70004 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

1Note 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. 

2Barrow, 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. 

3Oreopoulos, P. & Salvanes, K.G. (2011). 

Priceless: The Nonpecuniary Benefits of Schooling. 

Journal of Economic Perspectives, 25(1), 159–184. 

4Moretti, E. (2004). Workers’ Education, 

Spillovers, and Productivity: Evidence from PlantLevel Production Functions. American Economic 

Review, 94(3), 656–690. 

5 Dee, T.S. (2004). Are There Civic Returns to 

Education? Journal of Public Economics, 88(9–10), 

1697–1720. 

6Currie, 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. 

7Hendren, N. & Sprung-Keyser, B. (2020). A 

Unified Welfare Analysis of Government Policies. 

The Quarterly Journal of Economics, 135(3), 1209– 

1318. 

8Hoxby, 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. 

9Cellini, 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). 

10For 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/initialfresh-start-program-changes-followed-by-increasedcredit-scores-for-affected-borrowers/). 

DEPARTMENT OF EDUCATION 

34 CFR Parts 600 and 668 

[Docket ID ED–2023–OPE–0089] 

RIN 1840–AD57 

Financial Value Transparency and 

Gainful Employment 

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.1

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,2 and leads to 

myriad non-financial benefits including 

better health, job satisfaction, and 

overall happiness.3 In addition, 

increasing the number of individuals 

with postsecondary education creates 

social benefits, including productivity 

spillovers from a better educated and 

more flexible workforce,4 increased 

civic participation,5 improvements in 

health and well-being for the next 

generation,6 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.7

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.8 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.9 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. 

While increased borrowing is 

indicative of higher education costs-ofattendance, 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.10 From the Federal 

Government’s perspective, if borrowers 

earn less, then they are also entitled to 

repay less of their loans under IncomeDriven 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 


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11Baker, 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-centerchalkboard/2021/12/14/why-information-alone-isnot-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). 12 88 FR 32300, 32306 (May 19, 2023). 

postsecondary investments financed 

with student loans. 

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.11

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.12

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. 


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70006 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

13U.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). 

14See 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&overlay

TableId=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). 

15U.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). 

16U.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/p2324). 

17Cameron, 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). 

18Compare 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). 

19U.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). 

20Federal 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). 

21California 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/attorneygeneral-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 (https://www.ed.gov/news/ 

press-releases/biden-harris-administrationapproves-72-million-borrower-defense-dischargesover-2300-borrowers-who-attended-ashforduniversity). 

22U.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/schoolowner-and-ceo-convicted-federal-financial-aidfraud-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/schooland-owner-pay-over-1-million-resolve-allegationsattempts-improperly-influence). 

23Office 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/americanmilitary-university-pays-270000-for-alleged-failureto-disclose-job-prospects-high-pressure-enrollmenttactics). 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-DCWPSettles-With-ASA-College-for-DeceptiveAdvertising.page). 

24See Tables 4.4, 4.5, 4.8, and 4.9 below. 

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.13

The 2011 and 2014 rules were issued 

during a time of growth at private forprofit 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 2017–18.14 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 forprofit colleges in 2020–21 was at the 

same level as in 2016–17.15

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 lessthan-two-year institutions was 60 

percent at private for-profit institutions 

versus 10 percent at public 

institutions.16 Data from 2019–20 show 

that 63 percent of students in less-thantwo-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.17 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 2011–12.18

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 

2015.19 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 forprofit colleges (a reduction of 2.1 

percentage points versus 1.1 percentage 

points).20 And this is despite the closure 

of large for-profit colleges with poor 

track records, such as ITT Technical 

Institute and Corinthian Colleges. 

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 2020.21 The 

U.S. Department of Justice has also 

continued to settle cases involving forprofit colleges.22 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.23

According to the Department’s data 

and analyses, which are presented in 

the RIA of this final rule,24 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. 


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25See the NPRM, 88 FR 32300, 32341 (May 19, 

2023), for a detailed discussion of how these 

regulations are intended to be severable. 

26 20 U.S.C. 1221e–3. 

27 20 U.S.C. 3474. 

28 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). 

29See, for example, 20 U.S.C. 1015(e). 

30 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. 

31See, 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. 

32A 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 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. 

In light of the HEA differentiation 

between career training (GE) programs 

and other eligible programs, through 

statutory language that defines title IVeligible 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,25 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. 

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.26 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.27

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.28 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. 

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,29 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.30 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.31 Educational 

institutions have been distributing 

information to students at the direction 

of the Department and in accord with 

the applicable statutes for decades.32

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 


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33 20 U.S.C. 1001(b)(1); 20 U.S.C. 1002(b)(1)(A)(i), 

(c)(1)(A). 

34 20 U.S.C. 1088(b)(1)(A)(i). 

35See 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). 

36 88 FR 32300, 32325 (May 19, 2023). 

37 88 FR 32300, 32343 (May 19, 2023). 

recognized occupation.’’ 33 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.’’ 34 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-bysection 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,35

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. 

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 debtburden 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.36

(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.37

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 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70009 

programs (CIP) code,’’ ‘‘cohort period,’’ 

‘‘credential level,’’ ‘‘debt-to-earnings 

rates (D/E rates),’’ ‘‘discretionary debtto-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-financialvalue postsecondary programs to nonenrollment. 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 lowfinancial-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 


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70010 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

38 88 FR 32300, 32306 (May 19, 2023). 

39 88 FR 32300, 32392 (May 19, 2023). 

40 88 FR 32300, 32317 (May 19, 2023). 

41See 83 FR 40167, 40168 (Aug. 14, 2018). 

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,38 the 

relevant data available,39 and the key 

regulatory changes that the Department 

was proposing,40 including the changes 

from the 2019 Prior Rule currently in 

effect, and the differences between the 

NPRM’s proposal and the nowrescinded 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. 

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.41 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. 

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. NonFederal 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 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70011 

42 88 FR 32300, 32321–22 (May 19, 2023). 

43 20 U.S.C. 1221e–3. 

44 20 U.S.C. 3474. 

45 20 U.S.C. 1001(b)(1); 20 U.S.C. 1002(b)(1)(A)(i), 

(c)(1)(A). 

46 20 U.S.C. 1088(b). 

47Several 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-currentand-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-households202205.pdf). 

48For 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). 

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 42 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. 

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.43 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.44 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.’’ 45 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.’’ 46

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 47— 

threatening one of the key pathways to 

upward mobility in the United States. 

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).48 We believe 

the D/E and EP measures, singly and 

taken together, will help promote the 


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49Some 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. 

50Ass’n of Priv. Sector Colleges & Universities v. 

Duncan, 640 F. App’x 5, 8 (D.C. Cir. 2016) (per 

curiam). 

51Ass’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)). 

52Ass’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). 

53See 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. 

54See 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). 

55S. 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’’). 

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. 

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.49 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. 

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.’’ 50 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,’’ 51 and that ‘‘examining [GE] 

programs’ outputs in terms of earnings 

and debts’’ is consistent with the HEA.52

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 wellpositioned 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.53

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.54

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.’’ 55

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 


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56 20 U.S.C. 1071(a)(1). 

57 20 U.S.C. 1078(c) (Federal reinsurance for 

default claim payments); 20 U.S.C. 1080 (Federal 

insurance for default claims). 

58Public Law 111–152. 

59 88 FR 32300, 32306 (May 19, 2023). 

60 88 FR 32300, 32392 (May 19, 2023). 

61 88 FR 32300, 32317 (May 19, 2023). 

62See, for example, FCC v. Fox Television 

Stations, Inc., 556 U.S. 502, 515–16 (2009). 

63 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. 

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.56 Under either HEA component, 

taxpayers and the Government assume 

the direct financial risk of default.57

Since the Health Care and 

Reconciliation Act of 2010,58 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. 

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,59 the relevant data 

available,60 and the major changes 

proposed in that document,61 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.62

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.63

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 


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70014 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

64See 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). 65See, for example, 88 FR 32300, 32308, 32325– 

28, 32343–44 (May 19, 2023). Those discussions 

also address the D/E rates measure. 66 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. 

67Ass’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)). 

68See, for example, 88 FR 32300, 32308, 32333, 

32327 (May 19, 2023). 

69Regarding 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. 

70See 88 FR 32300, 32307–11 (May 19, 2023). 

71See, 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/wpcontent/uploads/2020/11/20210603-MatsTurner.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_HSEarningsUpdated.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-toearnings-premium-a-new-way-of-measuring-returnon-investment-in-higher-ed). For further discussion 

of such research, see the Regulatory Impact 

Analysis below. 

72See, 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. 

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 debtto-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.64 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.65 In 

this discussion, we summarize several 

connected reasons for adopting the EP 

measure for GE program eligibility in 

these final rules. 

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.66 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.’’ 67 At 

minimum, the statutory language 

permits the conclusion that the 

Department adopts here. 

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.68 The HEA generally requires 

students who receive title IV assistance 

to have already completed a high school 

education,69 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 posthigh school gain, in part, with an 

administrable test that reflects earnings 

beyond a typical high school graduate. 

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,70 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. 

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.71 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.72


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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. 

73See, for example, polling evidence in https:// 

www.wsj.com/articles/americans-are-losing-faithin-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-beingus-households-202305.pdf). 

74That figure is lower than the minimum wage 

in 15 States. See https://www.dol.gov/agencies/ 

whd/mw-consolidated. 

75See 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. 

76For 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. 

77See 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/). 

78See, for example, 88 FR 32300, 32307–09 (May 

19, 2023). 79See 88 FR 1894 (Jan. 11, 2023). The 

Department’s final rule for IDR can be found at 88 

FR 43820 (July 10, 2023). 80See Table 2.10 in the RIA for this document. 

Furthermore, there is increasing public 

recognition that some higher education 

programs are not ‘‘worth it’’ and do not 

promote economic mobility.73 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. 

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.74 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.75 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.76

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. 

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.77 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. 

In addition, we reaffirm that the EP 

measure will help protect taxpayers.78

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 welldesigned 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 

2023.79 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.80

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. 

Thus, the EP and D/E measures serve 

some of the same purposes, but we 

observe again that they measure 

importantly distinct dimensions of 


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81See, 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). 

82 142 S. Ct. 2587 (2022). 

83See, 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). 

84 88 FR 32300, 32306 (May 19, 2023). 

85See cases cited in notes 50–52 above, within 

that earlier discussion of authority for the GE 

program accountability framework. 

86Compare 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). 

87Under 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. 

88Compare 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 

gainful employment.81 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 debtaffordability, 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. 

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 82 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. 

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.83 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. 

As discussed above and in the 

NPRM,84 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.85 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.86

And far from taking any step toward 

mandating specific curricula when 

institutions prefer other educational 

strategies,87 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.88


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facilities is what [the Secretary of Health and 

Human Services] does.’’). 

89Cellini, 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. 

90Compare 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). 

91That 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). 

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.89 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 threequarters 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. 

Those predicted effects do not 

establish the kind of transformation or 

upheaval in higher education that might 

trigger the major questions doctrine.90

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. 

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 outcomebased 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.91 Congress did not, in 


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92Contrast 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.’’). 

93See 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.’’). 

94 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). 

95 20 U.S.C. 1094(c)(3)(A). 

96 88 FR 32300, 32344 (May 19, 2023). 

97Association of Private Sector Colleges and 

Universities (APSCU) v. Duncan, 870 F. Supp. 2d 

133, 150 (D.D.C. 2012). The adjudication involved 

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.92 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.93

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.’’ 94 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.’’ 95 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. 

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 outcomebased framework, noting that outcomebased 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,96 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. 

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.97


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the question whether a program in Jewish culture 

prepared students enrolled in the program for 

gainful employment in a recognized occupation. 

98See 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. 

99 88 FR 32300, 32306–11 (May 19, 2023). 

100 88 FR 32300, 32316 (May 19, 2023). 

101Our conclusions regarding reliance interests 

are guided by judicial opinions including FCC v. 

Fox Television Stations, Inc., 556 U.S. 502, 515–16 

(2009). 

Therefore, the Department did not 

depart from the ALJ’s interpretation 

when the Department adopted outcomebased measures for GE programs in the 

2011 Prior Rule.98 Nor is the 

Department departing from that 

interpretation with these regulations. 

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.99

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. 

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,100 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.101 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. 

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 ‘‘highdebt-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. 


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102 88 FR 32300, 32322 (May 19, 2023). 

103Steffel, 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). 

104Baum, Sandy & Schwartz, Saul (2006). How 

Much Debt is Too Much? Defining Benchmarks for 

Managing Student Debt (eric.ed.gov/?id=ED562688). 

105Trostel, 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-notjust-the-money.pdf). 

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.102 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.103 The 

Department believes that the financial 

value transparency framework serves as 

an evidence-based approach to provide 

relevant, trusted, and timely 

information for student decisionmaking. 

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,104 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. 

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 underresourced 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 wellbeing; 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 105 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. 

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 


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106See Nat’l Ed. Ass’n (2022). Teacher Salary 

Benchmarks (www.nea.org/resource-library/teachersalary-benchmarks). 

107See Nat’l Ed. Ass’n (2022). Teacher Salary 

Benchmarks (www.nea.org/resource-library/teachersalary-benchmarks). 

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 $40,000.106

Even States with lower salaries have 

average starting salaries at least $5,000 

higher than the State’s EP threshold.107

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 


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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 


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108See 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/). 

109Blagg, 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). 

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.108 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. 

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 upfront 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.109 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 


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70024 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

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. 

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 


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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 lowperforming 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 financialvalue measures in the proposed 

regulations. Commenters also suggested 

the Department should work with the 

higher education community to develop 


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70026 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

110 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). 

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-fitsall’’ 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.’’ 110 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. 

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 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70027 

111 87 FR 65426 (Oct. 28, 2022). 112See 88 FR 32300, 32333 (May 19, 2023). 

113According 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/samplesize-and-data-quality/coverage-rates/index.php. 

These figures indicate that Puerto Rico is an outlier. 

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.111

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 nonGE 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.112 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. 

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.113 Moreover, the 

Federal Poverty Line (officially known 

as the poverty guidelines), used in the 

calculation of discretionary debt-toearnings 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. 

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 


ddrumheller on DSK120RN23PROD with RULES2
70028 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

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 postgraduation 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 nondegree 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 


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114Reynolds v. United States, 292 U.S. 443, 449 

(1934). 

115Career College Ass’n v. Riley, No. 94–1214, 

1994 WL 396294 (D.D.C. July 19, 1994). 

116Ass’n of Accredited Cosmetology Schools v. 

Alexander, 979 F.2d 859, 860–62 (D.C. Cir. 1992). 

117Pro Schools Inc. v. Riley, 824 F. Supp. 1314 

(E.D. Wis. 1993). 

118See, for example, Ass’n of Accredited 

Cosmetology Schools, 979 F.2d at 865. 

119 870 F. Supp. 2d at 151–52. 

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.’’ 114 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.115 This 

principle has been confirmed in the 

context of the Department’s use of 

institutional cohort default rates.116 117

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.118 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.119

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-financialvalue to high-financial-value programs 

or, in some cases, away from lowfinancial-value postsecondary programs 

to non-enrollment. It is also possible 

that some students will shift from lowfinancial-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 nonparticipating programs, making it 

difficult to estimate the consequences of 

such transfers (although research cited 

in the RIA finds that among 

cosmetology programs, nonVerDate Sep<11>2014 21:07 Oct 06, 2023 Jkt 262001 PO 00000 Frm 00027 Fmt 4701 Sfmt 4700 E:\FR\FM\10OCR2.SGM 10OCR2

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70030 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

120 88 FR 32300, 32306 (May 19, 2023). 

121See the section in the RIA titled ‘‘Alternative 

Options Exist for Students to Enroll in High-Value 

Programs.’’ 

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.120 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. 

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 twoyear 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.121

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. 

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 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70031 

122 88 FR 43820 (July 10, 2023). 

123See, 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/). 

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,122

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. 

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 lowincome 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 programlevel 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.123 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 


ddrumheller on DSK120RN23PROD with RULES2
70032 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

124See 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/). 

125The referenced report is available here: 

https://freopp.org/accountable-or-not-evaluatingthe-biden-administrations-proposed-gainfulemployment-framework-a49231683263. 

Institutions (MSIs), in terms of 

increasing the number of programs at 

these institutions that pass the 

metrics.124

Even using the data in the 2022 PPD, 

which does not have that cap applied 

(since the cap will rely on institutionlevel 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. 

BILLING CODE 4000–01–P 

BILLING CODE 4000–01–C 

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,125 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 


ddrumheller on DSK120RN23PROD with RULES2ER10OC23.000</GPH>

Figure 1.1: Median debt and Pell receipt among Bachelor of Arts 

50,000 

40,000 

:1S 

(I) 

0 

! 30,000 

l 

.i 

,:J 20,000 (I) 

:; 

10,000 

0 

(BA) programs 

Relationship Between the Share of Students in a Program Who Receive Pell and Median Debt Levels 

For All Bacnelor's Degree Programs in the Program Perfonnance Data (PPD) 

0 

2015-2017 Average of Indicator for Student Pell forthis qedential 

Relationship~ Pell.and Debt 

LowestTuition Quartile • • •• • HighestTuition Quartile -· All Tuition Levels 
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70033 

126See ‘‘Alternative Earnings Threshold’’ in the 

‘‘Alternatives Considered’’ section of the RIA. 

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.126

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 


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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-toearnings 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. 


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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 postgraduate 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 forprofit 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 wellpaying 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 sixdigit programs offered at a school, and 

that if the program defined at a fourdigit 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 


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127 88 FR 32300, 32332 (May 19, 2023). 

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 rollup 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 sixdigit 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 sixdigit 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 carveouts 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. . . .’’ 127

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. 


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128Under 34 CFR 668.2(b), a ‘‘Direct Loan 

Program loan’’ is a loan made under the William D. 

Ford Federal Direct Loan Program. 

129These data are available at https://

lehd.ces.census.gov/data/pseo_experimental.html. 

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 nonGE 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).128 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. 

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.129 The correlations of 

programs’ 1-year and 5-year postgraduation 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 


ddrumheller on DSK120RN23PROD with RULES2
70038 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

130We replicated these analyses focusing on 

earnings growth from 1 year after graduation to 5 

years after graduation and found qualitatively 

similar results. 

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 programlevel 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.130 Figure 

1.2 below compares these estimated 3- 

year median earnings (on the x-axis) to 

the 10-year median earnings (on the yaxis), 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. 

BILLING CODE 4000–01–P 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70039 

131See, for example, Salsberg et al. (2020). The 

Social Work Profession: Findings from Three Years 

of Surveys of New Social Workers. 

132See, for example, Council on Social Work 

Education (2022). Annual Statistics on Social Work 

Education in the United States. 

133See, for example, Association of Social Work 

Boards (2022). 2022 ASWB Exam Pass Rate 

Analysis Final Report. 

BILLING CODE 4000–01–C 

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.131 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.132 The second column 

shows the number of first-time licensing 

exam takers, based on data from the 

Association of Social Work Boards.133

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. 

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 


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ti) 

Cl 

C 

·c 

.... 

Cll 

w 

C 

Cll 

'o 

a.> 

~ 

.... 

Cll 

~ I 

0 

..-

Figure 1.2: 3- and 10-Year Median Earnings for All Graduate 

Programs, Highlighting Programs in Medicine and Health 

400000 

300000 

200000 

100000 

0 

0 

Professions 

50000 100000 150000 200000 

3-Year Median Earnings 

c Medicine: Professional 

• Health Professions: Masters and Research Doctorate 

All Other 

-- Best-Fit Line 

250000 
70040 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

134There 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. 

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 tenyears) 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.134

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 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70041 

135 88 FR 32300, 32335 (May 29, 2023). 

136The 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/PLAW117publ2/html/PLAW-117publ2.htm). 

137 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. 

138 88 FR 32300, 32335 (May 19, 2023). 

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 incomedriven 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.135 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.136 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.137 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.138

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 incomedriven 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 


ddrumheller on DSK120RN23PROD with RULES2
70042 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

139See 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. 

140 88 FR 32300, 32329–35 (May 19, 2023). 

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.139

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. 

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.140

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. 

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 taxpayersupported 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 


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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 selfemployment 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 noncompleters but argued against it for the 

purposes of constructing a consumer 

information tool. The remaining 

commenters opposed the use of noncompleters 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 


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141 88 FR 32300, 32311 (May 19, 2023). 

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,141 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. 

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 


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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 poorperforming 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-toearnings 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 


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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 industrywide 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 fouryear 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 


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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 


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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 


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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-toearnings 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 highercredentialed programs (e.g., bachelor’s 

and graduate degree programs) are likely 

to have incurred more loan debt than 

borrowers who enrolled in lowercredentialed 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 


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70050 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

142The 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/nhscloan-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-tocongress/report-congress-nhsc-2021.pdf). 

143See 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-enrollmentgraduates-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). 

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 incomedriven 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.142 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.143 This 

means that these loan repayment 

programs are used by only a fraction of 

students. 

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 


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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 highdebt 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 


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70052 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

144 88 FR 32300, 32325 (May 19, 2023). 

145 79 FR 64889, 64944–45 (Oct. 31, 2014). 

146See 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). 

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 144 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. 

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.145

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.146

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 


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147 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). 

148See https://www.urban.org/urban-wire/devosmisrepresents-evidence-seeking-gainfulemployment-deregulation. 

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.147

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 debtburden. 

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.148

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 


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70054 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

149See 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-ValueVariation-and-Trends.PDF)—among other 

numerous examples. 

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 nonborrowers 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 postsecondary credential in research 

literature.149


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150Executive 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. 

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.’’ 150 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. 

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 nonstatistical 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 nonmetropolitan 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 


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TABLE 1.4—MEDIAN INCOME FOR HS GRADS 25–34 IN LABOR FORCE, BY STATE AND METRO STATUS—Continued 

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 

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 Statelevel 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. 


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151See the Census’s own analysis of poverty 

measurement in college towns here: 

www.census.gov/library/stories/2018/10/offcampus-college-students-poverty.html. 

LARGEST INSTITUTIONS WITH MAIN CAMPUSES IN PERSISTENT POVERTY COUNTIES IN TERMS OF ENROLLMENT— 

Continued 

Institution name 6-Digit 

OPEID 

Total 

enrollment 

Number of 

programs Location 

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 withincounty 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.151 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. 

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 


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70058 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

152See, for example, 20 U.S.C. 1098bb(a)(2)(E). 

153See www.census.gov/content/dam/Census/ 

library/working-papers/2016/acs/2016_Ohara_

01.pdf. 

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 subState 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.152

The Department is not convinced that 

the rules here should be further adapted 

to address such exceptional 

circumstances. 

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.153 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 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70059 

154For 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). 

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- postearnings 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.154 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. 


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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 


ddrumheller on DSK120RN23PROD with RULES2ER10OC23.002</GPH>

Figure 1.3: Pre-post Earnings Gains Measure and Student Age 

0 

2 A ~ • 

Share Aged >=24 at time of FAFSA 
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70061 

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 fourdigit 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 


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70062 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

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 


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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 


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155 studentprivacy.ed.gov/sites/default/files/ 

resource_document/file/Best%20Practices%

20for%20Data%20Destruction%20%282019-3- 

26%29.pdf. 

156See, for example, 88 FR 32427. 

157 88 FR 32300, 32306 (May 19, 2023). 

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.155 The reporting 

requirements established under this rule 

constitute such a requirement that 

necessitates the retention of relevant 

records, potentially beyond the threeyear periods referenced in § 668.24(e). 

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.156 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. 

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,157 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 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70065 

158www.whitehouse.gov/cea/written-materials/ 

2023/04/17/the-labor-supply-rebound-from-thepandemic. 

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. 

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.158 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. 


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70066 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

159See 88 FR 17777 (Mar. 24, 2023). 

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.159

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 nonFederal 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. 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70067 

160Rachel 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). 

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.’’ 160 We believe it would be 

unnecessarily burdensome to require 

institutions to report this supplementary 

information, and that such burden 


ddrumheller on DSK120RN23PROD with RULES2
70068 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

161www2.ed.gov/policy/highered/reg/ 

hearulemaking/2021/3ge.pdf. 

162www2.ed.gov/policy/highered/reg/ 

hearulemaking/2021/isspap3gainempl.pdf. 

would outweigh the benefits to 

students. 

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 161 and three 162 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 underresourced 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 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70069 

163Section 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. 

164See 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.’’). 

165See, 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. 

166See 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). 

167See 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). 

168See 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). 

169Contrast 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. 

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.163

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,164 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. 

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.165 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.166 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.167

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 taxfinanced resources, as well as 

innovation in educational programs, by 

making comparable information on 

program features and results readily 

available.168 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.169 As we discuss 

elsewhere in this document, institutions 

may correct errors in certain 

calculations. 

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 


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170 79 FR 64890, 64967 (Oct. 31, 2014). 

171Blagg, 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-informationhigher-education. 

172Hurwitz, 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. 

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.170 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.’’ 

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 taxfinanced 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 betterrounded 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 171 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 172 found the College Scorecard 

influenced the college search behavior 

of some higher income students but had 

little effect on lower income students. 

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 


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173 20 U.S.C. 1015c. 

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 134 173 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 nonGE 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 nonGE 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 


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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 ontime 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 firstgeneration 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-debtburden 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 


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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 shortterm 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 degreegranting 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 


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174Cellini, S.R. (2012). For Profit Higher 

Education: An Assessment of Costs and Benefits. 

National Tax Journal, 65 (1):153–180. 

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 forprofit 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.174 This analysis estimated 

taxpayer contributions, such as 

government grants, of $7,600 per year 

for for-profit institutions and $11,400 

for community colleges. 

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 


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175Carrel, S. & Sacerdote, B. (2017). Why Do 

College-Going Interventions Work? American 

Economic Journal; Applied Economics. 1(3) 124– 

151. 

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.175

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. 

Comments: 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 


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176 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.’’ 

177 88 FR 32300, 32336 (May 19, 2023). 

178We 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. 

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 poorperforming 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 decisionmaking 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,176

not enrolled students, must give 

acknowledgments when the relevant 

program has substandard results 

regarding debt burdens under the debtto-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. 

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,177

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.178

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 


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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 decisionmaking 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-debtburden 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-enrollmentagreement 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 


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179 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. 

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 lowincome 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,179 and they are 

limited to programs that do not lead to 


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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. 

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 nonGE programs, but opined that 

acknowledgments should also be 

required when students enter lowearning 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 nonGE 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 nonGE 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 


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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 minimumlength 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 fiveyear 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 nonGE 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 reenroll 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 


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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 


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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 decisionmaking 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 

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180 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. 

181See, 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). 

182See, 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. 

183See 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). 

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.180

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.181 Courts 

also have recognized broader 

government authority to require 

disclosure of accurate information about 

services and products,182 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.183

Whatever the applicable test, the GE 

warning rule will satisfy it. 

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) 


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184See 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). 

185Contrast 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. 

186 20 U.S.C. 1087d(a)(2). 

187 34 CFR 685.304(a)(3). 

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.184

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. 

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.185 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. 

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 186 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.187 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 classby-class as they progress. There may 


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188 87 FR 65904 (Nov. 1, 2022). 

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 188 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. 

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. 


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189This 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 notfederally aided students to the number of graduates 

in such programs reported to the National Student 

Loan Data System—covering only federally aided 

students. 

190California makes these data available at this 

website: https://www.barbercosmo.ca.gov/schools/ 

schls_rslts.shtml. 

191Cellini, 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. 

192See, 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. 

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.189 Moreover, a 

review of licensure examination results 

from California 190 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.191 The same data used in these 

studies, along with more rigorous 

academic studies,192 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. 

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 


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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 


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193 88 FR 32342. 

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,193 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. 

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 


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194 79 FR 16426, 16485 (Mar. 25, 2014). 

195See 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. 

Continued 

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,’’ 194 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 Statesponsored 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). 

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.195 But institutions lack 


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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.’’). 

196See 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.’’). 

197See 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). 

198See Dumas, 90 F.3d at 392. 

199See, 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). 

such a protected interest in continued 

eligibility to participate in Federal 

student aid programs.196 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.197

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.198

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.199

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 


ddrumheller on DSK120RN23PROD with RULES2
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70091 

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. 

BILLING CODE 4000–01–P 

BILLING CODE 4000–01–C 

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 


ddrumheller on DSK120RN23PROD with RULES2ER10OC23.003</GPH>

Figure 1.4: Median Debt Levels Among Undergraduate Cosmetology 

Certificate Programs Across States 

20,000 

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State 
70092 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

200See, for example, 88 FR 32300, 32306, 32322 

(May 19, 2023). 

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.200 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. 

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 eightdigit OPEID number. The commenters 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70093 

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 


ddrumheller on DSK120RN23PROD with RULES2
70094 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

201 258 F. Supp. 3d 50 (D.D.C. 2017). 

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).201 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. 

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 


ddrumheller on DSK120RN23PROD with RULES2
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70095 

202Formerly 34 CFR 668.406(b) through (d) 

(rescinded). 

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.202

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. 

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 taxpayersupported 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 


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203We further address due process in an above 

discussion of ‘‘Challenges, Hearings, and Appeals.’’ 

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 nsize 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.203 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 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 examinationlevel 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 taxVerDate Sep<11>2014 21:07 Oct 06, 2023 Jkt 262001 PO 00000 Frm 00094 Fmt 4701 Sfmt 4700 E:\FR\FM\10OCR2.SGM 10OCR2

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204See 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). 205 258 F. Supp. 3d 50 (D.D.C. 2017). 

206See 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). 207Above in ‘‘Tipped Income,’’ we address such 

evidence of unreported earnings along with more 

recent findings. 

208See 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). 

209See 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’’). 

210See id. at 63. 

211See 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.’’). 

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 selfinterested 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.204

The Department disagrees with the 

commenters who argued that the 

decision of the district court in 

American Association of Cosmetology 

Schools v. DeVos,205 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,206 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,207 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.208 The court 

ultimately ordered that AACS member 

schools be allowed to pursue earnings 

appeals without meeting the numerical 

survey requirements in the rule.209 The 

court did observe that the notice-andcomment 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.210

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.211 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. 

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 


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212For additional detail, see the discussion above 

in ‘‘Tipped Income.’’ 

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.212 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. 

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 reestablished 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 fourdigit 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 caseby-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 


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213 20 U.S.C. 3403(b). 

214The official monthly civilian unemployment 

rate data can be accessed here: https://www.bls.gov/ 

charts/employment-situation/civilianunemployment-rate.htm. 

system, or accrediting agency or 

association.213 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.214 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. 

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. 


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70100 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

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 debtto-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 


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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-toearnings 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 


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70102 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

TABLE 2.1—COMBINED NUMBER OF TITLE IV ELIGIBLE PROGRAMS AND TITLE IV ENROLLMENT BY CONTROL AND

CREDENTIAL LEVEL COMBINING GE AND NON-GE—Continued 

Number of 

Programs Enrollees 

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. 


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215Throughout the RIA, ‘‘not-for-profit’’ and 

‘‘nonprofit’’ are used interchangeably to refer to 

private nonprofit institutions. 

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.215 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. 


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70104 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

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 


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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 .............. 23450: 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 <50 208,20024: 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 


ddrumheller on DSK120RN23PROD with RULES2
70106 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

TABLE 2.3—TITLE IV ENROLLMENT OF

NON-GE PROGRAMS BY CIP2, CREDENTIAL

LEVEL, AND

CONTROL—Continued 

Public Private, nonprofit Foreign 

Total 

Assoc. Bach. Master’s Doct. Prof. Assoc. Bach. Master’s Doct. Prof. Assoc. Bach. Master’s Doct. Prof. 

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. 


ddrumheller on DSK120RN23PROD with RULES2
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70107 

216 ‘‘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. 

217Note 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. 

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.216 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.217 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 twodigit 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. 


ddrumheller on DSK120RN23PROD with RULES2
70108 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

TABLE 2.4—NUMBER OF GE PROGRAMS BY CIP2, CREDENTIAL

LEVEL, AND

CONTROL

Public Private, nonprofit Proprietary Foreign 

Total UG 

certs 

PostBA 

cert 

Grad 

cert 

UG 

certs 

PostBA 

cert 

Grad 

cert 

UG 

certs Assoc. Bach. 

PostBA 

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 


ddrumheller on DSK120RN23PROD with RULES2
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70109 

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 

PostBA 

cert 

Grad 

cert 

UG 

certs 

PostBA 

cert 

Grad 

cert 

UG 

certs Assoc. Bach. 

PostBA 

cert 

Master’s Doct. Prof. Grad cert UG certs Post- BA cert Mas- ter’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 


ddrumheller on DSK120RN23PROD with RULES2
70110 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

TABLE 2.5—TITLE IV ENROLLMENT OF GE PROGRAMS BY CIP2, CREDENTIAL

LEVEL, AND

CONTROL—Continued 

Public Private, nonprofit Proprietary Foreign 

Total UG 

certs 

PostBA 

cert 

Grad 

cert 

UG 

certs 

PostBA 

cert 

Grad 

cert 

UG 

certs Assoc. Bach. 

PostBA 

cert 

Master’s Doct. Prof. Grad cert UG certs Post- BA cert Mas- ter’s Doct. Prof. Grad cert 

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 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70111 

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 nonwhite. 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 nonwhite. 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: 


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I I I I 

I I I I 

I I I I I 
70112 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

218Barrow, 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. 

TABLE 2.7—CHARACTERISTICS OF GE STUDENTS BY CONTROL, PREDOMINANT DEGREE, AND CREDENTIAL LEVEL— 

Continued 

Average EFC 

Percent of students who are . . . 

Age 24+ Male Pell Non-white Independent 

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.218 Increased 

educational attainment also confers 

private nonpecuniary benefits, such as 

better health, job satisfaction, and 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70113 

219Oreopoulos, P., & Salvanes, K.G. (2011). 

Priceless: The Nonpecuniary Benefits of Schooling. 

Journal of Economic Perspectives, 25(1), 159–184. 

220Moretti, E. (2004). Workers’ Education, 

Spillovers, and Productivity: Evidence from PlantLevel Production Functions. American Economic 

Review, 94(3), 656–690. 

221 Dee, T.S. (2004). Are There Civic Returns to 

Education? Journal of Public Economics, 88(9–10), 

1697–1720. 222Currie, 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. 

223Avery, 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. 

overall happiness.219 Social benefits of 

higher or increased number of 

individuals with a postsecondary 

education include productivity 

spillovers from a better educated and 

more flexible workforce,220 increased 

civic participation,221 and 

improvements in health and well-being 

for the next generation.222 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.223

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 


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70114 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

224Black, 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 

TABLE 2.8—AVERAGE DEBT AND COHORT DEFAULT RATE, BY CONTROL AND CREDENTIAL LEVEL—Continued 

[Enrollment-weighted] 

Average debt Cohort 

default rate 

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.224 It is, 


ddrumheller on DSK120RN23PROD with RULES2
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70115 

Consequences of Academic Match Between 

Students and Colleges. Journal of Human Resources 

55.3: 767–808. 

225Hoxby, 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. 

226Carrell, 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. 

227Andrews, 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. 

228Minaya, 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. 

229Hastings, 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. 

230A 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. 

231Mulhern, Christine (2021). Changing College 

Choices with Personalized Admissions Information 

at Scale: Evidence on Naviance. Journal of Labor 

Economics 39.1: 219–262. 

232Hurwitz, Michael & Smith, Jonathan (2018). 

Student Responsiveness to Earnings Data in the 

College Scorecard. Economic Inquiry 56.2: 1220– 

1243. 

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. 

A recent study computed 

productivity—value-added per dollar of 

social investment—for 6,700 

undergraduate programs across the 

United States.225 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.’’ 

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,226

public two- and four-year programs in 

Texas,227 master’s degree programs in 

Ohio,228 law and medical schools, and 

programs outside the United States.229

Variation in institutional and program 

performance is a dominant feature of 

postsecondary education in the United 

States.230

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.’’ 231

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.232 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. 

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 nondegree 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. 


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233Aspen Institute (2015). From College to Jobs: 

Making Sense of Labor Market Returns to Higher 

Education. Washington, DC 

(www.aspeninstitute.org/publications/ 

labormarketreturns/). 234Much 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-termcredentials-landscape). 

235Soliz, A. (2016). Preparing America’s Labor 

Force: Workforce Development Programs in Public 

Community Colleges. Brookings: Washington, DC 

(www.brookings.edu/research/preparing-americaslabor-force-workforce-development-programs-inpublic-community-colleges/). 

236Aspen Institute (2015). From College to Jobs: 

Making Sense of Labor Market Returns to Higher 

Education. Washington, DC 

(www.aspeninstitute.org/publications/ 

labormarketreturns). 

237 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. 

238Cellini, S.R. & Chaudhary, L. (2014). The 

Labor Market Returns to a For-Profit College 

Education. Economics of Education Review, 43, 

125–140. 

239Armona, 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. 

240Liu, 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. 

241Lang, 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. 

242Cellini, 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. 

243 Government Accountability Office (2011). 

Postsecondary Education: Student Outcomes Vary 

at For-Profit, Nonprofit, and Public Schools (GAO– 

12–143). 

244U.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. 

245Cellini, 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. 

246 Id. 

247Lang, 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. 

248 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. 

249 Gicheva, D. (2016). Student Loans or 

Marriage? A Look at the Highly Educated. 

Economics of Education Review, 53, 207–2016. 

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,233 and even within the 

same narrow field and within the same 

institution.234 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.235

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.236

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,237

low earnings,238 and loan repayment 

difficulties.239 Students who transfer 

into for-profit institutions instead of 

public or nonprofit institutions face 

significant wage penalties.240 In some 

cases, researchers find similar earnings 

or employment outcomes between forprofit and not-for-profit associate and 

bachelor’s degree programs.241

However, students pay and borrow more 

to attend for-profit degree programs, on 

average.242 The result of higher debt 

levels paired with lower or equivalent 

earnings means students attending forprofit 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.243

These comparatively poor outcomes 

may not be surprising, as many forprofit 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.244

The report further found that at many 

institutions, the number of recruiters 

greatly outnumbered the career services 

and support services staff. 

Particularly strong evidence comes 

from a recent study that found that the 

average undergraduate certificateseeking student that attended a forprofit 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.245 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.246 At the same time, 

research also shows substantial 

variation in earnings gains from title IV, 

HEA-eligible undergraduate certificate 

programs by field of study,247 with 

students graduating from cosmetology 

and personal services programs in all 

sectors experiencing especially poor 

outcomes.248

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’ longterm probability of marriage.249 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 


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250Chakrabarti, R., Fos, V., Liberman, A. & 

Yannelis, C. (2023). Tuition, Debt, and Human 

Capital. The Review of Financial Studies, 36(4), 

1667–1702. 

251Mezza, A., Ringo, D., Sherlund, S. & Sommer, 

K. (2020). Student Loans and Homeownership. 

Journal of Labor Economics, 38(1), 215–260. 

252 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. 

253Federal Student Aid. Student Loan 

Delinquency and Default (studentaid.gov/manageloans/default). 

254Blagg, K. (2018). Underwater on Student Debt: 

Understanding Consumer Credit and Student Loan 

Default. Urban Institute Research Report. 

255Elliott, 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. 256Federal Student Aid. Student Loan 

Delinquency and Default (studentaid.gov/manageloans/default). 257 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. 

258Looney, 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. 

259The 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-sheetpresident-biden-announces-new-actions-to-providedebt-relief-and-support-for-student-loanborrowers/). 

260These estimates of the subsidy rate are not 

those used in the budget and do not factor in takeup. Rather, they show the predicted subsidy rates 

under the assumption that all students are enrolled 

in SAVE. 

261As 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 twoyear cohort period—that is, those programs that met 

the minimum cohort size requirements. 

degree 250 and less likely to take out a 

mortgage to purchase a home after 

leaving college.251

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.252 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.253 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.254 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.255

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.256

Research shows that borrowers who 

attend for-profit institutions have higher 

student loan default rates than students 

with similar characteristics who attend 

public institutions.257 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, twoyear public institutions.258

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 2023.259 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. 

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).260 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. 

Table 2.10 shows that, among all 

programs, students who attend 

programs that fall below the debt-toearnings standard are consistently 

projected to repay less on their loans, in 

present value terms, than they 

borrowed.261 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. 

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 


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70118 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

262These 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. 

263 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 ForProfit Colleges’ Share of Higher Education 

Expanded So Rapidly? Estimating the 

Responsiveness to Labor Market Changes. 

Economics of Education Review, 45, 53–63. 

264Cellini, S.R. (2020). The Alarming Rise in ForProfit College Enrollment. Brookings Institution: 

Washington, DC. 

265Cellini, 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. 

266Ma, J. & Pender, M. (2022). Trends in College 

Pricing and Student Aid 2022. College Board: New 

York. 

267Cellini, 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. 

268NCES (2022). Digest of Education Statistics 

(Table 330.10) (available at nces.ed.gov/programs/ 

digest/d21/tables/dt21_330.10.asp). 

269Cellini, S.R. (2010). Financial Aid and ForProfit 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. 

270Cellini, S.R. & Goldin, C. (2014). Does Federal 

Student Aid Raise Tuition? New Evidence on ForProfit Colleges. American Economic Journal: 

Economic Policy, 6(4), 174–206. 

TABLE 2.10—PREDICTED RATIO OF DOLLARS REPAID TO DOLLARS BORROWED BY CONTROL AND PASSAGE STATUS— 

Continued 

Predicted repayment 

ratio under SAVE 

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.262

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 263 and 

during the COVID–19 pandemic, it was 

the only sector to see increases in 

student enrollment.264 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.265 During economic downturns, 

this response is especially relevant since 

State and local funding is procyclical, 

falling during recessions even as student 

demand is increasing.266

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.267 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.268 Research 

suggests that Federal student aid 

supports for-profit expansions and 

higher prices.269 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.270

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 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70119 

271 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. 

272 Darolia, R. (2013). Integrity Versus Access? 

The Effect of Federal Financial Aid Availability on 

Postsecondary Enrollment. Journal of Public 

Economics, 106, 101–114. 

273Cellini, 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. 

274See 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-studentsexperienced-an-abrupt-campus-closure-betweenjuly-2004-and-june-2020). 

General Equivalency Degree.271

Evidence from prior research and our 

analyses presented in this RIA, 

however, suggests that sanctioning lowperforming programs would not reduce 

access to good quality programs. 

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.272 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.273 Similar conclusions were 

reached in recent studies of students 

who experienced program closures.274

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 HighValue 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. 

3. Summary of Comments and Changes 

From the NPRM 

TABLE 1—SUMMARY OF KEY CHANGES IN THE FINAL REGULATIONS

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 ............................................. § 668.2 ............................ 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. 


ddrumheller on DSK120RN23PROD with RULES2
70120 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

275See ‘‘Data Used in this RIA’’ and ‘‘Analysis of 

Data Coverage’’ from the NPRM. 

TABLE 1—SUMMARY OF KEY CHANGES IN THE FINAL REGULATIONS—Continued 

Provision Regulatory section Description of change from NPRM 

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 forprofit 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 twoyear, 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 postgraduation 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.275 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. 

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/ 


ddrumheller on DSK120RN23PROD with RULES2
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70121 

276See www2.ed.gov/policy/highered/reg/ 

hearulemaking/2021/nprm-2022ppddescription.pdf and www2.ed.gov/policy/highered/ 

reg/hearulemaking/2021/nprm-2022ppdcodebook.xlsx. 

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 nonpublic 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.276

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 selfreported 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 


ddrumheller on DSK120RN23PROD with RULES2
70122 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

277To 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. 

278This 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. 

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.277

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 nonpublic 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 programlevel 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-toearnings 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 nonexempted 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 postgraduation residency requirements such 

that it is evaluated based on a longer 

earnings periods.278 These programspecific 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. 

• 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. 


ddrumheller on DSK120RN23PROD with RULES2
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70123 

279 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. 

• 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 postgraduation 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.279

We used the 2010 CIP code instead of 

the 2020 codes to align with the 

completer cohorts used in this analysis. 

• 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 


ddrumheller on DSK120RN23PROD with RULES2
70124 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

280See 79 FR 64939–40. 

281See Technical Documentation: College 

Scorecard Data by Field of Study. 

282For 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. 

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 institutionreported 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 nonborrowers, 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 of 

D/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, postbaccalaureate 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.280 The interest rates used were: 

• 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.281

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. 

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.282 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. 

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 


ddrumheller on DSK120RN23PROD with RULES2
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70125 

283Age 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. 

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 

TABLE 4.1—EARNINGS THRESHOLDS

BY STATE, 2019—Continued 

Earnings 

threshold, 

2019 

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.283

BILLING CODE 4000–01–P 


ddrumheller on DSK120RN23PROD with RULES2
70126 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

284To 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 fulltime work for three quarters at the Federal 

minimum wage. We only compute average preprogram income if at least 30 students meet this 

criteria. 

285Across 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. 

286The 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. 

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 preprogram individual income for students 

at these same types of certificate 

programs, including any dependent and 

independent students that had 

previously been working.284 Figure 4.2 

also plots the ET and the average postprogram median earnings for programs 

under consideration. The programaverage share of students used to 

compute pre-program income is also 

reported in parentheses.285 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. 

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.286


ddrumheller on DSK120RN23PROD with RULES2ER10OC23.004</GPH>

Average Age by e1i:; Code,. UG For.profit Certificate Programs 

I 

I I 

Clental Support seJVieeS.and.Allled·Rll>fessions,. ••••••••••• ... • .. ••• ................................ t··• .. ····•···· .. t .............. , .. 

I I 

Allied Health and. Melltcal AssistirlgSenliees ........................... c ............................ t ................ f··•··· .. ····•·•· .. 

I I 

Precision Metal Working ······•·•····•··•·•····•··• ................ , ............. r····•····· ... •·y ............. _, ... 

t I Vehicle Maintenance and. Repair Technologies .•.• ., ......., •••M ..... • • •• • ........... • .. ) •••·• •• ....... T .................. .. 

t I COsmetology and RelaledPersonal GmormngSelVices ..................................... " .............. _.r••· ♦ ...... , r ................. .. 

All other programs ...................... ,. ....................... _..,. ... !••m••········ ➔· ........... "" .... . 

Heating; Air Condiliooing, Venlilatkln and ~ion Maintenance Technologyltecnmaan 

somauc Bodywodrand ~eiamd Therapeu!ie SelVlces 

....................................................... ·+·••·•·• .. ,·•· ... t,········ ... •·••·· 

•••••••••,•.•••• .. ••• .. ••• .... ••• ....................... •+••••••••••••••;••t••••dd•>•••••••• 

AlliedHeaffl"I tliagooslic; lnteivetmQn, and.TrealmenJ ProtessioliS •········· .............................................. L ............. L. ....... • ...... .. I I 

Praclk::al Nursing, Vocalional llluraillg and Nursing AssiSlants .................... , ............................... L .............. ,.L..... 0 " .. 

I I 

H@llh and Medica!AdministratiVe services ..... , .............................................. , .... i ................... i .. " .. • ....... .. 

I I 

0 10 20 30 

Mean Age Whell·EamJngs Measured 

Figure 4.1. Mean Age When Earnings are Measured, UG ForProfit Certificate Programs 

40 
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70127 

BILLING CODE 4000–01–C 

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 twoyear 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 nsize 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 sixdigit 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. 


ddrumheller on DSK120RN23PROD with RULES2ER10OC23.005</GPH>

--llillgJ,Mfi,tln-.lindT.,,...__,.,_(41!_1%) ....... , ....... ,,,, ....... , ....... , ....... , ....... ,.,, .. 9 .. , ....... ,(;) ........ , ... ,,, ... (),.c .. 

1!_"'1<1 ___ {53.4%1 .................................................................... ,0 ........................ . 

40,000 

Qeamii,gs-

~ ~hps~ ~theemdlment"'M!igbled-averagashan!Qf~'Mitttp~mincama Dfat lmst314fhe minimum-wage fariheitslate-.. 

Figure 4.2 Average Income Before Program and Earnings After 

Program, For-Profit UG Certificate Programs 
70128 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

287Unlike 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. 

288Programs 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. 

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 sixdigit 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.287

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.288 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. 

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 4.3a—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: 


ddrumheller on DSK120RN23PROD with RULES2
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70129 

289We use significance level, or alpha, of 0.05 

when assessing the statistical significance in our 

regression analysis. 

TABLE 4.3a—PERCENT OF PROGRAMS AND ENROLLMENT IN PROGRAMS WITH VALID D/E AND EP INFORMATION BY

CONTROL AND CREDENTIAL LEVEL—Continued 

[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 

Total .......................................................................... 17.7 61.3 0.4 0.3 81.9 38.4 

TABLE 4.3b—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.289 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 tstatistic 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. 

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 


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70130 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

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 


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TABLE 4.5—NUMBER AND PERCENT OF NON-GE PROGRAMS BY RESULT, CONTROL, AND CREDENTIAL LEVEL—Continued 

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 

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 


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TABLE 4.6—PERCENT OF NON-GE TITLE IV, HEA ENROLLMENT IN PROGRAMS FAILING EITHER D/E OR EP METRIC, BY

CIP2—Continued 

Credential level 

Associate Bachelor’s Master’s Doctoral Professional Total 

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 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70133 

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 


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70134 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

TABLE 4.9—NUMBER OF GE PROGRAMS BY RESULT, CONTROL, AND CREDENTIAL LEVEL—Continued 

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 

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 

PostBA 

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 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70135 

TABLE 4.10—PERCENT OF GE TITLE IV, HEA ENROLLMENT IN PROGRAMS FAILING EITHER D/E OR EP METRIC, BY

CIP2—Continued 

Credential level 

UG 

certificates Associate Bachelor’s 

PostBA 

certs 

Master’s Doctoral Professional Grad 

certs Total 

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 

PostBA 

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 


ddrumheller on DSK120RN23PROD with RULES2
70136 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

290Note 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. 

Program Ineligibility 

For GE programs, title IV, HEA 

ineligibility is triggered by two years of 

failing the same metric within a threeyear 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.290 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. 

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. 


ddrumheller on DSK120RN23PROD with RULES2ER10OC23.007</GPH>

Table 4.12. GE Program Performance Transition Between Years One and Two 

Percent of Enrollment by Result in Year Two 

No D/E Fail Fail 

both Fail EP or EP Pass D/E D/E and only data only EP Ineligible 

.:: No D/E or EP data 78.2 14.2 0.5 1.3 5.8 ·rl rl Pass 3.0 91.9 1.7 0.1 3.3 -1-l >-l rl rd Fail D/E only 3.5 24.0 57.7 14.6 0.1 72.3 ~ Q) 

~ :>-< Fail both D/E and EP 0.3 0.3 5.5 83.2 10.6 99.3 ~ Fail EP only 1.9 5.9 0.0 8.4 83.8 92.1 

Percent of Programs by Result in Year Two 

No D/E Fail Fail 

both Fail EP or EP Pass D/E D/E and only Ineligible 

data only EP 

.:: No D/E or EP data 95.6 3.0 0.1 0.2 1.1 ·rl rl Pass 9.5 82.9 1.5 0.4 5.7 -1-l >-l rl rd Fail D/E only 13.4 16.2 51.8 17.8 0.8 69.6 ~ Q) 

~ :>-< Fail both D/E and EP 2.2 1.5 5.5 72.9 17.9 96.3 ~ Fail EP only 9.1 4.1 0.1 8.1 78.5 86.6 
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70137 

291Under § 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/). 

292The 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 4.13—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 4.14.291

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.292 We 

conducted a similar analysis excluding 

institutions that do not have any GE 

programs. The patterns are similar. 

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 


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70138 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

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. 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70139 

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 


ddrumheller on DSK120RN23PROD with RULES2
70140 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

293We 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. 

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.293

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 


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294Specifically, 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). 

degree reported in the IPEDS 2016 and 

2017 Completions Surveys.294 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: 

• 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 firstgeneration, 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 firstgeneration 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 


ddrumheller on DSK120RN23PROD with RULES2
70142 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

295Though 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. 

296Only 4 percent of GE programs are the only 

GE program within the institution. The median 

number of programs within an institution is 18. 

4.20—DESCRIPTIVE STATISTICS OF THE DEMOGRAPHIC VARIABLES—Continued 

Programs Median Average Std. 

deviation 

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.295 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 programlevel 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. 

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.296 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 RVerDate Sep<11>2014 21:07 Oct 06, 2023 Jkt 262001 PO 00000 Frm 00140 Fmt 4701 Sfmt 4700 E:\FR\FM\10OCR2.SGM 10OCR2

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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70143 

297The 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. 

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.297

The final two columns report similar 

models, but weighting by average title 

IV, HEA enrollment, and the results are 

qualitatively similar. 

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. 


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70144 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

298Since each of the 20 groups includes the same 

number of programs, the income range varies across 

groups. 

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.298 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. 

BILLING CODE 4000–01–P 

BILLING CODE 4000–01–C 

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

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 


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Grou~.of FAFSA Famllyln@me 

o Program O Group Median 

Not&! Ea~ for hiQb sd100l'gractuates areuk:ulatl!d IJl!lll!l: the ~can Community Su!vt!Y as the median earnings of a high school 

graduate agea 25-34 m the state. a11111n9 gra~tes wilb JlOSl!we earnings. The earnings premium is defined as the. a11111unt 11bove or below 

the med.an eaf!li?gs for a high $11. ool. grailm.ate·in the state .. Each. d. o~ represents a program and programs. are dMded nto Qfl?Ups_ based. on average FAFSA family: income. Groups are filrmed by dividing.programs into 5'l{; groups froi:n lowestto hlghesUncomes l\'iglfltiles}. 

Figure 4.3 Distribution of Earnings Premium by Family 

Income, Certificate Programs 

I 

t 

I 

·t 
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70145 

299Blau, 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. 

300Cottom, 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. 

301Two 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. 

302Since the 2022 PPD are aggregated to each 

combination of the six-digit OPEID, four-digit CIP 

code, and credential level, we do not have precise 

data on geographic location. For example, a 

program can have multiple branch locations in 

different cities and States. At some of these 

Continued 

TABLE 4.24—GENDER AND RACIAL COMPOSITION OF UNDERGRADUATE CERTIFICATE PROGRAMS—Continued 

Share of 

programs 

failing 

Share of all completers who are . . . 

Black 

women 

Hispanic 

women 

Asian 

women 

Other 

women 

White 

women 

Women 

(any race) 

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 

Criminal Justice ......................................................................... 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.299 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.300 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. 

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.301 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


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70146 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

locations, the program could be offered as an online 

program while other locations offer only in-person 

programs. Each of these locations would present as 

a single program in our data set without detail 

regarding precise location or format. We do not 

possess more detailed geographic information that 

would allow us to address this issue, so we 

recognize that our analysis of geographic scope and 

alternatives may be incomplete and cause us to 

understate the number of options students have. 

Nonetheless, the vast majority of alternative options 

will be captured in our analysis. 

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. 

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 

institution, 

cred level, 

CIP2 

Same Zip3, 

cred level 

CIP4 

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 nonfailing 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

Level 

Same 

institution, 

cred level, 

CIP2 

Same Zip3, 

cred level, 

CIP4 

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 online 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 


ddrumheller on DSK120RN23PROD with RULES2
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70147 

303 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. 

304Cellini, 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. 

305Cellini, S.R. & Goldin, C. (2014). Does Federal 

Student Aid Raise Tuition? New Evidence on ForProfit Colleges. American Economic Journal: 

Economic Policy, 6(4), 174–206. 

306Cellini, 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. 

307The 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. 

licensure exams after completing nontitle IV, HEA programs in 

cosmetology.303 Non-title IV, HEA 

cosmetology schools operate in almost 

all counties in Texas.304 In Florida, nontitle IV, HEA cosmetology schools have 

similar licensure pass rates but much 

lower tuition.305

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.306 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 fourdigit 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. 

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 programlevel median debt between failing GE or 

non-GE programs and alternative 

programs.307 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. 

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. 


ddrumheller on DSK120RN23PROD with RULES2
70148 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

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 


ddrumheller on DSK120RN23PROD with RULES2
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70149 

TABLE 4.28—PERCENT EARNINGS DIFFERENCE BETWEEN TRANSFER OPTIONS AND FAILING NON-GE PROGRAMS, BY CIP 

AND CREDENTIAL LEVEL—Continued 

cip2 

Credential level 

Total 

Associate Bachelor’s Master’s Doctoral Professional 

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 


ddrumheller on DSK120RN23PROD with RULES2
70150 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

308Programs at foreign institutions are excluded 

from Table 4.31 as they do not have an institutional 

type. 

309Note 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 4.30—PERCENT DEBT DIFFERENCE BETWEEN TRANSFER OPTIONS AND FAILING NON-GE PROGRAMS, BY CIP AND

CREDENTIAL LEVEL—Continued 

2-digit CIP code 

Credential level 

Total 

Associate Bachelor’s Master’s Doctoral Professional 

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.308 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.309 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. 


ddrumheller on DSK120RN23PROD with RULES2
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70151 

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-financialvalue 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 bettervalue 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 


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70152 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

310Chakrabarti, 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. 

due to improved and standardized 

market information about GE and nonGE 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 nonGE 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.310

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. 

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 higherperforming 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 higherperforming 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 


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311Available at https://www.bls.gov/oes/current/ 

oes119033.htm. 

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 longterm, 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, PostSecondary of $48.05.311

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, 


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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. 


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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. 


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312AYs 2023 to 2034 are transformed to FYs 2023 

to 2033 later in the estimation process. 

313The number of programs in proprietary postBA 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. 

314The budget simulations separate lower and 

upper division enrollment in 4-year programs. We 

assume the same program transition rates for both. 

TABLE 6.1—MAIN ASSUMPTIONS AND SOURCES—Continued 

Category Detail Source Included in 

sensitivity? 

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.312 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.313 Table 6.2 below reports 

the assumed average annual percent 

change in title IV, HEA enrollment. 

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.314

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 


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315 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. 

316Fountain, 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. 

317Hentschke, 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). 

category to another is computed 

separately for each group.315

The left panels of Tables 6.3 and 6.4 

report the program transition 

assumptions from 2025 to 2026 for nonGE 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 nonGE 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 lowperforming 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.316 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.317 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. 

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 


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318 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). 

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 nonenrollment 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 noncompleting students who were at closed 

institutions transferred.318 This 

magnitude is similar to recent analysis 

that found that 47 percent of students 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70159 

319State 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-studentsexperienced-an-abrupt-campus-closure-betweenjuly-2004-and-june-2020/). 

320Cellini, 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. 

321Lower division includes students in their first 

two years of undergraduate education. Upper 

division includes students in their third year or 

higher. 

reenrolled after an institutional 

closure.319 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 forprofit 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.320 The Department also 

conducted its own internal analysis of 

ITT Technical Institute closures. About 

half of students subject to the closure reenrolled elsewhere (relative to preclosure 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 reenrolled, 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. 

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:321

• 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 


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322Note 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. 

TABLE 6.6—STUDENT RESPONSE ASSUMPTIONS, AMONG TRANSFERRING STUDENTS, SHARE SHIFTING SECTORS— 

Continued 

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 

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 nonGE 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: 322

• 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 programlevel 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, Preineligible (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 


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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 preineligibility. The possible program 

transitions for GE programs are: 

• Pass → Pass, Fail D/E, Fail EP, Fail 

Both 

• Fail D/E → Pass, Fail EP, PreIneligible 

• Fail EP → Pass, Fail D/E, PreIneligible 

• Fail Both → Pass, Pre-Ineligible 

Step 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 


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70162 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

323The 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. 324Hoekstra, 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. 

325Mountjoy, Jack & Hickman, Brent (Sept. 2021). 

The Returns to College(s): Relative Value-Added 

and Match Effects in Higher Education. NBER 

Working Paper 29276. 

326Note 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 lowerdivision four-year programs. 

327Hendren, Nathaniel & Sprung-Keyser, Ben 

(2020). A Unified Welfare Analysis of Government 

Policies. Quarterly Journal of Economics 135 (3): 

1209–1318. 

programs.323 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. 

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 324 and others 

finding smaller impacts.325

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. 

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).326 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. 

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 SprungKeyser (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.327 The rate is derived from 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70163 

328This may cause our estimates to slightly 

understate the instructional cost impact since 

failing programs are disproportionately in lowerearning 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. 

329Since 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. 

330 88 FR 43820 (July 10, 2023). 

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. 

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 programlevel spending, this will not fully 

capture spending differences between 

undergraduate and graduate enrollment, 

between upper and lower division, and 

across field of study.328

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 2033.329

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, 2023.330 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. 

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. 


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70164 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

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. 


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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 


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70166 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

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 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70167 

331The 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. 

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.331

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 nonGE 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 


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I I I I I I I I I I 
70168 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

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 lowperforming programs to higherperforming 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 


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I I I I I I I I I I 
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70169 

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: 


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70170 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

332 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 valueadded 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. 

333See 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 8.8—NO PROGRAM IMPROVEMENT SENSITIVITY ANALYSIS—ESTIMATED ANNUAL CHANGE IN TITLE IV, HEA AID

VOLUME RELATIVE TO BASELINE—Continued 

[Millions, $2019] 

2025 2026 2027 2028 2029 2030 2031 2032 2033 Total 

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).332 Even at 

these low values for the adjustment 

factor, the estimated earnings benefits of 

the rule by themselves outweigh the 

estimated costs. 

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 nonGE 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.333 With the inclusion of the 


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EP, the Department affirms that 

borrowers that postsecondary GE 

programs should help students reach a 

minimal level of labor market earnings. 

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 


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70172 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

TABLE 10.2—PERCENT OF NON-GE PROGRAMS AND ENROLLMENT AT GE PROGRAMS THAT FAIL UNDER D/E ONLY VS. 

D/E OR EP—Continued 

Programs Students 

Fail D/E only Fail D/E or EP Fail D/E only Fail D/E or EP 

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 


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TABLE 10.4—SHARE OF GE PROGRAMS THAT FAIL, BY WHERE EARNINGS THRESHOLD IS SET—Continued 

% Failing Total 

DTE + lower 

EP 

DTE + 

medium EP 

DTE + higher 

EP 

Number of 

Programs 

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 

DTE + lower of Enrollees 

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 

DTE + lower of programs 

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. 


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70174 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

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 nsize 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-toearnings 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 preprogram 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 preprogram 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. 


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334 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. 

335 88 FR 32300 (May 19, 2023). 

336 88 FR 43820 (July 10, 2023). 

337 87 FR 65426 (Oct. 28, 2022). 

338 In those prior rules, at least two but less-thanfour-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. 

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.334 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, 2023,335 the final rule published in 

the Federal Register on July 10, 2023, 

for the improving income driven 

repayment rule,336 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.’’ 337 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.338 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. 

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 


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339The 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 11.2—TOTAL REVENUES AT SMALL INSTITUTIONS—Continued 

Average Total 

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-toearnings (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.339

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. 


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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 nondegree 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 


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70178 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

TABLE 11.5—NUMBER OF ENROLLEES IN GE PROGRAMS AT SMALL INSTITUTIONS BY GE RESULT, BY CONTROL, IHE 

TYPE, AND CREDENTIAL LEVEL—Continued 

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 % 

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 nonVerDate Sep<11>2014 21:07 Oct 06, 2023 Jkt 262001 PO 00000 Frm 00176 Fmt 4701 Sfmt 4700 E:\FR\FM\10OCR2.SGM 10OCR2

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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70179 

340For §§ 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. 

341Available at www.bls.gov/oes/current/ 

oes119033.htm. 

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.340

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 

$48.05.341 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. 


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TABLE 11.8—ESTIMATED HOURS FOR REPORTING REQUIREMENTS—Continued 

Process Hours Hours basis 

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 


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342 44 U.S.C. 3506(c)(2)(A). 

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 nonGE 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 noninstitutional 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).342 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 


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70182 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

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 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70183 

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 Englishlanguage 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 


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70184 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

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. 


ddrumheller on DSK120RN23PROD with RULES2
Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70185 

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: 


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70186 Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 

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 sixdigit 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 debtto-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, firstprofessional 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. 

* * * * * 


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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 fourdigit 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. 


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(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 

Sec. 

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 


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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 postbaccalaureate 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 


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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 


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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 nonrecipients 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) 

Sec. 

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. 


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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 the 

D/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 funds. (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 


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Federal Register / Vol. 88, No. 194 / Tuesday, October 10, 2023 / Rules and Regulations 70193 

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 Englishlanguage 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. 

[FR Doc. 2023–20385 Filed 9–28–23; 8:45 am] 

BILLING CODE 4000–01–P 


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