What New Gainful Employment and Borrower Defense Rules May Look Like

President Trump is fond of negotiating, as can be evidenced through his long business career and many promises to renegotiate a whole host of international agreements. Federal higher education policy is also fond of negotiation, thanks to a process called negotiated rulemaking that brings a range of stakeholders together for an arduous series of negotiations regarding key changes to federal policies. Notably, if stakeholders do not come to an agreement, the Department of Education can write its own rules—something that the Obama administration did on multiple occasions. (For more on the nitty-gritty of negotiated rulemaking, I highly recommend Rebecca Natow’s new book on the topic.)

In a long-expected announcement, the Department of Education announced Wednesday morning that it would be renegotiating two key higher education regulations (gainful employment and borrower defense to repayment) that were initially negotiated during the Obama administration, with the first meetings beginning next month. To get an idea of how expected these announcements were, here are the stock prices for Adtalem (DeVry) and Capella right after the announcement (which began to break around 11:30 AM ET). Note the fairly small movement in share prices, suggesting that changes were baked into stock prices pretty well.

It is extremely likely that the negotiated rulemaking committees won’t be able to come to an agreement (again), so the new rules will reflect the Trump administration’s higher education priorities. Here is my take on what the two rules might look like.

Gainful Employment

The Obama administration first announced its intention to tie federal financial aid eligibility for select vocational programs (disproportionately at for-profit colleges) in 2009 and entered negotiated rulemaking in 2009-10. The first rules, released in 2011, were struck down in 2012 due a lack of a “reasoned basis” for the criteria used. The second attempt entered negotiated rulemaking in 2013, survived legal challenges in 2015, and began to take effect with the first data release in early 2017. Nearly all of the programs that failed in the first year were at for-profit colleges, but this also led to Harvard shutting down a failing graduate theater program. No colleges have lost aid eligibility yet, as two failing years are required before a college is at risk of losing funds.

The Trump administration is likely to take one of three paths in changing gainful employment regulations:

Path 1: Expand the rules to cover everyone. One of the common critiques against the current regulations is that they only cover nondegree programs at nonprofit colleges in addition to nearly all programs at for-profit colleges. For example, doctoral programs in education at Capella University are covered by gainful employment, while my program at Seton Hall University is not. Requiring all programs to be covered by gainful employment would both preserve the goals of the original regulations while silencing some of the concerns. But this would face intense pressure from colleges that are not currently covered (particularly private nonprofits).

Path 2: Restrict the rules to cover only the most at-risk programs. It is possible that gainful employment metrics could be used along other risk factors (such as heightened cash monitoring status or high student loan default rates) to determine federal loan eligibility. If written a certain way, this would free nearly all programs from the rules without completely unwinding the regulations.

Path 3: Make the rates for informational purposes instead of accountability purposes. This is the most likely outcome in my view. The Trump administration can provide useful consumer information without tying federal funds (a difficult thing to actually do, anyway). In this case, I could see all programs being included since the data will be somewhat lower-stakes.

Borrower Defense to Repayment

Unlike gainful employment, borrower defense to repayment regulations were set to affect for-profit and nonprofit colleges relatively equally. Here is what I wrote back in October about the regulations when they were announced.

These wide-ranging regulations, which will take effect on July 1, 2017 (a summary is available here) allow individuals with student loans to get relief if there is a breach of contract or court decision affecting that college or if there is “a substantial misrepresentation by the school about the nature of the educational program, the nature of financial changes, or the employability of graduates.” The language regarding “substantial misrepresentation” could have the largest impact for both for-profit and nonprofit colleges, as students will have six years to bring lawsuits if loans are made after July 1, 2017.

These regulations have been halted and will not take effect until a new round of negotiated rulemaking takes place. They were generally unpopular among colleges, as evidenced by a strong lobbying effort from historically black colleges that were worried about the vague definition of “misrepresentation.” The outcome of this negotiated rulemaking session is likely to be a significant rollback of the scope to cover only the most egregious examples of fraud.

Although these two sets of negotiated rulemaking sessions are likely to mainly be for show due to the Department of Education’s final ability to write rules when the committee deadlocks, they will provide insight into how various portions of the higher education community view the federal role in accountability under the Trump administration. The Department of Education doesn’t livestream these meetings (a real shame), but I’ll be following along on Twitter with great interest. Pass the popcorn, please?

Which Factors Affect Student Loan Repayment and Default Rates?

As student loan debt has surpassed $1.25 trillion, policymakers and members of the public are increasingly concerned about whether students are able to manage rising (but often still modest) loan burdens. The federal government has relied on a measure called cohort default rates—the percentage of former borrowers who defaulted on their loans within a few years of entering repayment—to deny federal financial aid access to colleges with a high percentage of struggling students. Yet default rates can be easily manipulated using strategies such as deferment and forbearance (which often don’t help students in the long run), meaning that default rates are a very weak measure of students’ post-college outcomes.

The 2015 release of the College Scorecard dataset included a new measure—student loan repayment rates, defined as the percentage of borrowers repaying any principal within a certain period of entering repayment. This gets at whether students are paying down their loans, which seems to be a more helpful indicator than relying heavily on default rates. But since repayment rates are a new measure, colleges had no incentive to manipulate repayment rates as they did default rates. This creates a research opportunity to examine whether colleges may have been acting strategically to lower default rates even as their students’ underlying financial situations did not change.

I teamed up with Amy Li, an assistant professor at the University of Northern Colorado, to examine whether the factors affecting loan repayment rates differ from those factors affecting default rates—and whether the factors affecting repayment rates varied based on the number of years after the student entered repayment. Our article on this topic is now out in the ANNALS of the American Academy of Political and Social Science, with a pre-publication version available on my personal website.

We used default and repayment data on students who entered repayment in fiscal years 2006 and 2007 so we could track repayment rates over time. Default rates at the time covered the same time period as the one-year repayment rate, while we also looked at repayment rates three, five, and seven years after entering repayment. (And we had to scramble to redo our analyses this January, as the Department of Education announced a coding error in their repayment rate data in the last week of the Obama Administration that significantly lowered loan repayment rates. If my blog post on the error was particularly scathing, trying to revise this paper during the journal editing process was why!) We then used regressions to see which institutional-level factors were associated with both default and non-repayment rates.

Our key findings were the following:

(1) Being a traditionally underrepresented student was a stronger predictor of non-repayment than default. Higher percentages of first-generation, independent, first-generation, or African-American students were much more strongly associated with not repaying loans than defaulting after controlling for other factors. This suggests that students may be avoiding default (perhaps with some help from their former colleges), but they are struggling to pay down principal soon after leaving college.

(2) For-profit colleges had higher non-repayment rates than default rates. Being a for-profit college (compared to a public college) was associated with a 1.7 percent increase in default rates, yet an 8.5% increase in non-repayment. Given the pressure colleges face to keep default rates below the threshold needed to maintain federal loan eligibility—and the political pressures for-profit colleges have faced—this result strongly suggests that colleges are engaging in default management strategies.

(3) The factors affecting repayment rates changed relatively little in importance over time. Although there were some statistically significant differences in coefficients between one-year and seven-year repayment rates, the general story is that a higher percentage of underrepresented students was associated with higher levels of non-repayment across time.

As loan repayment rates (hopefully!) continue to be reported in the College Scorecard, it will be interesting to see whether colleges try to manipulate that measure by helping students close to repaying $1 in principal get over that threshold. If the factors affecting repayment rates significantly change for students who entered repayment after 2015, that is another powerful indicator that colleges try to look good on performance metrics. On the other hand, the growth of income-driven repayment systems that allow students to be current on their loans without repaying principal, could also change the relationships. In either case, as colleges adapt to a new accountability system, policymakers would be wise to consider additional metrics in order to get a better measure of a college’s true performance.

Do Financial Responsibility Scores Predict College Closures?

The U.S. Department of Education’s Office of Federal Student Aid quietly released data on the financial responsibility scores of private nonprofit and for-profit colleges earlier this week, something that they have done for each of the last nine years. These scores, which can range from -1.0 to 3.0, are designed to represent a college’s financial health (although some colleges dispute the value of these scores). A score of 1.5 or above represents a passing score, meaning colleges can receive federal financial aid dollars without any additional restrictions.

Colleges scoring 0.9 or below fail the financial responsibility test and must submit a letter of credit to the Department of Education and submit to additional oversight in order to receive federal funds, while colleges scoring between 1.0 and 1.4 receive additional oversight but do not have to submit a letter of credit. Colleges in the worst financial shape may not even receive a score, as the Department of Education can instead choose to place a college under heightened cash monitoring rules (similar to the penalties for failing) without even doing the calculations.

In the newly-released data for the 2014-15 fiscal year, 187 colleges failed, 139 were in the oversight zone, while 3,048 passed unconditionally. The number of failures is the lowest on record, while the number in the oversight zone is also relatively low compared to past years. But at the same time, the rate of college closures increased sharply last year. Does this mean that financial responsibility scores are identifying financially struggling colleges, or is the metric incorrectly identifying colleges at risk of closure as being financially stable?

To answer this question, I used the best existing database of college closures—from Ray Brown’s College History Garden blog. (Check it out!) I examined the fourteen accredited private nonprofit colleges that closed in 2016 to see what the college’s financial responsibility score was in the 2014-15 fiscal year. (For colleges without a score, I checked the heightened cash monitoring (HCM) list as of September 1, 2015.) The results are below.

Name Score (2014-15)
AIB College of Business  N/A
American Indian College -0.2
Barber-Scotia College  N/A
Burlington College HCM
Colorado Heights University 2.2
Crossroads College HCM
Dowling College 0.6
Kilian Community College 1.8
Northwest Institute of Literary Arts -0.9
Ohio College of Massotherapy 2.7
Saint Catharine College HCM
The Robert B. Miller College -1
Trinity Lutheran College 0.6
Wright Career College 1.1


Two of the 14 colleges did not show up as either having a financial responsibility score or being under HCM, while three other colleges were on HCM due to financial issues and did not receive a financial responsibility score. Of the other nine colleges, four received a passing financial responsibility score (the Ohio College of Massotherapy received the same score as Yale), two were in the additional oversight zone, and three failed. This suggests that either financial conditions changed considerably between mid-2015 and 2016 for some colleges or that financial responsibility scores are an imperfect measure of a college’s fiscal health.

How Much Did A Coding Error Affect Student Loan Repayment Rates?

Mistakes happen. I should know—I make more than my fair share of them (including on this blog). But some mistakes are a little more noticeable than others, such as when your mistake has been viewed more than a million times. That is what happened to the U.S. Department of Education recently, when they found a coding error in the popular College Scorecard website and dataset.

Here is a description of the coding error from the Department of Education’s announcement:

“Repayment rates measure the percentage of undergraduate borrowers who have not defaulted and who have repaid at least one dollar of their principal balance over a certain period of time (1, 3, 5, or 7 years after entering repayment). An error in the original college scorecard coding to calculate repayment rates led to the undercounting of some borrowers who had not reduced their loan balances by at least one dollar, and therefore inflated repayment rates for most institutions. The relative difference—that is, whether an institution fell above, about, or below average—was modest.  Over 90 percent of institutions on the College Scorecard tool did not change categories (i.e., above, about, or below average) from the previously published rates. However, in some cases, the nominal differences were significant.”

As soon as I learned about the error, I immediately started digging in to see how much it affected loan repayment rates. After both my trusty computer and I made a lot of noise trying to process the large files in a short period of time, I was able to come up with some top-level results. It turns out that the changes in loan repayment rates are very large. Three-year repayment rates fell from 61% to 41%, five-year repayment rates fell from 61% to 47%, and seven-year repayment rates fell from 66% to 57%. These changes were quite similar across sectors.


Difference between corrected and previous loan repayment rates (pct).
Corrected Previous Difference N
All colleges
  3-year 41.0 61.0 -20.0 6,090
  5-year 47.1 61.1 -14.0 5,842
  7-year 56.7 66.3 -9.6 5,621
  3-year 46.6 66.8 -20.2 1,646
  5-year 54.2 68.9 -14.7 1,600
  7-year 62.1 72.1 -10.0 1,565
Private nonprofit
  3-year 57.7 77.5 -19.8 1,386
  5-year 63.7 77.3 -13.6 1,375
  7-year 70.4 79.3 -8.9 1,338
  3-year 30.5 50.4 -19.9 3,058
  5-year 35.0 48.9 -13.9 2,850
  7-year 46.9 56.5 -9.6 2,700
Source: College Scorecard.


For those who wish to dig into individual colleges’ repayment rates, here is a spreadsheet of the new and old 3, 5, and 7-year repayment rates.

Fixing the coding error made a big difference in the percentage of students who are making at least some progress repaying their loans. (And ED’s announcement yesterday that it will create a public microdata file from the National Student Loan Data System will help make these errors less likely in the future as researchers spot discrepancies.) This change is likely to get a lot of discussion in coming days, particularly as the new Congress and the incoming Trump administration get ready to consider potential changes to the federal student loan system.

How Much Do For-Profit Colleges Rely on Federal Funds?

Note: This post initially appeared on the Brookings Institution’s Brown Center Chalkboard blog.

The outgoing Obama administration placed for-profit colleges under a great deal of scrutiny. This includes gainful employment regulations that will require graduates of vocationally-oriented programs to meet debt-to-earnings requirements and borrower defense to repayment rules (which will likely be quickly abandoned by the Trump administration) designed to help students who feel they were defrauded by their college.

But special federal scrutiny of the for-profit sector has been around for decades, with one rule shaping the behavior of many colleges. This post explores the extent to which for-profit colleges rely on federal funds. It turns out that many rely heavily on these funds, although it’s not always clear what the implications are for the public.

In the 1992 Higher Education Act reauthorization, Congress included a provision that only applied to for-profit colleges, limiting the percentage of total revenue that for-profits could receive from federal grant, loan, and work-study programs to 85%. (This notably excludes veterans’ benefits, which are a large source of revenue for some colleges.) This percentage was increased to 90% in the 1998 reauthorization, which led to the rule being commonly referred to as “90/10.”

For-profit colleges that exceed 90% of their revenue from federal financial aid in two consecutive years can lose access to federal aid for the following two years. Some Democrats have tried to move back to the 85/15 rule or include veterans’ benefits in the federal financial aid portion of revenue, but these efforts will likely be unsuccessful given the support Republicans have received from for-profit colleges. Notably, some for-profits get a sizable portion of their revenue from veterans’ benefits.

I examined data from the Department of Education between the 2007-08 and 2014-15 academic years to look at how many for-profit colleges are close to the 90% threshold. As the table below shows, a sizable percentage of for-profit colleges get between 80% and 90% of their revenue from federal financial aid. In 2007-08 (the last year before the Great Recession), 23% of colleges were in this category. This rose to 35% in 2009-10 and 38% in 2011-12—the beginning of a sizable enrollment decline in the for-profit sector. As the for-profit sector contracted, the percentage of colleges receiving 80% and 90% of their revenue from federal aid fell to 29% in 2014-15. Yet very few colleges have crossed over the 90% threshold, and just two small colleges lost federal aid eligibility this year for going over 90% in two consecutive years.

Distribution of for-profit colleges’ reliance on federal financial aid dollars by year.
  Pct of total revenue from Title IV funds (number of colleges) Number of colleges
Year 0-70 70-75 75-80 80-85 85-90 90-100
2007-2008 56.9 9.1 11.2 12.5 10.3 0.1 1,831
2008-2009 46.2 12.0 13.2 15.1 13.1 0.4 1,798
2009-2010 37.5 10.9 15.8 19.8 15.5 0.5 1,884
2010-2011 39.5 11.4 14.2 17.5 16.6 0.7 1,976
2011-2012 36.5 10.7 13.6 17.6 20.2 1.4 1,999
2012-2013 37.7 11.9 14.2 15.2 19.5 1.4 1,888
2013-2014 40.5 11.7 14.4 15.1 17.6 0.7 1,888
2014-2015 45.2 12.1 12.8 15.1 13.9 0.9 1,838
Source: Office of Federal Student Aid, U.S. Department of Education.
Note: Institutions based outside the 50 United States and Washington, DC are excluded from the analyses.


I then looked at the reliance on federal aid among the eleven for-profit colleges with at least $600 million in overall revenue in the 2013-14 academic year (as 2014-15 revenue data were incomplete as of this analysis). Most of these colleges became slightly less reliant on federal funds between 2010-11 and 2014-15, highlighted by DeVry’s drop from 81% to 66%. DeVry has notably pledged to voluntarily abide by the 85/15 rule across all of its colleges (including veterans’ benefits), so its declining reliance on federal aid is not surprising. ITT Tech saw a 20% increase in its share of revenues coming from financial aid before its closure, while Ashford, Kaplan, and Phoenix consistently remained at or above 80% across the five years. The American Public University System, which focuses on veterans, got less than half of its revenue from federal financial aid.



In December, the Department of Education worked with the Department of Defense and Department of Veterans Affairs to produce a dataset that included colleges’ revenue from various military and veterans’ benefits programs. A key finding of the departments is that an estimated 200 for-profit colleges would get more than 90% of their revenue from federal sources if all federal funds were counted, up from 17 under the current version of the 90/10 rule. In other words, roughly 200 for-profit colleges are almost entirely funded by the federal government, although some of this funding is returned to the government when students repay their loans. Yet this fact is obscured when military and veterans’ benefits are excluded from the calculations.

Below is a summary of the approximate revenue percentages from Department of Education and military sources for the eleven largest for-profits in the 2013-14 academic year.


Five of these top eleven colleges exceed the 90/10 rule once all federal sources are included. All for-profit colleges are estimated to have at least 70% of revenue come from federal sources.  However, this calculation may be several percent off due to differences in how each source calculates an academic year (as evidenced by ITT Tech’s 103% of revenue coming from the federal government).

The data suggest that American Public University gets more revenue from military sources than the Department of Education, while four other for-profits (Ashford, ITT Tech, Phoenix, and Strayer) got at least ten percent. From this table, it is clear that some for-profits consider military benefits as an important revenue source (others, such as DeVry and Argosy, do not).

Is it a problem that for-profit colleges generate such a large portion of their revenues from federal funds? To me, the answer is not entirely clear. A concern with many for-profit colleges’ heavy reliance on federal funds is that it signals a lack of interest from employers in these colleges’ programs. Given that many for-profit colleges were founded to train employees for specific jobs, the lack of private funding is a concern. The post-college outcomes of many for-profit colleges also deserve additional scrutiny, particularly as newly released gainful employment data show that for-profit colleges are the vast majority of institutions that failed both performance metrics.


On the other hand, the heavy reliance on federal funds also reflects the reality that for-profit colleges serve a large percentage of financially needy students. Many of these students are unable to attend college without some sort of financial assistance, whether it be the Pell Grant, student loans, or state appropriations that help to lower the price tag for college. A sizable percentage of public and private nonprofit colleges get a majority of their revenue from the federal or state governments, but they do not face the same level of public scrutiny as for-profit colleges.

Finally, it would be helpful if the Department of Education provided data on how much revenue all colleges received from military sources in addition to federal financial aid dollars. This could be used to highlight colleges that rely heavily on government funding, but it could also be used to showcase colleges that serve a particularly large percentage of active-duty military members and veterans.

Highlights from the Gainful Employment Data Release

In one of the Obama administration’s final education policy actions, the U.S. Department of Education released a long-awaited dataset of earnings and debt burdens under the gainful employment accountability regulations. These regulations, which survived several legal challenges from the for-profit college sector, require programs that are defined to be vocationally-oriented in nature (the majority of programs at for-profit colleges and a small subset of nondegree programs at public and private nonprofit colleges) to meet one of two debt-to-earnings metrics in order to continue receiving federal financial aid.

Option 1 (annual earnings): The average student loan payment of graduates in a program must be less than 8% of either mean or median earnings in order to pass. Payments between 8% and 12% of income puts programs “in the zone,” while payments above 12% of income result in a failure.

Option 2 (discretionary income): The average student loan payment of graduates in a program must be less than 20% of discretionary income (earnings above 150% of the federal poverty line) in order to pass. Payments between 20% and 30% of discretionary income puts programs “in the zone,” while payments above 30% of discretionary income result in a failure.

Any colleges that fail both metrics twice in a three-year period (using both mean and median earnings) or colleges in the oversight zone for four consecutive years are currently at risk of losing access to federal financial aid. However, both the Trump administration and Congressional Republicans have expressed interest in scrapping this accountability metric, meaning that colleges may not actually face sanctions in the future.

This data release covered 8,637 programs at 2,616 colleges, with about two-thirds of these programs being at for-profit institutions. Overall, 803 programs (9.3%) failed and 1,239 programs (14.4%) were in the oversight zone, with the remaining 76% of programs passing. As shown below, there were large differences in the pass rates by type of institution (note: the incorrect headers on the original post have been fixed). No public colleges failed (likely due to lower tuition levels because of state and local subsidies), and failure rates in the private nonprofit sector were also fairly low. Yet Harvard, Johns Hopkins, and the University of Southern California all had one program fail—leaving these prestigious institutions with some egg on their face. (UPDATE: Harvard suspended admissions for their graduate program in theater that failed gainful employment within one week of the data release.)

Distribution of gainful employment scores by sector and level.
Percentage of programs
Sector Fail Zone Pass N
Public, <2 year 0.0 0.7 99.3 293
Public, 2-3 year 0.0 0.3 99.7 1,898
Public, 4+ year 0.0 0.3 99.7 302
Private nonprofit, <2 year 0.0 10.3 89.7 78
Private nonprofit, 2-3 year 3.5 22.0 74.6 173
Private nonprofit, 4+ year 4.7 9.0 86.3 212
For-profit, <2 year 4.4 19.7 76.0 1,460
For-profit, 2-3 year 11.5 20.1 68.4 2,042
For-profit, 4+  year 22.5 21.4 56.1 2,174
Total 9.3 14.4 76.4 8,637
Source: U.S. Department of Education.
(1) Percentages may not add up to 100 due to rounding.
(2) The “total” row excludes five foreign colleges.


For-profit colleges that only offer shorter programs (primarily certificates) did pretty well in the gainful employment metrics, with only 4% failing and 20% in the oversight zone. The worst outcomes were by far among four-year for-profit colleges, with 23% failing and 21% in the oversight zone. These poorer outcomes are not being driven by the large for-profit chains. DeVry, Kaplan, Strayer, and Phoenix combined to have just 16 programs fail, while four colleges (Vaterott, Sanford-Brown, the Art Institute of Phoenix, and Virginia College) all had at least 19 programs fail.

I then examined how the different sectors of colleges performed on the debt-to-earnings ratios for both annual income and discretionary income, with the distributions of ratios shown on the charts below. (Red vertical lines represent the cutoffs for being in the oversight zone (left) and failing (right).) These graphs confirm that public colleges have the lowest debt-to-earnings ratios, followed by private nonprofit colleges and for-profit colleges.



There are three important drawbacks of this data release that are worth emphasizing. First, 133 programs, all at for-profit colleges, are still in the process of appealing their classification (67 that failed and 66 that are in the oversight zone). Second, this only includes a small subset of programs at public and private nonprofit colleges even as similar programs are covered at for-profit colleges. For example, for-profit law schools are included in the gainful employment regulations (and the outcomes aren’t always great). But law programs at nonprofit law schools aren’t covered by the regulations, even though the goal at the end of the program is similar and many colleges expect their law schools to generate excess revenue for their university. Third, by only covering people who completed a program, colleges with low completion rates may look good even if the quality of education induces students to leave the program in disgust.

Regardless of whether federal financial aid dollars are tied to graduates’ debt-to-earnings ratios, it is important to make more program-level outcome data available to students, their families, and the general public. There have been discussions about including program-level data in the College Scorecard, but that is far from a certainty at this point. At the very least, the incoming Trump administration should propose making comparable earnings and debt available for vocationally-focused degree programs at public and private nonprofit colleges.

How to Improve Income-Driven Repayment Plan Cost Estimates

The Government Accountability Office (GAO) took the U.S. Department of Education (ED) behind the proverbial woodshed in a new report that was extremely critical of how ED estimated the cost of income-driven repayment (IDR) programs. (Senate Republicans, which asked for the report, immediately piled on.) Between fiscal years 2011 and 2017, ED estimated that IDR plans would cost $25.1 billion. The current estimated cost is up to $52.5 billion, as shown in the figure below from the GAO report.


The latest estimate from the GAO—and the number that got front-page treatment in The Wall Street Journal—is that the federal government expects to forgive $108 billion of the estimated $352 billion of loans currently enrolled in income-driven repayment plans. Much of the forgiven loan balances are currently scheduled to be taxable (a political hot topic), but some currently unknown portion will be completely forgiven through Public Service Loan Forgiveness.


The GAO report revealed some incredible concerns with how ED estimated program costs. Alexander Holt of New America has a good summary of these concerns, calling them “gross negligence.” In addition to the baffling choices not to even account for Grad PLUS loans in IDR models until 2015 (!) and to not assume borrowers’ incomes increased at the rate of inflation (!!), ED ran very few sensitivity analyses about how different reasonable assumptions would affect program costs. As a result, the estimates have not tracked tremendously closely with reality over the last several years.

But there are several reasonable steps that could be taken to improve the accuracy of cost estimates within a reasonable period of time. They are the following:

(1) Share the current methodology and take suggestions for improvement from the research community. This idea comes from Doug Webber, a higher ed finance expert and assistant professor at Temple University:

ED could then take one of two paths to improve the models. First, they could simply collect submissions of code from the education community to see what the resulting budget estimates look like. A second—and better—way would be to convene a working group similar to the technical review panels used to improve National Center for Education Statistics surveys. This group of experts could help ED develop a set of reasonable models to estimate costs.

(2) Make available institutional-level data on income-driven repayment takeup rates and debt burdens of students enrolled in IDR plans. This would require ED to produce a new dataset from the National Student Loan Data System, which is no small feat given the rickety nature of the data system. But, as the College Scorecard shows, it is possible to compile better information on student outcomes from available data sources. ED also released information on the number of borrowers in IDR plans by state last spring, so it’s certainly possible to release better data.

(3) Make a percentage of student-level loan data available to qualified researchers. This dataset already exists—and is in fact the same dataset that ED uses in making budget projections. Yet, aside from one groundbreaking paper that looked at loan defaults over time, no independent researchers have been allowed access to the data. Researchers can use other sensitive student-level datasets compiled by ED (with the penalty for bad behavior being a class E felony!), but not student loan data. I joined over 100 researchers and organizations this fall calling for ED to make these data available to qualified researchers who already use other sensitive data sources.

These potential efforts to involve the research community to improve budget estimates are particularly important during a Presidential transition period. The election of Donald Trump may lead to a great deal of turnover within career staff members at the Department of Education—the types of people who have the skills needed to produce reasonable cost estimates. I hope that the Trump Administration works to keep top analysts in the Washington swamp, while endeavoring to work with academics to help improve the accuracy of IDR cost projections.

Five Higher Education Suggestions for President-Elect Trump

It’s pretty safe to say that Donald Trump wasn’t the candidate of choice for much of American higher education. Hillary Clinton received nearly 100 times as much in donations from academics as Trump, and the list of academics supporting Trump doesn’t have a lot of well-known names. But the typical American saw the election in a far different way than your average New York Times reader (as evidenced by the big divide in support by educational attainment), and Trump is now the president-elect after a stunning victory.

Here are my recommendations for Trump in the realm of higher education policy as he prepares to move from Trump Tower to the White House in just over two months.

(1) The Department of Education won’t go away, but certain functions could be reassigned. Although the Republicans kept control of the House and Senate, the margins are razor-thin—perhaps a four-vote margin in the Senate and a tenuous grip on the House thanks to divides between establishment and activist Republicans. This makes getting rid of the Department of Education extremely unlikely. Some functions, such as handling student loans, could go to the Department of the Treasury. Others could possibly go to states in the form of block grants. Yet there will still be a need for some administration in Washington to handle basic functions.

(2) Reach out to career staff members at the Department of Education. Trump ran on the concept of “draining the swamp,” but replacing longtime Washington staffers all at once comes at a risk. Career staff members who have served in multiple administrations have knowledge about how programs work that is difficult to replace, so it is essential to keep some of those staff members to help ensure a smooth transition across administrations. Will longtime staffers want to work for Trump? It’s anyone’s guess, but Trump’s transition team should make a good-faith effort to reach out.

(3) Make Higher Education Act reauthorization a priority. With unified (but tenuous) Republican control, Higher Education Act reauthorization suddenly looks more plausible than it did last week. A Trump administration should focus on the HEA in an effort to govern through the legislative branch rather than using executive orders and administrative rules—policies that conservatives have despised. 2017 reauthorization is probably unlikely given the administration’s other priorities, but 2018 or 2019 could work.

(4) Make more higher education data available to the public. The Obama administration made some good strides in the area of consumer information, culminating in the College Scorecard. Yet they also didn’t make data on a range of outcomes (such as PLUS loan default rates or program-level data) available to either the public or researchers. I signed onto a letter along with over 100 researchers last month calling for the Department of Education to release additional data on the federal student loan portfolio, and the Trump administration should release the data. Even if Trump wants to back down in terms of high-stakes accountability, consumer information is important.

(5) Visit a number of colleges across the higher education spectrum. Like most presidents, Trump is a product of high-prestige colleges (attending Fordham and Penn). I’d love to see him experience the great diversity of American higher education, including rural community colleges, HBCUs, technical institutes, and the workhorse regional public university sector. I hope that some colleges extend invitations to Trump—and that he accepts them.

Borrower Defense to Repayment Regulations: The Obama Administration’s Greatest Higher Education Legacy?

President Obama famously said in 2014 that “I’ve got a pen, and I’ve got a phone.” Although he has used his pen to sign some substantial changes in federal higher education policy (such as ending the bank-based student loan program in favor of federal Direct Loans), his pen has been used more frequently to authorize the Department of Education to start implementing new regulations without going through Congress. The regulatory process has been used to expand income-driven repayment programs, implement gainful employment rules for students in select vocationally-oriented programs, and tie federal TEACH grants to some measure of teachers’ effectiveness. These efforts have been generally opposed by congressional Republicans, which have held a majority in at least one chamber of Congress since 2011.

But from the perspective of colleges, the newest set of regulations may end up being the most influential. The Department of Education recently unveiled the final regulations known as “borrower defense to repayment” in a response to concerns about colleges defrauding students or suddenly closing their doors. These wide-ranging regulations, which will take effect on July 1, 2017 (a summary is available here) allow individuals with student loans to get relief if there is a breach of contract or court decision affecting that college or if there is “a substantial misrepresentation by the school about the nature of the educational program, the nature of financial changes, or the employability of graduates.”

The language regarding “substantial misrepresentation” could have the largest impact for both for-profit and nonprofit colleges, as students will have six years to bring lawsuits if loans are made after July 1, 2017. Notably, this language treats intentional misrepresentation and honest errors in the same way, and also does not define what “substantial” is. For example, if a student enrolls in a program with a posted job placement rate of 98% and later finds out that college administrators e-mailed each other about how to hide a 48% placement rate, most courts would probably consider this to be substantial misrepresentation. But what if a well-meaning person accidentally transposed an 89% placement rate to get 98%? These errors do happen in data submitted to the federal government, and currently there is no penalty for this type of mistake.

As some have warned, the ambiguity of the language will likely open up the door for more lawsuits against colleges with a wide range of misrepresentations—particularly as the regulations allow for class-action lawsuits that colleges could previously restrict. Courts across the country vary considerably in their friendliness toward plaintiffs relative to defendants, meaning that colleges located in more plaintiff-friendly states such as California and Illinois may be more at risk of lawsuits than colleges in defendant-friendly states such as Delaware and Iowa. But even if a college can prevail in a lawsuit, it still has to pay its legal fees and also may be subject to bad publicity.

Although these new regulations are a clear and needed victory for students who attended undeniably fraudulent colleges, the ripple effects regarding the definition of “substantial” misrepresentation could affect a broad group of well-intending nonprofit colleges that either made honest mistakes or happened across a sympathetic judge or jury. Eventually, a series of court cases—perhaps in conjunction with additional federal guidance—should help settle the legal landscape, but in the meantime colleges will be watching these regulations with a great deal of anxiety.

The Price and Cost of College Are Different Things

As someone who spends a lot of time thinking about some of the wonkier issues of higher education finance, there are some common statements that just drive me nuts. For example, people who refer to the U.S. Department of Education as the “DOE” (it’s “ED” and the Department of Energy is “DOE”) or pronounce the FAFSA as “FASFA” might as well be screeching their fingernails on a chalkboard. But, as much as those things annoy me, they’re examples of inside baseball at their finest—they don’t affect students, but they’re still deviations from the norm. So I’ll try to hide my grimaces in those situations going forward.

However, I will say something every time someone erroneously refers to the cost of college when they truly mean the price of college, as these are two distinctly different concepts. Here are the definitions of the two terms:

Price: This represents how much money a student and/or their family has to pay for college.

Cost: This represents how much money it takes to provide an education.

With the presence of federal, state, and institutional financial aid as well as direct state appropriations to colleges, the price that many students pay can be far below the true cost of providing the education. On the other hand, due to the tangled web of subsidies present in the “awkward economics” of higher education, some students (such as full-freight international students and master’s students as well as those enrolled in large lecture classes) may be paying far more than it costs to provide their education.

From a policymaker’s perspective, it if far easier to propose bringing down the price of college than the cost of college—even though these proposals have large price tags and finding funding can be difficult. (An exception is so-called “last dollar” programs at community colleges, which often leverage other grant aid sources instead of using much of their own money.) Bending the cost curve is a far more difficult endeavor, as technology generally hasn’t done much to reduce costs (a promising master’s degree program at Georgia Tech notwithstanding) and other options such as increasing class sizes or spending less on facilities frequently run into opposition.

Efforts to bring down the price of college have become increasingly popular over the last several years, but they must be accompanied with a willingness to reduce costs in order for these programs to be financially feasible in the long run. To this point, cost control has remained a distant goal for most policymakers—a perfectly reasonable position given the shorter time horizons of most politicians. Bringing down prices today gets attention, while the crucial step of bringing down costs in the future is nowhere near as exciting.