Look Up Your Institution: Where Three Federal Policies Overlap

Three federal policies now bear on the same programs at the same time: the new earnings test, the elimination of Grad PLUS, and the new borrowing caps. The tool below combines them. Search your institution to see which of your programs are flagged, and by what.

Open the full tool in a new tab →

How to Read Your Result

If nothing is flagged, that is the honest answer for most institutions. Roughly 55% have no failing program and no program sitting within $2,000 of the benchmark. Read the program mix figure anyway: it tells you how much of your portfolio the test can actually see.

If programs are flagged, sort your attention by two things the tool surfaces directly. Enrollment tells you the scale of what is exposed. Margin tells you how far from the line it sits. A program failing by $800 is a different problem from one failing by $12,000, and a program passing by $800 may be more fragile than one already failing.

Look for programs carrying more than one flag. A program that fails the earnings test, carries a large per-student funding gap under the new borrowing caps, and enrolls hundreds of students is a categorically different risk from a small program that narrowly misses on earnings alone. That overlap is the subject of the rest of this piece.

Why Compound Risk Matters

Institutions do not experience these policies in isolation. They experience them simultaneously, and the programs most vulnerable to one are often the same programs most exposed to another. Each policy has been analyzed on its own, including here: we have written about the earnings test, Grad PLUS elimination, and the final rule timeline separately.

Consider a graduate nursing program at a mid-size private university. Under the earnings test alone, it passes. Its graduates earn above the benchmark, though only by a narrow margin. Under the Grad PLUS elimination alone, it has a large funding gap: students have been borrowing $45k per year, and the new cap is $20.5k, or $50k, depending on which week’s court ruling you are reading. Neither policy, viewed independently, is existential.

Together, they create a feedback loop. If the funding gap causes enrollment to decline, the program may fall below the reporting threshold and lose the ability to demonstrate passing earnings. If a future cohort’s earnings dip, because fewer students completed, or because the students who could not secure private loans to fill the gap were the ones who dropped out, the program could fail the earnings test. A first failure triggers mandatory disclosure to prospective students, which could depress enrollment further.

This is the compound effect: individually manageable risks that, stacked together, become structurally destabilizing.

Three Patterns That Emerge

Failure clusters, rather than isolated outliers

At most institutions the earnings test is a manageable issue. Among institutions with any failing programs, the median number failing is one. But at the tail the concentration is severe. A handful of institutions have 15 or more failing programs, often with a large share of their enrollment flowing through them. For those institutions the earnings test is not a program-level problem. It is an institutional viability question, and the institution-level trigger in the final rule, provisional certification if low-earning programs account for more than half of Title IV recipients or dollars, makes it an explicit one.

The certificate and PLUS overlap

Undergraduate certificate programs account for 58% of all earnings test failures. Many of these same programs carry significant Parent PLUS borrowing: parents taking on debt for programs whose graduates earn less than the regional high school median. The tool makes this overlap visible program by program, so you can see which failing programs also carry substantial PLUS volumes.

The at-risk band deserves more attention than the failing count

The 934 programs passing within $2,000 of the benchmark are, in some ways, more strategically important than the 2,880 that currently fail. Failing programs have clarity. They know where they stand and can plan accordingly. At-risk programs face uncertainty: a small shift in the next cohort’s earnings, a benchmark adjustment, or a change in the completer mix could push them over the line. For institutions with clusters of at-risk programs, the question is not “do we fail today?” but “how fragile is our passing status?”

What You Cannot See

This tool has real limitations, and we want to be transparent about them.

76% of programs have no earnings data. The IRS suppresses earnings when a program has 15 or fewer graduates in the measurement cohort. Only 49,860 of 209,321 programs can be tested at all, and 835 institutions have no testable programs whatsoever. Small programs, which may be disproportionately vulnerable, are invisible here. The 2,880 failures are almost certainly a lower bound.

The data is backward-looking. The PPD:2026 earnings reflect students who completed programs in 2017-18 and 2018-19, with earnings measured in 2022 and 2023. These graduates entered the workforce before the pandemic, before generative AI reshaped entry-level labor markets, and before anyone knew this test was coming. The first operational test will use a different cohort, primarily completers from the 2021 award year with earnings measured in calendar year 2025, at a finer CIP6 granularity. That first round is informational; the rule takes effect July 1, 2027 and the first award year carrying sanctions begins July 2028. Results may differ.

Revenue exposure is computable for fewer than one in five institutions. It requires IPEDS finance data that is unavailable for most, which is why the figure appears for some institutions and not others. Where it does appear it combines net tuition revenue per FTE with enrollment in failing programs. That is a reasonable proxy, not a financial model. It gives you the right order of magnitude, not the exact dollar.

The two PLUS sources do not perfectly agree. The tool shows FSA institution-level disbursement totals alongside PPD program-level per-student averages. These come from different cohort windows and different suppression rules, so dividing the FSA total by FSA recipients will not reproduce the PPD per-student figure. At the median the PPD-derived figure runs about 16% below what FSA actuals imply, and a third of institutions diverge by more than 25%. The likely cause is that PPD excludes privacy-suppressed small programs that FSA totals still include. Both are valid for their intended purpose, FSA for aggregate institutional volume and PPD for program-level comparison, but they should not be read against each other as though they measure the same thing.

PLUS exposure reflects the outgoing regime. The Grad PLUS and Parent PLUS volumes shown are from AY 2024-25, the last year under uncapped borrowing. They represent what students were borrowing, not what they will be able to borrow under the new caps. The gap between the two is the problem.

Methodology

This analysis integrates four federal data sources.

Program Performance Data (PPD:2026). Released by the U.S. Department of Education for the AHEAD negotiated rulemaking process. 209,321 programs at 5,096 institutions. Earnings are IRS-sourced medians measured four years after program exit for the pooled AY 2017-18 and 2018-19 completer cohorts, adjusted to 2024 dollars using CPI-U. The master OBBBA fail flag (mstr_obbb_fail_cip2_wageb) from the corrected January 2, 2026 release is used.

FSA Direct Loan Dashboard. AY 2024-25, Q4 release. Institution-level Grad PLUS and Parent PLUS recipient counts and disbursement totals. Not subject to privacy suppression. Used for aggregate PLUS exposure figures.

IPEDS Finance Data. FY 2022-23. Net tuition revenue per FTE, used to estimate institution-level revenue exposure from failing programs.

Revenue exposure. Net tuition revenue per FTE, from IPEDS FY 2022-23 finance data, multiplied by enrollment in earnings-test-failing programs. Computable for the 938 institutions that have both failing programs and IPEDS finance data. This measures how much institutional revenue is concentrated in programs that fall below the federal earnings floor. It is not a prediction of revenue loss.

PLUS exposure. Institution-level Grad PLUS and Parent PLUS totals use the FSA Direct Loan Dashboard (AY 2024-25, Q4), which reports actual disbursements and is not subject to privacy suppression. The per-student funding gap in the program table is calculated per borrower, not per enrolled student. For each graduate program, total per-borrower graduate borrowing is capped unsubsidized loans plus Grad PLUS borrowing. Roughly 1,365 programs show per-borrower unsubsidized values above the $20.5k statutory cap, an artifact of misaligned volume and borrower-count cohort windows, and are corrected down to the regulatory maximum. That total is compared against the applicable annual cap: $50k for the eleven professional fields designated by the RISE final rule of May 1, 2026, or $20.5k for every other graduate program. The gap is the greater of zero and total borrowing minus the applicable cap. Where a borrower has taken the full $20.5k of unsubsidized loans, this reduces to the Grad PLUS amount itself, because the unsubsidized component and the cap cancel. That holds for about 13% of the programs shown. For the rest, the borrower is below the unsubsidized maximum and the gap is correspondingly smaller than their Grad PLUS borrowing. “Programs over cap” counts how many graduate programs at an institution have borrowers whose total federal graduate borrowing exceeds the new limits. The professional classification uses the RISE rule’s original eleven-field list, not the interim 29-field expansion from the June 24 court stay.

Status classifications. “Failing” means the OBBBA master fail flag equals 1. “At Risk” means passing, with the flag at 0, and an earnings margin less than $2,000 above benchmark. “Passing” means passing with a margin at or above $2,000, or no margin data. “Not Testable” means no fail flag, indicating insufficient earnings data. Tipped occupations are flagged per final rule Section 668.402(c)(3), which delays consequences for the 20 six-digit CIP codes listed in Table 5.22 of the rule: cosmetology and personal grooming (12.04), bartending (12.0502), casino services (12.06 and 52.0908), and massage and bodywork (51.35). Because the core PPD files identify programs only at the four-digit level, these are flagged here as the families 12.04, 12.05, 51.35, and 52.09. That over-includes culinary arts and hospitality management programs that are not tipped occupations.

Data sources: (1) U.S. Department of Education, Office of the Chief Economist and Office of Federal Student Aid. (2026). Program Performance Data (PPD:2026) for AHEAD Negotiated Rulemaking. (2) U.S. Department of Education, Federal Student Aid. (2026). Direct Loan Program Data: Award Year 2024-25, Quarter 4. (3) National Center for Education Statistics. (2024). IPEDS Finance Survey, FY 2022-23.

Read More

For the underlying framework, How the New Federal Earnings Test for Colleges Works explains what a failure actually triggers, and Every Program, One Test covers the final rule and its compliance timeline. To pull your own institution’s numbers directly from the federal files, see How to Download and Use the Program Performance Data.

Questions? Get in touch! We’re happy to help.

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