senate HELP Committee) found that almost 23 percent of revenues at proprietary institutions were spent on marketing and recruiting but only 17 percent on instruction. The report further found that at many institutions, the number of recruiters greatly outnumbered the career services and support services staff.

Deming, D.J., Yuchtman, N., Abulafi, A., Goldin, C. & Katz, L.F. (2016). The Value of Postsecondary Credentials in the Labor Market: An Experimental Study. American Economic Review, 106(3), 778–806.

Cellini, S.R. & Chaudhary, L. (2014). The Labor Market Returns to a For-Profit College Education. Economics of Education Review, 43, 125–140.

Armona, L., Chakrabarti, R. & Lovenheim, M.F. (2022). Student Debt and Default: The Role of For-Profit Colleges. Journal of Financial Economics, 144(1), 67–92.

Liu, V.Y.T. & Belfield, C. (2020). The Labor Market Returns to For-Profit Higher Education: Evidence for Transfer Students. Community College Review, 48(2), 133–155.

Lang, K. & Weinstein, R. (2013). The Wage Effects of Not-For-Profit and For-Profit Certifications: Better Data, Somewhat Different Results. Labour Economics, 24, 230–243.

Cellini, S.R. & Darolia, R. (2015). College Costs and Financial Constraints. In Hershbein, B. & Hollenbeck, K. (ed). Student Loans and the Dynamics of Debt (137–174). W.E. Upjohn Institute for Employment Research: Kalamazoo, MI. Cellini, S.R. & Darolia, R. (2017). High Costs, Low Resources, and Missing Information: Explaining Student Borrowing in the For-Profit Sector. The ANNALS of the American Academy of Political and Social Science, 671(1), 92–112.

Government Accountability Office (2011). Postsecondary Education: Student Outcomes Vary at For-Profit, Nonprofit, and Public Schools (GAO–12–143).

U.S. Senate, Health, Education, Labor and Pensions Committee (July 30, 2012). For Profit Higher Education: The Failure to Safeguard the Federal Investment and Ensure Student Success. Senate HELP Committee, July 30, 2012.

Particularly strong evidence comes from a recent study that found that the average undergraduate certificate-seeking student that attended a for-profit institution did not experience any earnings gains relative to the typical worker in a matched sample of high school graduates. They also had significantly lower earnings gains than students who attended certificate programs in the same field of study at public institutions. Furthermore, the earnings gain for the average for-profit certificate-seeking student was not sufficient to compensate them for the amount of student debt taken on to attend the program. At the same time, research also shows substantial variation in earnings gains from title IV, HEA-eligible undergraduate certificate programs by field of study, with students graduating from cosmetology and personal services programs in all sectors experiencing especially poor outcomes.

Cellini, S.R. & Turner, N. (2019). Gainfully Employed? Assessing the Employment and Earnings of For-Profit College Students using Administrative Data. Journal of Human Resources, 54(2), 342–370.

Id.

Lang, K. & Weinstein, R. (2013). The Wage Effects of Not-For-Profit and For-Profit Certifications: Better Data, Somewhat Different Results. Labour Economics, 24, 230–243.

Dadgar, M. & Trimble, M.J. (2015). Labor Market Returns to Sub-Baccalaureate Credentials: How Much Does a Community College Degree or Certificate Pay? Educational Evaluation and Policy Analysis, 37(4), 399–418.

Consequences of Attending Low Financial Value Programs

Attending a postsecondary education or training program where the typical student takes on debt that exceeds their capacity to repay can cause substantial harm to borrowers. For instance, high debt may cause students to delay certain milestones; research shows that high levels of debt decreases students' long-term probability of marriage. Being overburdened by student loan payments can also reduce the likelihood that borrowers will invest in their future. Research shows that when students borrow more due to high tuition, they are less likely to obtain a graduate degree and less likely to take out a mortgage to purchase a home after leaving college.

Gicheva, D. (2016). Student Loans or Marriage? A Look at the Highly Educated. Economics of Education Review, 53, 207–2016.

Chakrabarti, R., Fos, V., Liberman, A. & Yannelis, C. (2023). Tuition, Debt, and Human Capital. The Review of Financial Studies, 36(4), 1667–1702.

Mezza, A., Ringo, D., Sherlund, S. & Sommer, K. (2020). Student Loans and Homeownership. Journal of Labor Economics, 38(1), 215–260.

Unmanageable debt can also have adverse financial consequences for borrowers, including default on their student loans. For those who do not complete a degree, more student debt may raise the probability of bankruptcy. Borrowers who default on their loans face potentially serious repercussions. Many aspects of borrowers' lives may be affected, including their ability to sign up for utilities, obtain insurance, or rent an apartment. The Department reports loans more than 90 days delinquent or in default to the major national credit bureaus, and being in default has been shown to be correlated with a 50-to-90-point drop in borrowers' credit scores. A defaulted loan can remain on borrowers' credit reports for up to seven years and lead to higher costs that make insurance, housing, and other services and financial products less affordable and, in some cases, harm borrowers' ability to get a job. Borrowers who default also lose access to some repayment options and flexibilities. At the same time, their full balances are accelerated and become due immediately, and borrowers become subject to involuntary collections such as administrative wage garnishment and Treasury offset which can result in the redirection of income tax refunds toward the defaulted loan.

Gicheva, D. & Thompson, J. (2015). The Effects of Student Loans on Long-Term Household Financial Stability. In Hershbein, B. & Hollenbeck, K. (ed.). Student Loans and the Dynamics of Debt (137–174). W.E. Upjohn Institute for Employment Research: Kalamazoo, MI.

Federal Student Aid. Student Loan Delinquency and Default ( studentaid.gov/manage-loans/default).

Blagg, K. (2018). Underwater on Student Debt: Understanding Consumer Credit and Student Loan Default. Urban Institute Research Report.

Elliott, D. & Granetz Lowitz, R. (2018). What Is the Cost of Poor Credit? Urban Institute Report. Corbae, D., Glover, A. & Chen, D. (2013). Can Employer Credit Checks Create Poverty Traps? 2013 Meeting Papers, No. 875, Society for Economic Dynamics.

Federal Student Aid. Student Loan Delinquency and Default ( studentaid.gov/manage-loans/default).

Research shows that borrowers who attend for-profit institutions have higher student loan default rates than students with similar characteristics who attend public institutions. Furthermore, most of the rise in student loan default rates from 2000 to 2011 can be traced to increases in enrollment in for-profit institutions and, to a lesser extent, two-year public institutions.

Deming, D., Goldin, C., & Katz, L. (2012). The For-Profit Postsecondary School Sector: Nimble Critters or Agile Predators? Journal of Economic Perspectives, 26(1), 139–164. Hillman, N.W. (2014). College on Credit: A Multilevel Analysis of Student Loan Default. Review of Higher Education 37(2), 169–195.

Looney, A. & Yannelis, C. (2015). A Crisis in Student Loans? How Changes in the Characteristics of Borrowers and in the Institutions They Attended Contributed to Rising Loan Defaults. Brookings Papers on Economic Activity, 2, 1–89.

Low loan repayment also has consequences for taxpayers. Calculating the precise magnitude of these costs would require decades of realized repayment periods for millions of borrowers. However, Table 2.10 shows estimates of the share of disbursed loans that will not be repaid based on simulated debt and earnings trajectories at each program in the 2022 PPD under the income-driven repayment Saving on a Valuable Education (SAVE) plan announced in June 2023. These estimates incorporate the subsidy coming from the features of the repayment plan itself (capped payments, forgiveness), not accounting for default or delinquency. Starting with the median earnings and debt at each program, the Department simulated typical repayment trajectories for each program with data available for both measures.

The White House (June 30, 2023). Fact Sheet: President Biden Announces New Actions to Provide Debt Relief and Support for Student Loan Borrowers ( www.whitehouse.gov/briefing-room/statements-releases/2023/06/30/fact-sheet-president-biden-announces-new-actions-to-provide-debt-relief-and-support-for-student-loan-borrowers/ ).

Using U.S. Census Bureau (Census) microdata on earnings and family formation for a nationally representative sample of individuals, the Department projected the likely repayment experience of borrowers at each program assuming all were enrolled in the SAVE plan (which can be found at 88 FR 43820). Starting from the median earnings level of each program, the projections incorporate the estimated earnings growth over the life course through age sixty for individuals starting from the same earnings level in a given State. The projections also include likely spousal earnings, student debt, and family size of each borrower (also derived from the Census data), which makes it possible to calculate the total amount repaid by borrowers under each plan when paying in full each month (even if that means making a payment of $0). The simulation incorporates different demographic and income groups probabilistically due to important non-linearities in plan structure.

These estimates of the subsidy rate are not those used in the budget and do not factor in take-up. Rather, they show the predicted subsidy rates under the assumption that all students are enrolled in SAVE.

Table 2.10 shows that, among all programs, students who attend programs that fall below the debt-to-earnings standard are consistently projected to repay less on their loans, in present value terms, than they borrowed. This is true regardless of whether a program is in the public, private nonprofit, or proprietary sector. The projected repayment ratio is even lower for programs that only fail the EP measure because at very low earnings levels, students are expected to make zero-dollar payments over extended periods of time.

As explained in more detail later, the Department computed D/E and EP metrics only for those programs with 30 or more students who completed the program during the applicable two-year cohort period—that is, those programs that met the minimum cohort size requirements.

Table 2.10—Predicted Ratio of Dollars Repaid to Dollars Borrowed by Control and Passage Status

Predicted repayment ratio under SAVE
Public:
No D/E or EP data 0.54
Pass 0.72
Fail D/E (regardless of EP) 0.29
Fail EP only 0.13
Private, Nonprofit:
No D/E or EP data 0.69
Pass 0.96
Fail D/E (regardless of EP) 0.36
Fail EP only 0.19
Proprietary:
No D/E or EP data 0.43
Pass 0.80
Fail D/E (regardless of EP) 0.25
Fail EP only 0.08
Total:
No D/E or EP data 0.58
Pass 0.77
Fail D/E (regardless of EP) 0.29
Fail EP only 0.12

Our analysis, provided in more detail in “Analysis of the Regulations,” shows that for many GE programs, the typical graduate earns less than the typical worker with only a high school diploma or has debt payments that are higher than is considered manageable given typical earnings. As we show below, high rates of student loan default are especially common among GE programs that are projected to fail either the D/E rates or the earnings premium metric. Furthermore, low earnings can cause problems in aspects of a graduate's financial life beyond those related to loan repayment. In 2019, US individuals between ages 25 and 34 who had any type of postsecondary credential reported much higher rates of material hardship if their annual income was below the high school earnings threshold, with those below the threshold reporting being food insecure and behind on bills at more than double the rate of those with earnings above the threshold.

These findings come from ED's analysis of the 2019 Survey of Income and Program Participation. This analysis compares individuals with annual income below the 2019 U.S. National median income for individuals with a high school diploma aged 25–34 who had positive earnings or reported looking for work in the previous year, according to the Census Bureau's ACS.

In light of the low earnings, high debt, and student loan repayment difficulties for students in some GE programs, the Department has identified a risk that students may be spending their time and money and taking on Federal debt to attend programs that do not provide sufficient value to justify these costs. While even very good programs will have some students who struggle to obtain employment or repay their student loans, the metrics identify programs where the majority of students experience adverse financial outcomes upon completion.

Although enrollment in for-profit and sub-baccalaureate programs has declined following the Great Recession, past patterns suggest that future economic downturns could reverse this trend. For-profit institutions have shown to be more responsive than public and nonprofit institutions to changes in economic conditions and during the COVID–19 pandemic, it was the only sector to see increases in student enrollment. Additionally, research shows that reductions in State and local funding for public higher education institutions tend to shift college students into the for-profit sector. During economic downturns, this response is especially relevant since State and local funding is procyclical, falling during recessions even as student demand is increasing.

Deming, D., Goldin, C. & Katz, L. (2012). The For-Profit Postsecondary School Sector: Nimble Critters or Agile Predators? Journal of Economic Perspectives, 26(1), 139–164. Gilpin, G.A., Saunders, J. & Stoddard, C. (2015). Why Has For-Profit Colleges' Share of Higher Education Expanded So Rapidly? Estimating the Responsiveness to Labor Market Changes. Economics of Education Review, 45, 53–63.

Cellini, S.R. (2020). The Alarming Rise in For-Profit College Enrollment. Brookings Institution: Washington, DC.

Cellini, S.R. (2009). Crowded Colleges and College Crowd-Out: The Impact of Public Subsidies on the Two-Year College Market. American Economic Journal: Economic Policy, 1(2), 1–30. Goodman, S. & Volz, A.H. (2020). Attendance Spillovers between Public and For-Profit Colleges: Evidence from Statewide Variation in Appropriations for Higher Education. Education Finance and Policy, 15(3), 428–456.

Ma, J. & Pender, M. (2022). Trends in College Pricing and Student Aid 2022. College Board: New York.

For-profit institutions that participate in title IV, HEA programs are also more reliant on Federal student aid than public and nonprofit institutions. In recent years, around 70 percent of revenue received by for-profit institutions came from Pell grants and Federal student loans. For-profit institutions also have substantially higher tuition than public institutions offering similar degrees. In recent years, average for-profit tuition and fees charged by two-year for-profit institutions were over 4 times the average tuition and fees charged by community colleges. Research suggests that Federal student aid supports for-profit expansions and higher prices. One study finds that for-profit programs in institutions that participate in title IV, HEA programs charge tuition that is approximately 80 percent higher than tuition charged by programs in the same field and with similar outcomes in nonparticipating for-profit institutions.

Cellini, S. & Koedel, K. (2017). The Case for Limiting Federal Student Aid to For-Profit Colleges. Journal of Policy Analysis and Management, 36(4), 934–942.

NCES (2022). Digest of Education Statistics (Table 330.10) (available at nces.ed.gov/programs/digest/d21/tables/dt21_330.10.asp).

Cellini, S.R. (2010). Financial Aid and For-Profit Colleges: Does Aid Encourage Entry? Journal of Policy Analysis and Management, 29(3), 526–552. Lau, C.V. (2014). The Incidence of Federal Subsidies in For-Profit Higher Education. Unpublished manuscript. Northwestern University: Evanston, IL.

Cellini, S.R. & Goldin, C. (2014). Does Federal Student Aid Raise Tuition? New Evidence on For-Profit Colleges. American Economic Journal: Economic Policy, 6(4), 174–206.

A commonly expressed concern with past GE regulations is that if programs lose title IV, HEA aid eligibility due to the rule's sanctions this might result in a loss of education options for disadvantaged students. Past research has shown that for-profit institutions do indeed disproportionately enroll students with barriers to postsecondary access—low-income, non-white, and older students, as well as students who are veterans, single parents, or have a General Equivalency Degree. Evidence from prior research and our analyses presented in this RIA, however, suggests that sanctioning low-performing programs would not reduce access to good quality programs.

Deming, D., Goldin, C. & Katz, L. (2012). The For-Profit Postsecondary School Sector: Nimble Critters or Agile Predators? Journal of Economic Perspectives, 26(1), 139–164. Cellini, S.R. & Darolia, R. (2015). College Costs and Financial Constraints. In Hershbein, B. & Hollenbeck, K. (ed). Student Loans and the Dynamics of Debt (137–174). W.E. Upjohn Institute for Employment Research: Kalamazoo, MI.

For example, in the 1990s, sanctions related to high cohort default rates led a large number of for-profit institutions to close, significantly reducing enrollment in this sector. Yet, these actions did not reduce access to higher education. Instead, a large share of students who would have attended a sanctioned for-profit institution instead enrolled in local open access public institutions and, as a result, took on less student debt and were less likely to default. Similar conclusions were reached in recent studies of students who experienced program closures. Better evidence is now available on the enrollment outcomes of students who would otherwise attend sanctioned or closed schools than when the 2014 GE Rule was considered. Further, as shown in the RIA section “Alternative Options Exist for Students to Enroll in High-Value Programs,” most students who enroll in a GE program projected to fail the D/E rates or EP measure have better options available to them at the same or nearby institutions, and the graduates of these programs bend to have higher earnings and less debt.

Darolia, R. (2013). Integrity Versus Access? The Effect of Federal Financial Aid Availability on Postsecondary Enrollment. Journal of Public Economics, 106, 101–114.

Cellini, S.R., Darolia, R. & Turner, L.J. (2020). Where Do Students Go When For-Profit Colleges Lose Federal Aid? American Economic Journal: Economic Policy, 12(2), 46–83.

See Government Accountability Office (2022). College Closures: Education Should Improve Outreach to Borrowers about Loan Discharges (GAO–22–104403) ( www.gao.gov/products/gao-22-104403 ). State Higher Ed. Executive Officers Ass'n (2022). More than 100,000 Students Experienced an Abrupt Campus Closure Between July 2004 and June 2020 ( sheeo.org/more-than-100000-students-experienced-an-abrupt-campus-closure-between-july-2004-and-june-2020).

3. Summary of Comments and Changes From the NPRM

Table 1—Summary of Key Changes in the Final Regulations

§ 668.2
Provision Regulatory section Description of change from NPRM
Date, Extent, and Consequence of Eligibility § 600.10(c) Repositioning § 600.10(c)(1)(v) to § 600.10(c)(3), with a slight rewording for additional clarity.
Definitions Updating definition of “cohort period” to extend the earnings measurement period for qualifying graduate programs beyond medical and dental programs.
Updating definition of “earnings threshold” to specifically reference Census Bureau data.
Updating definition of “earnings threshold” to clarify that national earnings are used if fewer than 50 percent of the students in the program come from the State where the institution is located, rather than where the students are located while enrolled.
Updating definition of Institutional Grants and Scholarships for clarity.
Adding a new definition of “qualifying graduate program” to establish an extended earnings measurement period for certain graduate programs beyond medical and dental programs.
Adding a new definition of “substantially similar program.”
Removing references to “title IV loan” and uses “Direct Loan Program loan” that is already defined.
Institutional and Programmatic Information and Student Acknowledgments §§ 668.43(d), 668.407, and 668.605 Specifying that the program information website requirements and the acknowledgment requirements are not applicable until July 1, 2026.
Institutional and Programmatic Information § 668.43(a)(5)(v) and (d)(1) Removing the requirement for an institution to post a list of States where a program meets or does not meet applicable State licensure requirements, in expectation that this provision will be published under a separate final rule.
Revising § 668.43(d) to refer to the Department's website as the “program information website” rather than the “disclosure website.” We have also made conforming revisions to § 668.605(c)(2) and (3) by changing the reference from “disclosure website” to “program information website.
Revising the list of information items to include a list of the minimum elements that the Secretary must include on the program information website and an example list of supplemental information the Secretary may additionally include.
Removing the link to the College Navigator website from the list of required information items.
Financial Value Transparency Scope and Purpose § 668.401 Adding § 668.401(b)(1) to exempt institutions located in U.S. Territories or the freely associated states from the provisions of subpart Q other than reporting requirements under § 668.408, noting that the informational requirements at § 668.43 also continue to apply.
Adding § 668.401(b)(2) to exempt from subpart Q institutions that offered no groups of substantially similar programs with 30 or more completers over the four most recently completed award years.
Process for Obtaining Data and Calculating D/E Rates and Earnings Premium Measure § 668.405(b)(1)(iii) Revising to clarify that an institution can correct the information about the students on the completer list or provide evidence showing that a student should be included or removed from the list no later than 60 days after the date the Secretary provides the list to the institution.
Student Acknowledgments § 668.407(a)(1), (b)(3), (c), and (d) Revising to exempt undergraduate degree programs from the acknowledgment requirements.
Revising to require a student in high-debt-burden non-GE program to provide an acknowledgment before the institution enters into an agreement to enroll the student, rather than before the institution may disburse title IV, HEA funds.
Revising to clarify that the Department monitors an institution's compliance with the student acknowledgment requirements through audits, program reviews, or other investigations.
Revising to clarify that the acknowledgment requirements apply annually if the program has failing rates for the most recent year calculated, and continue to apply for three years if no new rates are calculated.
Revising to specify that the provision of an acknowledgement will not be considered “dispositive” evidence in any borrower defense claim.
Reporting Requirements § 668.408(a) and (c) Revising to limit the reporting requirements to institutions offering any program with at least 30 total completers during the four most recently completed award years.
Expanding the transitional reporting and rates option from non-GE programs to all programs.
Clarifying that the transitional reporting and rates option applies for the first six years the regulation is in effect.
Gainful Employment Scope and Purpose § 668.601(b) Adding § 668.601(b)(1) to exempt institutions located U.S. Territories or the freely associated states from the provisions of subpart S.
Adding § 668.601(b)(2) to exempt from subpart S institutions that offered no groups of substantially similar programs with 30 or more completers over the four most recently completed award years.
Gainful Employment Criteria § 668.602(d) and (g) Revising to clarify that in determining a program's eligibility, the Secretary disregards any failing D/E rates and earnings premiums that were calculated more than five calculation years prior.
Student Warnings § 668.605(h) Revising to specify that the provision of a warning will not be considered “dispositive” evidence in any borrower defense claim.

General

Comments: One commenter questioned why the Department's RIA data were less complete for nonprofit institutions than similarly provided data under the 2014 GE rules. The commenter also wondered what data motivated the extra regulation of for-profit institutions relative to nonprofit schools.

Discussion: The commenter did not specify how they determined that the data for nonprofit institutions were less complete in the NPRM RIA relative to the 2014 rule. Nonetheless, the Department provided the available data, subject to privacy standards as part of the NPRM. Moreover, the additional scrutiny of for-profit institutions is warranted because for-profit programs have demonstrated particularly poor outcomes. A large body of research provides causal evidence on the many ways students at for-profit institutions are economically disadvantaged upon exiting their institutions, as we described in the “Need for Regulatory Action” section above.

Changes: None.

Comments: A few commenters stated that the NPRM RIA's comparison of failure rates of public and nonprofit certificate programs to those of proprietary programs was misleading because many public and nonprofit programs are too small to have sufficient data to calculate metrics.

Discussion: Under the rule, only programs with sufficient data will be subject to failure. Therefore, the NPRM RIA contained an accurate description of the share of programs that fail.

Changes: None.

Benefits and Costs—RIA

Comments: One commenter questioned whether the benefits of the regulations would exceed the costs, claiming that the in the NPRM, the Department did not provide specific data and evidence about net benefits, did not consider negative impacts on students and institutions, provided an incomplete assessment of costs associated with implementing the regulations, and did not consider the perspectives of students, institutions, and other stakeholders who would be directly affected by the regulation.

Discussion: The Department disagrees that the NPRM failed to consider these elements. We included extensive discussion of potential impacts on students and institutions (for example, see the “Discussion of Costs, Benefits, and Transfers” in the NPRM). The NPRM also included a robust discussion of the costs associated with implementing the regulations, including discussion of costs associated with the reporting, disclosure, and acknowledgment requirements (see the “Costs to Institutions” section of the NPRM). In addition, the NPRM was issued after a negotiated rulemaking process in which a diverse set of stakeholders participated, including representatives from accrediting agencies, civil rights organizations, consumer advocacy groups, financial aid administrators, institutions of higher education (public four-year and two-year, minority-serving, proprietary, private nonprofit), State attorneys general, and U.S. military service groups.

Changes: None.

Data Used in This RIA

Comments: Several commenters noted that the NPRM RIA considered information that differed in certain ways from the data measurement that the Department proposed to use in the rule, including: that the RIA analyzed programs at the 4-digit CIP code level; used 2010 CIP codes; used data from earlier cohorts; used State-level earnings thresholds even in cases when more than half of a program's students are out-of-State, did not evaluate medical professional programs that have post-graduation residency requirements, and did not provide 4-year completer cohort data. Some commenters further noted that the data used to calculate D/E in the NPRM RIA did not include private education loan data or cap the loan debt by an amount equivalent to cost of attendance less institutional grants. Some of these commenters claimed that this omission particularly harms cosmetology schools or that the NPRM RIA does not offer institutions a way to fully understand the potential impact of the regulations on their programs.

Discussion: We used the best available data in the NPRM RIA and in the RIA for the final rule to analyze the implications of the rule, and in these, and other comments, commenters did not suggest alternative sources of data that could be used to evaluate the rule proposed in the NPRM or in the final rule. Additionally, we described in detail the differences between data used for modeling and data used in the final rule, and when possible, included a discussion of expected differences in coverage between the NPRM RIA and the final rule. For example, the NPRM RIA estimated that for GE programs, an additional 8 percent of enrollment and 11 percent of programs would likely have metrics computed using a 4-year completer cohort but did not have metrics computed using a 2-year completer cohort. For eligible non-GE programs, the use of four-year cohort rates likely increases coverage rates of enrollment and programs by 13 and 15 percent, respectively. To the extent that commenters seek perfect data that perfectly predict the effects of the rule, that is neither feasible nor the applicable legal standard. Further, institutions have ready access to data that would allow them to identify debt levels for students in their programs, and it is not unreasonable to expect institutions to have a sense of students' earnings.

See “Data Used in this RIA” and “Analysis of Data Coverage” from the NPRM.

Changes: None.

Comments: One commenter stated their appreciation for providing analysis of programs in 2-year cohorts, but a few commenters were concerned about the lack of information related to 4-year cohorts. A specific concern of the latter/ these commenter(s) was that the RIA in the NPRM might have understated the number of programs that might be affected by the regulations.

Discussion: The data we used in the NPRM RIA was the best data available to analyze the implications of the rule. We included an estimate in the NPRM RIA of the share of enrollment in programs that would be covered under the four-year cohort approach (see, for example, Table 3.2 of the NPRM).

Changes: None.

Comments: One commenter claimed that they were unable to recreate or identify the source data for data used in the NPRM RIA. A few other commenters claimed that the PPD 2022 differed from other data, such as the College Scorecard or previously released data.

Discussion: We fulsomely documented the data used in the NPRM RIA analysis and in supplementary documentation posted on the Department's website and regulations.gov. Under the “Data Used in this RIA” section of the NPRM, the RIA explains that the data used non-public records contained in Department administrative systems, earnings data produced by the U.S. Treasury, and data from the Integrated Postsecondary Education Data System (IPEDS), Postsecondary Education Participants System (PEPS), and the College Scorecard, and further explained, in the following pages, how we constructed each data field. Further, the Data Codebook and Description provide detailed descriptions of the exact source of each variable and differences from previously released data.

Changes: None.

Comments: One commenter indicated that the 2022 PPD data released along with the NPRM does not match with their college's internal data. The commenter further conducted a survey of some graduates in one their programs and among respondents, found higher median earnings than was included in the PPD. Further, the commenter claimed that the 2022 PPD included more completers than the college's internal data and had a different number of bachelor's programs.

Discussion: The Department used administrative IRS data from tax filings, which we believe to be the most accurate source of data on student earnings available. While graduate surveys can provide useful information about student outcomes, such data can be subject to response bias (and that is possible in this case where only a portion of borrowers volunteered self-reported earnings information). Related to accuracy of completers and programs, the rule allows institutions to review and correct completer lists to review for and promote accuracy (see § 668.405).

Changes: None.

Comments: Two commenters asserted, for different reasons, that the PPD was in some way flawed. One commenter noted that only a fraction of the programs in the PPD file include data, and that this is too small a fraction of programs nationwide to analyze and use for the basis of a rule.

The other commenter noted that the PPD file contains fewer programs than the equivalent College Scorecard program file, even though they measure the same cohort. The same commenter opined that the PPD was not a valid source of data, because for programs that exist in both data sources, the earnings data are substantially different.

Discussion: The Department understands that not all programs include data that can be analyzed for the purposes of the final rule. However, we believe that the degree to which student enrollment concentrates in larger programs mitigates the concerns noted by the commenter. The number of students who enroll in programs large enough to produce data is the more relevant measure of the rule's effectiveness, in our opinion. As shown in the RIA, we estimate that the majority of enrolled students, approximately 83 percent, are enrolled in programs that would be covered by existing data.

The Department is aware of the differences in how the PPD and the College Scorecard universes of programs and data are constructed. As noted in the rule and in the RIA, the coverage of programs is different, and the two datasets should not be expected to be the same. A primary reason why the PPD has fewer programs is that the sample frame is different: the PPD is limited to programs with completers in the 2015–2017 academic years and who are currently in operation based on the Postsecondary Education Participation System (PEPS) data as of March 25, 2022.

The methodology for calculating median debt differ in the two data sources because in the College Scorecard, median debt is measured only among borrowers, whereas in the PPD programs that have completers who graduate with debt have those students' lack of debt factored into their median debt amounts.

The Department disputes the fact that the earnings measures differ substantially between the College Scorecard and the PPD. The same data file forms the basis of both the Scorecard and the PPD earnings measures for 3-year earnings among students who are not enrolled. It is worth noting that the not-enrolled population that forms the basis of the 3-year program-level measure in the Scorecard is a different sample of students than the 1- and 4-year measures at the program level, which are calculated only for the working and not-enrolled population of graduates from each program. This may explain any confusion commenters have about comparability of measures, as commenters noted inconsistency across earnings horizons (arguing that the data showed an implausible jump from the three- to four-year measurement period. This disparity results from different measurement populations and is not a sign of mismeasurement. When examining program earnings for the same cohorts and measurement periods for the programs present in both samples, they differ only by a small inflation adjustment that serves to construct the GE measures properly to best approximate the true structure of the rule when implemented. For reasons explained in the NPRM, median debt in the rule (and hence the PPD) is based on all graduates regardless of whether they borrow. Similarly, median earnings are measured using all graduates regardless of whether they are employed.

Changes: None.

4. Analysis of the Financial Value Transparency and GE Regulations

This section presents a detailed analysis of the likely consequences of the Financial Value Transparency and GE provisions of the final regulations.

Methodology

Data Used in This RIA

This section describes the data referenced in this regulatory impact analysis. To generate information on the performance of different postsecondary programs offered in different higher education sectors, the Department relied on data on the program enrollment, demographic characteristics, borrowing levels, post-completion earnings, and borrower outcomes of students who received title IV, HEA aid for their studies. The Department produced program performance information, using measures based on the typical debt levels and post-enrollment earnings of program completers, from non-public records contained in the administrative systems the Department uses to administer the title IV, HEA programs along with earnings data produced by the U.S. Treasury. This performance information was supplemented with information from publicly available sources including the Integrated Postsecondary Education Data System (IPEDS), Postsecondary Education Participants System (PEPS), and the College Scorecard. The data used for the State earnings thresholds come from the Census Bureau's 2019 ACS, while statistics about the price level used to adjust for inflation come from the Bureau of Labor Statistics' Consumer Price Index. This section describes the data used to produce this program performance information and notes several differences from the measures used for this purpose and the D/E rates and earning premium measures set forth in the rule, as well as differences from the data disseminated during negotiated rulemaking. The data described below are referred to as the “2022 Program Performance Data (2022 PPD),” where 2022 refers to the year the programs were indicated as active. The data are unchanged from that used in the NPRM RIA, and those data were released with the NPRM.

To protect student privacy, we applied certain protocols to the publicly released 2022 PPD and therefore that dataset differs somewhat from the 2022 PPD analyzed in this RIA. Such protocols include omitting the values of variables derived from fewer than 30 students. For instance, the title IV enrollment in programs with fewer than 30 students is used to determine the number and share of enrollment in GE programs in this RIA, while the exact program-level enrollment of such programs is omitted in the public 2022 PPD. The privacy protocols are described in the data documentation accompanying the NPRM. The Department would not have reached different conclusions on the impact of the regulation or on the proposed rules if we had instead relied on the privacy-protective dataset, though the Department views analysis based on the 2022 PPD and described in this regulation to provide a more precise representation of such impact. We view the differences in the analyses as substantively minor for purposes of this rulemaking. As described in the final rule, institutions that do not have enough students completing over the most recent four award years to permit the Department to calculate metrics will be exempt—these programs are listed as “no data” in the public PPD.

The final rule relies on non-public measures of the cumulative borrowing and post-completion earnings of federally aided title IV, HEA students, including both grant and loan recipients. The Department has information on all title IV, HEA grant and loan recipients at all institutions participating in the title IV, HEA programs, including the identity of the specific programs in which students are enrolled and whether students complete the program. This information is stored in the National Student Loan Data System (NSLDS), maintained by the Department's Office of Federal Student Aid (FSA).

Using this enrollment and completion information, in conjunction with non-public student loan information also stored in NSLDS, and earnings information obtained from Treasury, the Department calculated annual and discretionary debt-to-earnings (D/E) ratios, or rates, for all title IV, HEA programs. The Department also calculated the median earnings of high school graduates aged 25 to 34 in the labor force in the State where the program is located using public data, which is referred to as the Earnings Threshold (ET). This ET is compared to a program's graduates' annual earnings to determine the Earnings Premium (EP), the extent to which a programs' graduates earn more than the typical high school graduate in the same State. The methodology that was used to calculate D/E rates, the ET, and the EP is described in further detail below. In addition to the D/E rates and earnings data, we also calculated informational outcome measures, including program-level cohort default rates, to evaluate the likely consequences of the final rule.

In our analysis, we identify a program by a unique combination consisting of the first six digits of its institution's Office of Postsecondary Education Identification (OPEID) number, also referred to as the six-digit OPEID, the program's 2010 Classification of Instructional Programs (CIP) code, and the program's credential level. The terms OPEID number, CIP code, and credential level are defined below. Throughout, we distinguish “GE Programs” from those that are not subject to the GE provisions of the final rule, referred to as “non-GE Programs.” The 2022 PPD includes information for 155,582 programs that account for more than 19 million title IV, HEA enrollments annually in award years 2016 and 2017. This includes 2,931,000 enrollments in 32,058 GE Programs (certificate programs at all institution types, and degree programs at proprietary institutions) and 16,337,000 enrollments in 123,524 non-GE Programs (degree programs at public and private not-for-profit institutions).

We calculated the performance measures in the 2022 PPD for all programs based on the debt and earnings of the cohort of students who both received title IV, HEA program funds, including Federal student loans and Pell grants, and completed programs during an applicable two-year cohort period. Consistent with the final rule, students who do not complete their program are not included in the calculation of the metrics. The annual loan payment component of the debt-to-earnings formulas for the 2022 PPD D/E rates was calculated for each program using student loan information from NSLDS for students who completed their program in award years 2016 or 2017 ( i.e., between July 1, 2015, and June 30, 2017—we refer to this group as the 16/17 completer cohort). The earnings components of the rates were calculated for each program using information obtained from Treasury for students who completed between July 1, 2014, and June 30, 2016 (the 15/16 completer cohort), whose earnings were measured in calendar years 2018 and 2019.

Programs were excluded from the 2022 PPD if they were operated by an institution that was not currently active in the Department's PEPS system as of March 25, 2022, if the program did not have a valid credential type, or if the program did not have title IV, HEA completers in both the 15/16 and 16/17 completer cohorts.

Consistent with the regulations, the Department computed D/E and EP metrics in the 2022 PPD only for non-exempted programs with 30 or more students who completed the program during the applicable two-year cohort period—that is, those programs that met the minimum cohort size requirements. A detailed analysis of the likely coverage rate under the rule and of the number and characteristics of programs that met the minimum size in the 2022 PPD is included in “Analysis of Data Coverage” below.

We determined, under the provisions in the final regulations for the D/E rates and EP measures, whether each program would “Pass D/E,” “Fail D/E,” “Pass EP,” and “Fail EP” based on its 2022 PPD results, or “No data” if it did not meet the cohort size requirement, was located in Puerto Rico, U.S. Territories and freely associated states, or was a program for which we do not have data because the program has post-graduation residency requirements such that it is evaluated based on a longer earnings periods. These program-specific outcomes are then aggregated to determine the fraction of programs that pass or fail either metric or have insufficient data, as well as the enrollment in such programs.

This is a simplification. Under the regulation, a “no data” year is not considered passing when determining eligibility for GE programs based on two out of three years. For non-GE programs, passing with data and without data are treated the same for the purposes of the warnings.

Pass D/E: Programs with an annual D/E earnings rate less than or equal to 8 percent OR a discretionary D/E earnings rate less than or equal to 20 percent.

Fail D/E: Programs with an annual D/E earnings rate over 8 percent AND a discretionary D/E earnings rate over 20 percent.

Pass EP: Programs with median annual earnings greater than the median earnings among high school graduates aged 25 to 34 in the labor force in the State in which the program is located.

Fail EP: Programs with median annual earnings less than or equal to the median earnings among high school graduates aged 25 to 34 in the labor force in the State in which the program is located.

No data: Programs that had fewer than 30 students in the two-year completer cohorts such that earnings and debt levels could not be determined; exempted programs from Puerto Rico, U.S. Territories and freely associated states; or programs with longer earnings periods due to post-graduation residency requirements.

Under the final regulations, a GE program will become ineligible for title IV, HEA program funds if it fails the D/E rates measure for two out of three consecutive years or fails the EP measure for two out of three consecutive years. GE programs will be required to provide warnings in any year in which the program could lose eligibility based on the next D/E rates or earnings premium measure calculated by the Department. Students at such programs would be required to acknowledge having seen the warning and information about debt and earnings before receiving title IV, HEA funds. Eligible programs (excepting undergraduate degree programs) not meeting the D/E standards would need to have students acknowledge viewing this information before students sign enrollment agreements. These acknowledgment requirements will apply until the program passes the D/E measure, or for three years from the last published rate, whichever is earlier.

The Department analyzed the estimated impact of the final regulations on GE and non-GE programs using the following data elements defined below:

Enrollment: Number of students receiving title IV, HEA program funds for enrollment in a program. To estimate enrollment, we used the count of students receiving title IV, HEA program funds, averaged over award years 2016 and 2017. Since students may be enrolled in multiple programs during an award year, aggregate enrollment across programs will be greater than the unduplicated number of students.

OPEID: Identification number issued by the Department that identifies each postsecondary educational institution (institution) that participates in the Federal student financial assistance programs authorized under title IV of the HEA.

CIP code: Identification code from the Department's National Center for Education Statistics' (NCES) Classification of Instructional Programs, which is a taxonomy of instructional program classifications and descriptions that identifies instructional program specialties within educational institutions. The rule will define programs using six-digit CIP codes, but due to data limitations, the statistics used in this RIA are measured using four-digit codes to identify programs. We used the 2010 CIP code instead of the 2020 codes to align with the completer cohorts used in this analysis.

In many cases the loss of information from conducting analysis at a four- rather than six-digit CIP code is minimal. According to the Technical Documentation: College Scorecard Data by Field of Study, 70 percent of credentials conferred were in four-digit CIP categories that had only one six-digit category with completers at an institution. The 2015 official GE rates can be used to examine the extent of variation in program debt and earnings outcomes across 6-digit CIP programs within the same credential level and institution.

Control: The control designation for a program's institution—public, private nonprofit, private for-profit (proprietary), foreign nonprofit, and foreign for-profit—using PEPS control data as of March 25, 2022.

Credential level: A program's credential level—undergraduate certificate, associate degree, bachelor's degree, post-baccalaureate certificate, master's degree, doctoral degree, first professional degree, or post-graduate certificate.

Institution predominant degree: The type designation for a program's institution which is based on the predominant degree the institution awarded in IPEDS and reported in the College Scorecard: less than 2 years, 2 years, or 4 years or more.

State: Programs are assigned to a U.S. State, DC, or territory based on the State associated with the main institution.

The information contained in the 2022 PDD and used in the analysis necessarily differs from what will be used to evaluate programs under the final rule in a few ways due to certain information not being currently collected in the same form as it would under the final rule. These include:

  • 4-digit CIP code is used to define programs in the 2022 PPD, rather than 6-digit CIP code. Program earnings are not currently collected at the 6-digit CIP code level, but will be under the final rule. Furthermore, the 2022 PPD use 2010 CIP codes to align with the completer cohorts used in the analysis, but programs will be defined using the 2020 CIP codes under the final rule;
  • Unlike the final rule, the total loan debt associated with each student is not capped at an amount equivalent to the program's tuition, fees, books, and supplies in the 2022 PPD, nor does debt include institutional and other private debt. Doing so requires additional institutional reporting of relevant data items not currently available to the Department. In the 2014 Prior Rule, using information reported by institutions, the tuition and fees cap was applied to approximately 15 percent of student records for the 2008–2009 2012 D/E rates cohort, though this does not indicate the share of programs whose median debt would be altered by the cap.

• D/E rates using earnings levels measured in calendar years 2018 and 2019 would ideally use debt levels measured for completers in 2015 and 2016. Since program level enrollment data are more accurate for completers starting in 2016, we use completers in 2016 and 2017 to measure debt. We measure median debt levels and assume completers in the 2015 and 2016 cohorts would have had total borrowing that was the same in real terms ( i.e., we use the CPI to adjust their borrowing levels to estimate what the earlier cohort would have borrowed in nominal terms). This use of one cohort to measure earnings outcomes and another to measure debt necessarily reduces the estimated coverage in the 2022 PPD to a lower level than will be experienced in practice, as we describe in more detail below. Finally, the methodology used to assign borrowing to particular programs in instances where a borrower may be enrolled in multiple programs is different in the 2022 PPD than the methodology that would be used in the final rule (which is the same as that used in the 2014 Prior Rule);

  • Medical and dental professional programs, and graduate mental health programs that lead to licensure, are not evaluated because earnings six years after completion are not available. The earnings and debt levels of these programs are set to missing and not included in the tabulations presented here;
  • 150 percent of the Federal Poverty Guideline is used to define the ET for institutions in foreign institutions in the 2022 PPD, rather than a national ET;
  • The final rule will use a national ET if more than half of a program's students are out-of-state, but the 2022 PPD uses an ET determined by the State an institution is located;

• Programs at institutions that have merged with other institutions since 2017 are excluded, but these programs' enrollment will naturally be incorporated into the merged institution when the final rule goes into effect.

  • Under the final rule, if the two-year completer cohort has too few students to publish debt and earnings outcomes, but the four-year completer cohort has a sufficient number of students, then debt and earnings outcomes would be calculated for the four-year completer cohort. This was not possible for the 2022 PPD, so some programs with no data in our analysis would have data to evaluate performance under the rule.

The 2022 PPD also differ from those published in the Negotiated Rulemaking data file in several ways. The universe of programs in the previously published Negotiated Rulemaking data file were based, in part, on the College Scorecard universe which included programs as they are reported to IPEDS, but not necessarily to NSLDS. IPEDS is a survey, so institutions may report programs (degrees granted by credential level and CIP code) differently in IPEDS than is reflected in NSLDS. To reflect the impact of the rule more accurately, the universe of the 2022 PPD is based instead on NSLDS records because NSLDS captures programs as reflected in the data systems used to administer title IV, HEA aid. Nonetheless, the 2022 PPD accounts for the same loan volume reflected in the Negotiated Rulemaking data file. In addition, the Negotiated Rulemaking data file included programs that were based on a previous version of College Scorecard prior to corrections made to resolve incorrect institution-reported information in underlying data sources.

Methodology for D/E Rates Calculations

The D/E rates measure is comprised of two debt-to-earnings ratios, or rates. The first, the annual earnings rate, is based on annual earnings, and the second, the discretionary earnings rate, is based on discretionary earnings. These two components together define a relationship between the maximum typical amount of debt program graduates should borrow based on the programs' graduates' typical earnings. Both conceptually and functionally the two metrics operate together, and so should be thought of as one “debt to earnings (D/E)” metric. The formulas for the two D/E rates are:

Annual Earnings Rate = (Annual Loan Payment) / (Annual Earnings) Discretionary Earnings Rate = (Annual Loan Payment / (Discretionary Earnings)

A program's annual loan payment, the numerator in both rates, is the median annual loan payment of the 2016–2017 completer cohort. This loan payment is calculated based on the program's cohort median total loan debt at program completion, including non-borrowers, subject to assumptions on the amortization period and interest rate. Cohorts' median total loan debt at program completion were computed as follows.

  • Each student's total loan debt includes both FFEL and Direct Loans. Loan debt does not include PLUS Loans made to parents, Direct Unsubsidized Loans that were converted from TEACH Grants, private loans, or institutional loans that the student received for enrollment in the program.
  • In cases where a student completed multiple programs at the same institution, all loan debt is attributed to the highest credentialed program that the student completed, and the student is not included in the calculation ofD/E rates for the lower credentialed programs that the student completed.
  • The calculations exclude students whose loans were in military deferment, or who were enrolled at an institution of higher education for any amount of time in the earnings calendar year, or whose loans were discharged because of disability or death.

The median annual loan payment for each program was derived from the median total loan debt by assuming an amortization period and annual interest rate based on the credential level of the program. The amortization periods used were:

  • 10 years for undergraduate certificate, associate degree, post-baccalaureate certificate programs, and graduate certificate programs;
  • 15 years for bachelor's and master's degree programs;
  • 20 years for doctoral and first professional degree programs.

The amortization periods account for the typical outcome that borrowers who enroll in higher-credentialed programs ( e.g., bachelor's and graduate degree programs) are likely to have more loan debt than borrowers who enroll in lower-credentialed programs and, as a result, are more likely to take longer to repay their loans. These amortization rates mirror those used in the 2014 Prior Rule, which were based on Department analysis of loan balances and the differential use of repayment plan periods by credential level at that time. The interest rates used were:

See 79 FR 64939–40.

  • 4.27 percent for undergraduate programs;
  • 5.82 percent for graduate programs.

For both undergraduate and graduate programs, the rate used is the average interest rate on Federal Direct Unsubsidized loans over the three years prior to the end of the applicable cohort period, in this case, the average rate for loans disbursed between the beginning of July 2013 and the end of June 2016.

The denominators for the D/E rates are two different measures of student earnings. Annual earnings are the median total earnings in the calendar year three years after completion, obtained from the U.S. Treasury. Earnings were measured in calendar years 2018 and 2019 for completers in award years 2014–2015 and 2015–2016, respectively, and were converted to 2019 dollars using the Consumer Price Index for all Urban Consumers (CPI–U). Earnings are defined as the sum of wages and deferred compensation for all W–2 forms plus self-employment earnings from Schedule SE. Graduates who were enrolled in any postsecondary program during calendar year 2018 (2014–2015 completers) or 2019 (2015–2016 completers) are excluded from the calculation of earnings and the count of students. Discretionary earnings are equal to annual earnings, calculated as above, minus 150 percent of the Federal Poverty Guidelines for a single person, which for 2019 is earnings in excess of $18,735.

See Technical Documentation: College Scorecard Data by Field of Study.

Professional programs in Medicine (MD) and Dentistry (DDS), and mental health graduate programs that lead to clinical licensure will have earnings measured over a longer time horizon to accommodate lengthy post-graduate internship training, where earnings are likely much lower three years after graduation than they would be even a few years further removed from completion. Since longer horizon earnings data are not currently available, earnings for these programs were set to missing and treated as if they lacked sufficient number of completers to be measured.

For example, the average medical resident earns between roughly $62,000 and $67,000 in the first three years of residency, according to the Association of American Medical Colleges (AAMC) Survey of Resident/Fellow Stipends and Benefits, and the mean composition for physicians is $260,000 for primary care and $368,000 for specialists, according to the Medscape Physician Compensation Report.

Methodology for EP Rate Calculation

The EP measures the extent to which a program's graduates earn more than the typical high school graduate in the same State. The Department first calculated the ET, which is the median earnings of high school graduates in the labor force in each State where the program is located. The ET is adjusted for differences in high school earnings across States and over time so it naturally accounts for variations across these dimensions to reflect what workers would be expected to earn in the absence of postsecondary participation. The ET is computed as the median annual earnings among respondents aged 25–34 in the ACS who have a high school diploma or GED, but no postsecondary education, and who are in the labor force when they are interviewed, indicated by working or looking for and being available to work. This computation method yields a lower ET that is lower than the method proposed during negotiated rulemaking, which would compute median annual earnings among respondents aged 25–34 in the ACS who have a high school diploma or GED, but no postsecondary education, and who reported working ( i.e., having positive earnings) in the year prior to being surveyed. Table 4.1 below shows the ET for each State (along with the District of Columbia) in 2019. The ET ranges from $31,294 (North Dakota) to $20,859 (Mississippi). The threshold for institutions outside the United States is $18,735. We provide evidence in support of the chosen threshold below. Estimates of the impact of the regulations using these alternative thresholds are presented in the “Regulatory Alternatives Considered” section.

Table 4.1—Earnings Thresholds by State, 2019

Earnings threshold, 2019
State of Institution:
Alabama 22,602
Alaska 27,489
Arizona 25,453
Arkansas 24,000
California 26,073
Colorado 29,000
Connecticut 26,634
Delaware 26,471
District of Columbia 21,582
Florida 24,000
Georgia 24,435
Hawaii 30,000
Idaho 26,073
Illinois 25,030
Indiana 26,073
Iowa 28,507
Kansas 25,899
Kentucky 24,397
Louisiana 24,290
Maine 26,073
Maryland 26,978
Massachusetts 29,830
Michigan 23,438
Minnesota 29,136
Mississippi 20,859
Missouri 25,000
Montana 25,453
Nebraska 27,000
Nevada 27,387
New Hampshire 30,215
New Jersey 26,222
New Mexico 24,503
New York 25,453
North Carolina 23,300
North Dakota 31,294
Ohio 24,000
Oklahoma 25,569
Oregon 25,030
Pennsylvania 25,569
Rhode Island 26,634
South Carolina 23,438
South Dakota 28,000
Tennessee 23,438
Texas 25,899
Utah 28,507
Vermont 26,200
Virginia 25,569
Washington 29,525
West Virginia 23,438
Wisconsin 27,699
Wyoming 30,544
Foreign Institutions 18,735

The EP is computed as the difference between Annual Earnings and the ET:

Earnings Premium = (Annual Earnings)−(Earnings Threshold)

Where the Annual Earnings is computed as above, and the ET is assigned for the State in which the program is located. For foreign institutions, 150 percent of the Federal Poverty Guideline for the given year is used as the ET because comparable information about high school graduate earnings is not available.

The Department conducted several analyses to support the decision of the particular ET chosen. The discussion here focuses on undergraduate certificate programs, which our analysis below suggests is the sector where program performance results are most sensitive to the choice of ET.

First, based on student age information available from students' Free Application for Federal Student Aid (FAFSA) data, we estimate that the typical undergraduate program graduate three years after completion, when their earnings are measured, would be 30 years old. The average age of students three years after completion for undergraduate certificate programs is 31 years, while for associate programs it is 30, bachelor's 29, master's 33, doctoral 38, and professional programs 32. There are very few Post-BA and Graduate Certificate programs (162 in total) and the average ages when their earnings are measured are 35 and 34, respectively.

Age at earnings measurement is not contained in the data, so we estimate it with age at FAFSA filing immediately before program enrollment plus typical program length (1 for certificate, 2 for Associate programs, 4 for bachelor's programs) plus 3 years. To the extent that students take longer to complete their programs, the average age will be even older than what is reported here. Using this approach, the mean age when earnings are likely to be measured in programs with at least 30 students is 30.34 across all undergraduate programs; the mean for undergraduate certificate students is 30.42.

Figure 4.1 shows the average estimated age for for-profit certificate holders 3 years after completion, when earnings would be measured, for the 10 most common undergraduate certificate programs (and an aggregate “other” category). All credentials have an average age that falls within or above the range of ages used to construct the earnings threshold. In cases where the average age falls above this range, our earnings threshold is lower than it would be if we adjusted the age band use to match the programs' completers ages.

Second, the ET is typically less than the average pre-program income of program entrants, as measured in their FAFSA. Figure 4.2 shows average pre-program individual income for students at these same types of certificate programs, including any dependent and independent students that had previously been working. Figure 4.2 also plots the ET and the average post-program median earnings for programs under consideration. The program-average share of students used to compute pre-program income is also reported in parentheses. Pre-program income falls above or quite close to the ET for most types of certificate programs. Furthermore, the types of certificate programs that we show as having very high failure rates—Cosmetology and Somatic Bodywork (massage), for example—are unusual in having very low post-program earnings compared to other programs that have similar pre-program income.

To exclude workers who are minimally attached to the labor force or in non-covered employment, the Census Postsecondary Employment Outcomes data requires workers to have annual earnings greater than or equal to the annual equivalent of full-time work at the prevailing Federal minimum wage and at least three quarters of non-zero earnings. ( lehd.ces.census.gov/data/pseo_documentation.html). We impose a similar restriction, including only those students whose pre-program earnings are equivalent to full-time work for three quarters at the Federal minimum wage. We only compute average pre-program income if at least 30 students meet this criteria.

Across undergraduate certificate programs for which the pre-program income measure was calculated, the average share of students meeting the criteria is 41 percent (weighting each program equally) or 38 percent (weighting programs by title IV, HEA enrollment). Given incomplete coverage and the potential for non-random selection into the sample measuring pre-program income, we view this analysis as only suggestive.

We view this as suggestive evidence that the ET chosen provides a reasonable, but conservative, guide to the minimum earnings that program graduates should be expected to obtain.

The earnings of 25 to 34 high school graduates used to construct the ET (similar in age to program completers 3 years after graduation) should be expected to exceed pre-program income because the former likely has more labor force experience than the latter. Therefore, the comparison favors finding that the ET exceeds pre-program income. The fact that pre-program income generally exceeds the ET suggests that the ET is conservative.

Analysis of Data Coverage

This section begins with a presentation of the Department's estimate of the share of enrollment and programs that would meet the n-size requirement and be evaluated under the rule. We assembled data on the number of completers in the two-year cohort period (AYs 2016–2017) and total title IV, HEA enrollment for programs defined at the six-digit OPEID, credential level, and six-digit CIP code from NSLDS. This is the level of aggregation that will be used in the final rule. Total title IV, HEA enrollment at this same level of disaggregation was also collected. Deceased students and students enrolled during the earnings measurement rule will be excluded from the earnings sample under the final rule. We therefore impute the number of completers in the earning sample by multiplying the total completer count in our data by 82 percent, which is the median ratio of non-enrolled earning count to total completer count derived from programs defined at a four-digit CIP code level.

Table 4.2 below reports the share of title IV, HEA enrollment and programs that would have metrics computed under an n-size of 30 and using six-digit CIP codes to define programs. We estimate that 75 percent of GE enrollment and 15 percent of GE programs would have sufficient n-size to have metrics computed with a two-year cohort. An additional 8 percent of enrollment and 11 percent of programs have an n-size of between 15 and 29 and would be likely have metrics computed using a four-year completer cohort. The comparable rates for eligible non-GE programs are 69 percent of enrollment and 19 percent of programs with a n-size of 30 and using two-year cohort metrics, with the use of four-year cohort rates likely increasing these coverage rates of enrollment and programs by 13 and 15 percent, respectively.

Table 4.2 also reports similar estimates aggregating programs to a four-digit CIP code level. Coverage does not diminish dramatically (3–5 percentage points) when moving from four-digit CIP codes, as presented in the 2022 PPD, to six-digit CIP codes to define programs.

We note that the high coverage of title IV, HEA enrollment relative to title IV, HEA programs reflects the fact that there are many very small programs with only a few students enrolled each year. For example, based on our estimates, more than half of all programs (defined at six-digit CIP code) have fewer than five students completing per year and about twenty percent have fewer than five students enrolled each year. The Department believes that the coverage of students based on enrollment is sufficiently high to generate substantial net benefits and government budget savings from the policy, as described in “Net Budget Impacts” and “Accounting Statement” below. We believe that the extent to which enrollment is covered by the final rule is the appropriate measure on which to focus coverage analysis on because the benefits, costs, and transfers associated with the policy almost all scale with the number of students (enrollment or completions) rather than the number of programs.

Table 4.2—Share of Enrollment and Programs Meeting Sample Size Restrictions, by CIP Code Level

Enrollment Programs
CIP4 CIP6 CIP4 CIP6
GE Programs:
n-size = 15 0.86 0.83 0.29 0.26
n-size = 30 0.79 0.75 0.18 0.15
Non-GE Programs:
n-size = 15 0.85 0.82 0.39 0.34
n-size = 30 0.74 0.69 0.23 0.19
Notes: Average school-certified enrollment in AY1617 is used as the measure of enrollment, but the 2022 PPD analyzed in the RIA uses total (certified and non-certified) enrollment, so coverage rates will differ. Non-enrolled earnings count for AY1617 completers is not available at a six-digit CIP level (for any n-size) or at a four-digit CIP level (for n-size = 15). Therefore, non-enrolled earnings counts are imputed based on the median ratio of non-enrolled earnings count to total completer counts at the four-digit CIP level where available. This median ratio is multiplied by the actual completer count for AY1617 at the four- and six-digit CIP level for all programs to determine the estimated n-size.

The rest of this section describes coverage rates for programs as they appear in the 2022 PPD to give context for the numbers presented in the RIA. Again, the analyses above are the better guide to the coverage of metrics we are publishing under the rule. The coverage in the 2022 PPD is lower than that reported in Table 4.2, due to differences in data used and because the 2022 PPD does not apply the four-year cohort period “look back” provisions and instead only uses two-year cohorts.

Unlike the final rule, the 2022 PPD also combines earnings and debt data from two different (but overlapping) two-year cohorts. Alternatively, the calculations in Table 4.2 use information for a single two-year completer cohort for both earnings and debt, as the rule would do, and therefore provides a more accurate representation of the expected overall coverage. A second difference between the coverage estimates in Table 4.2 and that in the 2022 PPD has do with different data sources that result in slightly different estimates of enrollment coverage between the two sources.

Tables 4.3a and 4.3b report the share of non-GE and GE enrollment and programs with valid D/E rates and EP rates in the 2022 PPD, by control and credential level. For Non-GE programs, metrics could be calculated for about 62 percent of enrollment who attended about 18 percent of programs. Coverage is typically highest for public bachelor's degree programs and professional programs at private nonprofit institutions. Doctoral programs in either sector are the least likely to have sufficient size to compute performance metrics. Programs at foreign institutions are very unlikely to have a sufficient number of completers.

Programs located in U.S. Territories and freely associated states are included in this table but are considered as having no available data, which slightly underestimates the enrollment and program coverage estimates provided.

Overall, about 66 percent of title IV, HEA enrollment is in GE programs that have a sufficient number of completers to allow the Department to construct both valid D/E and EP rates in the 2022 PPD. This represents about 13 percent of GE programs. Note that a small number of programs have an EP metric computed but a D/E metric is not available because there are fewer than 30 completers in the two-year debt cohort. Coverage is typically higher in the proprietary sector—we are able to compute D/E or EP metrics for programs accounting for about 87 percent of enrollment in proprietary undergraduate certificate programs. Comparable rates are about 62 percent and 22 percent of enrollment in the nonprofit and public undergraduate certificate sectors, respectively.

Table 4.3 a —Percent of Programs and Enrollment in Programs With Valid D/E and EP Information by Control and Credential Level

[Non-GE programs]

Data availability category
Has both D/E and EP Has EP only Does not have EP or D/E
Programs Enrollees Programs Enrollees Programs Enrollees
Public:
Associate 11.6 55.8 0.3 0.3 88.1 43.9
Bachelor's 39.3 74.3 0.5 0.2 60.2 25.5
Master's 14.1 50.7 0.7 0.9 85.2 48.5
Doctoral 2.8 21.0 0.3 0.7 96.9 78.4
Professional 37.3 55.0 0.7 0.6 62.0 44.4
Private, Nonprofit:
Associate 12.6 61.9 0.4 0.1 87.0 38.0
Bachelor's 13.4 50.6 0.3 0.4 86.3 49.1
Master's 18.3 60.5 0.9 0.9 80.8 38.6
Doctoral 6.9 45.8 0.3 1.9 92.8 52.3
Professional 42.9 74.4 1.9 0.8 55.2 24.8
Foreign Private:
Associate 100.0 100.0
Bachelor's 0.1 1.2 99.9 98.8
Master's 0.3 4.6 0.1 0.4 99.6 95.0
Doctoral 100.0 100.0
Professional 3.4 20.7 1.1 3.9 95.5 75.4
Total:
Total 17.7 61.3 0.4 0.3 81.9 38.4

Table 4.3 b —Percent of Programs and Enrollment in Programs With Valid D/E and EP Information by Control and Credential Level

[GE programs]

Data availability category
Has both D/E and EP Has EP only Does not have EP or D/E
Programs Enrollees Programs Enrollees Programs Enrollees
Public:
UG Certificates 4.8 21.4 0.3 0.4 94.9 78.2
Post-BA Certs 0.9 7.0 0.1 0.2 99.0 92.7
Grad Certs 2.7 21.7 0.2 1.3 97.1 77.0
Private, Nonprofit:
UG Certificates 12.4 61.5 0.5 0.1 87.1 38.4
Post-BA Certs 0.7 3.8 1.0 2.5 98.3 93.8
Grad Certs 3.9 25.6 0.4 1.1 95.8 73.4
Proprietary:
UG Certificates 50.8 87.0 1.4 0.4 47.8 12.7
Associate 34.9 84.4 2.3 0.7 62.9 15.0
Bachelor's 38.5 91.6 1.3 0.6 60.3 7.8
Post-BA Certs 8.7 62.2 91.3 37.8
Master's 40.6 89.6 1.9 0.3 57.5 10.1
Doctoral 32.5 68.7 0.8 3.3 66.7 28.0
Professional 31.0 65.1 3.4 21.2 65.5 13.7
Grad Certs 16.1 66.8 4.8 1.1 79.0 32.2
Total:
Total 12.7 65.0 0.6 0.6 86.6 34.4

Explanation of Terms

While most analysis will be simple cross-tabulations by two or more variables, we use linear regression analysis (also referred to as “ordinary least squares”) to answer some questions about the relationship between variables holding other factors constant. Regression analysis is a statistical method that can be used to measure relationships between variables. For instance, in the demographic analysis, the demographic variables we analyze are referred to as “independent” variables because they represent the potential inputs or determinants of outcomes or may be proxies for other factors that influence those outcomes. The annual debt to earnings (D/E) rate and earnings premium (EP) are referred to as “dependent” variables because they are the variables for which the relationship with the independent variables is examined. The output of a regression analysis contains several relevant points of information. The “coefficient,” also known as the point estimate, for each independent variable is the average amount that a dependent variable is estimated to change with a one-unit change in the associated independent variable, holding all other independent variables included in the model constant. The standard error of a coefficient is a measure of the precision of the estimate. The ratio of the coefficient and standard error, called a “t-statistic” is commonly used to determine whether the relationship between the independent and dependent variables is “statistically significant” at conventional levels. If an estimated coefficient is imprecise ( i.e., it has a large standard error relative to the coefficient), it may not be a reliable measure of the underlying relationship. Higher values of the t-statistic indicate a coefficient is more precisely estimated. The “R-squared” is the fraction of the variance of the dependent variable that is statistically explained by the independent variables.

We use significance level, or alpha, of 0.05 when assessing the statistical significance in our regression analysis.

Results of the Financial Value Transparency Measures for Programs Not Covered by Gainful Employment

In this subsection we examine the results of the analysis of the transparency provisions of the final regulations for the 123,524 non-GE programs. The analysis is focused on results for a single set of financial-value measures—approximating rates that would have been released in 2022 (with some differences, described above). Though programs with fewer than 30 completers in the cohort are not subject to the D/E and EP tests and would not have these metrics published, we retain these programs in our analysis and list them in the tables as “No Data” to provide a more complete view of the distribution of enrollment and programs across the D/E and EP metrics.

Tables 4.4 and 4.5 report the results for non-GE programs by control and credential level. Graduate programs with failing D/E metrics are required to have students acknowledge having seen the program outcome information before prospective students can sign enrollment agreements with an institution. Students at non-GE programs that do not pass the earnings premium metric are not subject to the student acknowledgment requirement, however, for informational purposes, we report rates of passing this metric for non-GE programs as well. We expect performance on the EP metric contained on the ED-administered program information website to be of interest to students even if it is not part of the acknowledgment requirement. This analysis shows that:

  • 842 public and 640 nonprofit degree programs (representing 1.2 and 1.5 percent of programs and 4.6 and 6.6 percent of enrollment, respectively) would fail at least one of the D/E or EP metrics.
  • At the undergraduate level, failure of the EP metric is most common at associate degree programs, whereas failure of the D/E metric is relatively more common among public bachelor's degree programs and at nonprofit associate degree programs.
  • Failure for graduate programs is almost exclusively due to the failure of the D/E metric and is most prominent for professional programs at private, nonprofit institutions.
  • In total, 125,600 students (1.1 percent) at public institutions and 231,100 students (5.8 percent) at nonprofit institutions are in programs with failing D/E metrics.

Table 4.4—Number and Percent of Title IV, HEA Enrollment in Non-GE by Result, Control, and Credential Level

Percent of enrollment Number of enrollments
No data Pass Fail D/E only Fail both D/E and EP Fail EP only No data Pass Fail D/E only Fail both D/E and EP Fail EP only
Public:
Associate 44.1 48.1 0.4 0.2 7.3 2,425,300 2,641,900 19,900 9,800 400,000
Bachelor's 25.9 72.3 1.1 0.2 0.5 1,502,200 4,195,900 63,000 10,300 29,400
Master's 49.4 49.4 1.2 0.0 0.0 375,800 375,400 9,000 300 0
Doctoral 79.0 18.4 2.6 0.0 0.0 114,800 26,700 3,800 0 0
Professional 45.1 47.4 7.5 0.0 0.0 57,400 60,400 9,600 0 0
Total 36.3 59.2 0.9 0.2 3.5 4,475,500 7,300,200 105,300 20,300 429,400
Private, Nonprofit:
Associate 40.6 36.2 8.0 14.5 0.6 108,500 96,600 21,500 38,600 1,700
Bachelor's 51.4 44.8 1.7 1.0 1.2 1,362,100 1,186,900 44,800 26,800 30,600
Master's 40.2 55.6 3.8 0.3 0.1 320,300 442,300 30,400 2,400 800
Doctoral 54.2 30.3 15.4 0.1 0.0 77,400 43,300 22,000 200 0
Professional 26.7 39.0 34.1 0.0 0.2 34,900 50,900 44,400 0 200
Total 47.7 45.6 4.1 1.7 0.8 1,903,200 1,820,000 163,000 68,100 33,300
Foreign Private:
Associate 100.0 0.0 0.0 0.0 0.0 100 0 0 0 0
Bachelor's 98.8 0.0 0.0 1.2 0.0 5,400 0 0 100 0
Master's 95.4 2.8 1.8 0.0 0.0 8,600 300 200 0 0
Doctoral 100.0 0.0 0.0 0.0 0.0 2,800 0 0 0 0
Professional 79.3 0.0 20.7 0.0 0.0 1,200 0 300 0 0
Total 95.7 1.3 2.6 0.4 0.0 18,100 300 500 100 0
Total:
Associate 44.0 47.5 0.7 0.8 7.0 2,533,800 2,738,500 41,400 48,400 401,700
Bachelor's 33.9 63.6 1.3 0.4 0.7 2,869,700 5,382,800 107,800 37,200 60,000
Master's 45.0 52.2 2.5 0.2 0.1 704,700 817,900 39,500 2,700 800
Doctoral 67.0 24.1 8.9 0.1 0.0 194,900 70,000 25,800 200 0
Professional 36.1 42.9 20.9 0.0 0.1 93,500 111,300 54,300 0 200
Total 39.2 55.8 1.6 0.5 2.8 6,396,700 9,120,500 268,800 88,500 462,700
Note: Enrollment counts rounded to the nearest 100.

Table 4.5—Number and Percent of Non-GE Programs by Result, Control, and Credential Level

Result in 2019
No D/E or EP data Pass Fail D/E only Fail both D/E and EP Fail EP Only
Percent N Percent N Percent N Percent N Percent N
Public:
Associate 88.5 24,165 9.9 2,693 0.1 24 0.1 19 1.5 411
Bachelor's 61.0 14,855 37.7 9,167 0.7 164 0.2 48 0.4 104
Master's 86.0 12,547 13.6 1,990 0.3 41 0.0 3 0.0 1
Doctoral 97.2 5,562 2.7 153 0.2 9 0.0 0 0.0 0
Professional 63.9 363 32.9 187 3.2 18 0.0 0 0.0 0
Total 79.3 57,492 19.6 14,190 0.4 256 0.1 70 0.7 516
Private, Nonprofit:
Associate 88.3 2,049 8.9 206 1.2 29 1.3 30 0.3 7
Bachelor's 87.0 25,891 12.1 3,608 0.4 119 0.2 69 0.2 65
Master's 82.2 8,513 16.1 1,665 1.6 162 0.2 17 0.0 5
Doctoral 93.1 2,658 5.0 142 1.8 52 0.1 2 0.0 0
Professional 58.6 289 24.5 121 16.2 80 0.0 0 0.6 3
Total 86.1 39,400 12.5 5,742 1.0 442 0.3 118 0.2 80
Foreign Private:
Associate 100.0 18 0.0 0 0.0 0 0.0 0 0.0 0
Bachelor's 99.9 1,227 0.0 0 0.0 0 0.1 1 0.0 0
Master's 99.7 3,067 0.1 4 0.1 3 0.0 0 0.0 1
Doctoral 100.0 793 0.0 0 0.0 0 0.0 0 0.0 0
Professional 97.1 101 0.0 0 2.9 3 0.0 0 0.0 0
Total 99.8 5,206 0.1 4 0.1 6 0.0 1 0.0 1
Total:
Associate 88.5 26,232 9.8 2,899 0.2 53 0.2 49 1.4 418
Bachelor's 75.9 41,973 23.1 12,775 0.5 283 0.2 118 0.3 169
Master's 86.1 24,127 13.1 3,659 0.7 206 0.1 20 0.0 7
Doctoral 96.2 9,013 3.1 295 0.7 61 0.0 2 0.0 0
Professional 64.6 753 26.4 308 8.7 101 0.0 0 0.3 3
Total 82.7 102,098 16.1 19,936 0.6 704 0.2 189 0.5 597

Tables 4.6 and 4.7 report results by credential level and 2-digit CIP code for non-GE programs. This analysis shows that—

  • Rates of not passing at least one of the metrics are particularly high for professional programs in law (CIP 22, about 19 percent of law programs representing 29 percent of enrollment in law programs), theology (CIP 39, about 7 percent, 25 percent) and health (CIP 51, about 10 percent, 19 percent). Recall that for graduate degrees, failure is almost exclusively due to the D/E metric, which would trigger the acknowledgment requirement.

Table 4.6—Percent of Non-GE Title IV, HEA Enrollment in Programs Failing Either D/E or EP Metric, by CIP2

Credential level
Associate Bachelor's Master's Doctoral Professional Total
1: Agriculture & Related Sciences 0.8 1.2 0.0 0.0 0.0 1.0
3: Natural Resources And Conservation 0.0 1.3 1.8 0.0 0.0 1.2
4: Architecture And Related Services 0.0 0.0 2.7 0.0 0.0 0.7
5: Area & Group Studies 0.0 0.6 0.0 0.0 0.0 0.5
9: Communication 3.5 1.8 2.0 0.0 0.0 2.0
10: Communications Tech 8.1 2.9 0.0 5.9
11: Computer Sciences 1.5 0.1 0.0 0.0 0.0 0.6
12: Personal And Culinary Services 9.5 0.0 0.0 8.3
13: Education 16.6 2.6 1.6 4.3 0.0 4.2
14: Engineering 0.0 0.0 0.0 0.0 0.0 0.0
15: Engineering Tech 0.3 0.0 0.0 0.0 0.2
16: Foreign Languages 1.0 2.1 0.0 0.0 0.0 1.8
19: Family & Consumer Sciences 11.2 8.0 3.8 0.0 0.0 9.2
22: Legal Professions 7.8 9.8 3.6 29.6 28.5 20.0
23: English Language 1.1 5.7 3.9 0.0 0.0 4.8
24: Liberal Arts 14.0 2.8 0.6 0.0 0.0 10.8
25: Library Science 0.0 0.0 0.0 0.0 0.0 0.0
26: Biological & Biomedical Sciences 4.9 2.2 6.0 1.4 0.0 2.7
27: Mathematics And Statistics 0.0 0.0 0.0 0.0 0.0 0.0
28: Military Science 0.0 0.0 0.0
29: Military Tech 0.0 0.0 0.0 0.0
30: Multi/Interdisciplinary Studies 1.3 1.1 1.6 0.0 0.0 1.2
31: Parks & Rec 4.8 1.8 0.6 0.0 0.0 2.2
32: Basic Skills 0.0 0.0 0.0 0.0
33: Citizenship Activities 0.0 0.0 0.0
34: Health-Related Knowledge And Skills 0.0 0.0 0.0 0.0 0.0 0.0
35: Interpersonal And Social Skills 0.0 0.0 0.0
36: Leisure And Recreational Activities 0.0 0.0 0.0 0.0 0.0
37: Personal Awareness And Self-Improvement 0.0 0.0
38: Philosophy And Religious Studies 40.5 1.3 0.0 0.0 0.0 4.2
39: Theology And Religious Vocations 9.4 21.5 7.7 0.0 25.4 14.8
40: Physical Sciences 0.0 0.3 0.0 0.0 0.0 0.2
41: Science Technologies/Technicians 4.2 0.0 0.0 0.0 3.7
42: Psychology 10.8 6.4 4.7 2.0 0.0 6.6
43: Homeland Security 3.7 2.5 5.5 0.0 0.0 3.2
44: Public Admin & Social Services 23.4 3.9 0.5 0.0 0.0 6.2
45: Social Sciences 4.9 0.9 3.2 0.0 0.0 1.6
46: Construction Trades 0.0 0.0 0.0 0.0 0.0
47: Mechanic & Repair Tech 0.4 0.0 0.4
48: Precision Production 0.0 0.0 0.0 0.0
49: Transportation And Materials Moving 0.0 0.0 0.0 0.0 0.0
50: Visual And Performing Arts 6.4 12.7 21.6 1.9 0.0 11.6
51: Health Professions And Related Programs 5.8 1.0 5.5 20.1 18.6 5.4
52: Business 5.3 0.5 0.3 0.0 0.0 1.9
53: High School/Secondary Diplomas 0.0 0.0 0.0 0.0
54: History 0.0 0.8 12.2 0.0 0.0 1.6
60: Residency Programs 0.0 0.0 0.0 0.0
Total 8.5 2.4 2.7 8.9 21.0 5.0

Table 4.7—Percent of Non-GE Programs Failing Either D/E or EP Metric, by CIP2

Credential level
Associate Bachelor's Master's Doctoral Professional Total
1: Agriculture & Related Sciences 0.1 0.7 0.0 0.0 0.0 0.3
3: Natural Resources And Conservation 0.0 0.4 0.3 0.0 0.0 0.3
4: Architecture And Related Services 0.0 0.0 0.8 0.0 0.0 0.3
5: Area & Group Studies 0.0 0.3 0.0 0.0 0.0 0.2
9: Communication 0.8 1.1 0.6 0.0 0.0 0.9
10: Communications Tech 2.2 2.4 0.0 2.1
11: Computer Sciences 0.4 0.1 0.0 0.0 0.0 0.2
12: Personal And Culinary Services 3.9 0.0 0.0 3.6
13: Education 3.5 0.8 0.7 0.1 0.0 0.9
14: Engineering 0.0 0.0 0.0 0.0 0.0 0.0
15: Engineering Tech 0.1 0.0 0.0 0.0 0.0 0.1
16: Foreign Languages 0.3 0.6 0.0 0.0 0.0 0.4
19: Family & Consumer Sciences 3.5 2.9 1.2 0.0 0.0 2.7
22: Legal Professions 1.0 1.4 0.4 14.3 19.2 4.9
23: English Language 0.4 1.9 1.0 0.0 0.0 1.4
24: Liberal Arts 15.2 2.1 0.4 0.0 0.0 8.0
25: Library Science 0.0 0.0 0.0 0.0 0.0 0.0
26: Biological & Biomedical Sciences 0.8 1.1 0.5 0.1 0.0 0.7
27: Mathematics And Statistics 0.0 0.0 0.0 0.0 0.0 0.0
28: Military Science 0.0 0.0 0.0
29: Military Tech 0.0 0.0 0.0 0.0
30: Multi/Interdisciplinary Studies 1.1 0.7 0.4 0.0 0.0 0.6
31: Parks & Rec 0.8 1.3 0.3 0.0 0.0 1.0
32: Basic Skills 0.0 0.0 0.0 0.0
33: Citizenship Activities 0.0 0.0 0.0
34: Health-Related Knowledge And Skills 0.0 0.0 0.0 0.0 0.0 0.0
35: Interpersonal And Social Skills 0.0 0.0 0.0
36: Leisure And Recreational Activities 0.0 0.0 0.0 0.0 0.0
37: Personal Awareness And Self-Improvement 0.0 0.0
38: Philosophy And Religious Studies 2.1 0.2 0.0 0.0 0.0 0.2
39: Theology And Religious Vocations 2.0 2.5 2.6 0.0 6.6 2.4
40: Physical Sciences 0.0 0.0 0.0 0.0 0.0 0.0
41: Science Technologies/Technicians 0.6 0.0 0.0 0.0 0.4
42: Psychology 3.1 2.9 0.9 0.6 0.0 2.0
43: Homeland Security 0.8 2.0 0.8 0.0 0.0 1.2
44: Public Admin & Social Services 6.3 1.1 0.4 0.0 0.0 1.7
45: Social Sciences 0.5 0.5 0.2 0.0 0.0 0.4
46: Construction Trades 0.0 0.0 0.0 0.0 0.0
47: Mechanic & Repair Tech 0.2 0.0 0.2
48: Precision Production 0.0 0.0 0.0 0.0
49: Transportation And Materials Moving 0.0 0.0 0.0 0.0 0.0
50: Visual And Performing Arts 1.4 4.4 4.9 0.4 0.0 3.7
51: Health Professions And Related Programs 1.3 0.6 2.5 4.5 9.7 2.0
52: Business 1.4 0.2 0.1 0.0 0.0 0.5
53: High School/Secondary Diplomas 0.0 0.0 0.0 0.0
54: History 0.0 0.3 0.5 0.0 0.0 0.3
60: Residency Programs 0.0 0.0 0.0 0.0 0.0
Total 1.8 1.0 0.8 0.7 8.9 1.2

Results of GE Accountability for Programs Subject to the Gainful Employment Rule

This analysis is based on the 2022 PPD described in the “Data Used in this RIA” above. In this subsection, we examine the combined results of the analysis of the final regulations for the 32,058 GE Programs. The analysis is primarily focused on GE metric results for a single year, though continued eligibility depends on performance in multiple years. The likelihood of repeated failure is discussed briefly below and is incorporated into the budget impact and cost-benefit analyses. Though programs with fewer than 30 completers in the cohort are not subject to the D/E and EP tests, we retain these programs in our analysis to provide a more complete view of program passage than if they were excluded.

Program-Level Results

Tables 4.8 and 4.9 report D/E and EP results by control and credential level for GE programs. This analysis shows that:

  • About 64 percent of enrollment is in the 3,937 GE programs for which rates can be calculated.
  • 40 percent of enrollment is in 2,228 programs (about 7 percent of all GE programs) that meet the size threshold and would pass both the D/E measure and EP metrics.
  • About 24 percent of enrollment is in 1,709 programs (about 5 percent of all GE programs) that would fail at least one of the two metrics.

• Failure rates are significantly lower for public certificate programs (about 4 percent of enrollment is in failing programs) than for proprietary (about 51 percent of enrollment is in failing programs) or nonprofit (about 41 percent of enrollment is in failing programs) certificate programs, though the latter represents a relatively small share of overall enrollment. Certificate programs that fail typically fail the EP metric, rather than the D/E metric.

  • Across all proprietary certificate and degree programs, about 33 percent of enrollment is in programs that fail one of the two metrics, representing about 22 percent of programs. Degree programs that fail typically fail the D/E metric, with only associate degree programs having a noticeable number of programs that fail the EP metric.

Table 4.8—Number and Percent of Title IV, HEA Enrollment in GE Programs by Result, Control, and Credential Level

Percent Number
No data Pass Fail D/E only Fail both D/E and EP Fail EP only No data Pass Fail D/E only Fail both D/E and EP Fail EP only
Public:
UG Certificates 78.5 17.2 0.0 0.3 4.0 682,300 149,300 200 3,000 34,700
Post-BA Certs 93.0 7.0 0.0 0.0 0.0 11,800 900 0 0 0
Grad Certs 78.3 21.3 0.4 0.0 0.0 32,800 8,900 200 0 0
Total 78.7 17.2 0.0 0.3 3.8 726,900 159,200 300 3,000 34,700
Private, Nonprofit:
UG Certificates 41.6 17.9 0.0 3.9 36.6 32,400 14,000 0 3,100 28,500
Post-BA Certs 96.2 3.8 0.0 0.0 0.0 7,600 300 0 0 0
Grad Certs 75.4 21.9 2.7 0.0 0.0 26,900 7,800 1,000 0 0
Total 55.1 18.2 0.8 2.5 23.4 67,000 22,100 1,000 3,100 28,500
Proprietary:
UG Certificates 15.2 34.0 0.2 8.5 42.1 83,700 187,000 1,100 46,500 231,700
Associate 18.3 44.6 19.4 14.2 3.4 59,900 145,700 63,500 46,500 11,200
Bachelor's 9.6 66.0 22.5 1.8 0.0 65,200 446,100 152,200 12,100 200
Post-BA Certs 37.8 62.2 0.0 0.0 0.0 300 500 0 0 0
Master's 10.7 72.6 15.7 0.9 0.0 25,800 174,300 37,700 2,200 0
Doctoral 31.3 58.1 10.6 0.0 0.0 16,900 31,400 5,700 0 0
Professional 34.9 14.5 50.7 0.0 0.0 4,200 1,800 6,100 0 0
Grad Certs 32.6 28.9 37.9 0.0 0.7 3,500 3,100 4,100 0 100
Total 13.9 52.9 14.5 5.7 13.0 259,400 989,800 270,400 107,300 243,100
Foreign Private:
UG Certificates 100.0 0.0 0.0 0.0 0.0 100 0 0 0 0
Post-BA Certs 100.0 0.0 0.0 0.0 0.0 0 0 0 0 0
Grad Certs 15.8 0.0 0.0 84.2 0.0 200 0 0 1,300 0
Total 20.4 0.0 0.0 79.6 0.0 300 0 0 1,300 0
Foreign For-Profit:
Master's 100.0 0.0 0.0 0.0 0.0 200 0 0 0 0
Doctoral 80.5 19.5 0.0 0.0 0.0 1,600 400 0 0 0
Professional 79.7 0.0 20.3 0.0 0.0 9,200 0 2,400 0 0
Total 80.0 2.8 17.2 0.0 0.0 11,000 400 2,400 0 0
Total:
UG Certificates 53.3 23.4 0.1 3.5 19.7 798,500 350,300 1,300 52,500 294,900
Associate 18.3 44.6 19.4 14.2 3.4 59,900 145,700 63,500 46,500 11,200
Bachelor's 9.6 66.0 22.5 1.8 0.0 65,200 446,100 152,200 12,100 200
Post-BA Certs 92.1 7.9 0.0 0.0 0.0 19,700 1,700 0 0 0
Master's 10.8 72.6 15.7 0.9 0.0 25,900 174,300 37,700 2,200 0
Doctoral 33.0 56.8 10.2 0.0 0.0 18,500 31,800 5,700 0 0
Professional 56.8 7.4 35.8 0.0 0.0 13,400 1,800 8,500 0 0
Grad Certs 70.6 22.1 5.8 1.4 0.1 63,500 19,900 5,200 1,300 100
Total 36.3 40.0 9.4 3.9 10.5 1,064,600 1,171,400 274,100 114,700 306,400
Note: Enrollment counts rounded to the nearest 100.

Table 4.9—Number of GE Programs by Result, Control, and Credential Level

Number Percent
No D/E or EP data Pass Fail D/E only Fail both D/E and EP Fail EP only No D/E or EP data Pass Fail D/E only Fail both D/E and EP Fail EP only
Public:
UG Certificates 18,051 729 1 6 184 95.2 3.8 0.0 0.0 1.0
Post-BA Certs 865 7 0 0 0 99.2 0.8 0.0 0.0 0.0
Grad Certs 1,887 50 2 0 0 97.3 2.6 0.1 0.0 0.0
Total 20,803 786 3 6 184 95.5 3.6 0.0 0.0 0.8
Private, Nonprofit:
UG Certificates 1,229 93 0 5 60 88.6 6.7 0.0 0.4 4.3
Post-BA Certs 625 4 0 0 0 99.4 0.6 0.0 0.0 0.0
Grad Certs 1,346 43 8 0 0 96.3 3.1 0.6 0.0 0.0
Total 3,200 140 8 5 60 93.8 4.1 0.2 0.1 1.8
Proprietary:
UG Certificates 1,659 528 5 153 873 51.6 16.4 0.2 4.8 27.1
Associate 1,155 327 98 78 62 67.2 19.0 5.7 4.5 3.6
Bachelor's 610 251 80 21 1 63.3 26.1 8.3 2.2 0.1
Post-BA Certs 48 4 0 0 0 92.3 7.7 0.0 0.0 0.0
Master's 289 143 37 9 0 60.5 29.9 7.7 1.9 0.0
Doctoral 83 29 10 0 0 68.0 23.8 8.2 0.0 0.0
Professional 23 5 4 0 0 71.9 15.6 12.5 0.0 0.0
Grad Certs 105 14 6 0 3 82.0 10.9 4.7 0.0 2.3
Total 3,972 1,301 240 261 939 59.2 19.4 3.6 3.9 14.0
Foreign Private:
UG Certificates 28 0 0 0 0 100.0 0.0 0.0 0.0 0.0
Post-BA Certs 27 0 0 0 0 100.0 0.0 0.0 0.0 0.0
Grad Certs 76 0 0 1 0 98.7 0.0 0.0 1.3 0.0
Total 131 0 0 1 0 99.2 0.0 0.0 0.8 0.0
Foreign For-Profit:
UG Certificates 1 0 0 0 0 100.0 0.0 0.0 0.0 0.0
Master's 6 0 0 0 0 100.0 0.0 0.0 0.0 0.0
Doctoral 3 1 0 0 0 75.0 25.0 0.0 0.0 0.0
Professional 5 0 2 0 0 71.4 0.0 28.6 0.0 0.0
Total 15 1 2 0 0 83.3 5.6 11.1 0.0 0.0
Total:
UG Certificates 20,968 1,350 6 164 1,117 88.8 5.7 0.0 0.7 4.7
Associate 1,155 327 98 78 62 67.2 19.0 5.7 4.5 3.6
Bachelor's 610 251 80 21 1 63.3 26.1 8.3 2.2 0.1
Post-BA Certs 1,565 15 0 0 0 99.1 0.9 0.0 0.0 0.0
Master's 295 143 37 9 0 61.0 29.5 7.6 1.9 0.0
Doctoral 86 30 10 0 0 68.3 23.8 7.9 0.0 0.0
Professional 28 5 6 0 0 71.8 12.8 15.4 0.0 0.0
Grad Certs 3,414 107 16 1 3 96.4 3.0 0.5 0.0 0.1
Total 28,121 2,228 253 273 1,183 87.7 6.9 0.8 0.9 3.7

Tables 4.10 and 4.11 report the results by credential level and 2-digit CIP code. This analysis shows—

  • The highest rate of failure is undergraduate certificate in Personal and Culinary Services (CIP2 12), where about 73 percent of enrollment, representing 37 percent of undergraduate certificate programs in that field, have failing metrics. This is primarily due to failing the EP metric.
  • In Health Professions and Related Programs (CIP2 51), where allied health, medical assisting, and medical administration are the primary specific fields, 28 percent of enrollment is in an undergraduate certificate program that fails at least one of the two metrics, representing 8 percent of programs.

Table 4.10—Percent of GE Title IV, HEA Enrollment in Programs Failing Either D/E or EP Metric, by CIP2

Credential level
UG certificates Associate Bachelor's Post-BA certs Master's Doctoral Professional Grad certs Total
1: Agriculture & Related Sciences 0.0 0.0 0.0 0.0 0.0 0.0
3: Natural Resources And Conservation 0.0 13.1 0.0 0.0 0.0 9.1
4: Architecture And Related Services 0.0 0.0 0.0 0.0 0.0 0.0 0.0
5: Area & Group Studies 0.0 0.0 0.0 0.0
9: Communication 42.4 0.0 22.9 0.0 21.8 0.0 30.1
10: Communications Tech 10.4 54.7 61.9 0.0 88.9 0.0 38.6
11: Computer Sciences 4.9 9.7 3.6 0.0 4.5 0.0 0.0 5.0
12: Personal And Culinary Services 73.2 59.4 31.8 0.0 0.0 0.0 0.0 31.5 72.4
13: Education 5.9 74.5 75.5 0.0 14.1 0.8 0.0 3.4 24.9
14: Engineering 0.0 37.0 14.5 0.0 0.0 0.0 3.4
15: Engineering Tech 2.0 1.8 0.0 0.0 0.0 0.0 1.6
16: Foreign Languages 0.0 94.8 0.0 0.0 4.5
19: Family & Consumer Sciences 1.8 90.2 72.0 0.0 100.0 100.0 0.0 21.7
22: Legal Professions 3.3 55.9 32.3 0.0 0.0 0.0 61.0 24.2 26.9
23: English Language 57.4 96.6 87.4 0.0 98.2 0.0 66.0
24: Liberal Arts 3.8 0.0 0.0 0.0 0.0 0.0 0.0 3.5
25: Library Science 0.0 100.0 0.0 0.0 23.5
26: Biological & Biomedical Sciences 0.0 0.0 0.0 0.0 0.0 0.0 9.1 1.1
27: Mathematics And Statistics 0.0 0.0 0.0 0.0 0.0
28: Military Science 0.0 0.0 0.0 0.0 0.0
29: Military Tech 0.0 0.0 0.0 0.0 0.0 0.0
30: Multi/Interdisciplinary Studies 0.0 96.2 92.0 0.0 0.0 8.8 55.3
31: Parks & Rec 4.3 66.0 0.0 0.0 0.0 0.0 0.0 9.3
32: Basic Skills 41.8 0.0 0.0 41.4
33: Citizenship Activities 0.0 0.0
34: Health-Related Knowledge And Skills 0.0 0.0 0.0
36: Leisure And Recreational Activities 0.0 0.0 0.0
37: Personal Awareness And Self-Improvement 0.0 0.0 0.0 0.0
38: Philosophy And Religious Studies 0.0 0.0 0.0 0.0 0.0 0.0
39: Theology And Religious Vocations 50.6 0.0 94.2 0.0 90.0 0.0 0.0 0.0 56.1
40: Physical Sciences 0.0 0.0 0.0 0.0 0.0 0.0
41: Science Technologies/Technicians 0.0 0.0 0.0 0.0 0.0
42: Psychology 0.0 0.0 50.3 0.0 27.7 38.0 33.3 36.3
43: Homeland Security 3.1 54.3 21.9 0.0 19.2 66.5 0.0 21.7
44: Public Admin & Social Services 0.0 81.9 57.5 0.0 15.0 9.2 2.8 36.7
45: Social Sciences 0.0 0.0 25.4 0.0 64.5 0.0 0.0 18.0
46: Construction Trades 5.2 0.0 0.0 5.1
47: Mechanic & Repair Tech 2.6 9.6 0.0 0.0 3.2
48: Precision Production 4.1 0.0 4.0
49: Transportation And Materials Moving 2.3 0.0 0.0 0.0 0.0 2.2
50: Visual And Performing Arts 9.8 46.8 52.4 0.0 83.5 0.0 0.0 38.7
51: Health Professions And Related Programs 28.4 33.0 25.2 0.0 24.0 3.3 36.7 15.1 27.8
52: Business 6.7 40.6 2.8 0.0 3.8 2.0 0.0 0.6 9.0
53: High School/Secondary Diplomas 0.0 0.0 0.0
54: History 0.0 0.0 36.4 0.0 0.0 0.0 20.3
60: Residency Programs 0.0 0.0 0.0 0.0
Total 23.3 37.1 24.3 0.0 16.6 10.2 35.8 7.3 23.7

Table 4.11—Percent of GE Programs Failing Either D/E or EP Metric, by CIP2

Credential level
UG certificates Associate Bachelor's Post-BA certs Master's Doctoral Professional Grad certs Total
1: Agriculture & Related Sciences 0.0 0.0 0.0 0.0 0.0 0.0
3: Natural Resources And Conservation 0.0 20.0 0.0 0.0 0.0 0.7
4: Architecture And Related Services 0.0 0.0 0.0 0.0 0.0 0.0 0.0
5: Area & Group Studies 0.0 0.0 0.0 0.0
9: Communication 1.9 0.0 12.0 0.0 11.1 0.0 2.4
10: Communications Tech 1.3 17.4 29.2 0.0 33.3 0.0 4.4
11: Computer Sciences 0.8 6.0 1.8 0.0 2.4 0.0 0.0 1.2
12: Personal And Culinary Services 37.2 12.7 18.2 0.0 0.0 0.0 0.0 11.1 35.5
13: Education 1.3 10.0 18.2 0.0 6.3 4.3 0.0 0.4 1.2
14: Engineering 0.0 20.0 10.0 0.0 0.0 0.0 0.7
15: Engineering Tech 0.2 2.8 0.0 0.0 0.0 0.0 0.3
16: Foreign Languages 0.0 50.0 0.0 0.0 0.4
19: Family & Consumer Sciences 0.7 25.0 27.3 0.0 100.0 100.0 0.0 1.9
22: Legal Professions 0.6 19.7 12.5 0.0 0.0 0.0 25.0 3.8 4.0
23: English Language 8.6 20.0 36.4 0.0 50.0 0.0 7.9
24: Liberal Arts 1.1 0.0 0.0 0.0 0.0 0.0 0.0 0.9
25: Library Science 0.0 100.0 0.0 0.0 1.9
26: Biological & Biomedical Sciences 0.0 0.0 0.0 0.0 0.0 0.0 1.1 0.4
27: Mathematics And Statistics 0.0 0.0 0.0 0.0 0.0
28: Military Science 0.0 0.0 0.0 0.0 0.0
29: Military Tech 0.0 0.0 0.0 0.0 0.0 0.0
30: Multi/Interdisciplinary Studies 0.0 25.0 28.6 0.0 0.0 0.7 1.4
31: Parks & Rec 1.6 12.0 0.0 0.0 0.0 0.0 0.0 2.3
32: Basic Skills 5.4 0.0 0.0 5.1
33: Citizenship Activities 0.0 0.0
34: Health-Related Knowledge And Skills 0.0 0.0 0.0
35: Interpersonal And Social Skills 0.0 0.0
36: Leisure And Recreational Activities 0.0 0.0 0.0
37: Personal Awareness And Self-Improvement 0.0 0.0 0.0 0.0
38: Philosophy And Religious Studies 0.0 0.0 0.0 0.0 0.0 0.0
39: Theology And Religious Vocations 4.9 0.0 20.0 0.0 14.3 0.0 0.0 0.0 2.8
40: Physical Sciences 0.0 0.0 0.0 0.0 0.0 0.0
41: Science Technologies/Technicians 0.0 0.0 0.0 0.0 0.0
42: Psychology 0.0 0.0 28.6 0.0 15.8 13.3 1.4 3.7
43: Homeland Security 0.6 21.6 12.1 0.0 13.0 25.0 0.0 3.0
44: Public Admin & Social Services 0.0 40.0 21.4 0.0 10.5 28.6 1.1 2.8
45: Social Sciences 0.0 0.0 13.3 0.0 20.0 0.0 0.0 0.8
46: Construction Trades 1.2 0.0 0.0 1.2
47: Mechanic & Repair Tech 1.5 6.2 0.0 0.0 0.0 1.7
48: Precision Production 1.6 0.0 1.6
49: Transportation And Materials Moving 0.9 0.0 0.0 0.0 0.0 0.8
50: Visual And Performing Arts 1.2 18.8 23.5 0.0 38.5 0.0 0.0 5.5
51: Health Professions And Related Programs 8.4 16.5 6.3 0.0 10.6 5.1 22.2 1.1 8.2
52: Business 1.4 14.9 5.2 0.0 4.3 4.3 0.0 0.2 2.4
53: High School/Secondary Diplomas 0.0 0.0 0.0
54: History 0.0 0.0 16.7 0.0 0.0 0.0 1.8
60: Residency Programs 0.0 0.0 0.0 0.0
Total 5.5 13.8 10.6 0.0 9.5 7.9 15.4 0.6 5.3

Program Ineligibility

For GE programs, title IV, HEA ineligibility is triggered by two years of failing the same metric within a three-year period. Years when a program does not meet the n-size requirement are not counted towards those three years. The top panel of Table 4.12 shows the share of GE enrollment and programs in each result category in a second year as a function of the result in the first year, along with the rate of becoming ineligible. Failure rates are quite persistent, with failure in one year being highly predictive of failure in the next year, and therefore ineligibility for title IV, HEA funds. Among programs that fail only the D/E metric in the first year, 69.6 percent of enrollment is in programs that also fail D/E in year 2 and would be ineligible for title IV, HEA participation the following year. The comparable rates for programs that fail EP only or both D/E and EP in the first year are 86.6 and 96.3 percent, respectively. The share of programs (rather than enrollment in such programs) that become ineligible conditional on first year results is similar, as shown in the bottom panel of Table 4.12. These rates understate the share of programs that would ultimately become ineligible when a third year is considered.

Institution-Level Analysis of GE Program Accountability Provisions

Many institutions have few programs that are subject to the accountability provisions of GE, either because they are nonproprietary institutions with relatively few certificate programs or because their programs tend to be too small in size to have published median debt or earnings measures. Characterizing the share of GE programs that have reported debt and earnings metrics that fail in particular postsecondary sectors can therefore give a distorted sense for the effect the rule might have on institutions in that sector. For example, a college (or group of colleges) might offer a single GE program that fails the rule and so appear to have 100 percent of its GE programs fail the rule. But if that program is a very small share of the institution's overall enrollment (or its title IV, HEA enrollment) then even if every student in that program were to stop enrolling in the institution—an unlikely scenario as discussed below—the effect on the institution(s) would be much less than would be implied by the 100 percent failure rate among its GE programs. To provide better context for evaluating the potential effect of the GE rule on institutions or sets of institutions, we describe the share of all title IV, HEA supported enrollment—including enrollment in both GE and non-GE programs—that is in a GE program and that fails a GE metric and, therefore, is at risk of losing title IV, HEA eligibility. Again, this should not be viewed as an estimate of potential enrollment (or revenue) loss to the institution—in many cases the most likely impact of a program failing the GE metrics or losing eligibility is that students enroll in higher performing programs in the same institution.

Note that these statistics still do not fully capture the financial impact of GE on institutions. A complete analysis would account for the share of institutional revenue accounted for by title IV, HEA students, and the extent to which students in programs that fail GE will unenroll from the institutions entirely (versus transferring to a passing program at the same institution). The measures here are best viewed as a proxy for the share of Federal title IV, HEA revenue at an institution that is potentially at risk due to the GE accountability provisions.

Table 4.13 reports the distribution of institutions by share of enrollment that is in a failing GE program, by control and institution type. It shows that about 91 percent of public institutions and 95 percent of nonprofit institutions have no enrollment in GE programs that fail the GE metric. This rate is much lower–about 44 percent -for proprietary institutions, where all types of credential programs are covered by GE accountability and failure rates tend to be higher.

Table 4.13—Distribution of Institutions by Share of Enrollment That Fails GE Accountability, by Control and Institution Type

[All Institutions]

Share of institutional enrollment in failing GE programs
Total 0% 0–5% 5–10% 10–20% 20–40% 40–99% 100%
Public:
Less-Than 2-Year 560 470 20 10 30 20 10 0
2-Year 650 610 40 0 0 0 0 0
4-Year or Above 380 380 0 0 0 0 0 0
Total 1,590 1,450 60 20 30 30 10 0
Private, Nonprofit:
Less-Than 2-Year 110 90 0 0 0 0 10 10
2-Year 60 50 0 0 0 0 0 0
4-Year or Above 560 550 10 0 0 0 0 0
Total 730 690 10 0 0 10 10 10
Proprietary:
Less-Than 2-Year 1,270 530 10 10 20 30 200 480
2-Year 120 70 0 10 0 10 30 0
4-Year or Above 100 60 0 0 10 10 20 0
Total 1,490 660 10 10 30 60 240 490
Total:
Less-Than 2-Year 1,940 1,080 30 20 50 60 210 490
2-Year 820 720 40 10 10 20 30 0
4-Year or Above 1,050 990 10 10 10 10 20 0
Total 3,810 2,800 80 30 60 90 260 500
Note: All counts rounded to the nearest 100. Columns may not sum to totals because of rounding.

Very few public community or technical colleges (CCs) have considerable enrollment in programs that would fail GE. About 6 percent of the predominant 2-year public colleges have any of their enrollment in certificate programs that would fail, and about 5 percent of the predominantly less than two-year technical colleges have more than 20 percent of enrollment that does.

The share of enrollment in failing GE programs for Historically Black Colleges and Universities (HBCUs), Tribal Colleges and Universities (TCUs), and other minority-serving institutions is even smaller, as shown in Table 4.14. At HBCUs, only one college out of 100 has more than five percent of enrollment in failing programs; across all HBCUs, only five programs at four schools fail. TCUs have no failing programs. Less than one percent of Hispanic-serving institutions (HSIs) have more than 10 percent of enrollment in failing programs. We conducted a similar analysis excluding institutions that do not have any GE programs. The patterns are similar.

Under § 668.403(b)(1)(i), debt considered in the calculation of the D/E rates is capped at the total net cost for tuition, fees, and books. However, due to data constraints noted in the RIA, this cap was not applied in the analysis of the impact of the rule. An analysis by New America suggests that this cap will lead to a large reduction in the number of graduate programs at HBCUs, HSIs, TCUs, and other MSIs projected to fail the D/E rates measure. See Caldwell, Tia & Garza, Roxanne (2023). Previous Projections Overestimated Gainful Employment Failures: Almost All HBCUs & MSI Graduate Programs Pass. New America ( https://www.newamerica.org/education-policy/edcentral/ge-failures-overestimated/ ).

The number of Hispanic Serving Institutions reported here differs slightly from the current eligibility list, as the 2022 PPD uses designations from 2021. The number of HBCUs and TCUs is the same in both sources, however.

Table 4.14—Distribution of Institutions by Share of Enrollment That Fails GE Accountability, by Special Mission Type

Total Share of institutional enrollment in failing GE programs
0% 0–5% 5–10% 10–20% 20–40% 40–99%
N of Institutions
HBCU 100 96 3 1 0 0 0
TCU 35 35 0 0 0 0 0
HSI 446 425 17 1 0 2 1
All Other Non-FP MSI 158 144 3 3 4 4 0
Total 739 700 23 5 4 6 1

As noted above, these estimates cannot assess the impact of the GE provisions on total enrollment at these institutions. Especially at institutions with diverse program offerings, many students in failing programs can be expected to transfer to other non-failing programs within the institution (as opposed to exiting the institution). Moreover, many institutions are likely to admit additional enrollment into their programs from failing programs at other (especially for-profit) institutions. We quantify the magnitude of this enrollment shift and revisit the implications for overall institution-level enrollment effects in a later section.

Regulation Targets Low-Performing GE Programs

The Department conducted an analysis on which specific GE programs fail the metrics. The analysis concludes that the metrics target programs where students earn little, borrow more, and default at higher rates on their student loans than similar programs providing the same credential.

Table 4.15 reports the average program-level cohort default rate for GE programs, separately by result, control, and credential level. Programs are weighted by their average title IV, HEA enrollment in AY 2016 and 2017 to better characterize the outcomes experienced by students. The overall 3-year program default rate is 12.9 percent but is higher for certificate programs and for programs offered by proprietary schools. The average default rate is higher for programs that fail the EP threshold than for programs that fail the D/E metric, despite debt being lower for the former. This is because even low levels of debt are difficult to repay when earnings are very low. Programs that pass the metrics, either with data or without, have lower default rates than those that fail.

Table 4.15—Average Program Cohort Default Rate by Result, Overall and by Control, and Credential Level

[Enrollment-weighted]

No data Pass Fail D/E only Fail both D/E and EP Fail EP only Total
Public:
UG Certificates 16.6 17.5 11.1 20.4 19.9 16.9
Post-BA Certs 2.3 2.4 2.3
Grad Certs 2.6 2.2 0.0 2.5
Total 15.8 16.5 6.2 20.4 19.9 16.1
Private, Nonprofit:
UG Certificates 10.0 9.9 15.9 14.5 12.0
Post-BA Certs 2.9 1.2 2.8
Grad Certs 2.6 1.9 0.4 2.4
Total 6.2 6.9 0.4 15.9 14.5 8.7
Proprietary:
UG Certificates 14.0 14.4 16.9 14.9 13.9 14.2
Associate 15.0 12.8 17.9 19.6 17.6 15.3
Bachelor's 13.7 11.5 14.4 14.8 11.9 12.4
Post-BA Certs 26.4 13.2 16.9
Master's 4.9 3.8 5.1 4.5 4.1
Doctoral 3.8 4.6 5.4 4.4
Professional 1.0 0.0 0.7 0.7
Grad Certs 1.4 4.2 5.5 . 3.9
Total 12.0 10.6 13.3 16.7 14.1 12.0
Foreign Private:
UG Certificates 0.0 0.0
Post-BA Certs 12.5 12.5
Grad Certs 5.2 0.0 0.2
Total 3.6 0.0 0.2
Foreign For-Profit:
Master's 0.0 0.0
Doctoral 0.5 5.3 1.4
Professional 1.3 1.3 1.3
Total 1.1 5.3 1.3 1.3
Total:
UG Certificates 16.1 15.4 16.1 15.3 14.6 15.5
Associate 15.0 12.8 17.9 19.6 17.6 15.3
Bachelor's 13.7 11.5 14.4 14.8 11.9 12.4
Post-BA Certs 2.9 5.4 3.2
Master's 4.8 3.8 5.1 4.5 4.1
Doctoral 3.5 4.6 5.4 4.3
Professional 1.2 0.0 0.8 1.0
Grad Certs 2.5 2.4 4.4 0.0 . 2.6
Total 13.9 11.3 13.1 16.6 14.7 12.9

To better understand the specific types of programs that underpin the aggregate patterns described above, Table 4.16 lists the 20 most common types of programs (the combination of field and credential level) by enrollment count in the 2022 PPD. The programs with the highest enrollments are undergraduate certificate programs in cosmetology, allied health, liberal arts, and practical nursing, along with bachelor's programs in business and nursing. These 20 most common types of programs represent more than half of all enrollments in GE programs. Table 4.17 provides the average program annual loan payment (weighted by the number of students completing a program), the average program earnings (weighted by the number of students completing a program), the average annual D/E rate, and the average cohort default rate (weighted by the number of students completing a program). This shows quite a bit of variability in debt, loan service, earnings, and default across different types of programs.

4.16—GE Programs With the Most Students, by CIP and Credential Level

Number of programs Percent of all programs Number of students Percent of students at all programs
Field of Study (Ordered by All-Sector Enrollment):
1204—Cosmetology & Personal Grooming—UG Certificates 1,267 4.0 191,600 6.5
5202—Business Administration—Bachelor's 72 0.2 149,000 5.1
5108—Allied Health (Medical Assisting)—UG Certificates 895 2.9 147,100 5.0
2401—Liberal Arts—UG Certificates 345 1.1 140,900 4.8
5139—Practical Nursing—UG Certificates 1,032 3.3 130,900 4.5
5107—Health & Medical Administrative Services—UG Certificates 910 2.9 83,500 2.8
5138—Registered Nursing, Nursing Administration, Nursing Research & Clinical Nursing—Bachelor's 56 0.2 75,600 2.6
4706—Vehicle Maintenance & Repair—UG Certificates 722 2.3 75,100 2.6
4301—Criminal Justice & Corrections—Bachelor's 47 0.2 55,500 1.9
5202—Business Administration—Master's 46 0.1 55,400 1.9
4805—Precision Metal Working—UG Certificates 761 2.4 49,000 1.7
5109—Allied Health (Diagnostic & Treatment)—UG Certificates 725 2.3 47,000 1.6
5108—Allied Health (Medical Assisting)—Associate 142 0.5 43,800 1.5
5107—Health & Medical Administrative Services—Bachelor's 46 0.1 42,100 1.4
5202—Business Administration—Associate 89 0.3 39,600 1.4
5107—Health & Medical Administrative Services—Associate 128 0.4 38,700 1.3
5138—Registered Nursing, Nursing Administration, Nursing Research & Clinical Nursing—Master's 20 0.1 37,800 1.3
5138—Registered Nursing, Nursing Administration, Nursing Research & Clinical Nursing—Associate 92 0.3 36,300 1.2
5202—Business Administration—UG Certificates 573 1.8 34,300 1.2
5106—Dental Support—UG Certificates 432 1.4 33,100 1.1
All Other Programs 22,920 73.2 1,424,900 48.6
Note: the number of students has been rounded to the nearest 100.

4.17—Annual Loan Payment, Earnings, D/E Rate, Cohort Default Rate by Program Type

[Enrollment-weighted]

Annual loan payment Median 2018–19 earnings (in 2019 $) of 3yrs after graduation Average annual DTE rate Cohort default rate
Field of Study (Ordered by All-Sector Enrollment):
1204—Cosmetology & Personal Grooming—UG Certificates 1,004 17,104 6.51 13.68
5202—Business Administration—Bachelor's 2,711 48,059 5.78 14.07
5108—Allied Health (Medical Assisting)—UG Certificates 947 24,137 4.28 16.58
2401—Liberal Arts—UG Certificates 99 29,893 0.26 16.38
5139—Practical Nursing—UG Certificates 1,075 39,763 3.07 10.23
5107—Health & Medical Administrative Services—UG Certificates 1,107 23,556 5.34 14.96
5138—Registered Nursing, Nursing Administration, Nursing Research & Clinical Nursing—Bachelor's 1,948 76,718 2.68 3.81
4706—Vehicle Maintenance & Repair—UG Certificates 1,410 37,746 4.03 19.48
4301—Criminal Justice & Corrections—Bachelor's 2,720 38,155 7.69 17.06
5202—Business Administration—Master's 3,725 58,366 6.60 4.09
4805—Precision Metal Working—UG Certificates 642 34,659 2.11 26.57
5109—Allied Health (Diagnostic & Treatment)—UG Certificates 564 42,953 2.15 11.7
5108—Allied Health (Medical Assisting)—Associate 2,275 31,598 7.98 12.16
5107—Health & Medical Administrative Services—Bachelor's 3,292 37,044 9.22 10.89
5202—Business Administration—Associate 2,532 32,427 8.30 21.66
5107—Health & Medical Administrative Services—Associate 2,721 26,779 10.51 14.02
5138—Registered Nursing, Nursing Administration, Nursing Research & Clinical Nursing—Master's 3,852 96,946 4.02 2.59
5138—Registered Nursing, Nursing Administration, Nursing Research & Clinical Nursing—Associate 2,535 61,494 4.69 6.93
5202—Business Administration—UG Certificates 705 35,816 1.60 20.07
5106—Dental Support—UG Certificates 1,024 24,557 4.42 14.00
All Other Programs 3,105 42,530 7.98 12.07

Table 4.18 lists the most frequent types of failing GE programs (by enrollment in failing programs). Failing programs are disproportionately in a small number of types of programs. About 22 percent of enrollment in failing programs is in UG Certificate Cosmetology programs alone, reflecting both high enrollment and high failure rates. Another 20 percent are in UG Certificate programs in Health/Medical administration and assisting, dental support, and massage, reflecting large enrollment and moderate failure rates. These 20 categories account for about 72 percent of all enrollments in programs that fail at least one GE metric. Table 4.19 provides the average program annual loan payment, the average program earnings, and the average default rate (all weighted by title IV, HEA enrollment) for the most frequent types (by field and credential) of GE programs that fail at least one GE metric (by enrollment count), separately for failing and passing programs. Within each type of program, failing programs have much higher loan payments, lower earnings, and higher default rates than programs that pass the GE metrics. This demonstrates that higher-performing GE programs exist even within the same field and credential level as programs that fail GE.

4.18—Failing GE Programs With the Most Students, by GE Result, CIP, and Credential Level

Number of failing programs Percent of failing programs Number of students Percent of students at failing programs
1204—Cosmetology & Personal Grooming—UG Certificates 638 35.9 153,700 21.5
5108—Allied Health (Medical Assisting)—UG Certificates 159 9.0 79,100 11.1
5107—Health & Medical Administrative Services—UG Certificates 106 6.0 37,600 5.3
5107—Health & Medical Administrative Services—Associate 37 2.1 28,800 4.0
5107—Health & Medical Administrative Services—Bachelor's 5 0.3 26,400 3.7
3017—Behavioral Sciences—Bachelor's 2 0.1 20,100 2.8
5202—Business Administration—Associate 23 1.3 19,000 2.7
5108—Allied Health (Medical Assisting)—Associate 38 2.1 17,600 2.5
1312—Teacher Education & Professional Development, Specific Levels & Methods—Bachelor's 2 0.1 17,500 2.4
5115—Mental & Social Health Services & Allied Professions—Master's 5 0.3 15,400 2.2
5106—Dental Support—UG Certificates 63 3.5 14,300 2.0
5135—Somatic Bodywork—UG Certificates 95 5.3 13,400 1.9
4301—Criminal Justice & Corrections—Bachelor's 7 0.4 13,100 1.8
4400—Human Services, General—Bachelor's 2 0.1 12,100 1.7
4301—Criminal Justice & Corrections—Associate 16 0.9 11,700 1.6
4201—Psychology—Bachelor's 4 0.2 10,200 1.4
1205—Culinary Arts—UG Certificates 21 1.2 5,800 0.8
2301—English Language & Literature, General—UG Certificates 8 0.5 5,600 0.8
5139—Practical Nursing—UG Certificates 27 1.5 5,500 0.8
5204—Business Operations—UG Certificates 33 1.9 5,400 0.8
All Other Programs 485 27.3 201,200 28.2
Total 1,776 100.0 713,200 100.0
Note: Student counts rounded to the nearest 100.

4.19—Annual Loan Payment, Earnings, Default Rate Among Top Types of Failing GE Programs

Annual loan payment indicator for failing GE metric in 2019 for any reason Earnings indicator for failing GE metric in 2019 for any reason Default rate (ever) indicator for failing GE metric in 2019 for any reason
Passing Failing Passing Failing Passing Failing
Field of Study & Level (Ordered by Failing Program Enrollment):
1204—Cosmetology & Personal Grooming—UG Certificates 566.7 1,063.9 27,199.4 16,913.1 17.2 13.0
5108—Allied Health (Medical Assisting)—UG Certificates 813.1 1,034.3 27,612.1 22,527.1 16.5 16.6
5107—Health & Medical Administrative Services—UG Certificates 860.2 1,279.7 28,803.9 21,243.7 14.6 15.4
5107—Health & Medical Administrative Services—Associate 2,250.0 2,857.4 32,807.9 25,598.2 9.5 15.5
5107—Health & Medical Administrative Services—Bachelor's 2,960.3 3,482.3 43,590.7 34,118.7 10.4 11.2
3017—Behavioral Sciences—Bachelor's 3,499.3 29,512.7 0.0 16.5
5202—Business Administration—Associate 2,304.5 2,762.1 37,887.8 27,280.5 19.6 23.9
5108—Allied Health (Medical Assisting)—Associate 3,458.0 3,121.2 36,729.0 31,081.2 9.2 11.0
1312—Teacher Education & Professional Development, Specific Levels & Methods—Bachelor's 2,027.4 2,707.3 35,298.8 26,152.5 10.1 16.0
5115—Mental & Social Health Services & Allied Professions—Master's 5,305.3 7,096.9 49,712.0 42,604.7 4.5 6.1
5106—Dental Support—UG Certificates 986.9 1,055.5 27,084.4 23,011.8 13.1 15.1
5135—Somatic Bodywork—UG Certificates 672.6 948.6 27,373.5 19,258.2 13.6 13.3
4301—Criminal Justice & Corrections—Bachelor's 2,465.7 3,527.6 40,112.4 32,371.9 15.4 22.3
4400—Human Services, General—Bachelor's 2,493.8 3,903.3 33,323.4 32,788.8 14.3 14.9
4301—Criminal Justice & Corrections—Associate 1,517.7 2,625.0 35,501.2 28,408.3 18.8 22.1
4201—Psychology—Bachelor's 2,068.4 3,333.3 36,641.7 28,865.8 11.1 17.4
1205—Culinary Arts—UG Certificates 2,399.3 0.0 19,361.7 35.0 6.0
2301—English Language & Literature, General—UG Certificates 3,661.0 36,873.0 25.0 9.9
5139—Practical Nursing—UG Certificates 104.7 0.0 30,557.3 26,423.7 16.6 11.9
5204—Business Operations—UG Certificates 494.1 635.9 28,985.0 18,202.5 13.5 16.0
All Other Programs 2,462.3 4,062.4 52,687.3 29,767.5 11.6 13.3

Student Demographic Analysis

Methodology for Student Demographic Analysis

The Department conducted analyses of the 2022 PPD to assess the role of student demographics as a factor in program performance. Our analysis demonstrates that GE programs that fail the metrics have particularly bad outcomes that are not explained by student demographics alone. We examined the demographic composition of program enrollment, comparing the composition of programs that pass, fail, or did not have data. We also conducted regression analysis, which permits us to hold constant several factors at once. This analysis focuses on GE programs since non-GE programs are not at risk of becoming ineligible for title IV, HEA aid.

We conducted the regression analysis discussed below for non-GE programs as well. Our conclusions about the relative contribution of demographic factors in explaining program performance on the D/E and EP metrics is similar for non-GE programs as for GE programs.

For the race and ethnicity variables, we used the proportion of individuals in each race and ethnicity category among all completers of each certificate or degree reported in the IPEDS 2016 and 2017 Completions Surveys. Race and ethnicity is not available for only title IV, HEA recipients, so we rely on information for all (including non-title IV, HEA student) completers instead from IPEDS. We construct four race/ethnicity variables:

Specifically, the C2016A and C2017A datasets available from the IPEDS data center. These cover the 2015–16 and 2016–17 academic years (July 1 to June 30).

  • Percent Black
  • Percent Hispanic
  • Percent Asian
  • Percent non-White.

We aggregated the number of completions in each race/ethnicity category reported for each program in IPEDS to the corresponding GE program definition of six-digit OPEID, CIP code, and credential level. While D/E and EP rates measure only the outcomes of students who completed a program and received title IV, HEA program funds, IPEDS completions data include both title IV, HEA graduates and non-title IV, HEA graduates. Race and ethnicity data is not available separately for title IV, HEA completers. We believe the IPEDS data provides a reasonable approximation of the proportion, by race and ethnicity, of title IV, HEA graduates completing GE programs. We determined percent of each race and ethnicity category for 25,278 of the 32,058 programs. Many smaller programs could not be matched primarily because, as stated above, IPEDS and NSLDS use different program categorization systems, and the two sources at times are not sufficiently consistent to match data at the GE program-level. Nonetheless, we do not believe this will substantially affect our results since programs that do not match are less likely to meet the n-size criteria and would be likely excluded from our analysis of program performance.

Percent Pell for this analysis is the percentage of title IV, HEA completers during award years 2015, 2016, and 2017 who received a Pell grant at any time in their academic career. Because Pell status is being used as a proxy for socioeconomic background, we counted students if they had received a Pell grant at any time in their academic career, even if they did not receive it for enrollment in the program. For instance, students that received Pell at their initial undergraduate institution but not at another institution they attended later would be considered a Pell grant recipient at both institutions.

Several other background variables were collected from students' Free Application for Federal Student Aid (FAFSA) form. For all students receiving title IV, HEA aid in award years 2015, 2016, and 2017, the Department matched their enrollment records to their latest FAFSA filed associated with their first award year in the program in which they were enrolled. First-generation status, described below, is taken from students earliest received FAFSA. From these, the Department constructed the following:

  • Percent of students that are male.
  • Percent of students that are first-generation, defined as those who indicated on the FAFSA not having a parent that had attended college. Children whose parents completed college are more likely to attend and complete college.
  • Average family income in 2019 dollars. For dependent students, this includes parental income and the students' own income. For independent students, it includes the student's own income and spousal income.
  • Average expected family contribution. We consider EFC as an indicator of socioeconomic status because EFC is calculated based on household income, other resources, and family size.
  • Average age at time of FAFSA filing.
  • Percent of students aged 24 or older at time of FAFSA filing.
  • Share of students that are independent. Independent status is determined by a number of factors, including age, marital status, having dependents, and veteran status.
  • Median student income prior to program enrollment among students whose income is greater than or equal to three-quarters of a year of earnings at Federal minimum wage. We only compute this variable for programs where at least 30 students meet this requirement, this variable should be viewed as a rough indicator of students' financial position prior to program entry. The average percentage of enrollees covered by this variable is 57.6 across all programs.

Based on these variables, we determined the composition of over 23,907 of the 32,058 programs in our data, though some demographic variables have more non-missing observations. Unless otherwise stated, our demographic analysis treats programs (rather than students) as the unit of analysis. The analysis, therefore, does not weight programs (and their student characteristics) by enrollment.

Table 4.20 provides program-level descriptive statistics for these demographic variables in the GE program dataset. The typical (median) program has 6 percent completers that are Black, 6 percent Hispanic, 0 percent Asian (program mean is 3 percent), and 38 percent non-White. At the median program, sixty-one percent are independent, half are over the age 24, and 31 percent are male. Half are first-generation college students and 77 percent have ever received a Pell Grant. Average family income at time of first FAFSA filing is $38,000 and the typical student who is attached to the labor force earns $29,900 before enrolling in the program.

4.20—Descriptive Statistics of the Demographic Variables

Programs Median Average Std. deviation
Share T4 Completers First Gen 24,199 50 49 34
Share T4 Completers Ever Pell 24,199 77 67 36
Share T4 Completers Out-of-State 24,199 0 16 30
Share of T4 Completers Male 24,199 31 42 41
Share of T4 Completers Age 24+ 24,199 50 51 37
Share T4 Completers Independent 24,199 61 58 36
Share All Completions Non-White 25,278 38 43 30
Share All Completions Black 25,278 6 14 20
Share All Completions Hispanic 25,278 6 15 23
Share All Completions Asian 25,278 0 3 9
Age at Time of FAFSA 23,907 26 28 8
FAFSA Family Income 23,907 38,137 47,726 45,433
Median Student Pre-Inc 17,599 29,908 38,585 32,806

Student Demographics Descriptive Analysis

Table 4.21 reports average demographic characteristics of GE programs separately by GE result. Programs that fail at least one GE metric have a higher share of students that are female, higher share of students that are Black or Hispanic, lower student and family income, and higher share of students that have ever received the Pell grant. Average student age and dependency status is similar for passing and failing programs.

4.21—Demographic Shares by Result

All Passing Fail (any) Fails D/E Fails EP
Share TIV Completers First Gen 49 48 61 55 62
Share TIV Completers Ever Pell 67 66 80 74 82
Share TIV Completers Out-of-State 16 15 21 40 16
Share of TIV Completers Male 42 44 21 28 19
Share of TIV Completers Age 24+ 51 51 49 57 46
Share TIV Completers Independent 58 58 59 66 57
Share All Completions Non-White 43 42 56 58 56
Share All Completions Black 14 13 22 26 21
Share All Completions Hispanic 15 15 22 18 23
Share All Completions Asian 3 3 4 2 4
Age at Time of FAFSA 28 28 27 29 27
FAFSA Family Income 47,700 48,600 35,900 41,100 34,200
Median Student Pre-Inc 38,600 39,600 29,200 34,200 27,400
Note: Income values rounded to the nearest 100.

Student Demographics Regression Analysis

One limitation of the descriptive tabulations presented above is that it is difficult to determine which factors, whether they be demographics or program characteristics, explain the higher failure rate of programs serving certain groups of students. To further examine the relationship between student demographics and program results under the regulations, we analyzed the degree to which specific demographic characteristics might be associated with a program's annual D/E rate and EP, while holding other characteristics constant.

For this analysis, the Department estimated the parameters of ordinary least squares (OLS) linear regression models with annual debt-to-earnings or the earnings premium as the dependent (outcome) variables and indicators of student, program, and institutional characteristics as independent variables. The independent demographic variables included in the regression analysis are: share of students in different race and ethnicity categories; share of students ever receiving Pell Grants; share of students that are male; share of students that are first-generation college students; share of students that are independent; and average family income from student's FAFSA. Program and institutional characteristics include credential level and control (public, private nonprofit, and proprietary). In some specifications we include institution fixed effects and omit control. When used with program-level data, institutional fixed effects control for any factors that differ between institutions but are common among programs in the same institution, such as institutional leadership, pricing strategy, and State or local factors.

Though not shown below, we have conducted parallel regression analysis with binary indicators for whether the program fails the D/E metric and whether it fails the EP metric as the outcomes. Results are qualitatively similar to those reported here using continuous outcomes, though the amount of variation in these binary outcomes that demographics explain is even more muted than that reported here.

Table 4.22 reports estimates from the D/E rate regressions described above, with each column representing a different regression model that includes different sets of independent variables. Comparing the R-squared across different columns demonstrates the degree to which different factors explain variation in the outcome. The first three columns quantify the extent to which variation in D/E rates are accounted for by program and institutional characteristics. The institutional control alone (column 1) explains 22 percent of the variation in D/E and adding credential level increases the R-squared to 33 percent (column 2). D/E rates are 2.5 to 3.9 percentage points higher for private nonprofit and for-profit institutions than public institutions (the omitted baseline category) after controlling for credential level. This may reflect the much higher tuition prices charged by private institutions, which can result in higher debt service. Graduate credential levels also have much higher debt-to-earnings ratios than undergraduate credentials, reflecting the typically higher tuition costs associated with graduate programs.

Almost all programs are in institutions with multiple GE programs, so column 3 includes institution fixed effects in place of indicators for control. Credential level and institution together account for 77 percent of the variation in D/E rates across programs. To illustrate how much more of the variation in outcomes is accounted for by student characteristics, column 4 adds the demographic characteristics on top of the model with credential level and institution effects. Doing so only slightly increases the model's ability to account for variation in D/E, lifting the R- squared to 79 percent. For example, this specification effectively compares programs with more Pell students to those with fewer Pell students within the same institution and same credential level, while also controlling for the other independent variables listed. Demographic characteristics, therefore, appear to explain little of the variation in D/E rates across programs beyond what can be predicted by institutional characteristics and program credential level. Evidently, institution- and program-level factors, which could include such things as institutional performance and decisions about institutional pricing along with other factors, are much more important. The final two columns report similar models, but weighting by average title IV, HEA enrollment, and the results are qualitatively similar.

Only 4 percent of GE programs are the only GE program within the institution. The median number of programs within an institution is 18.

The patterns by race are broadly similar to what was found in analysis of the 2014 final rule. The coefficient on % Black in the final column suggests that a 10-percentage point increase in the percent of students that are black is associated with a 0.15 higher debt-to-earnings ratio, holding institution, credential level, and the other demographic factors listed constant. Analysis of the prior rule found an increase of 0.19, though the set of controls is not the same.

4.22—Regression Analysis of the Demographic Variables, GE Programs, Outcome: D/E

1 2 3 4 5 6
Private, Nonprofit 3.062 (0.305) 2.512 (0.263)
Proprietary 4.928 (0.110) 3.868 (0.101)
Credential Level:
UG Certificates −2.118 (0.207) −2.495 (0.603) −4.083 (0.618) −1.079 (0.654) −5.037 (0.594)
Associate 0.084 (0.251) 0.295 (0.449) −0.651 (0.426) 1.401 (0.651) −0.927 (0.427)
Master's 2.780 (0.769) 1.552 (0.591) 1.303 (0.479) 0.983 (0.719) 1.683 (0.563)
Doctoral 4.451 (0.809) 3.758 (1.096) 5.701 (1.051) 3.824 (1.469) 7.892 (1.235)
Professional 12.480 (3.696) 5.841 (1.002) 5.672 (1.387) 6.753 (0.850) 8.839 (1.547)
Grad Certs 1.200 (0.596) 1.431 (1.748) 0.928 (1.679) 4.650 (2.577) 4.738 (2.415)
% Black 0.016 (0.009) 0.032 (0.016)
% Hispanic −0.015 (0.011) −0.035 (0.017)
% Asian −0.054 (0.028) −0.154 (0.043)
% Male −0.014 (0.002) −0.028 (0.004)
% Ever Pell 0.003 (0.012) 0.050 (0.017)
% First Generation 0.001 (0.008) −0.021 (0.015)
% Independent −0.008 (0.005) −0.008 (0.008)
FAFSA Family Income ($1,000) −0.056 (0.013) −0.087 (0.014)
Intercept 1.265 (0.064) 3.221 (0.217) 6.371 (0.468) 10.974 (1.618) 6.220 (0.423) 12.057 (2.079)
R-squared 0.22 0.33 0.77 0.79 0.64 0.78
Notes: Specifications 3 to 6 include fixed effects for each six-digit OPEID number. Bachelor's degree and public are the omitted categories for credential type and control, respectively. Columns 5 and 6 weight programs by average title IV, HEA enrollment in AY16 and AY17.

Table 4.23 reports estimates from identical regression models, but instead using EP as the outcome. Again, each column represents a different regression model that includes different sets of independent variables. Program and institutional characteristics still matter greatly to earnings outcomes. Institutional effects and credential level together explain 77 percent of the variation in program-level earnings outcomes (column 3). Adding demographic variables explains an additional 7 percentage points of the variation in program-level earnings (column 4). Note that the estimated regression coefficients will likely overstate the effect of the baseline characteristics on outcomes if these characteristics are correlated with differences in program quality not captured by the crude institution and program characteristics included in the regression.

4.23—Regression Analysis of the Demographic Variables, GE Programs, Outcome: EP

[$1,000s]

1 2 3 4 5 6
Private, Nonprofit 8.923 (2.420) 1.461 (1.711)
Proprietary −4.475 (0.611) −10.632 (0.489)
Credential Level:
UG Certificates −18.507 (0.835) −17.315 (1.658) −7.634 (1.415) −20.963 (2.350) −0.592 (1.922)
Associate −6.708 (1.000) −8.647 (1.333) −3.698 (1.128) −11.169 (2.014) −0.219 (1.271)
Master's 11.357 (1.661) 11.083 (2.072) 7.159 (1.778) 11.594 (3.496) 8.787 (2.811)
Doctoral 32.585 (3.078) 33.356 (4.576) 20.948 (4.079) 27.749 (6.390) 9.854 (4.553)
Professional 41.422 (12.277) 58.755 (13.661) 44.702 (11.280) 66.316 (9.890) 43.113 (11.599)
Grad Certs 23.756 (3.225) 13.475 (4.224) 11.475 (3.614) 7.105 (6.533) 7.995 (6.577)
% Black −0.116 (0.047) −0.201 (0.058)
% Hispanic −0.081 (0.038) 0.015 (0.061)
% Asian 0.487 (0.110) 1.376 (0.267)
% Male 0.099 (0.007) 0.096 (0.016)
% Ever Pell −0.158 (0.046) −0.094 (0.064)
% First Generation −0.052 (0.029) −0.006 (0.049)
% Independent 0.146 (0.018) 0.200 (0.032)
FAFSA Family Income ($1,000) 0.168 (0.056) 0.439 (0.071)
Intercept 11.267 (0.514) 27.745 (0.931) 20.126 (1.349) 9.874 (7.507) 22.128 (1.676) −20.312 (9.392)
R-squared 0.03 0.42 0.77 0.84 0.71 0.87
Notes: Specifications 3 to 6 include fixed effects for each six-digit OPEID number. Bachelor's degree and public are the omitted categories for credential type and control, respectively. Columns 5 and 6 weight programs by average title IV, HEA enrollment in AY16 and AY17.

Conclusions about the extent to which different factors explain variation in program outcomes can be sensitive to the order in which factors are entered into regressions. However, a variance decomposition analysis (that is insensitive to ordering) demonstrates that program and institutional factors explain the majority of the variance in both the D/E and EP metrics across programs when student characteristics are also included.

Figure 4.3 provides another view, demonstrating that many successful programs exist and enroll similar shares of low-income students. It shows the distribution of raw Eps for undergraduate certificate programs (the y-axis is in $1,000s) grouped by the average FAFSA family income of the program. Programs are placed in 20 equally sized groups from lowest to highest FAFSA family income. Each dot represents an individual program. The EP of the median program in each income group, indicated by the large black square, is clearly increasing, reflecting the greater earnings opportunities for students that come from higher income families. However, there is tremendous variation around this median. Even among programs with students that come from the lowest income families, there are clearly programs whose students go on to have earnings success after program completion. This graph demonstrates that demographics are not destiny when it comes to program performance.

Since each of the 20 groups includes the same number of programs, the income range varies across groups.

Gender Differences

The analysis above showed that programs failing the EP threshold have a higher share of female students. In Table 4.24, we show descriptively that there are many programs that have similar gender composition but have much higher rates of passage than programs in cosmetology and massage, where failure rates are comparatively higher. Other programs, such as practical nursing and dental support, are similar in terms of their gender and racial balance but have much higher passage rates.

Table 4.24—Gender and Racial Composition of Undergraduate Certificate Programs

Criminal Justice
Share of programs failing Share of all completers who are . . .
Black women Hispanic women Asian women Other women White women Women (any race)
Teacher Education 0.066 0.226 0.165 0.025 0.094 0.439 0.950
Human Development 0.019 0.216 0.284 0.039 0.063 0.366 0.968
Health & Medical Admin 0.441 0.209 0.171 0.029 0.086 0.442 0.938
Medical Assisting 0.535 0.171 0.292 0.030 0.067 0.317 0.876
Laboratory Science 0.211 0.163 0.138 0.030 0.079 0.434 0.843
Practical Nursing 0.034 0.154 0.134 0.033 0.067 0.498 0.886
Cosmetology 0.789 0.150 0.191 0.051 0.059 0.451 0.902
Dental Support 0.428 0.146 0.300 0.025 0.064 0.384 0.920
Business Operations 0.257 0.142 0.166 0.020 0.057 0.395 0.781
Business Administration 0.001 0.128 0.090 0.018 0.058 0.308 0.601
Culinary Arts 0.148 0.123 0.148 0.019 0.060 0.249 0.598
Somatic Bodywork 0.619 0.102 0.127 0.029 0.079 0.418 0.754
Accounting 0.071 0.096 0.141 0.060 0.067 0.361 0.725
0.039 0.072 0.079 0.004 0.027 0.151 0.333
Liberal Arts 0.038 0.049 0.205 0.043 0.055 0.262 0.613
Allied Health, Diagnostic 0.015 0.046 0.089 0.016 0.034 0.309 0.494
Information Technology (IT) Admin & Mgmt. 0.046 0.044 0.021 0.009 0.029 0.081 0.183
Ground Transportation 0.005 0.041 0.007 0.003 0.007 0.034 0.092
Computer & Info Svcs 0.074 0.030 0.078 0.012 0.017 0.113 0.250
Precision Metal Working 0.041 0.009 0.007 0.001 0.005 0.036 0.058
Heating, Ventilation, and Air Conditioning (HVAC) 0.025 0.008 0.003 0.000 0.001 0.012 0.025
Fire Protection 0.000 0.007 0.019 0.001 0.005 0.058 0.091
Power Transmission 0.021 0.007 0.006 0.000 0.003 0.019 0.035
Vehicle Maintenance 0.018 0.006 0.011 0.001 0.006 0.027 0.052
Environment Ctrl Tech 0.007 0.006 0.007 0.001 0.005 0.018 0.036

Conclusions of Student Demographic Analysis

On several dimensions, programs that have higher enrollment of underserved students have worse outcomes—lower completion, higher default, and lower post-college earnings levels—due to a myriad of challenges these students face, including fewer financial resources and structural discrimination in the labor market. And yet, there is evidence that some institutions aggressively recruited vulnerable students—at times with deceptive marketing and fraudulent data—into programs without sufficient institutional support and instructional investment, placing students at risk for having high debt burdens and low earnings. Nonetheless, our analysis demonstrates that GE programs that fail the metrics have particularly bad outcomes that are not explained by student demographics alone. Furthermore, alternative programs with similar student characteristics but where students have better outcomes exist and serve as good options for students that would otherwise attend low-performing programs. We quantify the extent of these alternative options more directly in the next section. The GE rule aims to protect students from low-value programs and steer them to programs that would be greater engines of upward economic mobility.

Blau, Francine D. & Kahn, Lawrence M. (2017). The Gender Wage Gap: Extent, Trends, and Explanations. Journal of Economic Literature, 55 (3): 789–865. Hillman, N.W. (2014). College on Credit: A Multilevel Analysis of Student Loan Default. Review of Higher Education, 37(2), 169–195. Pager, D., Western, B. & Bonikowski, B. (2009). Discrimination in a Low-Wage Labor Market: A Field Experiment. American Sociological Review, 74, 777–799.

Cottom, T.M. (2017). Lower Ed: The Troubling Rise of For-Profit Colleges in the New Economy. Government Accountability Office (2010). For-Profit Colleges: Undercover Testing Finds Colleges Encouraged Fraud and Engaged in Deceptive and Questionable Marketing Practices. U.S. Senate Committee on Health, Education, Labor, and Pensions (2012). For Profit Higher Education: The Failure to Safeguard the Federal Investment and Ensure Student Success.

Alternative Options Exist for Students To Enroll in High-Value Programs

Measuring Students' Alternative Options

One concern with limiting title IV, HEA eligibility for low-performing GE programs is that such measures could reduce postsecondary opportunities for some students. The Department conducted an analysis to estimate the short-term alternative options that are available to students that might, in the absence of these regulations, enroll in failing programs. The scope of alternative options in the longer term is likely to be broader than the results of this analysis, as other institutions can expand their program offerings and failing programs can improve their performance.

Students deterred from attending a specific program because of a loss of title IV, HEA aid eligibility at that program have several potential alternatives. For programs that are part of a multi-program institution, many may choose to remain at the same institution, but attend a different program in a related subject that did not lose access to title IV, HEA aid and, therefore, likely offers better outcomes for students in terms of student debt, earnings, or both. Some would stay in their local area and attend a nearby institution that offers a program in the same or related subject. Still others would attend an institution further away, but perhaps in the same State or online. In order to identify geographical regions where the easiest potential transfer options exist, we used the 3-digit ZIP code (ZIP3) in which each institution is located. Three-digit zip codes designate the processing and distribution center of the United States Postal Service that serves a given geographic area. For each combination of ZIP3, CIP code, and credential level, we determined the number of programs available and the number of programs that would pass both the D/E and EP rates measures. Since programs that do not fail due to insufficient n-size to compute D/E and EP rates represent real options for students at failing programs, we include these programs in our calculations. Importantly, we also include all non-GE programs at public and private nonprofit institutions. 302 Our characterization of programs by the number of alternative options available is also used in the simulations of enrollment shifts that underlie the budget impact and cost, benefit, and transfer estimates, which we describe later.

Two other possibilities, which we include in our simulation of budget impacts, is that students continue to enroll in programs without receiving title IV, HEA aid or decline to enroll altogether.

Table 4.25 reports the distribution of the number of transfer options available to the students who would otherwise attend GE programs that fail at least one of the two metrics. We present estimates for four different ways of conceptualizing and measuring these transfer options. We assume students have more flexibility over the specific field and institution attended than credential level, so all four measures assume students remain in the same credential level. While not captured in this analysis, it is possible that some students would pursue a credential at a higher level in the same field, thereby further increasing their available options. Half of students in failing GE programs (in 41 percent of failing programs) have at least one alternative non-failing program of the same credential level at the same institution, but in a related field (as indicated by being in the same 2-digit CIP code). More than a quarter have more than one additional option. Two-thirds of students (at 60 percent of the failing programs) have a transfer option passing the GE measures within the same geographic area (ZIP3), credential level, and narrow field (4-digit CIP code). More than 90 percent of students have at least one transfer option within the same geographic area and credential level when the field is broadened to include programs in the same 2-digit CIP code. Finally, all students have at least one transfer option in the same State, credential level, and 2-digit CIP code. While this last measure includes options that may not be viable for currently enrolled students—requiring moving across the State or attending virtually—it does suggest that at least some options are available for all students, both current and prospective, who would otherwise attend failing GE programs.

Table 4.25—Share of Programs and Enrollment in Failing GE Programs, by Number of Alternative Options

Same Zip3, cred level CIP4
Same institution, cred level, CIP2 Same Zip3, cred level, CIP2 Same state, cred level, CIP2
A. Programs Transfer options:
1 or more 0.41 0.60 0.88 1.00
5 or more 0.03 0.03 0.50 0.96
B. Enrollment Transfer options:
1 or more 0.50 0.65 0.91 1.00
5 or more 0.03 0.04 0.53 0.95

Table 4.26 repeats this analysis for non-GE programs with at least one failing GE metric. Students considering non-GE programs with D/E or EP metrics that do not meet Department standards may choose to enroll elsewhere. More than half of students at failing non-GE programs have a non-failing program in the same 4-digit CIP code, credential level, and geographic area that they could choose to enroll in. This share approaches three-quarters if the field is broadened to include programs in the same two-digit CIP code. Therefore, while the alternative options for non-GE programs are not as numerous as for GE programs, the number of alternatives is still quite high.

Table 4.26—Share of Programs and Enrollment in Failing Non-GE Programs, by Number of Transfer Options

Same Zip3, cred level, CIP4
Level Same institution, cred level, CIP2 Same Zip3, cred level, CIP2 Same state, cred level, CIP2
A. Programs Transfer options:
1 or more 0.54 0.47 0.80 0.99
5 or more 0.12 0.05 0.40 0.95
B. Enrollment Transfer options:
1 or more 0.37 0.49 0.71 0.99
5 or more 0.08 0.05 0.29 0.93

This analysis likely understates the transfer options available to students for three reasons. First, as stated above, it does not consider programs of a different credential level. For example, students who would have pursued a certificate program might opt for an associate degree program that shows higher earnings. Second, it does not consider the growth of online/distance education programs now available in most fields of study, from both traditional schools and primarily on-line institutions.

Third, we do not consider non-title IV, HEA institutions. Undergraduate certificate programs in cosmetology represent the largest group of programs without nearby passing options in the same four-digit CIP code, in large part because many of these programs do not pass the GE metrics. Nonetheless, recent data from California and Texas suggest that many students successfully pass licensure exams after completing non-title IV, HEA programs in cosmetology. Non-title IV, HEA cosmetology schools operate in almost all counties in Texas. In Florida, non-title IV, HEA cosmetology schools have similar licensure pass rates but much lower tuition.

In California, 55 percent of individuals passing either the practical or written components of the licensure test are from title IV, HEA schools according to Department analysis using licensing exam data retrieved from www.barbercosmo.ca.gov/schools/schls_rslts.shtml on December 7, 2022.

Cellini, S.R. & Onwukwe, B. (Aug. 2022). Cosmetology Schools Everywhere: Most Cosmetology Schools Exist Outside of the Federal Student Aid System. Postsecondary Equity & Economics Research Project working paper.

Cellini, S.R. & Goldin, C. (2014). Does Federal Student Aid Raise Tuition? New Evidence on For-Profit Colleges. American Economic Journal: Economic Policy, 6(4), 174–206.

Potential Alternative Programs Have Better Outcomes Than Failing Programs

A key motivation for more accountability via this rule is to steer students to higher value programs. As mentioned previously, research has shown that when an institution closed after failing accountability measures based on Cohort Default Rates, students were diverted to schools with better outcomes. The Department conducted an analysis of the possible earnings impact of students shifting from programs that fail one of the GE metrics to similar programs that do not fail. For each failing program, we computed the average program-level median earnings of non-failing programs included in the failing program's transfer options, which we refer to as “Alternative Program Earnings.” Earnings were weighted by average title IV, HEA enrollment in award years 2016 and 2017. Alternative options were determined in the same way as described above. In computing Alternative Program Earnings, priority was first given to passing programs in the same institution, credential level, and two-digit CIP code if such programs exist and have valid earnings. This assigned Alternative Program Earnings for 20 percent of failing programs. Next priority was given to programs in the same ZIP3, credential level, and four-digit CIP code, which assigned Alternative Program Earnings for 8 percent of programs. Next was programs in the same ZIP3, credential level, and two-digit CIP code, which assigned Alternative Program Earnings for 14 percent of programs. We did not use the earnings of programs outside the ZIP3 to assign Alternative Program Earnings given the wage differences across regions. It was not possible to compute the earnings of alternative options for the remaining 59 percent of programs primarily because the available options in those instances have insufficient number of completers to report median earnings (47 percent) or because they did not have alternative options in the same ZIP3 (12 percent). For these programs, we set the Alternative Program Earnings equal to the median earnings of high school graduates in the State (the same value used to determine the ET). The percent increase in earnings associated with moving from a failing program to a passing program was computed as the difference between a program's Alternative Program Earnings and its own median earnings, divided by its own median earnings. We set this earnings gain measure to 100 percent in the small number of cases where the median program earnings are zero or the ratio is greater than 100 percent.

Cellini, S.R., Darolia, R. & Turner, L.J. (2020). Where Do Students Go When For-Profit Colleges Lose Federal Aid? American Economic Journal: Economic Policy, 12(2): 46–83.

Table 4.27 reports the estimated percent difference in earnings between alternative program options and failing programs, separately by two-digit CIP and credential level. Across all subjects, the difference in earnings at passing undergraduate certificate programs and failing programs is about 50 percent. This is unsurprising, given that the EP metric explicitly identifies programs with low earnings, which in practice are primarily certificate programs. Encouragingly, many passing programs exist in the same subject, level, and market that result in much higher earnings than programs that fail. Failing associate degree programs also have similar non-failing programs with much higher earnings. Earnings differences are still sizable and positive, though not quite as large for higher credentials. Passing GE bachelor's degree programs have 31 percent higher earnings than bachelor's degree programs that fail the GE metrics.

Table 4.28 reports similar estimates for non-GE programs. The earnings difference between failing and passing non-GE programs is more modest than for GE programs, but still significant: 21 percent across all credential levels, ranging from close to zero for Doctoral programs to 30 percent for bachelor's degree programs.

We use a similar process to compute the percent change in average program-level median debt between failing GE or non-GE programs and alternative programs. Tables 4.29 and 4.30 report the percent change in debt between alternative program options and failing programs, separately by two-digit CIP and credential level. Across all subjects and credential levels, debt is 22 percent lower at alternative programs than at failing GE programs. Large differences in debt are seen at all degree levels (other than professional), with modest differences for undergraduate certificate programs. At non-GE programs, there is no aggregate debt difference between failing programs and their alternatives, though this masks heterogeneity across credential levels. For graduate degree programs, relative to failing programs, alternative programs have lower debt levels, with the differences (the percent difference in debt between alternative and failing programs) ranging from 24 percent (Professional programs) to 35 percent (Doctoral programs). Failing associate degree programs have debt that is 12 percent higher than in passing programs.

The only exception being that we use the debt for alternative programs in the same credential level, same two-digit CIP code, and State to impute alternative program debt if such a program is not available or calculable in students' ZIP3. This is because there is no other natural benchmark debt level analogous to the ET used to compute alternative program earnings.

While these differences do not necessarily provide a completely accurate estimate of the actual earnings gain or debt reduction that students would experience by shifting programs, they suggest alternative options exist that provide better financial outcomes than programs that fail the D/E and EP metrics.

Table 4.27—Percent Earnings Difference Between Transfer Options and Failing GE Programs, by CIP and Credential Level

cip2 Credential level Total
UG certificates Associate Bachelor's Master's Doctoral Professional Grad certs
1
3 −0.18 −0.18
9 0.12 0.24 0.24 0.17
10 0.42 0.19 −0.01 −0.38 0.07
11 0.48 0.26 0.79 −0.62 0.45
12 0.53 0.12 −0.18 1.00 0.52
13 0.38 0.34 0.13 0.46 0.18 −0.04 0.21
14 −0.01 −0.36 −0.19
15 0.14 −0.10 0.11
16 −0.03 −0.03
19 0.65 0.29 0.13 −0.28 −0.55 0.11
22 0.33 −0.03 −0.04 0.22 −0.60 0.00
23 0.57 −0.07 0.38 −0.09 0.44
24 0.06 0.06
25 −0.03 −0.03
26 −0.32 −0.32
30 0.15 −0.07 −0.34 −0.04
31 0.51 −0.00 0.09
32 0.32 0.32
39 0.40 −0.03 −0.20 0.04
42 0.06 0.25 −0.52 −0.34 −0.04
43 0.22 0.19 0.24 0.41 −0.56 0.21
44 0.04 0.43 0.62 0.46 −0.50 0.37
45 0.23 −0.24 0.06
46 0.40 0.40
47 0.39 0.14 0.33
48 0.25 0.25
49 0.77 0.77
50 0.38 0.22 0.27 0.46 0.29
51 0.51 0.83 0.75 0.87 −0.30 −0.06 0.08 0.60
52 0.50 0.31 0.61 0.22 0.34 0.20 0.38
54 −0.13 −0.13
Total 0.50 0.47 0.30 0.54 −0.40 −0.03 −0.11 0.43

Table 4.28—Percent Earnings Difference Between Transfer Options and Failing Non-GE Programs, by CIP and Credential Level

cip2 Credential level Total
Associate Bachelor's Master's Doctoral Professional
1 0.31 0.12 0.16
3 0.38 −0.14 0.31
4 −0.31 −0.31
5 0.02 0.02
9 0.12 0.24 −0.02 0.20
10 0.14 −0.01 0.11
11 0.36 1.00 0.40
12 0.25 0.25
13 0.22 0.32 0.21 −0.12 0.23
15 0.83 0.83
16 0.03 0.43 0.40
19 0.18 0.40 −0.42 0.27
22 0.00 −0.08 −0.26 −0.59 −0.07 −0.13
23 0.38 0.23 −0.18 0.20
24 0.15 0.10 −0.54 0.14
26 0.13 0.28 0.16 −0.70 0.22
30 0.12 0.06 −0.17 0.07
31 0.10 0.22 −0.22 0.18
38 −0.05 −0.10 −0.07
39 0.55 0.49 −0.02 0.20 0.38
40 0.58 0.58
41 0.08 0.08
42 0.31 0.04 −0.24 −0.35 0.07
43 0.19 −0.04 0.06 0.09
44 0.21 −0.16 −0.08 0.10
45 0.09 0.47 −0.12 0.23
47 0.38 0.38
50 0.23 0.40 0.31 −0.29 0.37
51 0.62 0.78 0.57 0.26 0.11 0.46
52 0.15 0.48 0.72 0.22
54 0.06 −0.19 −0.09
Total 0.22 0.27 0.26 0.07 0.04 0.21

Table 4.29—Percent Debt Difference Between Transfer Options and Failing GE Programs, by CIP and Credential Level

cip2 Credential level Total
UG certificates Associate Bachelor's Master's Doctoral Professional Grad certs
1 0.00 0.00
3 −0.65 −0.65
9 0.06 −0.26 −0.01 −0.04
10 0.15 0.63 −0.32 −0.15
11 0.21 −0.36 −0.23 −0.79 −0.14
12 −0.23 −0.49 0.13 0.00 −0.23
13 −0.28 −0.89 −0.31 −0.36 −0.18 −0.20 −0.39
14 0.01 −0.58 −0.30
15 −0.10 −0.69 −0.17
16 −0.52 −0.52
19 −0.05 −0.26 −0.24 −0.30 −0.23
22 1.00 −0.60 −0.26 −0.40 −0.47
23 0.00 −0.82 −0.33 0.00 −0.18
24 0.00 0.00
25
26 −0.25 −0.25
30 −0.91 −0.54 −0.58
31 −0.83 −0.75 −0.80
32 0.00 0.00
39 0.59 0.59
42 −0.49 −0.20 −0.16 −0.77 −0.35
43 −0.57 −0.70 −0.42 −0.10 −0.53
44 −0.74 −0.09 −0.32 −0.38 −0.23
45 −0.11 −0.11
46 0.07 0.07
47 0.05 −0.24 0.00
48 −0.21 −0.21
49 0.33 0.33
50 0.21 −0.59 −0.33 −0.23 −0.31
51 0.01 −0.16 −0.39 −0.48 −0.64 0.60 −0.43 −0.10
52 −0.14 −0.42 −0.33 −0.17 −0.17 −0.27 −0.35
54 −0.22 −0.22
Total −0.10 −0.38 −0.36 −0.36 −0.22 0.48 −0.34 −0.22

Table 4.30—Percent Debt Difference Between Transfer Options and Failing Non-GE Programs, by CIP and Credential Level

2-digit CIP code Credential level Total
Associate Bachelor's Master's Doctoral Professional
1 −0.37 −0.14 −0.19
3 0.02 −0.53 −0.06
4 −0.35 −0.35
5 −0.12 −0.12
9 0.64 −0.22 −0.37 −0.13
10 −0.19 −0.11 −0.18
11 −0.29 −0.42 −0.30
12 0.08 0.08
13 0.24 −0.13 −0.30 −0.03 0.05
15 0.22 0.22
16 −0.27 0.19 0.15
19 0.07 0.21 −0.39 0.14
22 −0.55 −0.28 −0.16 −0.26 −0.28
23 0.19 −0.04 −0.33 −0.04
24 0.19 −0.10 0.16
26 0.78 0.11 −0.28 0.16
30 −0.15 −0.16 0.00 −0.15
31 0.80 −0.22 0.12
38 −0.26 −0.26
39 −0.67 −0.03 −0.29 0.00 −0.10
40 1.00 1.00
41
42 0.33 −0.11 −0.04 −0.17 −0.03
43 −0.22 −0.30 −0.19 −0.25
44 −0.26 −0.23 −0.16 −0.24
45 −0.08 −0.19 −0.53 −0.18
47 0.21 0.21
50 0.25 −0.02 −0.28 −0.01
51 0.01 −0.03 −0.09 −0.38 −0.22 −0.11
52 −0.15 −0.26 −0.09 −0.17
54 0.39 −0.79 0.10
Total 0.12 −0.07 −0.19 −0.32 −0.23 0.02

Transfer Causes Net Enrollment Increase in Some Sectors

The aggregate change in enrollment overall, by sector, and by institution would likely be less than that implied by the program- and institution-level results presented in the “Results of GE Accountability” section above because those do not consider that many students would likely transfer to passing programs or even remain enrolled at failing programs in response to a program losing title IV, HEA eligibility. The Department simulated the likely destinations of students enrolled in failing GE programs. Based on the research literature and described more fully in “Student Response Assumptions” subsection in Section 5 below, we use assumptions about the share of students that transfer to another program, remain enrolled in the original program, or drop out entirely if a program loses title IV, HEA eligibility. These student mobility assumptions differ according to the number of alternative options that exist and are the same assumptions used in the Net Budget Impact section.

Using these assumptions, for every failing GE program, we estimate the title IV, HEA enrollment from that program that would remain, dropout, or transfer to another program. Our notion of “transfers” includes both current students and future students who attend an alternative program instead of one that fails the GE metrics. The number of transfers is then reallocated to specific other non-failing GE and non-GE programs in the same institution (OPEID6), credential level, and 2-digit CIP code. If multiple such programs exist, transfer enrollment is allocated based on the share of initial title IV, HEA enrollment in these programs. If no alternative options exist using this approach, the transfer enrollment is allocated to non-failing GE and non-GE programs in the same geographic area (ZIP3), credential level, and 4-digit CIP code. Again, initial title IV, HEA enrollment shares are used to allocate transfer enrollment if multiple such alternative programs exist. These two approaches reallocate approximately 80 percent of the transfer enrollments we would expect from failing GE programs. Finally, new title IV, HEA enrollment is computed for each program that sums existing enrollment (or retained enrollment, in the case of failing GE programs) and the allocated transfer enrollment.

Table 4.31 summarizes these simulation results, separately by type of institution. Without accounting for transfers or students remaining in failing GE programs, aggregate title IV, HEA enrollment drops by 715,200 (3.7 percent), with at least some enrollment declines in all sectors. This will greatly overstate the actual enrollment decline associated with the regulation because it assumes that students leave postsecondary education in response to their program failing a GE metric. The final column simulates enrollment after accounting for transfers within institution (to similar programs) and to similar programs at other geographically proximate institutions, along with permitting some modest enrollment retention at failing programs. In this scenario, aggregate enrollment declines by only 231,000 (1.2 percent) due to the rule. Importantly, some sectors experience an enrollment increase as students transfer from failing to passing programs. For instance, public 2-year community colleges are simulated to experience a 30,000-student enrollment increase once transfers are accounted for rather than a 30,000-student decrease when they are not. HBCUs are simulated to gain 1,200 students rather than lose 700.

Programs at foreign institutions are excluded from Table 4.31 as they do not have an institutional type.

Note that since many failing programs result in earnings lower than those of the typical high school graduate, students leaving postsecondary education still may be better off financially compared to staying in a failing program.

Table 4.31—Enrollment With and Without Transfers, by Sector

Number of inst. Initial enrollment No transfers or retention + within institution CIP2 transfers + within ZIP3–CIP4 transfers
Sector of institution:
Public, 4-year + 700 8,186,900 8,179,700 8,184,900 8,208,800
Private not-for-profit, 4-year + 1,400 4,002,400 3,994,500 3,999,200 4,004,500
Private for-profit, 4-year + 200 1,298,900 951,100 1,147,900 1,155,900
Public, 2-year 900 5,025,200 4,995,600 5,013,300 5,054,900
Private not-for-profit, 2-year 100 97,200 74,900 91,200 92,100
Private for-profit, 2-year 300 290,900 195,600 250,600 255,900
Public, <2-year 200 42,600 41,300 42,100 46,200
Private not-for-profit, <2-year <50 11,600 6,200 8,300 8,500
Private for-profit, <2-year 1,000 278,400 85,700 151,100 178,200
Total 4,900 19,234,100 18,524,500 18,888,500 19,004,900
Note: Enrollment counts have been rounded to the nearest 100.

5. Discussion of Costs, Benefits, and Transfers

Description of Baseline

In absence of the final regulations, many students enroll in low-financial-value programs where they either end up not being able to secure a job that leads to higher earnings, take on unmanageable debt, or both. Many of these students default on their student loans, with negative consequences for their credit and financial security and at substantial costs to the taxpayers. Many students with insufficient earnings to repay their debts would be eligible to have their payments reduced and eventually have their loans forgiven through income-driven repayment (IDR). This shields low-income borrowers from the consequences of unaffordable debts but shifts the financial burden onto taxpayers.

We have considered the primary costs, benefits, and transfers for the following groups or entities that will be affected by the final regulations:

  • Students
  • Institutions
  • State and local governments
  • The Federal Government

We first discuss the anticipated benefits of the final regulations, including improved market information. We then assess the expected costs and transfers for students, institutions, the Federal Government, and State and local governments. Table 5.1 below summarizes the major benefits, costs, and transfers and whether they are quantified in our analysis or not.

Table 5.1—Summary of Costs, Benefits, and Transfers for Financial Value Transparency and Gainful Employment Final Regulations

Students Institutions State and local governments Federal government
Benefits
Quantified Earnings gain from shift to higher value programs State tax revenue from higher earnings Federal tax revenue from higher earnings.
Not quantified Lower rates of default, higher rates of family & business formation, higher retirement savings, saving of opportunity cost for non-enrollees Increased enrollment and revenue associated with new enrollments from improved information about value; improvements in program quality
Costs
Quantified Time for acknowledgment Time for acknowledgment Additional spending at institutions that absorb students from failing programs Implementation of data collection and information website.
Not quantified Time, logistics, credit loss associated with program transfer Investments to improve program quality; decreased enrollment and revenue associated with fewer new enrollments from improved information about value
Transfers
Quantified Aid money from failing programs to govt for non-enrollments; aid money from failing to better-value programs for transfers Aid money from failing programs to govt for non-enrollments.
Not quantified Increased loan payments associated with less IDR forgiveness Aid money from failing programs to State govt for non-enrollments Aid money from failing programs to State govt for non-enrollments Increased loan payments associated with less IDR forgiveness and fewer defaults.

Benefits

We expect the primary benefits of both the accountability and transparency components of the final regulation to derive from a shift of students from low-value to high-value programs or, in some cases, a shift away from low-value postsecondary programs to non-enrollment. This shift will be due to improved and standardized market information about GE and non-GE programs. This will increase the transparency of student outcomes for better decision-making by current students, prospective students, and their families; the public, taxpayers, and the Government; and institutions. Furthermore, the accountability component should improve program quality by directly eliminating the ability of low-value GE programs to participate in the title IV, HEA programs. Finally, both the transparency and accountability provisions of the rule should lead to a more competitive postsecondary market that encourages improvement, thereby, improving the outcomes and/or reducing the cost of existing programs that continue to enroll students.

Benefits to Students

Under the final regulation, students, prospective students, and their families will have extensive, comparable, and reliable information about the outcomes of students who enroll in GE and non-GE programs such as cost, debt, earnings, completion, and repayment outcomes. This information should assist them in choosing institutions and programs where they believe they are most likely to complete their education and achieve the earnings they desire, while having debt that is manageable. This information should result in more informed decisions based on reliable information about a program's outcomes.

Students will potentially benefit from this information via higher earnings, lower costs and less debt, and better program quality. This can happen through three channels. First, students benefit by transferring to passing programs. Second, efforts to improve programs should lead to better labor market outcomes, such as improved job prospects and higher earnings, by offering better student services, working with employers so graduates have needed skills, improving program quality, and helping students with career planning. This may happen as institutions improve programs to avoid failing the D/E or EP measures or simply from programs competing more for students based on quality, with the rule providing greater transparency about program quality. As a result of these enrollment shifts, students who graduate with manageable debts and adequate earnings should be more likely to pay back their loans, marry, buy a home, and invest in their futures. Finally, some students that chose not to enroll in low-value programs will save opportunity costs by not investing their time in programs that do not lead to good outcomes. While these other factors are certainly important to student wellbeing, our analysis focuses on the improvement in earnings associated with a shift from low-value programs to higher value programs.

Chakrabarti, R., Fos, V., Liberman, A. & Yannelis, C. (2020). Tuition, Debt, and Human Capital. Federal Reserve Bank of N.Y. Staff Report No. 912. Gicheva, D. (2016). Student Loans or Marriage? A Look at the Highly Educated. Economics of Education Review, 53, 207–2016. Gicheva, D. & Thompson, J. (2015). The Effects of Student Loans on Long-Term Household Financial Stability. In Hershbein, B. & Hollenbeck, K. (Ed.). Student Loans and the Dynamics of Debt (137–174). W.E. Upjohn Institute for Employment Research: Kalamazoo, MI. Hillman, NW (2014). College on Credit: A Multilevel Analysis of Student Loan Default. Review of Higher Education 37(2), 169–195.

Mezza, A., Ringo, D., Sherlund, S. & Sommer, K. (2020). Student Loans and Homeownership. Journal of Labor Economics, 38(1): 215–260.

Benefits to Institutions

Institutions offering high-performing programs to students are likely to see growing enrollment and revenue and to benefit from additional market information that permits institutions to demonstrate the value of their programs without excessive spending on marketing and recruitment. Additionally, institutions that work to improve the quality of their programs could see increased revenues from improved retention and completion and therefore, additional tuition revenue.

We believe the information transparency will increase enrollment and revenues in well-performing programs. Improved information should increase market demand for programs that produce good outcomes. While the increases or decreases in revenues for institutions are benefits or costs from the institutional perspective, they are transfers from a social perspective. However, any additional demand for education due to overall program quality improvement would be considered a social benefit.

The improved information that will be available as a result of the regulations will also benefit institutions' planning and improvement efforts. Information about student outcomes will help institutions determine whether it would be prudent to expand, improve quality, reduce costs, or eliminate various programs. Institutions may also use this information to offer new programs in fields where students are experiencing positive outcomes, including higher earnings and steady employment. Additionally, institutions will be able to identify and learn from programs that produce exceptional results for students.

Benefits to State and Local Governments

State and local governments will benefit from additional tax revenue associated with higher student earnings and students' increased ability to spend money in the economy. They are also likely to benefit from reduced costs because, as institutions improve the quality of their programs, their graduates are likely to have improved job prospects and higher earnings, meaning that governments are likely to be able to spend less on unemployment benefits and other social safety net programs. State and local governments will also experience improved oversight of their investments in postsecondary education. Additionally, State, and local postsecondary education funding could be allocated more efficiently to higher-performing programs. State and local governments would also experience a better return on investment on their dollars spent on financial aid programs as postsecondary program quality improves or if students reallocate to higher-performing programs.

Benefits to Federal Government

The Federal Government should benefit from additional tax revenue associated with higher student earnings and students' increased ability to spend money in the economy. Another primary benefit of the regulations will be improved oversight and administration of the title IV, HEA programs, particularly the new data reported by institutions. Additionally, Federal taxpayer funds should be allocated more efficiently to higher-performing programs, where students are more likely to graduate with manageable amounts of debt and gain stable employment in a well-paying field, increasing the positive benefits of Federal investment in title IV, HEA programs.

The taxpayers and the Government will also benefit from improved information about GE programs. As the funders and stewards of the title IV, HEA programs, these parties have an interest in knowing whether title IV, HEA program funds are benefiting students. The information provided will allow for more effective monitoring of the Federal investment in GE programs.

Costs

Costs to Students

Students may incur some costs as a result of the final regulations. One cost is that all title IV, HEA students attending eligible non-GE programs that fail the D/E metric will be required to acknowledge having seen information about program outcomes before students sign enrollment agreements. Students attending GE programs with at least one failing metric will additionally be required to acknowledge a warning that the program could lose title IV, HEA eligibility. The acknowledgment is the main student cost we quantify in our analysis. We expect that over the long-term, all students will have increased access to programs that lead to successful outcomes. In the short term, students in failing programs could incur search and logistical costs associated with finding and enrolling in an alternative program, whether that be a GE or non-GE program. Further, at least some students may be temporarily left without transfer options. We expect that many of these students will re-enter postsecondary education later, but we understand that some students may not continue. We do not quantify these costs associated with searching for and transferring to new postsecondary programs.

Costs to Institutions

Under the regulations, institutions will incur costs as they make changes needed to comply, including costs associated with the reporting, disclosure, and acknowledgment requirements. These costs could include (1) Training of staff for additional duties, (2) potential hiring of new employees, (3) purchase of new, or modifications to existing, software or equipment, and (4) procurement of external services.

As described in the Preamble, much of the necessary information required from GE programs would already have been reported to the Department under the 2014 Prior Rule, and as such we believe the added burden of this reporting relative to existing requirements will be reasonable. Furthermore, 88 percent of public and 47 percent of private nonprofit institutions operated at least one GE program and have experience with similar data reporting for the subset of their students enrolled in certificate programs under the 2014 Prior Rule. Moreover, many institutions report more detailed information on the components of cost of attendance and other sources of financial aid in the Federal National Postsecondary Student Aid Survey (NPSAS) administered by the National Center for Education Statistics. Finally, for the first six years after the effective date of the rule, the Department provides flexibility for institutions to avoid reporting data on students who completed programs in the past, and instead to use data on more recent completer cohorts to estimate median debt levels. In part, this is intended to ease the administrative burden of providing this data for programs that were not covered by the 2014 Prior Rule reporting requirements, especially for the small number of institutions that may not previously have had any programs subject to these requirements.

Our initial estimate of the time cost of these reporting requirements for institutions is 5.0 million hours initially and then 1.4 million hours annually after the first year. The Department recognizes that institutions may have different approaches and processes for record-keeping and administering financial aid, so the burden of the GE and financial transparency reporting could vary by institution. Many institutions may have systems that can be queried or existing reports that can be adapted to meet these reporting requirements. On the other hand, some institutions may still have data entry processes that are very manual in nature and generating the information for their programs could involve many more hours and resources. Institutions may fall in between these poles and be able to automate the reporting of some variables but need more effort for others. The total reporting burden will be distributed across institutions depending on the setup of their systems and processes. We believe that, while the reporting relates to program or student-level information, the reporting process is likely to be handled at the institutional level.

Table 5.2 presents the Department's estimates of the hours associated with the reporting requirements. The reporting process will involve staff members or contractors with different skills and levels of responsibility. We have estimated this using Bureau of Labor statistics median hourly wage for Education Administrators, Post-Secondary of $48.05.

Table 5.2—Estimated Hours and Wage Rate for Reporting Requirements

Process Hours Hours basis
Review systems and existing reports for adaptability for this reporting 10 Per institution.
Develop reporting query/result template:
Program-level reporting 15 Per institution.
Student-level reporting 30 Per institution.
Run test reports:
Program-level reporting 0.25 Per institution.
Student-level reporting 0.5 Per institution.
Review/validate test report results:
Program-level reporting 10 Per institution.
Student-level reporting 20 Per institution.
Run reports:
Program-level reporting 0.25 Per program
Student-level reporting 0.5 Per program
Review/validate report results:
Program-level reporting 2 Per program
Student-level reporting 5 Per program
Certify and submit reporting 10 Per institution.

The ability to set up reports or processes that can be rerun in future years, along with the fact that the first reporting cycle includes information from several prior years, means that the expected burden should decrease significantly after the first reporting cycle. We estimate that the hours associated with reviewing systems, developing or updating queries, and reviewing and validating the test queries or reports will be reduced by 35 percent after the first year. After initial reporting is completed, the institution will need to confirm there are no program changes in CIP code, credential level, preparation for licensure, accreditation, or other items on an ongoing basis. We expect that process would be less burdensome than initially establishing the reporting. Table 5.3 presents estimates of reporting burden for the initial year and subsequent years under § 668.408.

Table 5.3.1—Estimated Reporting Burden for the Initial Reporting Cycle

Control and level Institution count Program count Hours Amount
Private 2-year 121 700 33,286 1,599,380
Proprietary 2-year 1,194 3,490 222,516 10,691,870
Public 2-year 1,036 37,612 1,265,169 60,791,370
Private 4-year 1,290 49,000 1,642,518 78,922,966
Proprietary 4-year 177 2,970 109,018 5,238,303
Public 4-year 700 56,088 1,805,753 86,766,432
Total 4,518 149,860 5,078,259 244,010,321

Table 5.3.2—Estimated Reporting Burden for Subsequent Reporting Cycles

Control and level Institution count Program count Hours Amount
Private 2-year 121 700 13,411 644,399
Proprietary 2-year 1194 3490 105,852 5,086,165
Public 2-year 1036 37612 359,869 17,291,705
Private 4-year 1290 49000 464,890 22,337,965
Proprietary 4-year 177 2970 34,700 1,667,311
Public 4-year 700 56088 480,882 23,106,380
Total 4,518 149,860 1,459,603 70,133,924

These burden estimates are not reduced for the exemption that allows institutions to not report on programs with less than thirty completers across the most recent four award years. We expect this provision would reduce the burden on foreign institutions and others across a variety of fields and institutional characteristics.

As described in the section titled “Paperwork Reduction Act of 1995,” the final estimates of reporting costs will be cleared at a later date through a separate information collection. Institutions' share of the annual costs associated with disclosures, acknowledgment for all programs, and warnings and acknowledgment for GE programs are estimated to be $12 million, $0.05 million, and $0.76 million, respectively. Note that most of the burden associated acknowledgments will fall on students, not institutions. These costs are discussed in more detail in the section titled “Paperwork Reduction Act of 1995.”

Institutions that make efforts to improve the outcomes of failing programs could face additional costs. For example, institutions that reduce the tuition and fees of programs would see decreased revenue. For students who are currently enrolled in a program, the reduced price would be a transfer to them in the form of a lower cost of attendance. In turn, some of this price reduction would be a transfer to the government if the tuition was being paid for with title IV, HEA funds. An institution could also choose to spend more on curriculum development to, for example, link a program's content to the needs of in-demand and well-paying jobs in the workforce, or allocate more funds toward other functions. These other functions could include hiring better faculty; providing training to existing faculty; offering tutoring or other support services to assist struggling students; providing career counseling to help students find jobs; acquiring more up-to-date equipment; or investing in other areas where increased spending could yield improved performance. However, as mentioned in the benefits section, institutions that improve program quality could see increased tuition revenue with improved retention and completion.

The costs of program changes in response to the regulations are difficult to quantify generally, as they would vary significantly by institution and ultimately depend on institutional behavior. For example, institutions with all passing programs could elect to commit only minimal resources toward improving outcomes. On the other hand, they could instead make substantial investments to expand passing programs and meet increased demand from prospective students, which could result in an attendant increase in enrollment costs. Institutions with failing programs could decide to devote significant resources toward improving performance, depending on their capacity, or could instead elect to discontinue one or more of the programs. However, as mentioned previously, some of these costs might be offset by increased revenue from improved program quality. Given these ambiguities, we do not quantify costs (or benefits) associated with program quality improvements.

Finally, some poorly performing programs will experience a reduction in enrollment that is not fully offset by gains to other institutions (which will experience increased enrollment) or the Federal Government (which will experience lower spending on Title IV, HEA aid). These losses should be considered as costs for institutions.

Costs to States and Local Governments

State and local governments may experience increased costs as enrollment in well-performing programs at public institutions increases as a result of some students transferring from failing programs, including those offered by for-profit institutions.

The Department recognizes that a shift in students to public institutions could result in higher State and local government costs, but the extent of this is dependent on student transfer patterns, State and local government choices, and the existing capacity of public programs. If States choose to expand the enrollment capacity of passing programs at public institutions, it is not necessarily the case that they would face marginal costs that are similar to their average cost or that they would only choose to expand through traditional brick-and-mortar institutions. The Department continues to find that many States across the country are experimenting with innovative models that use different methods of instruction and content delivery, including online offerings, that allow students to complete courses faster and at lower cost. Furthermore, enrollment shifts would likely be towards community colleges, where declining enrollment has created excess capacity. An under-subscribed college may see greater efficiency gains from increasing enrollment and avoid other costly situations such as unused classroom space or unsustainably low enrollment. Forecasting the extent to which future growth would occur in traditional settings versus online education or some other model is outside the scope of this analysis. Nonetheless, we do include the additional instructional cost associated with a shift from failing to passing programs in our analysis, some of which will fall on State and local governments.

Costs to Federal Government

The main costs to the Federal Government involve setting up the infrastructure to handle and process additional information reported by institutions, compute rates and other information annually, and maintain a program information website and acknowledgment process. Most of these activities will be integrated into the Department's existing processes. We estimate that the total implementation cost will be $30 million.

Transfers

Enrollment shifts between programs, and potentially to non-enrollment, will transfer resources between students, institutions, State and local governments, and the Federal Government. We model three main transfers. First, if some students drop out of postsecondary education or remain in programs that lose eligibility for title IV, HEA Federal student aid, there would be a transfer of Federal student aid from those students to the Federal Government. Second, if students change institutions based on program performance, or title IV, HEA eligibility, revenues and expenses associated with students would transfer between postsecondary institutions. Finally, additional earnings associated with movement from low- to high-value programs would result in greater loan repayment by borrowers. This is through both lower default rates and a lower likelihood of loan forgiveness through existing IDR plans. This represents a transfer from students to the Federal Government. We do not quantify the transfers between students and State governments associated with changes in State-financed student aid, as such programs differ greatly across States. Transfers between students and States could be net positive for States if fewer students apply for, or need, State aid programs or they could be negative if enrollment shifts to State programs results in greater use of State aid.

6. Methodology for Budget Impact and Estimates of Costs, Benefits, and Transfers

In this section we describe the methodology used to estimate the budget impact as well as the main costs, benefits, and transfers. Our modeling and impact only include the Financial Value Transparency and GE parts of the final rule.

The main behaviors that drive the direction and magnitudes of the budget impacts of the rule and the quantified costs, benefits, and transfers are the performance of programs and the enrollment and borrowing decisions of students. The Department developed a model based on assumptions regarding enrollment, program performance, student response to program performance, and average amount of title IV, HEA funds per student to estimate the budget impact of these regulations. Additional assumptions about the earnings outcomes and instructional spending associated with program enrollment and tax revenue from additional earnings were used to quantify costs, benefits, and transfers. The model (1) takes into account a program's past results under the D/E and EP rates measure to predict future results, and (2) tracks a GE program's cumulative results across multiple cycles of results to determine title IV, HEA eligibility.

Assumptions

We made assumptions in four areas in order to estimate the budget impact of the rule: (1) Program performance under the rule; (2) Student behavior in response to program performance; (3) Borrowing of students under the rule; and (4) Enrollment growth of students in GE and non-GE programs. Table 6.1 below provides an overview of the main categories of assumptions and the sources. Assumptions that are included in our sensitivity analysis are also highlighted. Wherever possible, our assumptions are based on past performance and student enrollment patterns in data maintained by the Department or documented by scholars in prior research. Additional assumptions needed to quantify costs, benefits, and transfers are described later when we describe the methodology for those calculations.

Table 6.1—Main Assumptions and Sources

Category Detail Source Included in sensitivity?
Assumptions for Budget Impact and Calculation of Costs, Benefits, and Transfers
Program Performance at Baseline Share in each performance category at baseline (GE and non-GE programs) ED data No.
Enrollment Growth Annual enrollment growth rate by sector/level and year Sector-level projections based on Department data No.
Program transition between performance categories AY2025–26, AY2026–27 onward, separately by loan risk group and for GE and non-GE programs Based on Department data + program improvement assumptions Yes.
Student response Share of students who remain in programs, transfer to passing programs, or withdraw or decline to enroll by program performance category and transfer group; separately for GE and non-GE programs Assumptions from 2014 RIA and prior work Yes.
Student borrowing Debt changes if students transfer to passing program by program performance, risk group, and cohort; separately for GE and non-GE programs Based on Department data No.
Additional Assumptions for Calculation of Costs, Benefits, and Transfers
Earnings gain Average program earnings by risk group and program performance, separately for GE and non-GE programs Based on Department data Yes.
Tax rates Federal and State average marginal tax and transfer rates Hendren and Sprung-Keyser 2020 estimates based on CBO No.
Instructional cost Average institution-level instructional expenditure by risk group and program performance; separately for GE and non-GE programs IPEDS No.

Enrollment Growth Assumptions

For AYs 2023 to 2034, the budget model assumes a constant yearly rate of growth or decline in enrollment of students receiving title IV, HEA program funds in GE and non-GE programs in absence of the rule. We compute the average annual rate of change in title IV, HEA enrollment from AY 2016 to AY 2022, separately by the combination of control and credential level. We assume this rate of growth for each type of program for AYs 2023 to 2034 when constructing our baseline enrollment projections. Table 6.2 below reports the assumed average annual percent change in title IV, HEA enrollment.

AYs 2023 to 2034 are transformed to FYs 2023 to 2033 later in the estimation process.

The number of programs in proprietary post-BA certificates and proprietary professional degrees was too low to reliably compute a growth rate. Therefore, we assumed a rate equal to the overall proprietary rate of −0.4 percent.

Table 6.2—Annual Enrollment Growth Rate (Percent) Assumptions

Public Private, nonprofit Proprietary
UG Certificates −2.6 −6.9 4.1
Associate −3.7 −3.9 −3.7
Bachelor's −0.5 −0.8 −2.7
Post-BA Certs 4.2 −2.3 −0.4
Master's 3.0 0.5 −1.1
Doctoral 4.9 3.1 −1.7
Professional 0.9 −0.1 −0.4
Grad Certs 1.2 2.0 −0.8

Program Performance Transition Assumptions

The methodology, described in more detail below, models title IV, HEA enrollment over time not for specific programs, but rather by groupings of programs by broad credential level and control, the number of alternative programs available, whether the program is GE or non-GE, and whether the program passes or fails the D/E and EP metrics. The model estimates the flow of students between these groups due to changes in program performance over time and reflects assumptions for the share of enrollment that would transition between the following four performance categories in each year:

  • Passing (includes with and without data)
  • Failing D/E rate only
  • Failing EP rate only
  • Failing both D/E and EP rates

A GE program becomes ineligible if it fails either the D/E or EP rate measures in two out of three consecutive years. We assume that ineligible programs remain that way for all future years and, therefore, do not model performance transitions after ineligibility is reached. The model applies different assumptions for the first year of transition (from year 2025 to 2026) and subsequent years (after 2026). It assumes that the rates of program transition reach a steady state in 2027. We assume modest improvement in performance, indicated by a reduction in the rate of failing and an increase in the rate of passing, among programs that fail one of the metrics, and an increase in the rate of passing again, among GE programs that pass the metrics. All transition probabilities are estimated separately for GE and non-GE programs and for four aggregate groups: proprietary 2-year or less; public or nonprofit 2-year or less; 4-year programs; graduate programs.

The budget simulations separate lower and upper division enrollment in 4-year programs. We assume the same program transition rates for both.

The assumptions for the 2025 to 2026 transition are taken directly from an observed comparison of actual rates results for two consecutive cohorts of students. The initial assignment of performance categories in 2025 is based on the 2022 PPD for students who completed programs in award years 2015 and 2016, whose earnings are measured in calendar years 2018 and 2019. The program transition assumptions for 2025 to 2026 are based on the outcomes for this cohort of students along with the earnings outcomes of students who completed programs in award years 2016 and 2017 (earnings measured in calendar years 2019 and 2020) and debt of students who completed programs in award years 2017 and 2018. A new set of D/E and EP metrics was computed for each program using this additional two-year cohort. Programs with fewer than 30 completers or with fewer than 30 completers with earnings records are determined to be passing, though can transition out of this category between years. The share of enrollment that transitions from each performance category to another is computed separately for each group.

In order to produce transition rates that are stable over time and that do not include secular trends in passing or failing rates (which are already reflected in our program growth assumptions), we compute transition rates from Year 1 to Year 2 and from Year 2 to Year 1 and average them to generate a stable rate shown in the tables.

The left panels of Tables 6.3 and 6.4 report the program transition assumptions from 2025 to 2026 for non-GE and GE programs, respectively. Program performance for non-GE is quite stable, with 95.8 percent of passing enrollment in two-year or less public and nonprofit expected to remain in passing programs. Persistence rates are even higher among 4-year and graduate programs. Among programs that fail the EP threshold, a relatively high share—more than one-third among 2-year and less programs—would be at passing programs in a subsequent year. The performance of GE programs is only slightly less persistent than that of non-GE programs. Note that GE programs would become ineligible for title IV, HEA funds the following year if they fail the same metric two years in a row. Among enrollment in less than two-year proprietary programs that fail the EP metric in 2025, 21.7 percent would pass in 2026 due to a combination of passing with data and no data.

The observed results also serve as the baseline for each subsequent transition of results (2026 to 2027, 2027 to 2028, etc.). The model applies additional assumptions from this baseline for each transition beginning with 2026 to 2027. Because the baseline assumptions are the actual observed results of programs based on a cohort of students that completed programs prior to the Department's GE rulemaking efforts, these transition assumptions do not account for changes that institutions have made to their programs in response to the Department's regulatory actions or would make after the final regulations are published.

As done with analysis of the 2014 rule, the Department assumes that institutions at risk of warning or sanction would take at least some steps to improve program performance by improving program quality, job placement, and lowering prices (leading to lower levels of debt), beginning with the 2026 to 2027 transition. There is evidence that institutions have responded to past GE measures by aiming to improve outcomes or redirecting enrollment from low-performing programs. Institutions subject to GE regulations have experienced slower enrollment and those that pass GE thresholds tend to have a lower likelihood of program or institution closure. Some leaders of institutions subject to GE regulation in 2014 did make improvements, such as lowering costs, increasing job placement and academic support staff, and other changes. We account for this by increasing the baseline observed probability of having a passing result by five percentage points for programs with at least one failing metric in 2026. Additionally, we improve the baseline observed probability of passing GE programs having a sequential passing result by two and a half percentage points to capture the incentive that currently passing programs have to remain that way. These new rates are shown in the right panels of Tables 6.3 and 6.4.

Fountain, J. (2019). The Effect of the Gainful Employment Regulatory Uncertainty on Student Enrollment at For-Profit Institutions of Higher Education. Research in Higher Education, Springer; Association for Institutional Research, vol. 60(8), 1065–1089. Kelchen, R. & Liu, Z. (2022). Did Gainful Employment Regulations Result in College and Program Closures? Education Finance and Policy; 17 (3): 454–478.

Hentschke, G.C. & Parry, S.C. (2015). Innovation in Times of Regulatory Uncertainty: Responses to the Threat of “Gainful Employment.” Innov High Educ 40, 97–109 ( doi.org/10.1007/s10755-014-9298-z).

We assume the same rates of transition between performance categories for subsequent years as we do for the 2026 to 2027 transitions.

Since the budget impact and net costs, benefits, and transfers depend on assumptions about institutional performance after the rule is enacted, we incorporate alternative assumptions about these transitions in our sensitivity analysis.

Table 6.3—Program Transition Assumptions Non-GE Programs

Percent in year t+1 status (2026) Percent in year t+1 status (2027–2033)
Pass Fail D/E only Fail EP only Fail Both Pass Fail D/E only Fail EP only Fail Both
Public and Nonprofit 2-year or less
Year t Status:
Pass 95.8 0.0 4.1 0.1 95.8 0.0 4.1 0.1
Fail D/E only 10.1 84.3 1.6 4.1 15.1 79.3 1.6 4.1
Fail EP only 37.7 0.1 62.1 0.1 42.7 0.1 57.1 0.1
Fail Both 22.2 6.5 8.6 62.7 27.2 6.5 8.6 57.7
4-year
Year t Status:
Pass 99.1 0.3 0.4 0.2 99.1 0.3 0.4 0.2
Fail D/E only 28.8 63.6 0.7 6.9 33.8 58.6 0.7 6.9
Fail EP only 45.5 1.1 48.1 5.3 50.5 1.1 43.1 5.3
Fail Both 24.3 11.3 5.4 59.0 29.3 11.3 5.4 54.0
Graduate
Year t Status:
Pass 98.3 1.6 0.0 0.0 98.3 1.6 0.0 0.0
Fail D/E only 29.2 69.3 0.0 1.5 34.2 64.3 0.0 1.5
Fail EP only 72.4 0.0 17.9 9.7 77.4 0.0 12.9 9.7
Fail Both 20.2 44.3 2.7 32.7 25.2 44.3 2.7 27.7

Table 6.4—Program Transition Assumptions GE Programs

Share in year t+1 status (2026) Share in year t+1 status (2027–2033)
Pass Fail D/E only Fail EP only Fail Both Pass Fail D/E only Fail EP only Fail Both
Proprietary 2-year or less
Year t Status:
Pass 91.1 2.3 5.8 0.9 93.6 1.7 4.2 0.6
Fail D/E only 18.8 66.7 0.2 14.4 23.8 61.7 0.2 14.4
Fail EP only 10.7 0.0 82.1 7.2 15.7 0.0 77.1 7.2
Fail Both 3.4 7.2 15.8 73.6 8.4 7.2 15.8 68.6
Public and Nonprofit 2-year or less
Year t Status:
Pass 95.8 0.0 4.1 0.1 98.3 0.0 1.7 0.1
Fail D/E only 60.5 0.0 0.0 39.5 65.5 0.0 0.0 34.5
Fail EP only 47.3 0.0 51.8 0.8 52.3 0.0 46.8 0.8
Fail Both 29.1 29.2 8.9 32.7 34.1 29.2 8.9 27.7
4-year
Year t Status:
Pass 94.1 5.4 0.0 0.4 96.6 3.1 0.0 0.2
Fail D/E only 21.4 70.3 0.0 8.3 26.4 65.3 0.0 8.3
Fail EP only 2.4 4.9 0.0 92.7 7.4 4.9 0.0 87.7
Fail Both 5.4 32.2 1.5 60.9 10.4 32.2 1.5 55.9
Graduate
Year t Status:
Pass 97.0 2.9 0.0 0.1 99.5 0.5 0.0 0.0
Fail D/E only 19.9 77.7 0.0 2.4 24.9 72.7 0.0 2.4
Fail EP only 100.0 0.0 0.0 0.0 100.0 0.0 0.0 0.0
Fail Both 8.7 37.4 0.0 53.9 13.7 37.4 0.0 48.9

Student Response Assumptions

The Department's model applies assumptions for the probability that a current or potential student would transfer or choose a different program, remain in or choose the same program, or withdraw from or not enroll in any postsecondary program in reaction to a program's performance. The model assumes that student response would be greater when a program becomes ineligible for title IV, HEA aid than when a program has a single year of inadequate performance, which initiates warnings and the acknowledgment requirement for GE programs, an acknowledgment requirement non-GE programs that fail D/E, and publicly reported performance information in the ED portal for both GE and non-GE programs. We also let the rates of transfer and withdrawal or non-enrollment differ with the number of alternative transfer options available to students enrolled (or planning to enroll) in a failing program. Specifically, building on the analysis presented in “Measuring Students' Alternative Options” above, we categorize individual programs into one of four categories:

High transfer options: Have at least one passing program in the same credential level at the same institution and in a related field (as indicated by being in the same 2-digit CIP code).

Medium transfer options: Have a passing transfer option within the same ZIP3, credential level, and narrow field (4-digit CIP code).

Low transfer options: Have a passing transfer option within the same ZIP3, credential level, and broad (2-digit) CIP code.

Few transfer options: Do not have a passing transfer option within the same ZIP3, credential level, and broad (2-digit) CIP code. Students in these programs would be required to enroll in either a distance education program or enroll outside their ZIP3. As shown in “Measuring Students' Alternative Options,” all failing programs have at least one non-failing program in the same credential level and 2-digit CIP code in the same State.

For each of the four categories above, we make assumptions for each type of student transition. Programs with passing metrics are assumed to retain all of their students.

Students that transfer are assumed to transfer to passing programs, and for the purposes of the budget simulation this includes programs with an insufficient n-size. We assume that rates of withdrawal (or non-enrollment) and transfer are higher for ineligible programs than those where only the warning/acknowledgment is required (GE programs with one year of a failing metric and non-GE programs with a failing D/E metric). We also assume that rates of transfer are weakly decreasing (and rates of dropout and remaining in program are both weakly increasing) as programs have fewer transfer options. These assumptions regarding student responses to program results are provided in Tables 6.5 and 6.6. Coupled with the scenarios presented in the “Sensitivity Analysis,” these assumptions are intended to provide a reasonable estimation of the range of impact that the regulations could have on the budget and overall social costs, benefits, and transfers.

The assumptions above are based on our best judgment and from extant research that we view as reasonable guides to the share of students likely to transfer to or choose another program when their program loses title IV, HEA eligibility. For instance, a 2021 GAO report found that about half of non-completing students who were at closed institutions transferred. This magnitude is similar to recent analysis that found that 47 percent of students reenrolled after an institutional closure. The authors of this report find very little movement from public or nonprofit institutions into for-profit institutions, but considerable movement in the other direction. For example, about half of re-enrollees at closed for-profit 2-year institutions moved to public 2-year institutions, whereas less than 3 percent of re-enrollees at closed public and private nonprofit 4-year institutions moved to for-profit institutions. Other evidence from historical cohort default rate sanctions indicates a transfer rate of about half of students at for-profit colleges that were subject to loss of Federal financial aid disbursement eligibility, with much of that shift to public two-year institutions. The Department also conducted its own internal analysis of ITT Technical Institute closures. About half of students subject to the closure re-enrolled elsewhere (relative to pre-closure patterns). The majority of students that re-enrolled did so in the same two-digit CIP code. Of associate degree students that re-enrolled, 45 percent transferred to a public institution, 41 percent transferred to a different for-profit institution, and 13 percent transferred to a private nonprofit institution. Most remained in associate or certificate programs. Of bachelor's degree students that re-enrolled, 54 percent transferred to a different for-profit institution, 25 percent shifted to a public institution, and 21 percent transferred to a private nonprofit institution.

Government Accountability Office (2022). College Closures: Education Should Improve Outreach to Borrowers about Loan Discharges (GAO–22–104403) ( https://www.gao.gov/products/gao-22-104403 ).

State Higher Ed. Executive Officers Ass'n (2022). More than 100,000 Students Experienced an Abrupt Campus Closure Between July 2004 and June 2020 ( sheeo.org/more-than-100000-students-experienced-an-abrupt-campus-closure-between-july-2004-and-june-2020/).

Cellini, S.R., Darolia, R. & Turner, L.J. (2020). Where Do Students Go When For-Profit Colleges Lose Federal Aid? American Economic Journal: Economic Policy, 12(2), 46–83.

Data from the Beginning Postsecondary Students Longitudinal 2012/2017 study provides further information on students' general patterns through and across postsecondary institutions (not specific to responses to sanctions or closures). Of students that started at a public or private nonprofit 4-year institution, about 3 percent shifted to a for-profit institution within 5 years. Of those that began at a public or private nonprofit 2-year institution, about 8 percent shifted to a for-profit institution within 5 years.

The attestations for non-GE programs are scheduled to begin the year following the attestations for GE programs. Therefore, we delay applying transfer rates to non-GE programs in the first year of our budget analysis. Additionally, since undergraduate associate and bachelor's degree programs will not have an attestation requirement, we decrease the rate of transfer out by one quarter for these programs.

Table 6.5—Student Response Assumptions, by Program Result and Number of Alternative Program Options Available

Program result → Pass Fail once Ineligible
Student Response → Remain Transfer Withdrawal/ non-enrollment Remain Transfer Withdrawal/ non-enrollment Remain Transfer Withdrawal/ non-enrollment
GE:
High Alternatives 1.00 0.00 0.00 0.40 0.45 0.15 0.20 0.60 0.20
Medium Alternatives 1.00 0.00 0.00 0.45 0.35 0.20 0.20 0.55 0.25
Low Alternatives 1.00 0.00 0.00 0.50 0.30 0.20 0.25 0.45 0.30
Few Alternatives 1.00 0.00 0.00 0.55 0.25 0.20 0.25 0.35 0.40
Non-GE, Attestation:
High Alternatives 1.00 0.00 0.00 0.80 0.20 0.00 na na na
Medium Alternatives 1.00 0.00 0.00 0.85 0.15 0.00 na na na
Low Alternatives 1.00 0.00 0.00 0.90 0.10 0.00 na na na
Few Alternatives 1.00 0.00 0.00 0.95 0.05 0.00 na na na
Non-GE, No Attestation:
High Alternatives 1.00 0.00 0.00 0.85 0.15 0.00 na na na
Medium Alternatives 1.00 0.00 0.00 0.8875 0.1125 0.00 na na na
Low Alternatives 1.00 0.00 0.00 0.925 0.075 0.00 na na na
Few Alternatives 1.00 0.00 0.00 0.9625 0.0375 0.00 na na na

In Table 6.6, we provide detail of the assumptions of the destinations among students who transfer, separately for the following groups:

Lower division includes students in their first two years of undergraduate education. Upper division includes students in their third year or higher.

  • Risk 1 (Proprietary <=2 year)
  • Risk 2 (Public, Nonprofit <=2 year)
  • Risk 3 (Lower division 4 year)
  • Risk 4 (Upper division 4 year)
  • Risk 5 (Graduate)

Table 6.6—Student Response Assumptions, Among Transferring Students, Share Shifting Sectors

Shift to GE programs Shift to non-GE programs
Shift from . . . Risk 1 Risk 2 Risk 3 Risk 4 Risk 5 Risk 2 Risk 3 Risk 4 Risk 5
GE:
Risk 1 0.50 0.30 0.10 0.00 0.00 0.10 0.00 0.00 0.00
Risk 2 0.30 0.50 0.10 0.00 0.00 0.10 0.00 0.00 0.00
Risk 3 0.00 0.00 0.80 0.00 0.00 0.00 0.20 0.00 0.00
Risk 4 0.00 0.00 0.00 0.80 0.00 0.00 0.00 0.20 0.00
Risk 5 0.00 0.00 0.00 0.00 0.80 0.00 0.00 0.00 0.20
Non-GE:
Risk 2 0.05 0.05 0.00 0.00 0.00 0.70 0.20 0.00 0.00
Risk 3 0.00 0.00 0.05 0.00 0.00 0.05 0.90 0.00 0.00
Risk 4 0.00 0.00 0.00 0.05 0.00 0.00 0.00 0.95 0.00
Risk 5 0.00 0.00 0.00 0.00 0.05 0.00 0.00 0.00 0.95

As we describe below, the assumptions for student responses are applied to the estimated enrollment in each aggregate group after factoring in enrollment growth.

Student Borrowing Assumptions

Analyses in the Regulatory Impact Analysis of the 2014 Prior Rule assumed that student debt was unchanged if students transferred from failing to passing programs, but we believe this assumption to be too conservative given that one goal of the GE rule is to reduce the debt burden of students. Recall that Tables 4.29 and 4.30 above reported the percent difference in mean debt between failing GE and non-GE programs and their transfer options, by credential level and 2-digit CIP code. Across all subjects and credential levels, debt is 22 percent lower at alternative programs than at failing GE programs. At non-GE programs, there is no aggregate debt difference between failing programs and their alternatives, though this masks heterogeneity across credential levels. For graduate degree programs, movement to alternative programs from failing programs is associated with lower debt levels while movement from failing to passing Associate programs is associated with an increase in debt. Students that drop out of (or decline to enroll in) failing programs are assumed to acquire no educational debt.

To incorporate changes in average loan volume associated with student transitions, we compute average subsidized and unsubsidized direct loan, Grad PLUS, and Parent PLUS per enrollment separately for GE and non-GE programs by risk group and program performance group. These averages are then applied to shifts in enrollment to generate changes in the amount of aid.

Methodology for Net Budget Impact

The budget model estimates a yearly enrollment for AYs 2023 to 2034 and the distribution of those enrollments in programs characterized by D/E and EP performance, risk group, transfer category, and whether it is a GE program. This enrollment is projected for a baseline (in absence of the rule) and under the final rule. The net budget impact for each year is calculated by applying assumptions regarding the average amount of title IV, HEA program funds received by this distribution of enrollments across groups of programs. The difference in these two scenarios provides the Department's estimate of the impact of the final rule. We do not simulate the impact on the rule at the individual program level because doing so would necessitate very specific assumptions about which programs' students transfer to in response to the regulations. While we made such assumptions in the “Measuring Students' Alternatives” section above, we do not think it is analytically tractable to do for all years. Therefore, for the purposes of budget modeling, we perform analysis with aggregations of programs into groups defined by the following:

Note that non-GE programs do not include risk group 1 (2-year and below for-profit institutions) or the pre-ineligible or ineligible performance categories. Some groups also do not have all four transfer group categories. There are 184 total groups used in the analysis.

  • Five student loan model risk groups: (1) 2-year (and below) for-profit; (2) 2-year (and below) public or nonprofit; (3) 4-year (any control) lower division, which is students in their first two years of a bachelor's program; (4) 4-year (any control) upper division, which is students beyond their first two years of a bachelor's program; (5) Graduate student (any control).
  • Four transfer categories (high, medium, low, few alternatives) by which the student transfer rates are assumed to differ. This is a program-level characteristic that is assumed not to change.
  • Two GE program categories (GE and eligible non-GE) by which the program transitions are assumed to differ.
  • Six performance categories: Pass, Fail D/E, Fail EP, Fail Both, Pre-ineligible (a program's current enrollment is Title IV, HEA eligible, but next year's enrollment would not be), Ineligible (current enrollment is not Title IV, HEA eligible).

We refer to groups defined by these characteristics as “program aggregate” groups.

We first generate a projected baseline (in absence of the final rule) enrollment, Pell grant volume, and loan volume for each of the program aggregate groups from AYs 2023 to 2034. This baseline projection includes several steps. First, we compute average annual growth rate for each control by credential level from 2016 to 2022. These growth rates are presented in Table 6.2. We then apply these annual growth rates to the actual enrollment by program in 2022 to forecast enrollment in each program in 2023. This step is repeated for each year to get projected enrollment by program through 2034. We then compute average Pell, subsidized and unsubsidized direct loan, Grad PLUS, and Parent PLUS per enrollment by risk group, program performance group, and GE vs. non-GE for 2022. These averages are then adjusted according to the PB2024 loan volume and Pell grant baseline assumptions for the change in average loan by loan type and the change in average Pell grant. We then multiply the projected enrollment for each program by these average aid amounts to get projected total aid volume by program through 2034. Finally, we sum the enrollment and aid amounts across programs for each year to get enrollment and aid volume by program aggregate group, AYs 2023 to 2034, and shift the baseline Pell and loan volume from AYs 2023 to 2034 to FYs 2023 to 2033 for calculating budget cost estimates.

The most significant task is to generate projected enrollment, Pell volume, and loan volume for each of the program aggregate groups from 2023 to 2033 with the rule in place. We assume the first set of rates would be released in 2025 award year, so this is starting year for our projections. Projecting counterfactual enrollment and aid volumes involves several steps:

Step 1: Start with the enrollment by program aggregate group in 2025. In this first year there are no programs that are ineligible for Title IV, HEA funding.

Step 2: Apply the student transition assumptions to the enrollment by program aggregate group. This generates estimates of the enrollment that is expected to remain enrolled in the program aggregate group, the enrollment that is expected to drop out of postsecondary enrollment, and the enrollment that is expected to transfer to a different program aggregate group.

Step 3: Compute new estimated enrollment for the start of 2026 (before the second program performance is revealed) for each cell by adding the remaining enrollment to the enrollment that is expected to transfer into that group. We assume that (1) students transfer from failing or ineligible programs to passing programs in the same transfer group and GE program group; (2) Students in risk groups 3 (lower division 4-year), 4 (upper division 4-year college) or 5 (graduate) stay in those risk groups; (3) Students in risk group 1 can shift to risk groups 2 or 3; (4) Students in risk group 2 can shift to risk groups 1 or 3. Therefore, we permit enrollment to shift between proprietary and public or nonprofit certificate programs and from certificate and associate programs to lower—division bachelor's programs. We also allow enrollment to shift between GE and non-GE program, based on the assumptions listed in Table 6.6.

Step 4: Determine the change in aggregate baseline enrollment between 2025 and 2026 for each risk group and allocate these additional enrollments to each program aggregate group in proportion to the group enrollment computed in Step 3.

Step 5: Apply the program transition assumptions to the aggregate group enrollment from Step 4. This results in estimates of the enrollment that would stay within or shift from each performance category to another performance category in the next year. This mapping would differ for GE and non-GE programs and by risk group, as reported in Tables 6.3 and 6.4 above. For non-GE programs, every performance category can shift enrollment to every performance category. For GE programs, however, enrollment in each failure category would not remain in the same category because if a metric is failed twice, this enrollment would move to pre-ineligibility. The possible program transitions for GE programs are:

  • Pass → Pass, Fail D/E, Fail EP, Fail Both
  • Fail D/E → Pass, Fail EP, Pre-Ineligible
  • Fail EP → Pass, Fail D/E, Pre-Ineligible
  • Fail Both → Pass, Pre-Ineligible

S tep 6: Compute new estimated enrollment at end of 2026 (after program performance is revealed) for each program aggregate group by adding the number that stay in the same performance category plus the number that shift from other performance categories.

Step 7: Repeat steps 1 to 6 above using the end of 2026 enrollment by group as the starting point for 2027 and repeat through 2034. The only addition is that in Step 5, two more program transitions are possible for GE programs: Pre-Ineligible moves to Ineligible and Ineligible remains Ineligible.

Step 8: Generate projected Pell grant and loan volume by program aggregate group from AYs 2023 to 2034 under the rule. We multiply the projected enrollment by group by average aid amounts (Pell and loan volume) to get projected total aid amounts by group through 2034. Any enrollment that has dropped out (not enrolled in postsecondary) or in the ineligible category get zero Pell and loan amounts. Note that the average aid amounts by cell come from the PB projections, so are allowed to vary over time.

Step 9: Shift Pell grant and loan volume under the rule from AYs 2025 to 2034 to FYs 2025 to 2033 for calculating budget cost estimates.

A net savings for the title IV, HEA programs comes through four mechanisms. The primary source is from students who drop out of postsecondary education in the year after their program receives a failing D/E or EP rate or becomes ineligible. The second is for the smaller number of students who remain enrolled at a program that becomes ineligible for title IV, HEA program funds. Third, we assume a budget impact on the title IV, HEA programs from students who transfer from programs that are failing to better-performing programs because the typical aid levels differ between programs according to risk group and program performance. For instance, subsidized Direct Loan borrowing is 24 percent less ($2044 vs. $1547) for students at GE programs failing the D/E metric in risk group 1 than in passing programs in the same risk group in 2026.

Finally, consistent with the requirements of the Credit Reform Act of 1990, budget cost estimates for the title IV, HEA programs also reflect the estimated net present value of all future non-administrative Federal costs associated with a cohort of loans. To determine the estimated budget impact from reduced loan volume, the difference in yearly loan volumes between the baseline and policy scenarios were calculated as a percent of baseline scenario volumes. This generated an adjustment factor that was applied to loan volumes in the Student Loan Model (SLM) for each cohort, loan type, and risk group combination in the President's Budget for FY2024 (PB2024). The reduced loan volumes are also expected to result in some decrease in future consolidations which is also captured in the model run. Since the implied subsidy rate for each loan type differs by risk group, enrollment shifts to risk groups with greater expected repayment would generate a net budget savings. Since our analysis does not incorporate differences in subsidy rates between programs in the same risk group, such as between programs passing and failing the D/E or EP metrics, these estimates potentially understate the increase in expected repayment resulting from the regulations.

Methodology for Costs, Benefits, and Transfers

The estimated enrollment in each aggregate program group is used to quantify the costs, benefits, and transfers resulting from the regulations for each year from 2023 to 2033. As described in the Discussion of Costs, Benefits, and Transfers, we quantify an earnings gain for students from attending higher financial value programs and the additional tax revenue that comes from that additional earnings. We quantify the cost associated with additional instructional expenses to educate students who shift to different types of programs and the transfer of instructional expenses as students shift programs. We also estimate the transfer of title IV, HEA program funds from programs that lose students to programs that gain students.

Earnings Gain Benefit

A major goal of greater transparency and accountability is to shift students towards higher financial value programs—those with greater earnings potential, lower debt, or both. To quantify the earnings gain associated with the final rule, we estimate the aggregate annual earnings of would-be program graduates under the baseline and policy scenarios and take the difference. For each risk group and program performance group, we compute the enrollment-weighted average of median program earnings. Average earnings for programs that have become ineligible is assumed to be the average of median earnings for programs in the three failing categories, weighted by the enrollment share in these categories. This captures, for instance, that the earnings of 2-year programs that become ineligible are quite lower than those that enroll graduate students. Since we have simulated enrollment, but not completion, annual program enrollment is converted into annual program completions by applying a ratio that differs for 2-year programs or less, bachelor's degree programs, or graduate programs. Earnings for students that do not complete are not available and not included in our calculations. Students that drop out of failing programs (or decline to enroll altogether) are assumed to receive earnings equal to the median earnings of high school graduates in the State (the same measure used for the Earnings Threshold). Therefore, earnings could increase for this group if students reduce enrollment in programs leading to earnings less than a high school graduate. We estimate aggregate earnings by program group by multiplying enrollment by average earnings, reported in Table 6.7, and the completion ratio.

The ratios used are 11.5% for programs of 2-year or less, 16.5% for bachelor's programs, and 27.3% for graduate programs. These are the ratio between number of title IV, HEA completers in the two-year earnings cohort and the average title IV, HEA enrollment in the 2016 and 2017 Award Years.

Table 6.7—Average Program Earnings by Group

[$2019]

Pass Fall D/E Fail EP only Fail both Ineligible
GE Programs
Proprietary 2yr or less 39,233 28,672 20,414 18,531 21,308
Public/Nonprofit (NP) 2yr or less 37,274 30,234 20,188 20,630 20,254
Bachelor Lower 51,663 31,102 24,048 23,227 30,513
Bachelor Upper 51,663 31,102 24,048 23,227 30,513
Graduate 67,615 46,433 15,891 19,972 44,890
Non-GE Programs
Public/NP 2yr or less 36,492 29,522 23,642 19,388 N/A
Bachelor Lower 47,839 29,158 21,508 21,925 N/A
Bachelor Upper 47,839 29,158 21,508 21,925 N/A
Graduate 76,619 58,444 19,765 22,747 N/A

Students experience earnings gain each year they work following program completion. We compute the earnings benefit over the analysis window by giving 2026 completers 7 years of earnings gains, 2027 completers 6 years of earnings gains, and so on. The earnings gain of students that graduate during 2033 are only measured for one year. In reality program graduates would experience an earnings gain annually over their entire working career; our estimates likely understate the total likely earnings benefit of the policy.

However, our approach can overstate the earnings gain of students that shift programs if students experience a smaller earnings gain than the average difference between passing and failing programs within each GE-by-risk group in Table 6.7. To account for this, we apply an additional adjustment factor to the aggregate earnings difference to quantify how much of the earnings difference is accounted for by programs.

There is no consensus in the research literature on the magnitude of this parameter, with some studies finding very large impacts of specific programs or institutions on earnings and others finding smaller impacts. Unfortunately, many of these studies are set in specific contexts ( e.g. only public four-year universities in one State) and most look at institutions overall rather than programs, which may not extrapolate to our setting given the large outcome variation across programs in the same institution.

Hoekstra, Mark (2009). The Effect of Attending the Flagship State University on Earnings: A Discontinuity-Based Approach. Review of Economics and Statistics, 91 (4): 717–724. Hoxby, C.M. (2019). The Productivity of US Postsecondary Institutions. In Productivity in Higher Education, Hoxby, C.M. & K.M. Stange, K.M. (eds.). University of Chicago Press: Chicago. Andrews, R.J. & Stange, K.M. (2019). Price Regulation, Price Discrimination, and Equality of Opportunity in Higher Education: Evidence from Texas. American Economic Journal: Economic Policy, 11.4, 31–65. Andrews, Rodney, Imberman, Scott, Lovenheim, Michael & Stange, Kevin (Aug. 2022). The Returns to College Major Choice: Average and Distributional Effects, Career Trajectories, and Earnings Variability. NBER Working Paper 30331.

Mountjoy, Jack & Hickman, Brent (Sept. 2021). The Returns to College(s): Relative Value-Added and Match Effects in Higher Education. NBER Working Paper 29276.

To select the value used for this adjustment factor, we compared the average earnings difference between passing and failing programs (conditional on credential level) before versus after controlling for the rich demographic characteristics described in “Student Demographic Analysis” (specifically, the share of students in each race/ethnic category, the share of students that are male, independent, first-generation, and a Pell grant recipient, and the average family income of students). Based on this analysis, our primary estimates adjust the raw earnings difference in Table 6.7 down using an adjustment factor of 75 percent. Given the uncertainty around the proper adjustment factor to use, we include a range of values in the sensitivity analysis.

Note that both the “raw” and fully controlled regressions include indicators for credential level, as enrollment is not permitted to move across credential levels in our budget simulations other than modest shift from 2-year programs to lower-division four-year programs.

In the analysis of alternative options above, we showed the expected change in earnings for students that transfer from failing programs for each credential-level by 2-digit CIP code. Across all credential levels, students that shift from failing GE programs were expected to increase annual earnings by about 43 percent and those transferring from failing non-GE programs were expected to increase annual earnings by about 21 percent. These estimates are in line with those from Table 6.7 and used in the benefit impact.

Fiscal Externality Benefit

The increased earnings of program graduates would generate additional Federal and State tax revenue and reductions in transfer program expenditure. To the earnings gain, we multiply an average marginal tax and transfer rate of 18.6 percent to estimate the fiscal benefit. This rate was computed in Hendren and Sprung-Keyser (2020) specifically to estimate the fiscal externality of earnings gains stemming from improvement in college quality, so it is appropriate for use in our setting. The rate is derived from 2016 CBO estimates and includes Federal and State income taxes and transfers from the Supplemental Nutrition Assistance Program (SNAP) but excludes payroll taxes, housing vouchers, and other safety-net programs. Note that this benefit is not included in our budget impact estimates.

Hendren, Nathaniel & Sprung-Keyser, Ben (2020). A Unified Welfare Analysis of Government Policies. Quarterly Journal of Economics 135 (3): 1209–1318.

Instructional Spending Cost and Transfer

To determine the additional cost of educating students that shift from one type of program to another or the cost savings from students who chose not to enroll, we estimate the aggregate annual instructional spending under the baseline and policy scenarios and take the difference. We used the instructional expense per FTE enrollee data from IPEDS to calculate the enrollment-weighted average institutional-level instructional expense per FTE student for programs by risk group and performance result, separately for GE programs and non-GE programs. Average spending for programs that have become ineligible is assumed to be the average of the three failing categories, weighted by the enrollment share in these categories. These estimates are reported in Table 6.8. We estimate aggregate spending by program group by multiplying enrollment from 2023 through 2033 by average spending.

Table 6.8—Average Instructional Cost per FTE by Group

Pass Fall D/E Fail EP only Fail both Ineligible
GE Programs:
Proprietary 2yr or less 4,341 3,007 4,442 3,990 4,106
Public/NP 2yr or less 7,325 5,859 4,984 3,688 4,873
Bachelor Lower 3,668 2,655 3,047 3,644 2,728
Bachelor Upper 3,668 2,655 3,047 3,644 2,728
Graduate 5,294 3,837 1,837 5,151 3,910
Non-GE Programs:
Public/NP 2yr or less 6,408 5,187 5,959 4,361 N/A
Bachelor Lower 11,263 7,563 9,036 12,021 N/A
Bachelor Upper 11,263 7,563 9,036 12,021 N/A
Graduate 15,666 16,434 7,528 24,355 N/A

Note that since we are using institution-level rather than program-level spending, this will not fully capture spending differences between undergraduate and graduate enrollment, between upper and lower division, and across field of study.

This may cause our estimates to slightly understate the instructional cost impact since failing programs are disproportionately in lower-earning fields and lower credential levels, which tend to have lower instructional costs. Though we anticipate most movement will be within field and credential level, which would mute this effect. See Hemelt, Steven W., Stange, Kevin M., Furquim, Fernando, Simon, Andrew & Sawyer, John E. (2021). Why Is Math Cheaper than English? Understanding Cost Differences in Higher Education. Journal of Labor Economics, vol. 39(2), pages 397–435.

To calculate the transfer of instructional expenses from failing to passing programs, we multiply the average instructional expense per enrollee shown in Table 6.7 by the estimated number of annual student transfers for 2023 to 2033 from each risk group and failing category.

Student Aid Transfers

To calculate the amounts of student aid that could transfer with students each year, we multiply the estimated number of students receiving title IV, HEA program funds transferring from ineligible or failing GE and non-GE programs to passing programs in each risk category each year by the average Pell grant, Stafford subsidized loan, unsubsidized loan, PLUS loan, and GRAD PLUS loan per enrollment in the same categories.

To annualize the amount of benefits, costs, and title IV, HEA program fund transfers from 2023 to 2033, we calculate the net present value (NPV) of the yearly amounts using a discount rate of 3 percent and a discount rate of 7 percent and annualize it over 10 years.

7. Net Budget Impacts

These final regulations are estimated to have a net Federal budget impact of $−13.8 billion, consisting of $−7.4 billion in reduced Pell grants and $−6.4 billion for loan cohorts 2024 to 2033. A cohort reflects all loans originated in a given fiscal year. Consistent with the requirements of the Credit Reform Act of 1990, budget cost estimates for the student loan programs reflect the estimated net present value of all future non-administrative Federal costs associated with a cohort of loans. The baseline for estimating the cost of these final regulations is the President's Budget for 2024 (PB2024) as modified for the finalization of the SAVE plan included in the final rule published July 10, 2023. This estimated net budget impact addresses the GE and Financial Transparency provisions, as described below. The provisions related to Financial Responsibility, Administrative Capability, Certification Procedures, and Ability to Benefit that were included in the NPRM published on May 19, 2023, will be addressed in a forthcoming separate document.

Since the policy is not estimated to shift enrollment until AY 2026 (which includes part of FY 2025), we present enrollment and budget impacts starting in 2025. Impacts in both AY and FY 2024 are zero.

88 FR 43820 (July 10, 2023).

Gainful Employment and Financial Transparency

The final regulations are estimated to shift enrollment towards programs with lower debt-to-earnings or higher median earnings or both, and away from programs that fail either of the two performance metrics. The vast majority of students are assumed to resume their education at the same or another program in the event they are warned about poor program performance or if their program loses eligibility. The final regulations are also estimated to reduce overall enrollment, as some students decide to not enroll. Table 7.1 summarize the main enrollment results for non-GE programs. Enrollment in non-GE programs is expected to increase by about 0.6 percent relative to baseline over the budget period. There is a modest enrollment shift towards programs that pass both metrics, with a particularly large (proportionate) reduction in the share of enrollment in programs that fail D/E. By the end of the analysis window, 96.0 percent of enrollment is expected to be in passing programs.

Table 7.1—Primary Enrollment Estimate

[Non-GE programs]

2025 2026 2027 2028 2029 2030 2031 2032 2033
Total Aggregate Enrollment (millions)
Baseline 14.12 13.97 13.84 13.71 13.59 13.47 13.36 13.26 13.17
Policy 14.12 14.01 13.89 13.78 13.66 13.54 13.43 13.33 13.22
Percent of Enrollment by Program Performance
Pass:
Baseline 95.9 96.0 96.0 96.1 96.1 96.1 96.2 96.2 96.2
Policy 95.9 95.7 96.1 96.3 96.5 96.5 96.6 96.6 96.7
Fail D/E:
Baseline 1.5 1.5 1.5 1.5 1.6 1.6 1.6 1.6 1.6
Policy 1.5 1.6 1.4 1.3 1.3 1.2 1.2 1.3 1.3
Fail EP:
Baseline 2.0 2.0 1.9 1.9 1.9 1.8 1.8 1.7 1.7
Policy 2.0 2.2 2.1 2.0 1.9 1.9 1.8 1.8 1.7
Fail Both:
Baseline 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5
Policy 0.5 0.5 0.5 0.4 0.4 0.4 0.4 0.3 0.3

Table 7.2 reports comparable estimates for GE programs. Note that for GE programs we estimate enrollment in two additional categories: Pre-Ineligible, i.e., programs that would be ineligible for title IV, HEA aid the following year; and Ineligible. Enrollment in GE programs is projected to decline by 9 percent relative to baseline, with the largest marginal decline in the first-year programs become ineligible. There is a large enrollment shift towards programs that pass both metrics, with a particularly large reduction in the share of enrollment in programs that fail EP. By the end of the analysis window, 95.0 percent of enrollment is expected to be in passing programs, compared to 71.8 percent in the baseline scenario.

Table 7.2—Primary Enrollment Estimate

[GE programs]

2025 2026 2027 2028 2029 2030 2031 2032 2033
Total Aggregate Enrollment (millions)
Baseline 2.63 2.61 2.60 2.60 2.59 2.59 2.59 2.59 2.60
Policy 2.63 2.47 2.43 2.43 2.42 2.41 2.39 2.37 2.34
Percent of Enrollment by Program Performance
Pass:
Baseline 76.2 75.7 75.3 74.8 74.3 73.8 73.3 72.8 72.3
Policy 76.2 85.1 91.5 93.5 94.3 94.6 94.8 94.8 94.9
Fail D/E:
Baseline 6.5 6.4 6.3 6.2 6.0 5.9 5.8 5.6 5.5
Policy 6.5 2.7 1.5 1.6 1.6 1.6 1.6 1.6 1.6
Fail EP:
Baseline 13.9 14.4 14.9 15.5 16.0 16.6 17.2 17.8 18.4
Policy 13.9 1.9 1.2 1.3 1.3 1.4 1.4 1.4 1.4
Fail Both:
Baseline 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.
Policy 0.5 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2
Pre-Inelig:
Baseline 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Policy 0.0 9.9 3.3 1.6 1.3 1.3 1.3 1.3 1.3
Inelig:
Baseline 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Policy 0.0 2.2 1.8 1.2 0.9 0.7 0.7 0.6 0.0

For non-GE programs, these shifts occur primarily across programs that have different performance in the same loan risk category, with a very modest shift from public and nonprofit two-year and less programs to lower-division 4-year programs. This is shown in Table 7.3. Shifts away from the public and nonprofit two-year sector within non-GE programs is partially offset from shifts into these programs from failing GE programs. Recall that in “Transfer Causes Net Enrollment Increase in Some Sectors” above we showed that the vast majority of community colleges would gain enrollment from the regulations.

Table 7.3—Primary Enrollment Estimates by Risk Group

[Non-GE programs]

2025 2026 2027 2028 2029 2030 2031 2032 2033
Projected Total Enrollment by Loan Risk Category (Millions)
Public/NP 2-year & below:
Baseline 3.02 2.91 2.80 2.70 2.61 2.51 2.42 2.34 2.25
Policy 3.02 2.92 2.82 2.72 2.62 2.53 2.44 2.35 2.26
4-year (lower):
Baseline 6.10 6.03 5.96 5.90 5.83 5.77 5.71 5.65 5.59
Policy 6.10 6.04 5.99 5.93 5.87 5.82 5.76 5.70 5.64
4-year (upper):
Baseline 2.57 2.55 2.54 2.52 2.50 2.49 2.47 2.45 2.44
Policy 2.57 2.55 2.54 2.53 2.51 2.49 2.48 2.46 2.45
Graduate:
Baseline 2.43 2.48 2.53 2.59 2.64 2.70 2.76 2.82 2.88
Policy 2.43 2.49 2.54 2.59 2.65 2.70 2.76 2.82 2.87
Percent of Enrollment by Loan Risk Category
Public/NP 2-year & below:
Baseline 21.38 20.82 20.27 19.73 19.19 18.66 18.14 17.62 17.11
Policy 21.38 20.87 20.32 19.77 19.22 18.67 18.13 17.61 17.09
4-year (lower):
Baseline 43.19 43.14 43.09 43.02 42.94 42.84 42.73 42.62 42.48
Policy 43.19 43.13 43.10 43.06 43.01 42.95 42.87 42.77 42.66
4-year (upper):
Baseline 18.20 18.26 18.33 18.38 18.42 18.45 18.48 18.50 18.51
Policy 18.20 18.24 18.29 18.33 18.38 18.42 18.46 18.49 18.51
Graduate:
Baseline 17.23 17.77 18.32 18.88 19.46 20.05 20.65 21.26 21.89
Policy 17.23 17.61 17.50 17.64 17.73 17.76 17.76 17.75 17.72

Table 7.4—reports a similar breakdown for GE programs. Shifts to passing programs are accompanied by a shift away from proprietary two-year and below programs and towards public and nonprofit programs of similar length, along with a more modest shift towards lower-division 4-year programs.

Table 7.4—Primary Enrollment Estimates by Risk Group

[GE programs]

2025 2026 2027 2028 2029 2030 2031 2032 2033
Projected Total Enrollment by Loan Risk Category (Millions)
Prop. 2-year & below:
Baseline 0.72 0.75 0.77 0.80 0.83 0.86 0.89 0.92 0.95
Policy 0.72 0.62 0.59 0.59 0.60 0.60 0.61 0.61 0.61
Public/NP 2-year & below:
Baseline 0.53 0.52 0.51 0.49 0.48 0.46 0.45 0.44 0.43
Policy 0.53 0.55 0.56 0.57 0.57 0.56 0.56 0.55 0.55
4-year (lower):
Baseline 0.78 0.77 0.75 0.74 0.73 0.71 0.70 0.69 0.68
Policy 0.78 0.74 0.73 0.72 0.72 0.70 0.69 0.68 0.67
4-year (upper):
Baseline 0.20 0.20 0.19 0.19 0.18 0.18 0.17 0.17 0.17
Policy 0.20 0.19 0.18 0.18 0.17 0.17 0.16 0.16 0.15
Graduate:
Baseline 0.38 0.38 0.38 0.38 0.38 0.37 0.37 0.37 0.37
Policy 0.38 0.37 0.37 0.37 0.37 0.37 0.36 0.36 0.36
Percent of Enrollment by Loan Risk Category
Prop. 2-year & below:
Baseline 27.52 28.58 29.65 30.77 31.91 33.05 34.22 35.41 36.63
Policy 27.52 25.12 24.33 24.40 24.69 25.03 25.40 25.77 26.14
Public/NP 2-year & below:
Baseline 20.36 19.88 19.44 18.94 18.44 17.96 17.47 16.97 16.44
Policy 20.36 22.18 23.06 23.36 23.45 23.46 23.44 23.40 23.35
4-year (lower):
Baseline 29.76 29.33 28.90 28.48 28.05 27.62 27.18 26.76 26.33
Policy 29.76 29.99 29.98 29.79 29.54 29.28 29.01 28.74 28.47
4-year (upper):
Baseline 7.79 7.62 7.44 7.27 7.09 6.91 6.73 6.55 6.37
Policy 7.79 7.73 7.55 7.36 7.18 7.01 6.86 6.71 6.56
Graduate:
Baseline 14.58 14.59 14.57 14.55 14.51 14.46 14.39 14.32 14.23
Policy 14.58 14.99 15.08 15.09 15.14 15.21 15.30 15.39 15.48

As reported in Tables 7.5 and 7.6, we estimate that the regulations would result in a reduction of title IV, HEA aid between fiscal years 2025 and 2033.

Table 7.5—Estimated Annual Change in Title IV, HEA Aid Volume Relative to Baseline

[millions, $2019]

2025 2026 2027 2028 2029 2030 2031 2032 2033 Total
Non-GE Programs:
Pell 25 57 89 101 108 116 118 116 110 840
Subs. 9 16 11 8 8 10 10 9 9 92
Unsub. 18 10 (45) (90) (120) (143) (164) (185) (209) (928)
Grad PLUS 4 (25) (91) (147) (183) (205) (221) (235) (248) (1,353)
Par. PLUS 7 30 52 61 65 68 67 66 64 480
GE Programs:
Pell (199) (511) (808) (936) (983) (1,050) (1,138) (1,247) (1,376) (8,248)
Subs. (149) (380) (472) (486) (501) (529) (565) (606) (653) (4,340)
Unsub. (226) (576) (707) (717) (732) (765) (809) (861) (921) (6,313)
Grad PLUS (20) (51) (63) (62) (60) (58) (56) (55) (55) (479)
Par. PLUS (18) (48) (59) (59) (64) (74) (86) (101) (117) (625)
Total:
Pell (174) (455) (719) (835) (875) (934) (1,020) (1,131) (1,266) (7,409)
Subs. (139) (364) (461) (477) (493) (519) (555) (597) (644) (4,248)
Unsub. (208) (566) (752) (807) (852) (908) (973) (1,046) (1,130) (7,241)
Grad PLUS (16) (77) (154) (209) (242) (263) (278) (290) (303) (1,832)
Par. PLUS (11) (18) (7) 2 1 (6) (19) (35) (53) (145)

Table 7.6—Estimated Annual Percent Change in Title IV, HEA Aid Volume by Fiscal Year

(%)

2025 2026 2027 2028 2029 2030 2031 2032 2033 Total
Non-GE Programs:
Pell 0.25 0.32 0.35 0.37 0.39 0.40 0.37 0.36 0.33 0.35
Subs. 0.09 0.15 0.11 0.08 0.08 0.10 0.10 0.09 0.09 0.10
Unsub. 0.08 0.04 −0.20 −0.40 −0.53 −0.63 −0.72 −0.81 −0.90 −0.46
Grad PLUS 0.07 −0.47 −1.62 −2.48 −2.95 −3.24 −3.42 −3.56 −3.68 −2.48
Par. PLUS 0.08 0.33 0.56 0.66 0.70 0.73 0.73 0.73 0.72 0.58
GE Programs:
Pell −9.46 −14.53 −14.66 −14.58 −15.06 −15.91 −16.97 −18.18 −19.54 −15.44
Subs. −5.36 −13.71 −17.00 −17.43 −17.91 −18.81 −19.97 −21.30 −22.76 −17.18
Unsub. −4.49 −11.47 −14.12 −14.32 −14.56 −15.16 −15.98 −16.95 −18.04 −13.91
Grad PLUS −2.83 −7.12 −8.59 −8.27 −7.84 −7.57 −7.40 −7.30 −7.25 −7.16
Par. PLUS −2.54 −6.62 −7.90 −7.67 −8.16 −9.26 −10.70 −12.35 −14.14 −8.97
Total:
Pell −1.46 −2.32 −2.36 −2.37 −2.48 −2.68 −2.95 −3.24 −3.61 −2.59
Subs. −1.03 −2.71 −3.46 −3.61 −3.75 −3.97 −4.28 −4.63 −5.03 −3.59
Unsub. −0.77 −2.08 −2.76 −2.95 −3.09 −3.27 −3.48 −3.72 −3.99 −2.91
Grad PLUS −0.28 −1.25 −2.42 −3.12 −3.49 −3.70 −3.84 −3.94 −4.04 −2.99
Par. PLUS −0.11 −0.18 −0.07 0.02 0.01 −0.06 −0.19 −0.35 −0.53 −0.16

Table 7.7 reports the annual net budget impact after accounting for estimated loan repayment. We estimate a net Federal budget impact of $−13.8 billion, consisting of $−7.4 billion in reduced Pell grants and $−6.4 billion for loan cohorts 2024 to 2033.

Table 7.7—Estimated Annual Net Budget Impact

[Outlays in millions]

2025 2026 2027 2028 2029 2030 2031 2032 2033 Total
Pell −174 −455 −719 −835 −875 −934 −1,020 −1,131 −1,266 −7,409
Subs. −39 −114 −153 −158 −158 −160 −166 −172 −181 −1,302
Unsub. −48 −149 −218 −237 −246 −255 −268 −281 −300 −2,003
PLUS (Par & Grad) −2 −22 −53 −79 −90 −98 −102 −104 −106 −656
Consol −12 −36 −80 −145 −229 −323 −431 −537 −641 −2,435
Total −275 −776 −1,223 −1,454 −1,598 −1,770 −1,987 −2,225 −2,494 −13,805

The Department's calculations of the net budget impacts represent our best estimate of the effect of the regulations on the Federal student aid programs. As noted in the NPRM published June, realized budget impacts will be heavily influenced by actual program performance, student response to program performance, student borrowing and repayment behavior, and changes in enrollment because of the regulations. For example, if students, including prospective students, react more strongly to the warnings, acknowledgment requirement, or potential ineligibility of programs than anticipated and, if many of these students leave postsecondary education, the impact on Pell grants and loans could increase. Similarly, if institutions react to the regulations by improving performance, the assumed enrollment and aid amounts could be overstated, though this would be very beneficial to students. Finally, if students' repayment behavior is different than that assumed in the model, the realized budget impact could be larger or smaller than our estimate.

8. Accounting Statement

As required by OMB Circular A–4, we have prepared an accounting statement showing the classification of the benefits, costs, and transfers associated with the provisions of these regulations.

Primary Estimates

We estimate that by shifting enrollment to higher financial-value programs, the regulations would increase student's earnings, resulting in net after-tax gains to students and benefits for taxpayers in the form of additional tax revenue. Table 8.1 reports the estimated aggregate earnings gain for each cohort of completers, separately for GE and non-GE programs, and the cumulative (not discounted) earnings gain over the budget window. The regulation is estimated to generate $32.3 billion of additional earnings gains over the budget window, both from GE and non-GE programs. Using the approach described in “Methodology for Costs, Benefits, and Transfers,” we expect $26.3 billion to benefit students and $6.0 billion to benefit Federal and State governments and taxpayers.

The earnings gains estimate in the NPRM did not include earnings gains over the full budget window, thereby underestimating that gain. For this final RIA, we recalculated earnings gains to account for this more comprehensive budget impact, which resulted in an increase in estimated earnings gains relative to the NPRM.

Table 8.1—Annual and Cumulative Earnings Gain and Distribution Between Students and Government

[Millions, $2019]

2025 2026 2027 2028 2029 2030 2031 2032 2033 Total
Single-year Earnings Gains of Each Cohort of Completers
Non-GE 0 139 411 542 598 596 566 497 421 3,770
GE 0 232 470 570 590 561 510 447 376 3,755
Total 0 370 881 1,112 1,189 1,157 1,075 944 797 7,525
Cumulative Earnings Gain
Cumulative gain 0 370 1,251 2,363 3,551 4,708 5,783 6,728 7,525 32,280
Student share 0 302 1,019 1,923 2,891 3,832 4,708 5,476 6,125 26,276
Gov't share 0 69 233 440 661 876 1,076 1,251 1,400 6,004

The final rule could also alter aggregate instructional spending, by shifting enrollment to higher-cost institutions (an increase in spending) or by reducing aggregate enrollment (a decrease in spending). Table 8.2 reports estimated annual and cumulative changes in instructional spending, overall and separately for GE and non-GE programs. The net effect is an increase in aggregate cumulative instructional spending of $2.7 billion (not discounted), though this masks differences between non-GE programs (net increase in spending) and GE programs (net decrease in spending). Spending is reduced in the first year of the policy due to the decrease in enrollment, but then increases as more students transfer to more costly programs.

Table 8.2—Instructional Spending Change

[Millions, $2019]

2025 2026 2027 2028 2029 2030 2031 2032 2033 Total
Non-GE 0 381 685 836 904 909 883 800 719 6,118
GE 0 −536 −456 −336 −301 −333 −399 −481 −576 −3,417
Total 0 −155 230 500 603 576 485 319 143 2,701

The rule would create transfers between students, the Federal Government, and among postsecondary institutions by shifting enrollment between programs, removing title IV, HEA eligibility for GE programs that fail a GE metric multiple times, and causing some students to choose non-enrollment instead of a low value program. Table 8.3 reports the number of enrolments that transfer programs, remain enrolled at ineligible programs, or decline to enroll in postsecondary education altogether. We estimate that almost 1.5 million enrollments would transfer from low financial value programs to better programs over the decade. A more modest number would remain enrolled at programs that are no longer eligible for title IV, HEA aid.

Table 8.3—Estimated Enrollment of Transfers and Ineligible Under the Regulation

2025 2026 2027 2028 2029 2030 2031 2032 2033 Total
Non-GE:
Transfer 0 33,481 96,886 81,495 72,531 67,660 64,896 63,184 62,009 542,142
Inelig 0 0 0 0 0 0 0 0 0 0
GE:
Transfer 0 204,541 195,213 132,844 96,996 79,268 70,668 66,360 64,057 909,948
Inelig 0 0 53,244 43,729 30,098 22,035 17,816 15,631 14,466 197,019
Total:
Transfer 0 238,022 292,099 214,339 169,527 146,928 135,565 129,544 126,066 1,452,089
Inelig 0 0 53,244 43,729 30,098 22,035 17,816 15,631 14,466 197,019

The resulting reductions in expenditures on title IV, HEA program funds from enrollment declines and continued enrollment at non-eligible institutions are classified as transfers from affected student loan borrowers and Pell grant recipients to the Federal Government. The combined reduction in title IV, HEA expenditures was presented in the Net Budget Impacts section above. Transfers also include title IV, HEA program funds that follow students as they shift from low-performing programs to higher-performing programs, which is presented in Table 8.4.

Table 8.4—Estimated Title IV, HEA Aid Transferred From Failing to Passing Programs Under the Regulation

[$2019, millions]

2025 2026 2027 2028 2029 2030 2031 2032 2033 Total
Non-GE 0 145 458 388 351 330 318 311 307 2,608
GE 0 1,109 1,057 720 530 434 387 362 349 4,948
Total 0 1,255 1,515 1,108 880 764 705 674 656 7,557

Transfers are neither costs nor benefits, but rather the reallocation of resources from one party to another. Table 8.5 provides our best estimate of the changes in annual monetized benefits, costs, and transfers as a result of these regulations. Our baseline estimate with a discount rate of 3 percent is that the regulation would generate $3.0 billion of annualized benefits against $0.4 billion of annualized costs and $1.3 billion of transfers to the Federal Government and $0.7 billion transfers from failing programs to passing programs. A discount rate of 7 percent results in $2.7 billion of benefits against $0.4 billion of annualized costs and $1.2 billion of transfers to the Federal Government and $0.7 billion transfers from failing programs to passing programs. Note that the accounting statement does not include benefits that are unquantified, such as benefits for students associated with lower default and better credit and benefits for institutions from improved information about their value.

Table 8.5—Accounting Statement for Primary Scenario

Annualized Impact (millions, $2023)
Discount rate = 3% Discount rate = 7%
Benefits
Earnings gain (net of taxes) for students 2,444 2,213
Additional Federal and State tax revenue and reductions in transfer program expenditure (not included in budget impact) 559 506
For students, lower default, better credit leading to family and business formation, more retirement savings. For institutions, increased enrollment and revenue associated with new enrollments from improved information about value Not quantified.
Costs
Reduced instructional spending 258 241
Additional reporting by institutions 90 93
Warning/acknowledgment by institutions and students 12 12
Implementation of reporting, website, acknowledgment by ED 4 4
Time/moving cost for transfers; Investments to improve program quality Not quantified.
Transfers
Transfer of Federal Pell dollars to Federal Government from enrollment reduction 709 667
Transfer of Federal loan dollars to Federal Government from reduced borrowing and greater repayment 607 564
Transfer of aid dollars from non-passing programs to passing programs 747 732
Transfer of State aid dollars from failing programs for dropouts Not quantified.

Sensitivity Analysis

We conducted the simulations of the rule while varying several key assumptions. Specifically, we provide estimates of the change in title IV, HEA volumes using varied assumptions about student transitions, student dropout, program performance, and the earnings gains associated with enrollment shifts. We believe these to be the main sources of uncertainty in our model.

Varying Levels of Student Transition

Our primary analysis assumes rates of transfer and dropout for GE programs based on the research literature, but these quantities are uncertain. The alternative models adjust transfer and dropout rates for all transfer groups to the rates for high alternatives and few alternatives, respectively, as shown in Table 6.5. As reported in Tables 8.6 and 8.7, we estimate that the regulations would result in a reduction of title IV, HEA aid between fiscal years 2025 and 2033, regardless of if all students have the highest or lowest amount of transfer alternatives.

Table 8.6—High Transfer Sensitivity Analysis—Estimated Annual Change in Title IV, HEA Aid Volume Relative to Baseline

[Millions, $2019]

2025 2026 2027 2028 2029 2030 2031 2032 2033 Total
Non-GE Programs:
Pell 29 63 94 101 105 108 107 104 97 808
Subs. 10 18 12 7 5 5 4 3 1 66
Unsub. 20 3 (67) (119) (152) (176) (198) (220) (244) (1,153)
Grad PLUS 4 (37) (121) (184) (223) (247) (263) (277) (290) (1,639)
Par. PLUS 8 32 53 61 65 68 68 68 67 491
GE Programs:
Pell (195) (484) (754) (867) (920) (999) (1,097) (1,213) (1,348) (7,877)
Subs. (149) (368) (446) (460) (481) (514) (553) (597) (645) (4,214)
Unsub. (226) (558) (669) (679) (701) (741) (790) (845) (906) (6,115)
Grad PLUS (21) (52) (61) (59) (57) (55) (54) (53) (52) (464)
Par. PLUS (15) (40) (48) (49) (56) (68) (82) (97) (114) (568)
Total
Pell (166) (419) (659) (766) (817) (891) (990) (1,110) (1,251) (7,069)
Subs. (138) (350) (434) (453) (474) (506) (545) (589) (638) (4,127)
Unsub. (206) (555) (736) (798) (854) (917) (988) (1,064) (1,150) (7,268)
Grad PLUS (17) (89) (182) (244) (281) (302) (317) (329) (342) (2,103)
Par. PLUS (7) (8) 5 12 9 0 (13) (29) (47) (77)

Table 8.7—Low Transfer Sensitivity Analysis—Estimated Annual Change in Title IV, HEA Aid Volume Relative to Baseline

[Millions, $2019]

2025 2026 2027 2028 2029 2030 2031 2032 2033 Total
Non-GE Programs:
Pell 16 43 73 95 113 129 137 142 142 890
Subs. 6 12 12 12 14 17 17 17 16 123
Unsub. 11 28 22 6 (6) (16) (29) (44) (62) (91)
Grad PLUS 2 7 (3) (24) (39) (49) (57) (64) (72) (300)
Par. PLUS 5 26 49 61 67 70 70 68 66 482
GE Programs:
Pell (187) (550) (921) (1,126) (1,184) (1,236) (1,302) (1,395) (1,513) (9,414)
Subs. (136) (399) (546) (570) (578) (595) (622) (657) (699) (4,803)
Unsub. (208) (607) (825) (851) (856) (874) (904) (948) (1,001) (7,074)
Grad PLUS (19) (54) (74) (75) (72) (69) (67) (66) (65) (561)
Par. PLUS (20) (62) (87) (89) (91) (98) (107) (120) (134) (808)
Total:
Pell (170) (508) (848) (1,030) (1,070) (1,106) (1,164) (1,253) (1,371) (8,520)
Subs. (131) (386) (534) (557) (564) (579) (605) (640) (683) (4,680)
Unsub. (197) (579) (803) (846) (862) (890) (934) (992) (1,063) (7,165)
Grad PLUS (16) (47) (77) (99) (111) (118) (124) (130) (137) (860)
Par. PLUS (15) (37) (37) (28) (24) (28) (37) (52) (69) (326)

No Program Improvement

Our primary analysis assumes that both non-GE and GE programs improve performance after failing either the D/E or EP metric and that GE programs that pass both metrics still improve performance in response to the rule. We incorporate this by increasing the fail to pass program transition rate by 5 percentage points for each type of program failure after 2026 for GE and non-GE programs, by reducing the rate of repeated failure by 5 percentage points for GE and non-GE programs, and by increasing the rate of a repeated passing result by two and a half percentage points for GE programs. The alternative model will assume no program improvement in response to failing metrics.

As reported in Table 8.8, we estimate that the regulations would result in a reduction of title IV, HEA aid between fiscal years 2025 and 2033, regardless of if programs show improvement.

Table 8.8—No Program Improvement Sensitivity Analysis—Estimated Annual Change in Title IV, HEA Aid Volume Relative to Baseline

[Millions, $2019]

2025 2026 2027 2028 2029 2030 2031 2032 2033 Total
Non-GE Programs:
Pell 25 57 94 118 142 165 183 197 207 1,188
Subs. 9 16 14 17 21 27 31 34 37 206
Unsub. 18 10 (31) (53) (67) (76) (85) (96) (109) (489)
Grad PLUS 4 (25) (79) (114) (138) (153) (164) (173) (182) (1,026)
Par. PLUS 7 30 54 68 78 85 89 92 93 597
GE Programs:
Pell (199) (511) (815) (962) (1,039) (1,137) (1,252) (1,387) (1,541) (8,843)
Subs. (149) (380) (477) (502) (532) (571) (617) (668) (723) (4,618)
Unsub. (226) (576) (716) (750) (792) (847) (910) (980) (1,056) (6,853)
Grad PLUS (20) (51) (64) (68) (70) (72) (74) (76) (79) (575)
Par. PLUS (18) (48) (62) (69) (79) (94) (110) (128) (147) (755)
Total:
Pell (174) (455) (721) (846) (898) (973) (1,069) (1,190) (1,334) (7,660)
Subs. (139) (364) (462) (485) (510) (544) (586) (634) (686) (4,411)
Unsub. (208) (566) (747) (803) (858) (923) (996) (1,076) (1,165) (7,342)
Grad PLUS (16) (77) (143) (182) (209) (226) (238) (250) (261) (1,602)
Par. PLUS (11) (18) (8) (0) (1) (8) (21) (36) (54) (157)

Alternative Earnings Gain

Our primary analysis assumes that the earnings change associated with shifts in enrollment is equal to the difference in average earnings between groups defined by loan risk group, program performance category, and whether the program is a GE program or not, multiplied by an adjustment factor equal to 0.75. This adjustment factor was derived from regression models where we compared the earnings difference between passing and failing programs conditional on credential level with and without a rich set of student characteristics controls. The estimated earnings gain associated with the rule scales directly with the value of this adjustment factor. A value of 1.0 (all of the difference in average earnings between groups would manifest as earnings gain) would increase the total annualized earnings gain for students from $2.4 billion up to $3.3 billion (3 percent discount rate).

A value of 0.40 reduces it to $1.3 billion; a value of 0.20 reduces it to $0.7 billion. The net fiscal externality increases or decreases proportionately. Each of these two scenarios would involve more of the raw earnings difference between passing and failing programs of the same credential level being explained by factors we are not able to measure (such as student academic preparation) than those that we are able to measure (such as race, gender, parent education, family income, and Pell receipt). Even at these low values for the adjustment factor, the estimated earnings benefits of the rule by themselves outweigh the estimated costs.

In unpublished analysis of approximately 600 programs (defined by 2-digit CIP by institution) at four-year public colleges in Texas as part of their published work, Andrews & Stange (2019) find that a 1 percent increase in log program earnings (unadjusted) is associated with a .72 percent increase in log program earnings after controlling for student race/ethnicity, limited English proficiency, economic disadvantage, and achievement test scores. Additionally controlling for students' college application and admissions behavior reduces this to 0.62. Using the correlation of institution-level average earnings and value-added in Figure 2.1 of Hoxby (2018), we estimate that an earnings gain of $10,000 is associated with a value added gain of roughly $6,000 over the entire sample, of roughly $4,000 for scores below 1200, and of roughly $2,000 for scores below 1000. These relationships imply parameter values of 0.72, 0.62, 0.60, 0.40, and 0.20, respectively. Again, institution-level correlations may not be directly comparable to program-level data.

9. Distributional Consequences

The final regulations advance distributional equity aims because the benefits of the regulation—better information, increased earnings, and more manageable debt repayment—would disproportionately be realized by students who otherwise would have low earnings. Students without access to good information about program performance tend to be more disadvantaged; improved transparency about program performance would be particularly valuable to these students. The final regulations improve program quality in the undergraduate certificate sector in particular, which, as documented above, disproportionately enrolls low-income students. Students already attending high-quality colleges, who tend to be more advantaged, would be relatively unaffected by the regulation. The major costs of the program involve additional paperwork and instructional spending, which are not incurred by students directly.

10. Alternatives Considered

As part of the development of these regulations, the Department engaged in a negotiated rulemaking process in which we received comments and proposals from non-Federal negotiators representing numerous impacted constituencies. These included higher education institutions, consumer advocates, students, financial aid administrators, accrediting agencies, and States. Non-Federal negotiators submitted a variety of proposals relating to the issues under discussion. Information about these proposals is available on our negotiated rulemaking website at www2.ed.gov/policy/highered/reg/hearulemaking/2021/index.html.

In response to comments received and further internal consideration of these final regulations, the Department reviewed and considered various changes to the proposed regulations detailed in the NPRM. We described the changes made in response to public comments in the Analysis of Comments and Changes section of this preamble. We summarize below the major proposals that we considered but ultimately chose not to implement in these regulations. In developing these final regulations, we contemplated the budgetary impact, administrative burden, and anticipated effectiveness of the options we considered.

D/E Rate Only

The Department considered using only the D/E rates metric, consistent with the 2014 Prior Rule. Tables 10.1 and 10.2 show the share of GE and non-GE programs and enrollment that would fail under only the D/E metric compared to our preferred rule that considers both D/E and EP metrics. A greater number of programs do not meet standards when considering both D/E and EP instead of D/E only, especially among certificate programs.

As discussed earlier at length, the D/E and EP measure distinct outcomes of gainful employment, and the EP adds an important protection for students and taxpayers. Even small amounts of debt can be unmanageable borrowers with low earnings, as shown in the RIA and in research. With the inclusion of the EP, the Department affirms that borrowers that postsecondary GE programs should help students reach a minimal level of labor market earnings.

See Brown, Meta et al. (2015). Looking at Student Loan Defaults Through a Larger Window. Liberty Street Economics, Fed. Reserve Bank of N.Y. ( https://libertystreeteconomics.newyorkfed.org/2015/02/looking_at_student_loan_defaults_through_a_larger_window/ ).

Table 10.1—Percent of GE Students and Programs That Fail Under D/E Only vs. D/E or EP

Programs Students
Fail D/E only Fail D/E or EP Fail D/E only Fail D/E or EP
Public:
UG Certificates 0.0 1.0 0.4 4.4
Post-BA Certs 0.0 0.0 0.0 0.0
Grad Certs 0.1 0.1 0.4 0.4
Total 0.0 0.9 0.4 4.1
Private, Nonprofit:
UG Certificates 0.4 5.6 3.9 42.9
Post-BA Certs 0.0 0.0 0.0 0.0
Grad Certs 0.6 0.7 2.7 3.5
Total 0.4 2.6 3.3 28.5
Proprietary:
UG Certificates 5.0 34.4 8.7 52.8
Associate 10.7 15.0 33.7 38.5
Bachelor's 10.7 10.9 24.3 24.4
Post-BA Certs 0.0 0.0 0.0 0.0
Master's 9.7 9.7 16.6 16.6
Doctoral 8.3 8.3 10.6 10.6
Professional 13.8 13.8 50.7 50.7
Grad Certs 4.8 7.3 37.9 38.6
Total 7.7 23.0 20.2 34.1
Foreign Private:
UG Certificates 0.0 0.0 0.0 0.0
Post-BA Certs 0.0 0.0 0.0 0.0
Grad Certs 1.5 1.5 84.2 84.2
Total 0.9 0.9 79.6 79.6
Foreign For-Profit:
Master's 0.0 0.0 0.0 0.0
Doctoral 0.0 0.0 0.0 0.0
Professional 28.6 28.6 20.3 20.3
Total 11.8 11.8 17.2 17.2

Table 10.2—Percent of Non-GE Programs and Enrollment at GE Programs That Fail Under D/E Only vs. D/E or EP

Programs Students
Fail D/E only Fail D/E or EP Fail D/E only Fail D/E or EP
Public:
Associate 0.2 1.7 0.5 7.8
Bachelor's 0.9 1.4 1.3 1.8
Master's 0.3 0.3 1.2 1.2
Doctoral 0.2 0.2 2.6 2.6
Professional 3.3 3.3 7.5 7.5
Total 0.5 1.2 1.0 4.5
Private, Nonprofit:
Associate 2.6 3.3 22.5 24.7
Bachelor's 0.6 0.9 2.7 4.3
Master's 1.7 1.9 4.1 4.7
Doctoral 1.9 1.9 15.5 15.5
Professional 16.7 17.5 34.1 34.7
Total 1.2 1.5 5.8 7.1
Foreign Private:
Associate 0.0 0.0 0.0 0.0
Bachelor's 0.1 0.1 1.2 1.2
Master's 0.1 0.1 1.8 1.9
Doctoral 0.0 0.0 0.0 0.0
Professional 3.4 3.4 20.7 20.7
Total 0.2 0.2 2.9 2.9

Alternative Earnings Thresholds

The Department examined the consequences of two different ways of computing the earnings threshold. For the first, we computed the earnings threshold as the annual earnings among all respondents aged 25–34 in the ACS who have a high school diploma or GED, but no postsecondary education. The second is the median annual earnings among respondents aged 25–34 in the ACS who have a high school diploma or GED, but no postsecondary education, and who worked a full year prior to being surveyed. These measures, which are included in the 2022 PPD, straddle our preferred threshold, which includes all respondents in the labor force, but excludes those that are not in the labor force.

Tables 10.3 and 10.4 reports the share of programs and enrollment that would pass GE metrics under three different earnings threshold methods, with our approach in the middle column. The share of enrollment in undergraduate proprietary certificate programs that would fail ranges from about 30 percent under the lowest threshold up to 61 percent under the highest threshold. The failure rate for public undergraduate certificate programs is much lower than proprietary programs under all three scenarios, ranging from about 2 percent for the lowest threshold to 9 percent under the highest. The earnings threshold chosen would have a much smaller impact on failure rates for degree programs, which range from about 34 percent to 42 percent of enrollment for associate programs and essentially no impact for bachelor's degree or higher programs.

Table 10.3—Share of Enrollment in GE Programs That Fail, by Where Earnings Threshold Is Set

% Failing Total
DTE + lower EP DTE + medium EP DTE + higher EP Number of enrollees
Public:
UG Certificates 1.7 4.4 9.1 869,600
Post-BA Certs 0.0 0.0 0.0 12,600
Grad Certs 0.4 0.4 0.4 41,900
Private, Nonprofit:
UG Certificates 25.8 40.5 43.0 77,900
Post-BA Certs 0.0 0.0 0.0 7,900
Grad Certs 2.7 2.7 4.7 35,700
Proprietary:
UG Certificates 30.0 50.8 61.2 549,900
Associate 33.9 37.1 42.4 326,800
Bachelor's 24.3 24.3 24.7 675,800
Post-BA Certs 0.0 0.0 0.0 800
Master's 16.6 16.6 16.6 240,000
Doctoral 10.6 10.6 10.6 54,000
Professional 50.7 50.7 50.7 12,100
Grad Certs 38.3 38.6 38.6 10,800
Note: Enrollment counts rounded to the nearest hundred.

Table 10.4—Share of GE Programs That Fail, by Where Earnings Threshold Is Set

% Failing Total
DTE + lower EP DTE + medium EP DTE + higher EP Number of Programs
Public:
UG Certificates 0.6 1.0 1.6 19,00
Post-BA Certs 0.0 0.0 0.0 900
Grad Certs 0.1 0.1 0.1 1,900
Private, Nonprofit:
UG Certificates 2.7 4.7 5.5 1,400
Post-BA Certs 0.0 0.0 0.0 600
Grad Certs 0.6 0.6 0.6 1,400
Proprietary:
UG Certificates 20.8 32.0 38.0 3,200
Associate 10.8 13.8 17.6 1,700
Bachelor's 10.5 10.6 11.2 1,000
Post-BA Certs 0.0 0.0 0.0 50
Master's 9.6 9.6 9.6 500
Doctoral 8.2 8.2 8.2 100
Professional 12.5 12.5 12.5 30
Grad Certs 5.5 7.0 7.0 100
Note: Program counts rounded to the nearest 100, except where 50 or fewer.

Tables 10.5 and 10.6 illustrate this for non-GE programs. As with GE programs, the earnings threshold chosen would have a relatively small impact on the share of Bachelors' or higher programs that fail but would impact failure rates for associate degree programs at public institutions, where the share of enrollment in failing programs ranges from about 2 percent at the lowest threshold to 23 percent at the highest. Our measure would result in 8 percent of enrollment in public failing programs.

Table 10.5—Share of Enrollment in Non-GE Programs That Fail, by Where Earnings Threshold Is Set

% Failing Total Number of Enrollees
DTE + lower EP DTE + medium EP DTE + higher EP
Public:
Associate 1.6 7.8 23.2 5,496,800
Bachelor's 1.4 1.8 4.2 5,800,700
Master's 1.2 1.2 1.3 760,500
Doctoral 2.6 2.6 2.6 145,200
Professional 7.5 7.5 7.5 127,500
Private, Nonprofit:
Associate 22.5 23.2 25.3 266,900
Bachelor's 3.5 3.9 5.2 2,651,300
Master's 4.2 4.2 4.4 796,100
Doctoral 15.5 15.5 15.5 142,900
Professional 34.2 34.2 34.2 130,400
Note:– Enrollment counts rounded to the nearest hundred.

Table 10.6—Share of Non-GE Programs That Fail, by Where Earnings Threshold Is Set

% Failing Total number of programs
DTE + lower EP DTE + medium EP DTE + higher EP
Public:
Associate 0.4 1.7 3.6 27,300
Bachelor's 1.0 1.3 2.9 24,300
Master's 0.3 0.3 0.3 14,600
Doctoral 0.2 0.2 0.2 5,700
Professional 3.2 3.2 3.2 600
Private, Nonprofit:
Associate 2.6 2.8 3.5 2,300
Bachelor's 0.7 0.9 1.3 29,800
Master's 1.7 1.8 1.8 10,400
Doctoral 1.9 1.9 1.9 2,900
Professional 16.8 16.8 16.8 500
Note: Program counts rounded to the nearest 100.

No Reporting and Acknowledgment for Non-GE Programs

The Department considered proposing to apply the reporting and acknowledgment requirements only to GE programs, and calculating D/E rates and the earnings premium measure only for these programs, similar to the 2014 Prior Rule. This approach, however, would fail to protect students, families, and taxpayers from investing in non-GE programs that deliver low value and poor debt and earnings outcomes. As higher education costs and student debt levels increase, students, families, institutions, and the public have a commensurately growing interest in ensuring their higher education investments are justified through positive career, debt, and earnings outcomes for graduates, regardless of the sector in which the institution operates or the credential level of the program. Furthermore, comprehensive performance information about all programs is necessary to guide students that would otherwise choose failing GE programs to better options.

Small Program Rates

While we believe the D/E rates and earnings premium measure are reasonable and useful metrics for assessing debt and earnings outcomes, we acknowledge that the minimum n-size of 30 completers would exempt small programs from these Financial Value Transparency measures. In our initial proposals during negotiated rulemaking, the Department considered calculating small program rates in such instances. These small program rates would have been calculated by combining all of an institution's small programs to produce the institution's small program D/E rates and earnings premium measure, which would be used for informational purposes only. In the case of GE programs, these small program rates would not have resulted in program eligibility consequences. Several negotiators questioned the usefulness of the small program rates because they would not provide information specific to any particular program, and because an institution's different small programs in various disciplines could lead to vastly different debt and earnings outcomes. In addition, several negotiators expressed concerns about the use of small program rates as a supplementary performance measure under proposed § 668.13(e). Upon consideration of these points, and in the interest of simplifying the final rule, the Department has opted to omit the small program rates.

Alternative Components of the D/E Rates Measure

The Department considered alternative ways of computing the D/E rates measure, including:

  • Lower completer thresholds n-size
  • Different ways of computing interest rates
  • Different amortization periods

We concluded that the parameters used in the D/E rates and earnings premium calculations were most consistent with best practices identified in prior analysis and research.

Discretionary Earnings Rate

The Department considered simplifying the D/E rates metric by only including a discretionary earnings rate. We believe that using only the discretionary earnings rate would be insufficient because there may be some instances in which a borrower's annual earnings would be sufficient to pass an 8 percent annual debt-to-earnings threshold, even if that borrower's discretionary earnings are insufficient to pass a 20 percent discretionary debt-to-earnings threshold. Utilizing both annual and discretionary D/E rates would provide a more complete picture of a program's true debt and earnings outcomes and would be more generous to institutions because a program that passes either the annual earnings rate or the discretionary earnings rate would pass the D/E rates metric.

Pre- and Post- Earnings Comparison

A standard practice for evaluating the effectiveness of postsecondary programs is to compare the earnings of students after program completion to earnings before program enrollment, to control for any student-specific factors that determine labor market success that should not be attributed to program performance. While the Department introduced limited analysis of pre-program earnings from students' FAFSA data into the evidence above, it is not feasible to perform such comparisons on a wide and ongoing scale in the regulation. Pre-program earnings data is only available for students who have labor market experience prior to postsecondary enrollment, which excludes many students who proceed directly to postsecondary education from high school. Furthermore, earnings data from part-time work during high school is mostly uninformative for earnings potential after postsecondary education. Although some postsecondary programs enroll many students with informative pre-program earnings, many postsecondary programs would lack sufficient numbers of such students to reliably incorporate pre-program earnings from the FAFSA into the regulation.

11. Regulatory Flexibility Act

This section considers the effects that the final regulations may have on small entities in the Educational Sector as required by the Regulatory Flexibility Act (RFA, 5 U.S.C. et seq., Public Law 96–354) as amended by the Small Business Regulatory Enforcement Fairness Act of 1996 (SBREFA). The purpose of the RFA is to establish as a principle of regulation that agencies should tailor regulatory and informational requirements to the size of entities, consistent with the objectives of a particular regulation and applicable statutes. The RFA generally requires an agency to prepare a regulatory flexibility analysis of any rule subject to notice and comment rulemaking requirements under the Administrative Procedure Act or any other statute unless the agency certifies that the rule will not have a “significant impact on a substantial number of small entities.” As we describe below, the Department anticipates that this regulatory action will have a significant economic impact on a substantial number of small entities. We therefore present this Final Regulatory Flexibility Analysis.

Description of the Reasons for Agency Action

The Secretary is establishing new regulations to address concerns about the rising cost of postsecondary education and training and increased student borrowing by establishing a final financial value transparency framework to encourage eligible postsecondary programs to produce acceptable debt and earnings outcomes, apprise current and prospective students of those outcomes, and provide better information about program price. In these final regulations, the Secretary also adopts a GE program accountability framework that establishes eligibility and certification requirements tied to the debt-to-earnings and median earnings (relative to high school graduates) of program graduates. The GE program accountability framework will address ongoing concerns about educational programs that are required by statute to provide training that prepares students for gainful employment in a recognized occupation, but instead are leaving students with unaffordable levels of loan debt in relation to their earnings or earnings lower than that of a typical high school graduate. These programs often lead to default or provide no earnings benefit beyond that provided by a high school education, failing to fulfill their intended goal of preparing students for gainful employment.

The regulations will provide a needed framework for oversight around title IV, HEA institutional eligibility for GE programs and increased transparency for all programs. The regulations will also clarify how the Department will determine whether a program is of reasonable length. The effect on small entities will vary by the extent that they currently participate in such programs or that they choose to do so going forward. Small entities could be vulnerable to program closure of poorly performing programs.

Succinct Statement of the Objectives of, and Legal Basis for, the Regulations

These final regulations amend the Student Assistance General Provisions regulations issued under the HEA in 34 CFR part 668. The changes to part 668 are authorized by 20 U.S.C. 1001–1003, 1070a, 1070g, 1085, 1087b, 1087d, 1087e, 1088, 1091, 1092, 1094, 1099c, 1099c–1, 1221e–3, and 3474.

The regulations are also designed to protect students and taxpayers from unreasonable risks. Inadequate consumer information could result in students enrolling in programs that will not help them benefit them financially. In addition, institutions may use taxpayer funds in ways that were not what Congress or the Department intended, resulting in greater risk to the taxpayers of waste, fraud, and abuse and to the institution of undeserved negative program review or audit findings that could result in liabilities. These regulations attempt to limit risks to students and taxpayers resulting by enhancing our oversight of GE programs and providing additional transparency for all programs.

Description of and, Where Feasible, An Estimate of the Number of Small Entities to Which the Regulations Will Apply

The Small Business Administration (SBA) defines “small institution” using data on revenue, market dominance, tax filing status, governing body, and population. The majority of entities to which the Office of Postsecondary Education's (OPE) regulations apply are postsecondary institutions, however, which do not report such data to the Department. As a result, for purposes of these final regulations, the Department continues to define “small entities” by reference to enrollment, to allow meaningful comparison of regulatory impact across all types of higher education institutions. The enrollment standard for small less-than-two-year institutions (below associate degrees) is less than 750 full-time-equivalent (FTE) students and for small institutions of at least two but less-than-4-years and 4-year institutions, less than 1,000 FTE students. As a result of discussions with the Small Business Administration, this is an update from the standard used in some prior rules, such as the NPRM associated with this final rule, “Financial Value Transparency and Gainful Employment (GE), Financial Responsibility, Administrative Capability, Certification Procedures, Ability to Benefit (ATB),” published in the Federal Register May 19, 2023, the final rule published in the Federal Register on July 10, 2023, for the improving income driven repayment rule, and the final rule published in the Federal Register on October 28, 2022, “Pell Grants for Prison Education Programs; Determining the Amount of Federal Education Assistance Funds Received by Institutions of Higher Education (90/10); Change in Ownership and Change in Control.” Those prior rules applied an enrollment standard for a small two-year institution of less than 500 full-time-equivalent (FTE) students and for a small 4-year institution, less than 1,000 FTE students. The Department consulted with the Office of Advocacy for the SBA and the Office of Advocacy has approved the revised alternative standard for this rulemaking. The Department continues to believe this approach most accurately reflects a common basis for determining size categories that is linked to the provision of educational services and that it captures a similar universe of small entities as the SBA's revenue standard.

In regulations prior to 2016, the Department categorized small businesses based on tax status. Those regulations defined “nonprofit organizations” as “small organizations” if they were independently owned and operated and not dominant in their field of operation, or as “small entities” if they were institutions controlled by governmental entities with populations below 50,000. Those definitions resulted in the categorization of all private nonprofit organizations as small and no public institutions as small. Under the previous definition, proprietary institutions were considered small if they are independently owned and operated and not dominant in their field of operation with total annual revenue below $7,000,000. Using FY 2017 IPEDs finance data for proprietary institutions, 50 percent of 4-year and 90 percent of 2-year or less proprietary institutions would be considered small. By contrast, an enrollment-based definition applies the same metric to all types of institutions, allowing consistent comparison across all types.

88 FR 32300 (May 19, 2023).

88 FR 43820 (July 10, 2023).

87 FR 65426 (Oct. 28, 2022).

In those prior rules, at least two but less-than-four-years institutions were considered in the broader two-year category. In this iteration, after consulting with the Office of Advocacy for the SBA, we separate this group into its own category.

Table 11.1—Small Institutions Under Enrollment-Based Definition

Small Total Percent
Proprietary 2,114 2,331 91
2-year 1,875 1,990 94
4-year 239 341 70
Private not-for-profit 997 1,831 54
2-year 199 203 98
4-year 798 1,628 49
Public 524 1,924 27
2-year 461 1,145 40
4-year 63 779 8
Total 3,635 6,086 60
Source: 2020–21 IPEDS data reported to the Department.

Table 11.1 summarizes the number of institutions potentially affected by these final regulations. As seen in Table 11.2, the average total revenue at small institutions ranges from $3.0 million for proprietary institutions to $16.5 million at private institutions.

Table 11.2—Total Revenues at Small Institutions

Average Total
Proprietary 2,959,809 6,257,035,736
2-year 2,257,046 4,231,961,251
4-year 8,473,115 2,025,074,485
Private not-for-profit 16,531,376 16,481,781,699
2-year 3,664,051 729,146,103
4-year 19,740,145 15,752,635,596
Public 11,084,101 5,808,068,785
2-year 8,329,653 3,839,969,872
4-year 31,239,665 1,968,098,913
Total 7,853,339 28,546,886,220
Note: Based on analysis of IPEDS enrollment and revenue data for 2020–21.

These final regulations require additional reporting and compliance by title IV, HEA participating postsecondary institutions, including small entities, and will have a significant impact on a substantial number of small entities. As described in a previous section, institutions are exempt from the reporting requirements if none of their groups of substantially similar programs have more than 30 completers in total during the four most recently completed award years. Furthermore, GE programs at small institutions could be at risk of losing the ability to distribute title IV, HEA funds under the GE program accountability framework if they fail either the debt-to-earnings (D/E) rate measure or earnings premium (EP) measure. Non-GE programs at small institutions, excluding undergraduate associate and bachelor's degree programs, that fail the D/E metric would be required to have students acknowledge having seen this information prior to entering into enrollment agreements.

Therefore, many small entities will be impacted by the reporting and compliance aspects of the rule, which we quantify below. As we describe in more detail below, the Department estimates that 1.4 percent of non-GE programs at small institutions would fail the D/E metric, therefore triggering the acknowledgment requirement. The Department also estimates that 12.8 percent of GE programs at small institutions would fail either the D/E or EP metric, therefore, being at risk of losing title IV, HEA eligibility. GE programs represent 46 percent of enrollment at small institutions.

The Department's analysis shows programs at small institutions are much more likely to have insufficient sample size to compute and report D/E and EP metrics, though the rate of failing to pass both metrics is higher for programs at such institutions.

The minimum number of program completers in a 2-year cohort that is required for the Department to compute the D/E and EP performance metrics is referred to as the “n-size.” An n-size of 30 is used in the final rule; GE and non-GE programs with fewer than 30 completers across 2 years would not have performance metrics computed.

Table 11.3 and 11.4 show the number and percentage of non-GE enrollees and non-GE programs at small institutions in each status relative to the performance standard. The share of non-GE programs that have sufficient data and fail the D/E metric is higher for programs at small institutions (1.4 percent) than it is for all institutions (0.8 percent, Table 4.5). Failing the D/E metric for non-GE programs initiates a requirement that the institution must have title IV, HEA students acknowledge having seen the information before an enrollment agreement can be signed. The share of title IV, HEA enrollment in such programs is also higher at small institutions (8.6 percent for small institutions vs. 2.1 percent for all institutions, Table 4.4).

Table 11.3—Number of Enrollees in Non-GE Programs at Small Institutions by GE Result, by control, IHE Type, and Credential Level

Result in 2019
No D/E or EP data Pass Fail D/E only Fail both D/E and EP Fail EP only
N % N % N % N % N %
Public:
Associate 89,200 68.8 28,100 21.7 0 0.0 0 0.0 12,300 9.5
Bachelor's 9,700 72.8 3,000 22.1 0 0.0 0 0.0 689 5.1
Master's 500 32.2 1,100 67.8 0 0.0 0 0.0 0 0.0
Doctoral 300 36.3 600 63.7 0 0.0 0 0.0 0 0.0
Professional 2,100 45.3 1,400 29.8 1,200 24.9 0 0.0 0 0.0
Total 101,900 67.8 34,100 22.7 1,200 0.8 0 0.0 13,000 8.7
Private, Nonprofit:
Associate 28,700 57.0 15,800 31.4 2,500 5.0 2,100 4.1 1,300 2.5
Bachelor's 162,500 74.9 41,400 19.1 4,600 2.1 5,100 2.4 3,400 1.5
Master's 29,600 61.1 14,600 30.2 3,100 6.3 1,100 2.3 54 0.1
Doctoral 7,600 45.4 3,600 21.3 5,500 32.9 100 0.4 0 0.0
Professional 9,000 25.0 7,400 20.5 19,400 53.8 0 0.0 200 0.7
Total 237,400 64.4 82,700 22.5 35,100 9.5 8,300 2.3 4,900 1.3
Total:
Associate 117,900 65.5 43,900 24.4 2,500 1.4 2,100 1.2 13,600 7.6
Bachelor's 172,300 74.8 44,300 19.2 4,600 2.0 5,100 2.2 4,000 1.8
Master's 30,100 60.2 15,700 31.4 3,100 6.1 1,100 2.2 100 0.1
Doctoral 8,000 45.0 4,200 23.5 5,500 31.2 100 0.4 0 0.0
Professional 11,100 27.3 8,800 21.6 20,500 50.5 0 0.0 200 0.6
Total 339,300 65.4 116,900 22.5 36,300 7.0 8,300 1.6 18,000 3.5
Note: Enrollment counts in this table have been rounded to the nearest 100.

Table 11.4—Number of Non-GE Programs at Small Institutions by GE Result, by Control, IHE Type, and Credential Level

Result in 2019
No D/E or EP data Pass Fail D/E only Fail both D/E and EP Fail EP only
N % N % N % N % N %
Public:
Associate 2,180 94.6 96 4.2 0 0.0 0 0.0 28 1.2
Bachelor's 195 95.1 9 4.4 0 0.0 0 0.0 1 0.5
Master's 30 81.1 7 18.9 0 0.0 0 0.0 0 0.0
Doctoral 17 89.5 2 10.5 0 0.0 0 0.0 0 0.0
Professional 9 60.0 4 26.7 2 13.3 0 0.0 0 0.0
Total 2,431 94.2 118 4.6 2 0.1 0 0.0 29 1.1
Private, Nonprofit:
Associate 759 90.8 62 7.4 3 0.4 7 0.8 5 0.6
Bachelor's 4,204 94.8 176 4.0 19 0.4 19 0.4 15 0.3
Master's 924 87.9 95 9.0 24 2.3 6 0.6 2 0.2
Doctoral 198 88.4 11 4.9 14 6.2 1 0.4 0 0.0
Professional 86 67.2 12 9.4 27 21.1 0 0.0 3 2.3
Total 6,171 92.5 356 5.3 87 1.3 33 0.5 25 0.4
Total:
Associate 2,939 93.6 158 5.0 3 0.1 7 0.2 33 1.1
Bachelor's 4,399 94.8 185 4.0 19 0.4 19 0.4 16 0.3
Master's 954 87.7 102 9.4 24 2.2 6 0.6 2 0.2
Doctoral 215 88.5 13 5.3 14 5.8 1 0.4 0 0.0
Professional 95 66.4 16 11.2 29 20.3 0 0.0 3 2.1
Total 8,602 93.0 474 5.1 89 1.0 33 0.4 54 0.6

Tables 11.5 and 11.6 report similar tabulations for GE programs at small institutions. GE programs include non-degree certificate programs at all institutions and all degree programs at proprietary institutions. GE programs at small institutions are more likely to have a failing D/E or EP metrics (12.8 percent of all GE programs at small institutions, compared to 5.4 percent for all institutions in Table 4.9) and have a greater share of enrollment in such programs (40.5 percent vs. 23.8 percent for all institutions in Table 4.8). GE programs that fail the same performance metric in two out of three consecutive years will become ineligible to administer Federal title IV, HEA student aid.

Table 11.5—Number of Enrollees in GE Programs at Small Institutions by GE Result, by Control, IHE Type, and Credential Level

Result in 2019
No D/E or EP data Pass Fail D/E only Fail both D/E and EP Fail EP only
N % N % N % N % N %
Public:
UG Certificates 53,800 74.7 15,600 21.6 0 0.0 0 0.0 2,700 3.7
Post-BA Certs <50 100.0 0 0.0 0 0.0 0 0.0 0 0.0
Grad Certs 100 77.4 <50 22.6 0 0.0 0 0.0 0 0.0
Total 54,000 74.7 15,600 21.6 0 0.0 0 0.0 2,700 3.7
Private, Nonprofit:
UG Certificates 9,400 41.7 6,600 29.3 0 0.0 400 1.7 6,200 27.3
Post-BA Certs 1,400 100.0 0 0.0 0 0.0 0 0.0 0 0.0
Grad Certs 1,700 83.7 0 0.0 300 16.3 0 0.0 0 0.0
Total 12,500 48.1 6,600 25.4 300 1.3 400 1.5 6,200 23.7
Proprietary:
UG Certificates 55,600 21.8 52,900 20.7 100 0.0 29,800 11.7 116,500 45.7
Associate 22,400 38.7 19,700 34.0 7,200 12.5 5,400 9.4 3,100 5.4
Bachelor's 8,800 65.1 3,400 25.1 1,100 8.1 200 1.7 0 0.0
Post-BA Certs <50 55.8 <50 44.2 0 0.0 0 0.0 0 0.0
Master's 3,200 80.4 200 3.9 100 2.0 500 13.6 0 0.0
Doctoral 1,700 75.4 300 11.3 300 13.3 0 0.0 0 0.0
Professional 1,000 37.7 100 3.7 1,600 58.6 0 0.0 0 0.0
Grad Certs 300 77.8 0 0.0 0 0.0 0 0.0 73 22.2
Total 93,000 27.7 76,500 22.8 10,400 3.1 36,000 10.7 119,700 35.7
Total:
UG Certificates 118,800 34.0 75,100 21.5 100 0.0 30,200 8.6 125,300 35.8
Associate 22,400 38.7 19,700 34.0 7,200 12.5 5,400 9.4 3,100 5.4
Bachelor's 8,800 65.1 3,400 25.1 1,100 8.1 200 1.7 0 0.0
Post-BA Certs 1,400 97.4 <50 2.6 0 0.0 0 0.0 0 0.0
Master's 3,200 80.4 200 3.9 100 2.0 500 13.6 0 0.0
Doctoral 1,700 75.4 300 11.3 300 13.3 0 0.0 0 0.0
Professional 1,000 37.7 100 3.7 1,600 58.6 0 0.0 0 0.0
Grad Certs 2,100 82.6 <50 1.4 300 13.1 0 0.0 73 2.9
Total 159,500 36.8 98,800 22.8 10,700 2.5 36,400 8.4 128,500 29.6
Note: Enrollment counts in this table have been rounded to the nearest 100.

Table 11.6—Number of GE Programs at Small Institutions by GE Result, by Control, IHE Type, and Credential Level

Result in 2019
No D/E or EP data Pass Fail D/E only Fail both D/E and EP Fail EP only
N % N % N % N % N %
Public:
UG Certificates 3,194 93.4 174 5.1 0 0.0 0 0.0 50 1.5
Post-BA Certs 6 100.0 0 0.0 0 0.0 0 0.0 0 0.0
Grad Certs 13 92.9 1 7.1 0 0.0 0 0.0 0 0.0
Total 3,213 93.5 175 5.1 0 0.0 0 0.0 50 1.5
Private, Nonprofit:
UG Certificates 352 81.5 44 10.2 0 0.0 2 0.5 34 7.9
Post-BA Certs 138 100.0 0 0.0 0 0.0 0 0.0 0 0.0
Grad Certs 103 99.0 0 0.0 1 1.0 0 0.0 0 0.0
Total 593 88.0 44 6.5 1 0.1 2 0.3 34 5.0
Proprietary:
UG Certificates 1,202 53.0 285 12.6 1 0.0 133 5.9 648 28.6
Associate 626 76.4 112 13.7 38 4.6 23 2.8 20 2.4
Bachelor's 199 88.1 16 7.1 9 4.0 2 0.9 0 0.0
Post-BA Certs 11 91.7 1 8.3 0 0.0 0 0.0 0 0.0
Master's 92 92.9 2 2.0 1 1.0 4 4.0 0 0.0
Doctoral 33 94.3 1 2.9 1 2.9 0 0.0 0 0.0
Professional 16 80.0 1 5.0 3 15.0 0 0.0 0 0.0
Grad Certs 16 84.2 0 0.0 0 0.0 0 0.0 3 15.8
Total 2,195 62.7 418 11.9 53 1.5 162 4.6 671 19.2
Total:
UG Certificates 4,748 77.6 503 8.2 1 0.0 135 2.2 732 12.0
Associate 626 76.4 112 13.7 38 4.6 23 2.8 20 2.4
Bachelor's 199 88.1 16 7.1 9 4.0 2 0.9 0 0.0
Post-BA Certs 155 99.4 1 0.6 0 0.0 0 0.0 0 0.0
Master's 92 92.9 2 2.0 1 1.0 4 4.0 0 0.0
Doctoral 33 94.3 1 2.9 1 2.9 0 0.0 0 0.0
Professional 16 80.0 1 5.0 3 15.0 0 0.0 0 0.0
Grad Certs 132 96.4 1 0.7 1 0.7 0 0.0 3 2.2
Total 6,001 78.8 637 8.4 54 0.7 164 2.2 755 9.9

Description of the Projected Reporting, Recordkeeping, and Other Compliance Requirements of the Regulations, Including of the Classes of Small Entities That Will Be Subject to the Requirement and the Type of Professional Skills Necessary for Preparation of the Report or Record

As noted in the Paperwork Reduction Act section, burden related to the final regulations will be assessed in a separate information collection process and that burden is expected to involve individuals more than institutions of any size.

The final rule involves four types of reporting and compliance requirements for institutions, including small entities. First, under § 668.43, institutions will be required to provide additional programmatic information to the Department and make this and additional information assembled by the Department available to current and prospective students by providing a link to a Department-administered program information website. Second, under § 668.407, the Department will require acknowledgments from current and prospective students if an eligible non- GE certificate or graduate program leads to high debt outcomes based on its D/E rates. Third, under § 668.408, institutions will be required to provide new annual reporting about programs, current students, and students that complete or withdraw during each award year. As described in the Preamble of this final rule, reporting includes student-level information on enrollment, cost of attendance, tuition and fees, allowances for books and supplies, allowances for housing, institutional and other grants, and private loans disbursed. Finally, under § 668.605, institutions with GE programs that fail at least one of the metrics will be required to provide warnings to current and prospective students about the risk of losing title IV, HEA eligibility and would require that students must acknowledge having seen the warning before the institution may disburse any title IV, HEA funds.

Initial estimates of the reporting and compliance burden for these four items for small entities are provided in Table 11.7, though these are subject to revision as the content of the required reporting is refined.

For §§ 668.43, 668.407, and 668.605, we obtained these estimates by proportioning the total PRA burden on institutions by the share of institutions that are small entities, as reported in Table 10.1 (60 percent). The estimate for § 668.605 is reduced from the NPRM estimate that included burden on individuals in the calculation. The estimate for the final includes the burden on institutions only.

Table 11.7—Initial and Subsequent Reporting and Compliance Burden for Small Entities

§ 668.43 Amend § 668.43 to establish a website for the posting and distribution of key information pertaining to the institution's educational programs, and to require institutions to provide information about how to access that website to a prospective student before the student enrolls, registers, or makes a financial commitment to the institution $6,512,697.
§ 668.407 Add a new § 668.407 to require current and prospective students to acknowledge having seen the information on the program information website maintained by the Secretary if an eligible program has failed the D/E rates measure, to specify the content and delivery of such acknowledgments, and to require that students must provide the acknowledgment before the institution may enter into an enrollment agreement with the student $22,459.
§ 668.408 Add a new § 668.408 to establish institutional reporting requirements for students who enroll in, complete, or withdraw from a GE program or eligible non-GE program and to establish the reporting timeframe $32,636,989 initial year; $12,502,598 subsequent years.
§ 668.605 Add a new § 668.605 to require warnings to current and prospective students if a GE program is at risk of losing title IV, HEA eligibility, to specify the content and delivery parameters of such notifications, and to require that students must acknowledge having seen the warning before the institution may disburse any title IV, HEA funds $21,227.

As described in this preamble, much of the necessary information for GE programs would already have been reported to the Department under the 2014 Prior Rule, and as such we believe the added burden of this reporting relative to existing requirements would be reasonable. Furthermore, 88 percent of public and 47 percent of private nonprofit institutions operated at least one GE program and, therefore, have experience with similar data reporting for the subset of their students enrolled in certificate programs under the 2014 Prior Rule. Moreover, many institutions report more detailed information on the components of cost of attendance and other sources of financial aid in the Federal National Postsecondary Student Aid Survey (NPSAS) administered by the National Center for Education Statistics. Finally, the Department proposes flexibility for institutions to avoid reporting data on students who completed programs in the past for the first year of implementation, and instead to use data on more recent completer cohorts to estimate median debt levels. In part, we intend to ease the administrative burden of providing this data for programs that were not covered by the 2014 Prior Rule reporting requirements, especially for the small number of institutions that may not previously have had any programs subject to these requirements.

The Department recognizes that institutions may have different processes for record-keeping and administering financial aid, so the burden of the GE and financial transparency reporting could vary by institution. As noted previously, a high percentage of institutions have already reported data related to the 2014 Prior Rule or similar variables for other purposes. Many institutions can query systems or adapt existing reports to meet these requirements. On the other hand, some institutions may still have data entry processes that are very manual, and generating the information for their programs could involve many more hours and resources. Small entities may be less likely to have invested in systems and processes that allow easy data reporting because it is not needed for their operations. Institutions may fall in between these poles and be able to automate the reporting of some variables but need more effort for others.

We believe that, while the reporting relates to program or student-level information, the reporting process is likely to be handled at the institutional level. There would be a cost to establish the query or report and validate it upfront, but then the marginal increase in costs to process additional programs or students should not be too significant. The reporting process will involve personnel with different skills and responsibility levels. We estimated this using Bureau of Labor statistics median hourly wage rates for postsecondary administrators of $48.05. Table 11.8 presents the Department's estimates of the hours associated with the reporting requirements.

Table 11.8—Estimated Hours for Reporting Requirements

Process Hours Hours basis
Review systems and existing reports for adaptability for this reporting 10 Per institution.
Develop reporting query/result template:
Program-level reporting 15 Per institution.
Student-level reporting 30 Per institution.
Run test reports:
Program-level reporting 0.25 Per institution.
Student-level reporting 0.5 Per institution.
Review/validate test report results:
Program-level reporting 10 Per institution.
Student-level reporting 20 Per institution.
Run reports:
Program-level reporting 0.25 Per program.
Student-level reporting 0.5 Per program.
Review/validate report results:
Program-level reporting 2 Per program.
Student-level reporting 5 Per program.
Certify and submit reporting 10 Per institution.

The ability to set up reports or processes that can be rerun in future years, along with the fact that the first reporting cycle includes information from several prior years, should significantly decrease the expected burden after the first reporting cycle. We estimate that the hours associated with reviewing systems, developing or updating queries, and reviewing and validating the test queries or reports will be reduced by 35 percent after the first year. The institution would need to run and validate queries or reports to make sure no system changes have affected them and confirm there are no program changes in CIP code, credential level, preparation for licensure, accreditation, or other items, but we expect that would be less burdensome than initially establishing the reporting. Table 11.9 presents estimates of reporting burden for small entities for the initial year and subsequent years under § 668.408 on an overall and a per institution average basis.

Table 11.9.1—Estimated Reporting Burden for Small Entities for the Initial Reporting Cycle

Control and level Institution count Program count Hours Amount
Private 2-year 112 323 20,737 996,413
Proprietary 2-year 1,077 2,459 179,352 8,617,852
Public 2-year 355 4,871 184,992 8,888,878
Private 4-year 470 6,156 235,839 11,332,040
Proprietary 4-year 96 800 33,992 1,633,316
Public 4-year 39 664 24,318 1,168,492
Total 2,149 15,273 679,230 32,636,989

Table 11.9.2—Estimated Reporting Burden for Small Entities for the Initial Reporting Cycle

Control and level Institution count Program count Hours Amount
Private 2-year 112 323 9,895 475,467
Proprietary 2-year 1,077 2,459 90,139 4,331,191
Public 2-year 355 4,871 61,180 2,939,711
Private 4-year 470 6,156 78,729 3,782,928
Proprietary 4-year 96 800 12,536 602,355
Public 4-year 39 664 7,720 370,946
Total 2,149 15,273 260,200 12,502,598

Table 11.9.3—Estimated Average Reporting Burden per Institution for Small Entities for the Initial Reporting Cycle

Control and level Institution count Program count Initial average hours per institution Initial average amount per institution As % of average revenues
Private 2-year 112 323 185 8,897 0.24
Proprietary 2-year 1,077 2,459 167 8,002 0.35
Public 2-year 355 4,871 521 25,039 0.30
Private 4-year 470 6,156 502 24,111 0.12
Proprietary 4-year 96 800 354 17,014 0.20
Public 4-year 39 664 624 29,961 0.09
Total 2,149 15,273 316 15,187 0.19

Table 11.9.4—Estimated Average Reporting Burden per Institution for Small Entities for Subsequent Reporting Cycles

Control and level Institution count Program count Average hours per institution Average amount per institution As % of average revenues
Private 2-year 112 323 88 4,245 0.11
Proprietary 2-year 1,077 2,459 84 4,022 0.18
Public 2-year 355 4,871 172 8,281 0.10
Private 4-year 470 6,156 168 8,049 0.04
Proprietary 4-year 96 800 131 6,275 0.28
Public 4-year 39 664 198 9,511 0.03
Total 2,149 15,273 121 5,818 0.07

Identification, to the Extent Practicable, of All Relevant Federal Regulations That May Duplicate, Overlap, or Conflict With the Regulations

The regulations are unlikely to conflict with or duplicate existing Federal regulations.

Alternatives Considered

As described in section 10 of the Regulatory Impact Analysis above, “Alternatives Considered”, we evaluated several alternative provisions and approaches including using D/E rates only, alternative earnings thresholds, no reporting or acknowledgment requirements for non-GE programs, and several alternative ways of computing the performance metrics (smaller n-sizes and different interest rates or amortization periods). Most relevant to small entities was the alternative of using a lower n-size, which would result in larger effects on programs at small entities, both in terms of risk for loss of eligibility for GE programs and greater burden for providing warnings and/or acknowledgment. The alternative of not requiring reporting or acknowledgments in the case of failing metrics for non-GE programs would result in lower reporting burden for small institutions but was deemed to be insufficient to achieve the goal of creating greater transparency around program performance. However, for the final regulations the Department did remove the reporting obligation for programs that have fewer than thirty completers in the previous four award years, which does reduce the burden for institutions with very small programs.

The Department sought to limit the number of hours for occupationally related educational programs to the amount that States require to obtain licensure, where applicable. We believe that this change would particularly benefit students by keeping tuition costs, as well as related non-institutional expenses, lower.

12. Paperwork Reduction Act of 1995

As part of its continuing effort to reduce paperwork and respondent burden, the Department provides the general public and Federal agencies with an opportunity to comment on proposed and continuing collections of information in accordance with the Paperwork Reduction Act of 1995 (PRA). This helps so that the public understands the Department's collection instructions, respondents can provide the requested data in the desired format, reporting burden (time and financial resources) is minimized, collection instruments are clearly understood, and the Department can properly assess the impact of collection requirements on respondents. Sections 600.21, 668.43, 668.407, 668.408, and 668.605 of this final rule contain information collection requirements.

Under the PRA, the Department has or will at the required time submit a copy of these sections and an Information Collections Request to OMB for its review.

A Federal agency may not conduct or sponsor a collection of information unless OMB approves the collection under the PRA and the corresponding information collection instrument displays a currently valid OMB control number. Notwithstanding any other provision of law, no person is required to comply with, or is subject to penalty for failure to comply with, a collection of information if the collection instrument does not display a currently valid OMB control number.

PRA Comments

Comments: One commenter suggested that, in calculating administrative burden, the Department should consider the administrative burden of all the proposed rules together, not individually.

Discussion: The Department took great care to analyze the impact of the proposed regulations. The Department has separated the GE and Financial Value Transparency Framework topics from the other rules covered in the NPRM. We, therefore, updated the RIA to reflect that, as well as to reflect changes we made from the proposed rules to these final rules.

Changes: None.

Comments: Some commenters claimed the regulations will increase the cost of higher education because institutions will pass on the increased costs of reporting and data requirements to students, decreasing returns for students and potentially negatively impacting program DTE and EP outcomes.

Discussion: The Department is concerned that programs with poor outcomes continue to receive title IV, HEA funding subsidized by taxpayers. We acknowledged increases in costs to institutions in the NPRM and this final rule; however, we believe they will ultimately bring down the cost of postsecondary education by providing prospective students with the necessary resources to make an informed decision about their education. Students deserve to know whether their program will leave the in the same place or worse off if they never had attended in the first place.

We believe these rules will also protect taxpayer dollars by eliminating poor performing programs prior to the need for reactive actions like closed school discharges or borrower defense to repayment discharges. Further the public deserves access to more information and more data regarding the postsecondary institutions and programs that they are supporting through their tax dollars.

Changes: None.

Updating Application Information § 600.21.

Requirements: The change to § 600.21(a)(11)(v) and (vi), would require an institution with GE programs to update any changes in certification of those program(s).

Burden Calculations: The regulatory change would require an update to the current institutional application form, 1845–0012. The form update would be made available for comment through a full public clearance package before being made available for use by the effective dates of the regulations. The burden changes would be assessed to OMB Control Number 1845–0012, Application for Approval to Participate in Federal Student Aid Programs.

Institutional and Programmatic Information § 668.43

Requirements: Under final § 668.43(d), the Department will establish and maintain a website for posting and distributing key information pertaining to the institution's educational programs. An institution will provide such information as the Department prescribes through a notice published in the Federal Register for prospective and enrolled students through the website.

This information could include, but will not be limited to, as reasonably available, the primary occupations that the program prepares students to enter, along with links to occupational profiles on O*NET or its successor site; the program's or institution's completion rates and withdrawal rates for full-time and less-than-full-time students, as reported to or calculated by the Department; the length of the program in calendar time; the total number of individuals enrolled in the program during the most recently completed award year; the total cost of tuition and fees, and the total cost of books, supplies, and equipment, that a student would incur for completing the program within the length of the program; the percentage of the individuals enrolled in the program during the most recently completed award year who received a title IV, HEA loan, a private education loan, or both; and whether the program is programmatically accredited and the name of the accrediting agency.

The institution will be required to provide a prominent link and any other needed information to access the website on any web page containing academic, cost, financial aid, or admissions information about the program or institution. The Department could require the institution to modify a web page if the information about how to access the Department's website is not sufficiently prominent, readily accessible, clear, conspicuous, or direct.

In addition, the Department will require the institution to provide the relevant information to access the website to any prospective student or third party acting on behalf of the prospective student before the prospective student signs an enrollment agreement, completes registration, or makes a financial commitment to the institution.

Burden Calculations: The final regulatory language in § 668.43(d) will add burden to all institutions, domestic and foreign. The changes in § 668.43(d) will require institutions to supply the Department with specific information about programs it is offering as well as provide to enrolled and prospective students this information.

We believe that this reporting activity will require an estimated 50 hours per institution. We estimate that it will take private nonprofit institutions 70,500 hours (1,410 × 50 = 70,500) to complete the required reporting activity. We estimate that it will take proprietary institutions 68,600 hours (1,372 × 50 = 68,600) to complete the required reporting activity. We estimate that it will take public institutions 86,800 hours (1,736 × 50 = 86,800) to complete the required reporting activity.

The total estimated increase in burden to OMB Control Number 1845–0022 for § 668.43 is 225,900 hours with a total rounded estimated cost of $10,854,495.

Student Assistance General Provisions—OMB Control Number 1845–0022

Affected entity
Respondent Responses Burden hours Cost $48.05 per institution
Private nonprofit 1,410 1,410 70,500 3,387,525.00
Proprietary 1,372 1,372 68,600 3,296,230.00
Public 1,736 1,736 86,800 4,170,740.00
Total 4,518 4,518 225,900 10,854,495.00

Student Acknowledgments § 668.407

Requirements: The final rule provides in § 668.407(a) that a student will be required to provide an acknowledgment of the D/E rate information for any year for which the Secretary notifies an institution that the program has failing D/E rates for the year in which the D/E rates were most recently calculated by the Department. This final rule excludes undergraduate degree programs from the acknowledgment requirements at § 668.407(a).

Burden Calculations: The final regulatory language in § 668.407 will add burden to institutions. The changes in § 668.407 will require institutions to develop and provide notices to prospective students that they are required to review information on the Secretary's website and complete acknowledge that they have viewed this information if the program to which they are applying has unacceptable D/E rates. The institution would also be obligated to check whether an individual has completed the acknowledgment before entering into an agreement to enroll the student. However, to reduce burden for institutions and students, such an acknowledgment will only be required when a student will attend a program that does not lead to an undergraduate degree and leads to high debt burden, or when a student will attend a GE program at risk of losing title IV, HEA eligibility.

In the burden calculation for § 668.407 here, we account for burden for non-GE programs. We account for all burden related to GE programs, including where such burden comes from provisions that apply to all programs, as in 668.407, under our discussion of 668.605. We believe that most institutions will develop the notice directing impacted students to the Department's program information website and make it available electronically to current and prospective students. We believe that this action will require an estimated 1 hour per affected program. We estimate that it would take private institutions 670 hours (670 programs × 1 hour = 670) to develop and deliver the required notice based on the information provided by the Department. We estimate that it will take public institutions 109 hours (109 programs × 1 hour = 109) to develop and deliver the required notice based on the information provided by the Department.

The changes in § 668.407(a) will require institutions to direct prospective and students enrolled in programs that failed the D/E rates for the year in which the D/E rates were most recently calculated by the Department to the Department's program information website. We estimate that it will take the 88,000 students 10 minutes to read the notice and go to the program information website to acknowledge receiving the information for a total of hours (88,000 students × .17 hours = 14,960).

The total estimated increase in burden to OMB Control Number 1845–0174 for § 668.407 is 15,739 hours with a total rounded estimated cost of $370,441.

Student Acknowledgments—OMB Control Number 1845–0174

Affected entity
Respondent Responses Burden hours Cost $48.05 per institution $22.26 per individual
Individual 88,000 88,000 14,960 $333,010
Private nonprofit 134 670 670 32,194
Public 11 109 109 5,237
Total 88,145 88,779 15,739 370,441

Reporting Requirements § 668.408

Requirements: The final rule in subpart Q, Financial Value Transparency, adds new § 668.408 to establish institutional reporting requirements for students who enroll in, complete, or withdraw from a GE program or eligible non-GE program and to define the timeframe for institutions to report this information.

Based on projected data provided earlier in the RIA, the Department anticipates that approximately 4,518 institutions will be required to provide the data specified in § 668.408. We anticipate there will be initial estimated reporting year's burden of 5,078,259 hours total for all institutions. This estimate incorporates establishing required data routines, testing of reports and returned data, and ultimately submission of the data to the Department. It is anticipated that once these data routines and reporting mechanism are established, subsequent year estimated reporting will decrease to 1,459,603 hours total for all institutions.

Burden Calculations: The regulatory change will require an update to a Federal Student Aid data system. Once the systems for receiving and sharing the data are established, the reporting update will be made available for comment through a full information collection package with public comment periods before being made available for use on or after the effective dates of the regulations. The burden changes will be assessed to the OMB Control Number assigned to the system.

Student Warnings and Acknowledgments § 668.605

Requirements: The final rule adds a new § 668.605 to require warnings to current and prospective students if a GE program is at risk of losing title IV, HEA eligibility, to specify the content and delivery parameters of such notifications, and to require that students must acknowledge having seen the warning before the institution may enter an enrollment agreement, complete registration, or disburse any title IV, HEA funds.

In addition, warnings provided to students enrolled in GE programs will include a description of the academic and financial options available to continue their education in another program at the institution in the event that the program loses eligibility, including whether the students could transfer academic credit earned in the program to another program at the institution and which course credit would transfer; an indication of whether, in the event of a loss of eligibility, the institution would continue to provide instruction in the program to allow students to complete the program, and refund the tuition, fees, and other required charges paid to the institution for enrollment in the program; and an explanation of whether, in the event that the program loses eligibility, the students could transfer credits earned in the program to another institution through an established articulation agreement or teach-out.

The institution will be required to provide alternatives to an English-language warning for current and prospective students with limited English proficiency.

Burden Calculations: The final regulatory language in § 668.605 will add burden to institutions. The changes in § 668.605 will require institutions to provide warning notices to enrolled and prospective students that a GE program has unacceptable D/E rates or an unacceptable earnings premium measure for the year in which the D/E rates or earnings premium measure were most recently calculated by the Department along with warnings about the potential loss of title IV, HEA eligibility.

We account for all burden related to GE programs, including where such burden comes from provisions that apply to all programs, as in § 668.407, under our discussion of § 668.605. We believe that most institutions will develop the warning and make it available electronically to current and prospective students. We believe that this action will require an estimated 1 hour per affected program. We estimate that it will take private institutions 9 hours (9 programs × 1 hour = 9) to develop and deliver the required warning based on the information provided by the Department. We estimate that it will take proprietary institutions 71 hours (71 programs × 1 hour = 71) to develop and deliver the required warning based on the information provided by the Department. We estimate that it will take public institutions 2 hours (2 programs × 1 hour = 2) to develop and deliver the required warning based on the information provided by the Department.

The changes in § 668.605(d) will require institutions to provide alternatives to the English-language warning notices to enrolled and prospective students with limited English proficiency.

We estimate that it will take private institutions 72 hours (9 programs × 8 hours = 72) to develop and deliver the required alternate language the required warning based on the information provided by the Department. We estimate that it will take proprietary institutions 568 hours (71 programs × 8 hours = 568) to develop and deliver the required alternate language the required warning based on the information provided by the Department. We estimate that it will take public institutions 16 hours (2 programs × 8 hours = 16) to develop and deliver the required warning based on the information provided by the Department.

The final changes in § 668.605(e) will require institutions to provide the warning notices to students enrolled in the GE programs with failing metrics. We estimate that it will take the 60,700 students 10 minutes to read the warning and go to the program information website to acknowledge receiving the information for a total of 10,319 hours (60,700 students × .17 hours = 10,319).

The changes in § 668.605(f) will require institutions to provide the warning notices to prospective students who express interest in the effected GE programs. We estimate that it will take the 69,805 prospective students 10 minutes to read the warning and go to the program information website to acknowledge receiving the information for a total of 11,867 hours (69,805 students × .17 hours = 11,867).

The total estimated increase in burden to OMB Control Number 1845–0173 for § 668.605 is 22,924 hours with a total rounded estimated cost of $529,322.

GE Student Warnings and Acknowledgments—OMB Control Number 1845–0173

Affected entity
Respondent Responses Burden hours Cost $48.05 per institution $22.26 per individual
Individual 130,505 130,505 22,186 $493,860
Private nonprofit 9 18 81 3,893
Proprietary 71 142 639 30,704
Public 2 4 18 865
Total 130,587 130,669 22,924 529,322

Consistent with the discussions above, the following chart describes the sections of the final regulations involving information collections, the information being collected and the collections that the Department will submit to OMB for approval and public comment under the PRA, and the estimated costs associated with the information collections. The monetized net cost of the increased burden for institutions, lenders, guaranty agencies and students, using wage data developed using Bureau of Labor Statistics (BLS) data. For individuals, we have used the median hourly wage for all occupations, which is $22.26 per hour according to BLS ( www.bls.gov/oes/current/oes_nat.htm#00-0000 ). For institutions we have used the median hourly wage for Education Administrators, Postsecondary, which is $48.05 per hour according to BLS ( www.bls.gov/oes/current/oes119033.htm ).

Regulatory section Information collection OMB control number and estimated burden Estimated costs— $48.05 institutional $22.26 individual unless otherwise noted
§ 668.43 Amend § 668.43 to establish a website for the posting and distribution of key information pertaining to the institution's educational programs, and to require institutions to provide information about how to access that website to a prospective student before the student enrolls, registers, or makes a financial commitment to the institution 1845–0022 +225,900 hrs $+10,854,495.
§ 668.407 Add a new § 668.407 to require current and prospective students to acknowledge having seen the information on the program information website maintained by the Secretary if an eligible program has failed the D/E rates measure, to specify the content and delivery of such acknowledgments, and to require that students must provide the acknowledgment before the institution enters an enrollment agreement 1845–0174 +15,739 $+370,441.
§ 668.408 Add a new § 668.408 to establish institutional reporting requirements for students who enroll in, complete, or withdraw from a GE program or eligible non-GE program and to establish the reporting timeframe Burden will be cleared at a later date through a separate information collection Costs will be cleared through separate information collection.
§ 668.605 Add a new § 668.605 to require warnings to current and prospective students if a GE program is at risk of losing title IV, HEA eligibility, to specify the content and delivery parameters of such notifications, and to require that students must acknowledge having seen the warning before the institution may enter an enrollment agreement, complete registration, or disburse any title IV, HEA funds 1845–0173 +22,924 $+529,322.

The total burden hours and change in burden hours associated with each OMB Control number affected by the final regulations follows: 1845–0022, 1845–0173, 1845–0174.

Control No. Total burden hours Change in burden hours
1845–0022 2,514,148 +225,900
1845–0173 15,739 +15,739
1845–0174 22,924 +22,924
Total 2,552,811 264,563

If you want to comment on the final information collection requirements, please send your comments to the Office of Information and Regulatory Affairs in OMB, Attention: Desk Officer for the U.S. Department of Education. Send these comments by email to OIRA_DOCKET@omb.eop.gov or by fax to (202)395–6974. You may also send a copy of these comments to the Department contact named in the ADDRESSES section of the preamble.

We have prepared the Information Collection Request (ICR) for these collections. You may review the ICR which is available at www.reginfo.gov. Click on Information Collection Review. These collections are identified as collections 1845–0022, 1845–0173, and 1845–0174.

Intergovernmental Review

This program is subject to Executive Order 12372 and the regulations in 34 CFR part 79. One of the objectives of the Executive order is to foster an intergovernmental partnership and a strengthened federalism. The Executive order relies on processes developed by State and local governments for coordination and review of proposed Federal financial assistance.

This document provides early notification of our specific plans and actions for this program.

13. Federalism

Executive Order 13132 requires us to provide meaningful and timely input by State and local elected officials in the development of regulatory policies that have federalism implications. “Federalism implications” means substantial direct effects on the States, on the relationship between the National Government and the States, or on the distribution of power and responsibilities among the various levels of government. The final regulations do not have federalism implications.

Accessible Format: On request to one of the program contact persons listed under FOR FURTHER INFORMATION CONTACT , individuals with disabilities can obtain this document in an accessible format. The Department will provide the requestor with an accessible format that may include Rich Text Format (RTF) or text format (txt), a thumb drive, an MP3 file, braille, large print, audiotape, or compact disc, or other accessible format.

Electronic Access to This Document: The official version of this document is the document published in the Federal Register . You may access the official edition of the Federal Register and the Code of Federal Regulations at www.govinfo.gov. At this site you can view this document, as well as all other documents of this Department published in the Federal Register , in text or Adobe Portable Document Format (PDF). To use PDF, you must have Adobe Acrobat Reader, which is available free at the site.

You may also access documents of the Department published in the Federal Register by using the article search feature at www.federalregister.gov. Specifically, through the advanced search feature at this site, you can limit your search to documents published by the Department.

List of Subjects

34 CFR Part 600

  • Colleges and universities
  • Foreign relations
  • Grant programs—education
  • Loan programs-education
  • Reporting and recordkeeping requirements
  • Selective Service System
  • Student aid
  • Vocational education

34 CFR Part 668

  • Administrative practice and procedure
  • Aliens
  • Colleges and universities
  • Consumer protection
  • Grant programs-education
  • Loan programs—education
  • Reporting and recordkeeping requirements
  • Selective Service System
  • Student aid
  • Vocational education

Miguel A. Cardona,

Secretary of Education.

For the reasons discussed in the preamble, the Secretary amends parts 600 and 668 of title 34 of the Code of Federal Regulations as follows:

PART 600—INSTITUTIONAL ELIGIBILITY UNDER THE HIGHER EDUCATION ACT OF 1965, AS AMENDED

1. The authority citation for part 600 continues to read as follows:

Authority: 20 U.S.C. 1001, 1002, 1003, 1088, 1091, 1094, 1099b, and 1099c, unless otherwise noted.

2. Section 600.10 is amended by redesignating paragraph (c)(3) as paragraph (c)(4) and adding a new paragraph (c)(3) to read as follows:

§ 600.10
Date, extent, duration, and consequence of eligibility.

(c) * * *

(3) For a gainful employment program under 34 CFR part 668, subpart S, subject to any restrictions in 34 CFR 668.603 on establishing or reestablishing the eligibility of the program, an eligible institution must update its application under § 600.21.

3. Section 600.21 is amended by:

a. Revising paragraph (a) introductory text.

b. In paragraph (a)(11)(iv), removing the word “or”.

c. Revising paragraph (a)(11)(v).

d. Adding paragraph (a)(11)(vi).

The revisions and addition read as follows:

§ 600.21
Updating application information.

(a) Reporting requirements. Except as provided in paragraph (b) of this section, an eligible institution must report to the Secretary, in a manner prescribed by the Secretary and no later than 10 days after the change occurs, any change in the following:

(11) * * *

(v) Changing the program's name, classification of instructional program (CIP) code, or credential level; or

(vi) Updating the certification pursuant to 34 CFR 668.604(b).

PART 668—STUDENT ASSISTANCE GENERAL PROVISIONS

4. The authority citation for part 668 is revised to read as follows:

Authority: 20 U.S.C. 1001–1003, 1070g, 1085, 1088, 1091, 1092, 1094, 1099c, 1099c–1, 1221e–3, and 1231a, unless otherwise noted.

Section 668.14 also issued under 20 U.S.C. 1085, 1088, 1091, 1092, 1094, 1099a–3, 1099c, and 1141.

Section 668.41 also issued under 20 U.S.C. 1092, 1094, 1099c.

Section 668.91 also issued under 20 U.S.C. 1082, 1094.

Section 668.171 also issued under 20 U.S.C. 1094 and 1099c and 5 U.S.C. 404.

Section 668.172 also issued under 20 U.S.C. 1094 and 1099c and 5 U.S.C. 404.

Section 668.175 also issued under 20 U.S.C. 1094 and 1099c.

5. Section 668.2 is amended by adding to paragraph (b), in alphabetical order, definitions of “Annual debt-to-earnings rate (annual D/E rate),” “Classification of instructional program (CIP) code,” “Cohort period,” “Credential level,” “Debt-to-earnings rates (D/E rates),” “Discretionary debt-to-earnings rate (discretionary D/E rate),” “Earnings premium,” “Earnings threshold,” “Eligible non-GE program,” “Federal agency with earnings data,” “Gainful employment program (GE program),” “Institutional grants and scholarships,” “Length of the program,” “Metropolitan statistical area,” “Poverty Guideline,” “Prospective student,” “Qualifying graduate program,” “Student,” and “Substantially similar program” to read as follows:

§ 668.2
General definitions.

(b) * * *

Annual debt-to-earnings rate (annual D/E rate): The ratio of a program's annual loan payment amount to the annual earnings of the students who completed the program, expressed as a percentage, as calculated under § 668.403.

Classification of instructional program (CIP) code: A taxonomy of instructional program classifications and descriptions developed by the U.S. Department of Education's National Center for Education Statistics (NCES). Specific programs offered by institutions are classified using a six-digit CIP code.

Cohort period: The set of award years used to identify a cohort of students who completed a program and whose debt and earnings outcomes are used to calculate debt-to-earnings rates and the earnings premium measure under subpart Q of this part. The Secretary uses a 2-year cohort period to calculate the debt-to-earnings rates and earnings premium measure for a program when the number of students (after exclusions identified in §§ 668.403(e) and 668.404(c)) in the 2-year cohort period is 30 or more. The Secretary uses a 4-year cohort period to calculate the debt-to-earnings rates and earnings premium measure when the number of students completing the program in the two-year cohort period is fewer than 30 and when the number of students completing the program in the 4-year cohort period is 30 or more. The cohort period covers consecutive award years that are—

(1) For the 2-year cohort period—

(i) The third and fourth award years prior to the year for which the most recent data are available from the Federal agency with earnings data at the time the D/E rates and earnings premium measure are calculated, pursuant to §§ 668.403 and 668.404; or

(ii) For a qualifying graduate program, the sixth and seventh award years prior to the year for which the most recent data are available from the Federal agency with earnings data at the time the D/E rates and earnings premium measure are calculated.

(2) For the four-year cohort period—

(i) The third, fourth, fifth, and sixth award years prior to the year for which the most recent data are available from the Federal agency with earnings data at the time the D/E rates and earnings premium measure are calculated, pursuant to §§ 668.403 and 668.404; or

(ii) For a qualifying graduate program, the sixth, seventh, eighth, and ninth award years prior to the year for which the most recent earnings data are available from the Federal agency with earnings data at the time the D/E rates and earnings premium measure are calculated.

Credential level: The level of the academic credential awarded by an institution to students who complete the program. For the purposes of this part, the undergraduate credential levels are: undergraduate certificate or diploma, associate degree, bachelor's degree, and post-baccalaureate certificate; and the graduate credential levels are master's degree, doctoral degree, first-professional degree ( e.g., MD, DDS, JD), and graduate certificate (including a postgraduate certificate).

Debt-to-earnings rates (D/E rates): The discretionary debt-to-earnings rate and annual debt-to-earnings rate as calculated under § 668.403.

Discretionary debt-to-earnings rate (discretionary D/E rate): The percentage of a program's annual loan payment compared to the discretionary earnings of the students who completed the program, as calculated under § 668.403.

Earnings premium: The amount by which the median annual earnings of students who recently completed a program exceed the earnings threshold, as calculated under § 668.404. If the median annual earnings of recent completers is equal to the earnings threshold, the earnings premium is zero. If the median annual earnings of recent completers is less than the earnings threshold, the earnings premium is negative.

Earnings threshold: Based on data from the Census Bureau, the median earnings for working adults aged 25–34, who either worked during the year or indicated they were unemployed ( i.e., not employed but looking for and available to work) when interviewed, with only a high school diploma (or recognized equivalent)—

(1) In the State in which the institution is located; or

(2) Nationally, if fewer than 50 percent of the students in the program are from the State where the institution is located, or if the institution is a foreign institution.

Eligible non-GE program: An educational program other than a gainful employment (GE) program offered by an institution and included in the institution's participation in the title IV, HEA programs, identified by a combination of the institution's six-digit Office of Postsecondary Education ID (OPEID) number, the program's six-digit CIP code as assigned by the institution or determined by the Secretary, and the program's credential level. Includes all coursework associated with the program's credential level.

Federal agency with earnings data: A Federal agency with which the Department enters into an agreement to access earnings data for the D/E rates and earnings threshold measure. The agency must have individual earnings data sufficient to match with title IV, HEA recipients who completed any eligible program during the cohort period and may include agencies such as the Treasury Department (including the Internal Revenue Service), the Social Security Administration (SSA), the Department of Health and Human Services (HHS), and the Census Bureau.

Gainful employment program (GE program): An educational program offered by an institution under § 668.8(c)(3) or (d) and identified by a combination of the institution's six-digit OPEID number, the program's six-digit CIP code as assigned by the institution or determined by the Secretary, and the program's credential level.

Institutional grants and scholarships: Assistance that the institution or its affiliate controls or directs to reduce or offset the original amount of a student's institutional costs and that does not have to be repaid. Typically, an institutional grant or scholarship includes a grant, scholarship, fellowship, discount, or fee waiver.

Length of the program: The amount of time in weeks, months, or years that is specified in the institution's catalog, marketing materials, or other official publications for a student to complete the requirements needed to obtain the degree or credential offered by the program.

Metropolitan statistical area: A core area containing a substantial population nucleus, together with adjacent communities having a high degree of economic and social integration with that core.

Poverty Guideline: The Poverty Guideline for a single person in the continental United States, as published by the U.S. Department of Health and Human Services and available at https://aspe.hhs.gov/poverty or its successor site.

Prospective student: An individual who has contacted an eligible institution for the purpose of requesting information about enrolling in a program or who has been contacted directly by the institution or by a third party on behalf of the institution about enrolling in a program.

Qualifying graduate program: (1) For the first three award years that the Secretary calculates debt-to-earnings rates and the earnings premium measure under subpart Q of this part (“initial period”), a graduate program—

(i) Whose students must complete required postgraduation training programs to obtain licensure in one of the following fields: medicine, osteopathy, dentistry, clinical psychology, marriage and family counseling, clinical social work, and clinical counseling; and

(ii) For which the institution attests, in the manner established by the Secretary, that—

(A) If necessary for licensure, the program is accredited by an accrediting agency that meets State requirements; and

(B) At least half of the program's graduates obtain licensure in a State where the postgraduation training requirements apply.

(2)(i) After the initial period, the graduate programs that are on the list described in paragraph (2)(ii) of this definition and for which the Secretary has received an attestation that meets the requirements in paragraph (1)(ii) of this definition.

(ii) For the first award year following the initial period, and every three years thereafter, using publicly available information and information received in response to a request for information, the Secretary publishes in the Federal Register a list of graduate degree fields (based on their credential level and CIP codes) that may contain qualifying graduate programs by identifying fields—

(A) That lead to a graduate (master's, first-professional, or doctoral) degree;

(B) For which the Department determines that graduates must complete a required postgraduate training program that takes, on average, three or more years to complete; and

(C) For which, based on College Scorecard data, the Secretary determines that a majority of programs with the same credential level and CIP code have outlier earnings growth. An individual program has outlier earnings growth if the percent change in median earnings between its earnings measured one or three years post-completion and its earnings measured either five or ten years post-completion is more than two standard deviations above the average earnings growth for other programs with the same credential level.

(3) For the purpose of this definition, a “required postgraduation training program” is a supervised training program that—

(i) Requires the student to hold a degree in one of the listed fields in paragraph (1)(i) of this definition or one of the fields identified in the list described in paragraph (2)(ii) of this definition; and

(ii) Must be completed before the student may be licensed by a State and board certified for professional practice or service.

Student: For the purposes of subparts Q and S of this part and of § 668.43(d), an individual who received title IV, HEA program funds for enrolling in the program.

Substantially similar program: For the purposes of subpart Q and S of this part, a program is substantially similar to another program if the two programs share the same four-digit CIP code. The Secretary presumes a program is not substantially similar to another program if the two programs have different four-digit CIP codes, but the institution must provide an explanation of how the new program is not substantially similar to the ineligible or voluntarily discontinued program with its certification under § 668.604.

6. Section 668.43 is amended by:

a. Revising the section heading.

b. Adding paragraph (d).

The revisions and addition read as follows:

§ 668.43
Institutional and programmatic information.

(d)(1) Program information website. Beginning on July 1, 2026, the Secretary will establish and maintain a website with information about institutions and their educational programs. For this purpose, an institution must provide to the Department such information about the institution and its programs as the Secretary prescribes through a notice published in the Federal Register . The Secretary may conduct consumer testing to inform the design of the website.

(i) The website must include, but is not limited to, the following items, to the extent reasonably available:

(A) The published length of the program in calendar time ( i.e., weeks, months, years).

(B) The total number of individuals enrolled in the program during the most recently completed award year.

(C) The total cost of tuition and fees, and the total cost of books, supplies, and equipment, that a student would incur for completing the program within the published length of the program.

(D) Of the individuals enrolled in the program during the most recently completed award year, the percentage who received a Direct Loan Program loan, a private loan, or both for enrollment in the program.

(E) As calculated by the Secretary, the median loan debt of students who completed the program during the most recently completed award year or for all students who completed or withdrew from the program during that award year.

(F) As provided by the Secretary, the median earnings of students who completed the program or of all students who completed or withdrew from the program, during a period determined by the Secretary.

(G) Whether the program is programmatically accredited and the name of the accrediting agency, as reported to the Secretary.

(H) As calculated by the Secretary, the program's debt-to-earnings rates.

(I) As calculated by the Secretary, the program's earnings premium measure. (ii) The website may also include other information deemed appropriate by the Secretary, such as the following items:

(A) The primary occupations (by name, SOC code, or both) that the program prepares students to enter, along with links to occupational profiles on O*NET ( www.onetonline.org ) or its successor site.

(B) As reported to or calculated by the Secretary, the program or institution's completion rates and withdrawal rates for full-time and less-than-full-time students.

(C) As calculated by the Secretary, the medians of the total cost of tuition and fees, and the total cost of books, supplies, and equipment, and the total net cost of attendance paid by students completing the program.

(D) As calculated by the Secretary, the loan repayment rate for students or graduates who entered repayment on Direct Loan Program loans during a period determined by the Secretary.

(E) Whether students who graduate from a program are required to complete postgraduation training program to obtain licensure before eligible for independent practice.

(2) Program web pages. The institution must provide a prominent link to, and any other needed information to access, the website maintained by the Secretary on any web page containing academic, cost, financial aid, or admissions information about the program or institution. The Secretary may require the institution to modify a web page if the information is not sufficiently prominent, readily accessible, clear, conspicuous, or direct.

(3) Distribution to prospective students. The institution must provide the relevant information to access the website maintained by the Secretary to any prospective student, or a third party acting on behalf of the prospective student, before the prospective student signs an enrollment agreement, completes registration, or makes a financial commitment to the institution.

(4) Distribution to enrolled students. The institution must provide the relevant information to access the website maintained by the Secretary to any enrolled title IV, HEA recipient prior to the start date of the first payment period associated with each subsequent award year in which the student continues enrollment at the institution.

7. Section 668.91 is amended by:

a. In paragraph (a)(3)(v)(B)( 2), removing the period at the end of the paragraph and adding, in its place, “; and”.

b. Adding paragraph (a)(3)(vi).

The addition reads as follows:

§ 668.91
Initial and final decisions.

(a) * * *

(3) * * *

(vi) In a termination action against a GE program based upon the program's failure to meet the requirements in § 668.403 or § 668.404, the hearing official must terminate the program's eligibility unless the hearing official concludes that the Secretary erred in the applicable calculation.

8. Add subpart Q to read as follows:

Subpart Q—Financial Value Transparency
668.401
Financial value transparency scope and purpose.
668.402
Financial value transparency framework.
668.403
Calculating D/E rates.
668.404
Calculating earnings premium measure.
668.405
Process for obtaining data and calculating D/E rates and earnings premium measure.
668.406
Determination of the D/E rates and earnings premium measure.
668.407
Student acknowledgments.
668.408
Reporting requirements.
668.409
Severability.

Subpart Q—Financial Value Transparency

§ 668.401
Financial value transparency scope and purpose.

(a) General. Except as provided under paragraph (b) of this section, this subpart applies to a GE program or eligible non-GE program offered by an eligible institution, and establishes the rules and procedures under which—

(1) An institution reports information about the program to the Secretary; and

(2) Except as provided in paragraph (b)(1) of this section, the Secretary assesses the program's debt and earnings outcomes.

(b) Applicability. (1) This subpart does not apply to institutions located in U.S. Territories or freely associated states, except that such institutions are subject to the reporting requirements in § 668.408 and the Secretary will follow the procedures in §§ 668.403(b) and (d) and 668.405(b) and (c) to calculate median debt and obtain earnings information for their GE programs and eligible non-GE programs.

(2) For each award year that the Secretary calculates D/E rates or the earnings premium measure under § 668.402, this subpart does not apply to an institution if, over the most recently completed four award years, it offered no groups of substantially similar programs, defined as all programs in the same four-digit CIP code at an institution, with 30 or more completers.

§ 668.402
Financial value transparency framework.

(a) General. The Secretary assesses the program's debt and earnings outcomes using debt-to-earnings rates (D/E rates) and an earnings premium measure.

(b) Debt-to-earnings rates. The Secretary calculates for each award year two D/E rates for an eligible program, the discretionary debt-to-earnings rate, and the annual debt-to-earnings rate, using the procedures in §§ 668.403 and 668.405.

(c) Outcomes of the D/E rates. (1) A program passes the D/E rates if—

(i) Its discretionary debt-to-earnings rate is less than or equal to 20 percent;

(ii) Its annual debt-to-earnings rate is less than or equal to 8 percent; or

(iii) The denominator (median annual or discretionary earnings) of either rate is zero and the numerator (median debt payments) is zero.

(2) A program fails the D/E rates if—

(i) Its discretionary debt-to-earnings rate is greater than 20 percent or the income for the denominator of the rate (median discretionary earnings) is negative or zero and the numerator (median debt payments) is positive; and

(ii) Its annual debt-to-earnings rate is greater than 8 percent or the denominator of the rate (median annual earnings) is zero and the numerator (median debt payments) is positive.

(d) Earnings premium measure. For each award year, the Secretary calculates the earnings premium measure for an eligible program, using the procedures in §§ 668.404 and 668.405.

(e) Outcomes of the earnings premium measure. (1) A program passes the earnings premium measure if the median annual earnings of the students who completed the program exceed the earnings threshold.

(2) A program fails the earnings premium measure if the median annual earnings of the students who completed the program are equal to or less than the earnings threshold.

§ 668.403
Calculating D/E rates.

(a) General. Except as provided under paragraph (f) of this section, for each award year, the Secretary calculates D/E rates for a program as follows:

(1) Discretionary debt-to-earnings rate = annual loan payment/(the median annual earnings—(1.5 x Poverty Guideline)). For the purposes of this paragraph (a)(1), the Secretary applies the Poverty Guideline for the most recent calendar year for which annual earnings are obtained under paragraph (c) of this section.

(2) Annual debt-to-earnings rate = annual loan payment/the median annual earnings.

(b) Annual loan payment. The Secretary calculates the annual loan payment for a program by—

(1)(i) Determining the median loan debt of the students who completed the program during the cohort period, based on the lesser of the loan debt incurred by each student as determined under paragraph (d) of this section or the total amount for tuition and fees and books, equipment, and supplies for each student, less the amount of institutional grant or scholarship funds provided to that student;

(ii) Removing, if applicable, the appropriate number of largest loan debts as described in § 668.405(d)(2); and

(iii) Calculating the median of the remaining amounts; and

(2) Amortizing the median loan debt—

(i)(A) Over a 10-year repayment period for a program that leads to an undergraduate certificate, a post-baccalaureate certificate, an associate degree, or a graduate certificate;

(B) Over a 15-year repayment period for a program that leads to a bachelor's degree or a master's degree; or

(C) Over a 20-year repayment period for any other program; and

(ii) Using an annual interest rate that is the average of the annual statutory interest rates on Federal Direct Unsubsidized Loans that were in effect during—

(A) The three consecutive award years, ending in the final year of the cohort period, for undergraduate certificate programs, post-baccalaureate certificate programs, and associate degree programs. For these programs, the Secretary uses the Federal Direct Unsubsidized Loan interest rate applicable to undergraduate students;

(B) The three consecutive award years, ending in the final year of the cohort period, for graduate certificate programs and master's degree programs. For these programs, the Secretary uses the Federal Direct Unsubsidized Loan interest rate applicable to graduate students;

(C) The six consecutive award years, ending in the final year of the cohort period, for bachelor's degree programs. For these programs, the Secretary uses the Federal Direct Unsubsidized Loan interest rate applicable to undergraduate students; and

(D) The six consecutive award years, ending in the final year of the cohort period, for doctoral programs and first professional degree programs. For these programs, the Secretary uses the Federal Direct Unsubsidized Loan interest rate applicable to graduate students.

(c) Annual earnings. (1) The Secretary obtains from a Federal agency with earnings data, under § 668.405, the most currently available median annual earnings of the students who completed the program during the cohort period and who are not excluded under paragraph (e) of this section; and

(2) The Secretary uses the median annual earnings to calculate the D/E rates.

(d) Loan debt and assessed charges. (1) In determining the loan debt for a student, the Secretary includes—

(i) The amount of Direct Loans that the student borrowed (total amount disbursed less any cancellations or adjustments except for those related to false certification, borrower defense discharges, or categorical debt relief initiated under the Secretary's statutory authority) for enrollment in the program, excluding Direct PLUS Loans made to parents of dependent students and Direct Unsubsidized Loans that were converted from TEACH Grants;

(ii) Any private education loans as defined in 34 CFR 601.2, including private education loans made by the institution, that the student borrowed for enrollment in the program and that are required to be reported by the institution under § 668.408; and

(iii) The amount outstanding, as of the date the student completes the program, on any other credit (including any unpaid charges) extended by or on behalf of the institution for enrollment in any program attended at the institution that the student is obligated to repay after completing the program, including extensions of credit described in paragraphs (1) and (2) of the definition of, and excluded from, the term “private education loan” in 34 CFR 601.2;

(2) The Secretary attributes all the loan debt incurred by the student for enrollment in any—

(i) Undergraduate program at the institution to the highest credentialed undergraduate program subsequently completed by the student at the institution as of the end of the most recently completed award year prior to the calculation of the D/E rates under this section; and

(ii) Graduate program at the institution to the highest credentialed graduate program subsequently completed by the student at the institution as of the end of the most recently completed award year prior to the calculation of the D/E rates under this section; and

(3) The Secretary excludes any loan debt incurred by the student for enrollment in any program at any other institution. However, the Secretary may include loan debt incurred by the student for enrollment in programs at other institutions if the institution and the other institutions are under common ownership or control, as determined by the Secretary in accordance with 34 CFR 600.31.

(e) Exclusions. The Secretary excludes a student from both the numerator and the denominator of the D/E rates calculation if the Secretary determines that—

(1) One or more of the student's Direct Loan Program loans are under consideration by the Secretary, or have been approved, for a discharge on the basis of the student's total and permanent disability, under 34 CFR 674.61, 682.402, or 685.212;

(2) The student was enrolled full time in any other eligible program at the institution or at another institution during the calendar year for which the Secretary obtains earnings information under paragraph (c) of this section;

(3) For undergraduate programs, the student completed a higher credentialed undergraduate program at the institution subsequent to completing the program as of the end of the most recently completed award year prior to the calculation of the D/E rates under this section;

(4) For graduate programs, the student completed a higher credentialed graduate program at the institution subsequent to completing the program as of the end of the most recently completed award year prior to the calculation of the D/E rates under this section;

(5) The student is enrolled in an approved prison education program;

(6) The student is enrolled in a comprehensive transition and postsecondary program; or

(7) The student died.

(f) D/E rates not issued. The Secretary does not issue D/E rates for a program under § 668.406 if—

(1) After applying the exclusions in paragraph (e) of this section, fewer than 30 students completed the program during the two-year or four-year cohort period; or

(2) The Federal agency with earnings data does not provide the median earnings for the program as provided under paragraph (c) of this section.

§ 668.404
Calculating earnings premium measure.

(a) General. Except as provided under paragraph (d) of this section, for each award year, the Secretary calculates the earnings premium measure for a program by determining whether the median annual earnings of the students who completed the program exceed the earnings threshold.

(b) Median annual earnings; earnings threshold. (1) The Secretary obtains from a Federal agency with earnings data, under § 668.405, the most currently available median annual earnings of the students who completed the program during the cohort period and who are not excluded under paragraph (c) of this section; and

(2) The Secretary uses the median annual earnings of students with a high school diploma or GED using data from the Census Bureau to calculate the earnings threshold described in § 668.2.

(3) The Secretary determines the earnings thresholds and publishes the thresholds annually through a notice in the Federal Register .

(c) Exclusions. The Secretary excludes a student from the earnings premium measure calculation if the Secretary determines that—

(1) One or more of the student's Direct Loan Program loans are under consideration by the Secretary, or have been approved, for a discharge on the basis of the student's total and permanent disability, under 34 CFR 674.61, 682.402, or 685.212;

(2) The student was enrolled full-time in any other eligible program at the institution or at another institution during the calendar year for which the Secretary obtains earnings information under paragraph (b)(1) of this section;

(3) For undergraduate programs, the student completed a higher credentialed undergraduate program at the institution subsequent to completing the program as of the end of the most recently completed award year prior to the calculation of the earnings premium measure under this section;

(4) For graduate programs, the student completed a higher credentialed graduate program at the institution subsequent to completing the program as of the end of the most recently completed award year prior to the calculation of the earnings premium measure under this section;

(5) The student is enrolled in an approved prison education program;

(6) The student is enrolled in a comprehensive transition and postsecondary program; or

(7) The student died.

(d) Earnings premium measures not issued. The Secretary does not issue the earnings premium measure for a program under § 668.406 if—

(1) After applying the exclusions in paragraph (c) of this section, fewer than 30 students completed the program during the two-year or four-year cohort period; or

(2) The Federal agency with earnings data does not provide the median earnings for the program as provided under paragraph (b) of this section.

§ 668.405
Process for obtaining data and calculating D/E rates and earnings premium measure.

(a) Administrative data. In calculating the D/E rates and earnings premium measure for a program, the Secretary uses student enrollment, disbursement, and program data, or other data the institution is required to report to the Secretary to support its administration of, or participation in, the title IV, HEA programs. In accordance with procedures established by the Secretary, the institution must update or otherwise correct any reported data no later than 60 days after the end of an award year.

(b) Process overview. The Secretary uses the administrative data to—

(1) Compile a list of students who completed each program during the cohort period. The Secretary—

(i) Removes from those lists students who are excluded under § 668.403(e) or § 668.404(c);

(ii) Provides the list to institutions; and

(iii) Allows the institution to correct the information reported by the institution on which the list was based, no later than 60 days after the date the Secretary provides the list to the institution;

(2) Obtain from a Federal agency with earnings data the median annual earnings of the students on each list, as provided in paragraph (c) of this section; and

(3) Calculate the D/E rates and the earnings premium measure and provide them to the institution.

(c) Obtaining earnings data. For each list submitted to the Federal agency with earnings data, the agency returns to the Secretary—

(1) The median annual earnings of the students on the list whom the Federal agency with earnings data has matched to earnings data, in aggregate and not in individual form; and

(2) The number, but not the identities, of students on the list that the Federal agency with earnings data could not match.

(d) Calculating D/E rates and earnings premium measure. (1) If the Federal agency with earnings data includes reports from records of earnings on at least 30 students, the Secretary uses the median annual earnings provided by the Federal agency with earnings data to calculate the D/E rates and earnings premium measure for each program.

(2) If the Federal agency with earnings data reports that it was unable to match one or more of the students on the final list, the Secretary does not include in the calculation of the median loan debt for D/E rates the same number of students with the highest loan debts as the number of students whose earnings the Federal agency with earnings data did not match. For example, if the Federal agency with earnings data is unable to match three students out of 100 students, the Secretary orders by amount the debts of the 100 listed students and excludes from the D/E rates calculation the three largest loan debts.

§ 668.406
Determination of the D/E rates and earnings premium measure.

(a) For each award year for which the Secretary calculates D/E rates and the earnings premium measure for a program, the Secretary issues a notice of determination.

(b) The notice of determination informs the institution of the following:

(1) The D/E rates for each program as determined under § 668.403.

(2) The earnings premium measure for each program as determined under § 668.404.

(3) The determination by the Secretary of whether each program is passing or failing, as described in § 668.402, and the consequences of that determination.

(4) Whether the student acknowledgment is required under § 668.407.

(5) For GE programs, whether the institution is required to provide the student warning under § 668.605.

(6) For GE programs, whether the program could become ineligible under subpart S of this part based on its final D/E rates or earnings premium measure for the next award year for which D/E rates or the earnings premium measure are calculated for the program.

§ 668.407
Student acknowledgments.

(a) Beginning on July 1, 2026, if an eligible program, other than an undergraduate degree program, has failing D/E rates, the Secretary notifies the institution under § 668.406(b)(4) that student acknowledgments are required for such program in the manner specified in this section.

(b)(1) If student acknowledgements are required, prospective students must acknowledge that they have viewed the information provided through the program information website established and maintained by the Secretary described in § 668.43(d).

(2) The Department will administer and collect the acknowledgment from students through the program information website.

(3) Prospective students must provide such acknowledgments until:

(i) The Secretary notifies the institution pursuant to § 668.406 that the program has passing D/E rates; or

(ii) Three years after the institution was last notified that the program had failing D/E rates, whichever is earlier.

(c)(1) A prospective student must provide the acknowledgment before the institution enters into an agreement to enroll the student.

(2) The Secretary monitors the institution's compliance with the requirements in paragraph (c)(1) of this section through audits, program reviews, or other investigations.

(d) The acknowledgment required in paragraph (c)(1) of this section does not mitigate the institution's responsibility to provide accurate information to students concerning program status, nor will it be considered as dispositive evidence against a student's claim if applying for a loan discharge.

§ 668.408
Reporting requirements.

(a) Data elements. In accordance with procedures established by the Secretary, an institution offering any group of substantially similar programs, defined as all programs in the same four-digit CIP code at an institution, with 30 or more completers in total over the four most recent award years must report to the Department—

(1) For each GE program and eligible non-GE program, for its most recently completed award year—

(i) The name, CIP code, credential level, and length of the program;

(ii) Whether the program is programmatically accredited and, if so, the name of the accrediting agency;

(iii) Whether the program meets licensure requirements or prepares students to sit for a licensure examination in a particular occupation for each State in the institution's metropolitan statistical area;

(iv) The total number of students enrolled in the program during the most recently completed award year, including both recipients and non-recipients of title IV, HEA funds; and

(v) Whether the program is a qualifying graduate program whose students are required to complete postgraduate training programs, as described in the definition under § 668.2;

(2) For each student—

(i) Information needed to identify the student and the institution;

(ii) The date the student initially enrolled in the program;

(iii) The student's attendance dates and attendance status ( e.g., enrolled, withdrawn, or completed) in the program during the award year;

(iv) The student's enrollment status ( e.g., full time, three-quarter time, half time, less than half time) as of the first day of the student's enrollment in the program;

(v) The student's total annual cost of attendance (COA);

(vi) The total tuition and fees assessed to the student for the award year;

(vii) The student's residency tuition status by State or district;

(viii) The student's total annual allowance for books, supplies, and equipment from their COA under HEA section 472;

(ix) The student's total annual allowance for housing and food from their COA under HEA section 472;

(x) The amount of institutional grants and scholarships disbursed to the student;

(xi) The amount of other State, Tribal, or private grants disbursed to the student; and

(xii) The amount of any private education loans disbursed to the student for enrollment in the program that the institution is, or should reasonably be, aware of, including private education loans made by the institution;

(3) If the student completed or withdrew from the program during the award year—

(i) The date the student completed or withdrew from the program;

(ii) The total amount the student received from private education loans, as described in § 668.403(d)(1)(ii), for enrollment in the program that the institution is, or should reasonably be, aware of;

(iii) The total amount of institutional debt, as described in § 668.403(d)(1)(iii), the student owes any party after completing or withdrawing from the program;

(iv) The total amount of tuition and fees assessed the student for the student's entire enrollment in the program;

(v) The total amount of the allowances for books, supplies, and equipment included in the student's title IV, HEA COA for each award year in which the student was enrolled in the program, or a higher amount if assessed the student by the institution for such expenses; and

(vi) The total amount of institutional grants and scholarships provided for the student's entire enrollment in the program; and

(4) As described in a notice published by the Secretary in the Federal Register , any other information the Secretary requires the institution to report.

(b) Initial and annual reporting. (1) Except as provided under paragraph (c) of this section, an institution must report the information required under paragraph (a) of this section no later than—

(i) For programs other than qualifying graduate programs, July 31, following July 1, 2024, for the second through seventh award years prior to July 1, 2024;

(ii) For qualifying graduate programs, July 31, following July 1, 2024, for the second through eighth award years prior to July 1, 2024; and

(iii) For subsequent award years, October 1, following the end of the award year, unless the Secretary establishes different dates in a notice published in the Federal Register .

(2) For any award year, if an institution fails to provide all or some of the information required under paragraph (a) of this section, the institution must provide to the Secretary an explanation, acceptable to the Secretary, of why the institution failed to comply with any of the reporting requirements.

(c) Transitional reporting period and metrics. (1) For the first six years for which D/E rates and the earnings premium are calculated under this part, institutions may opt to report the information required under paragraph (a) of this section for its eligible programs either—

(i) For the time periods described in paragraphs (b)(1)(i) and (ii) of this section; or

(ii) For only the two most recently completed award years.

(2) If an institution provides transitional reporting under paragraph (c)(1)(ii) of this section, the Department will calculate transitional D/E rates and earnings premium measures using the median debt for the period reported and the earnings for six years.

§ 668.409
Severability.

If any provision of this subpart or its application to any person, act, or practice is held invalid, the remainder of this part and subpart, and the application of this subpart's provisions to any other person, act, or practice, will not be affected thereby.

9. Add subpart S to read as follows:

Subpart S—Gainful Employment (GE)
668.601
Gainful employment (GE) scope and purpose.
668.602
Gainful employment criteria.
668.603
Ineligible GE programs.
668.604
Certification requirements for GE programs.
668.605
Student warnings.
668.606
Severability.

Subpart S—Gainful Employment (GE)

§ 668.601
Gainful employment (GE) scope and purpose.

(a) General. Except as provided under paragraph (b) of this section, this subpart applies to an educational program offered by an eligible institution that prepares students for gainful employment in a recognized occupation and establishes rules and procedures under which the Secretary determines that the program is eligible for title IV, HEA program funds.

(b) Applicability. (1) This subpart does not apply to programs offered by institutions located in U.S. Territories or freely associated states.

(2) For each award year that the Secretary calculates D/E rates or the earnings premium measure under § 668.402, this subpart does not apply to an institution if, over the most recently completed four award years, it offered no groups of substantially similar programs, defined as all programs in the same four-digit CIP code at an institution, with 30 or more completers in total.

§ 668.602
Gainful employment criteria.

(a) A GE program provides training that prepares students for gainful employment in a recognized occupation if the program—

(1) Satisfies the applicable certification requirements in § 668.604;

(2) Is not a failing program under the D/E rates measure in § 668.402 in two out of any three consecutive award years for which the program's D/E rates are calculated; and

(3) Is not a failing program under the earnings premium measure in § 668.402 in two out of any three consecutive award years for which the program's earnings premium measure is calculated.

(b) If the Secretary does not calculate or issue D/E rates for a program for an award year, the program receives no result under the D/E rates for that award year and remains in the same status under the D/E rates as the previous award year.

(c) In determining a program's eligibility, the Secretary disregards any D/E rates that were calculated more than five calculation years prior.

(d) If the Secretary does not calculate or issue earnings premium measures for a program for an award year, the program receives no result under the earnings premium measure for that award year and remains in the same status under the earnings premium measure as the previous award year.

(e) In determining a program's eligibility, the Secretary disregards any earnings premium that was calculated more than five years prior.

§ 668.603
Ineligible GE programs.

(a) Ineligible programs. If a GE program is a failing program under the D/E rates measure in § 668.402 in two out of any three consecutive award years for which the program's D/E rates are calculated, or the earnings premium measure in § 668.402 in two out of any three consecutive award years for which the program's earnings premium measure is calculated, the program is ineligible and its participation in the title IV, HEA programs ends upon the earliest of—

(1) The issuance of a new Eligibility and Certification Approval Report that does not include that program;

(2) The completion of a termination action of program eligibility, if an action is initiated under subpart G of this part; or

(3) A revocation of program eligibility if the institution is provisionally certified.

(b) Basis for appeal. If the Secretary initiates an action under paragraph (a)(2) of this section, the institution may initiate an appeal under subpart G of this part if it believes the Secretary erred in the calculation of the program's D/E rates under § 668.403 or the earnings premium measure under § 668.404. Institutions may not dispute a program's ineligibility based upon its D/E rates or the earnings premium measure except as described in this paragraph (b).

(c) Restrictions —(1) Ineligible program. Except as provided in § 668.26(d), an institution may not disburse title IV, HEA program funds to students enrolled in an ineligible program.

(2) Period of ineligibility. An institution may not seek to reestablish the eligibility of a failing GE program that it discontinued voluntarily either before or after D/E rates or the earnings premium measure are issued for that program, or reestablish the eligibility of a program that is ineligible under theD/E rates or the earnings premium measure, until three years following the earlier of the date the program loses eligibility under paragraph (a) of this section or the date the institution voluntarily discontinued the failing program.

(3) Restoring eligibility. An ineligible program, or a failing program that an institution voluntarily discontinues, remains ineligible until the institution establishes the eligibility of that program under § 668.604(c).

§ 668.604
Certification requirements for GE programs.

(a) Transitional certification for existing programs. (1) Except as provided in paragraph (a)(2) of this section, an institution must provide to the Secretary no later than December 31, 2024, in accordance with procedures established by the Secretary, a certification signed by its most senior executive officer that each of its currently eligible GE programs included on its Eligibility and Certification Approval Report meets the requirements of paragraph (d) of this section. The Secretary accepts the certification as an addendum to the institution's program participation agreement with the Secretary under § 668.14.

(2) If an institution makes the certification in its program participation agreement pursuant to paragraph (b) of this section between July 1 and December 31, 2024, it is not required to provide the transitional certification under this paragraph (a).

(b) Program participation agreement certification.

As a condition of its continued participation in the title IV, HEA programs, an institution must certify in its program participation agreement with the Secretary under § 668.14 that each of its currently eligible GE programs included on its Eligibility and Certification Approval Report meets the requirements of paragraph (d) of this section. As provided under 34 CFR 600.21(a)(11)(vi), an institution must update the certification within 10 days if there are any changes in the approvals for a program, or other changes for a program that render an existing certification no longer accurate.

(c) Establishing eligibility and disbursing fund s. (1) An institution establishes a GE program's eligibility for title IV, HEA program funds by updating the list of the institution's eligible programs maintained by the Department to include that program, as provided under 34 CFR 600.21(a)(11)(i). By updating the list of the institution's eligible programs, the institution affirms that the program satisfies the certification requirements in paragraph (d) of this section. Except as provided in paragraph (c)(2) of this section, after the institution updates its list of eligible programs, the institution may disburse title IV, HEA program funds to students enrolled in that program.

(2) An institution may not update its list of eligible programs to include a GE program, or a GE program that is substantially similar to a failing program that the institution voluntarily discontinued or became ineligible as described in § 668.603(c), that was subject to the three-year loss of eligibility under § 668.603(c), until that three-year period expires.

(d) GE program eligibility certifications. An institution certifies for each eligible GE program included on its Eligibility and Certification Approval Report, at the time and in the form specified in this section, that such program is approved by a recognized accrediting agency or is otherwise included in the institution's accreditation by its recognized accrediting agency, or, if the institution is a public postsecondary vocational institution, the program is approved by a recognized State agency for the approval of public postsecondary vocational education in lieu of accreditation.

§ 668.605
Student warnings.

(a) Events requiring a warning to students and prospective students. Beginning on July 1, 2026, the institution must provide a warning with respect to a GE program to students and prospective students for any year for which the Secretary notifies an institution that the GE program could become ineligible under this subpart based on its final D/E rates or earnings premium measure for the next award year for which D/E rates or the earnings premium measure are calculated for the GE program.

(b) Subsequent warning. If a student or prospective student receives a warning under paragraph (a) of this section with respect to a GE program, but does not seek to enroll until more than 12 months after receiving the warning, the institution must again provide the warning to the student or prospective student, unless, since providing the initial warning, the program has passed both the D/E rates and earnings premium measures for the two most recent consecutive award years in which the metrics were calculated for the program.

(c) Content of warning. The institution must provide in the warning—

(1) A warning, as specified by the Secretary in a notice published in the Federal Register , that—

(i) The program has not passed standards established by the U.S. Department of Education based on the amounts students borrow for enrollment in the program and their reported earnings, as applicable; and

(ii) The program could lose access to Federal grants and loans based on the next calculated program metrics;

(2) The relevant information to access the program information website maintained by the Secretary described in § 668.43(d);

(3) A statement that the student must acknowledge having viewed the warning through the program information website before the institution may disburse any title IV, HEA funds to the student;

(4) A description of the academic and financial options available to students to continue their education in another program at the institution, including whether the students could transfer credits earned in the program to another program at the institution and which course credits would transfer, in the event that the program loses eligibility for title IV, HEA program funds;

(5) An indication of whether, in the event that the program loses eligibility for title IV, HEA program funds, the institution will—

(i) Continue to provide instruction in the program to allow students to complete the program; and

(ii) Refund the tuition, fees, and other required charges paid to the institution by, or on behalf of, students for enrollment in the program; and

(6) An explanation of whether, if the program loses eligibility for title IV, HEA program funds, the students could transfer credits earned in the program to another institution in accordance with an established articulation agreement or teach-out plan or agreement.

(d) Alternative languages. In addition to providing the English-language warning, the institution must also provide translations of the English-language student warning for those students and prospective students who have limited proficiency in English.

(e) Delivery to enrolled students. An institution must provide the warning required under this section in writing, by hand delivery, mail, or electronic means, to each student enrolled in the program no later than 30 days after the date of the Secretary's notice of determination under § 668.406 and maintain documentation of its efforts to provide that warning. The warning must be the only substantive content contained in these written communications.

(f) Delivery to prospective students. (1) An institution must provide the warning as required under this section to each prospective student or to each third party acting on behalf of the prospective student at the first contact about the program between the institution and the student or the third party acting on behalf of the student by—

(i) Hand-delivering the warning as a separate document to the prospective student or third party, individually or as part of a group presentation;

(ii) Sending the warning to the primary email address used by the institution for communicating with the prospective student or third party about the program, provided that the warning is the only substantive content in the email and that the warning is sent by a different method of delivery if the institution receives a response that the email could not be delivered; or

(iii) Providing the warning orally to the student or third party if the contact is by telephone.

(2) An institution may not enroll, register, or enter into a financial commitment with the prospective student with respect to the program earlier than three business days after the institution delivers the warning as described in this paragraph (f).

(g) Acknowledgment prior to enrollment and disbursement. An institution may not allow a prospective student seeking title IV, HEA assistance to sign an enrollment agreement, complete registration, or make a financial commitment to the institution, or disburse title IV, HEA funds to the student until the student or prospective student completes the acknowledgment described in paragraph (c)(3) of this section.

(h) Discharge claims. The provision of a student warning or the acknowledgment described in paragraph (c)(3) of this section does not mitigate the institution's responsibility to provide accurate information to students concerning program status, nor will it be considered as dispositive evidence against a student's claim if applying for a loan discharge.

§ 668.606
Severability.

If any provision of this subpart or its application to any person, act, or practice is held invalid, the remainder of this part and subpart, and the application of this subpart's provisions to any other person, act, or practice, will not be affected thereby.

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[FR Doc. 2023–20385 Filed 9–28–23; 8:45 am]

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