Gainful Employment and the Federal Ability to Sanction Colleges

The U.S. Department of Education’s second attempt at “gainful employment” regulations, which apply to the majority of vocationally-oriented programs at for-profit colleges and certain nondegree programs at public and private nonprofit colleges, was released to the public this morning. The Department’s first effort in 2010 was struck down by a federal judge after the for-profit sector challenged a loan repayment rate metric on account of it requiring additional student data collection that would be illegal under current federal law.

The 2014 measure was widely expected to contain two components: a debt-to-earning s ratio that required program completers to have annual loan debt be less than 8% of total income or 20% of “discretionary income” above 150% of the poverty line, and a cohort default rate measure that required fewer than 30% of program borrowers (regardless of completion status) to default on federal loans in less than three years. As excellent articles on the newly released measure in The Chronicle of Higher Education and Inside Higher Ed this morning detail, the cohort default rate measure was unexpectedly dropped from the final regulation. This change in rules, Inside Higher Ed reports, would reduce the number of affected programs from 1,900 to 1,400 and the number of affected students from about one million to 840,000.

There will be a number of analyses of the exact details of gainful employment over the coming days (I highly recommend anything written by Ben Miller at the New America Foundation), but I want to briefly discuss on what the changes to the gainful employment rule mean for other federal accountability policies. Just over a month ago, the Department of Education released cohort default rate data, but they tweaked a calculation at the last minute that had the effect of allowing more colleges to get under the 30% default rate threshold at least once in three years to avoid sanctions.

The last-minute changes to both gainful employment and cohort default rate accountability measures highlight the political difficulty of the current sanctioning system, which is on an all-or-nothing basis. When the only funding lever the federal government uses is so crude, colleges have a strong incentive to lobby against rules that could effectively shut them down. It is long past time for the Department of Education to consider sliding sanctions against colleges with less-than-desirable outcomes if the goal is to eventually cut off financial aid to the poorest performing institutions.

Finally, the successful lobbying efforts of different sectors of higher education make it appear less likely that the Obama Administration’s still-forthcoming Postsecondary Institution Ratings System (PIRS) will be able to tie financial aid to college ratings. This measure still requires Congressional approval, but the Department of Education’s willingness to propose sanctions has been substantially weakened over the last month. It remains to be seen if the Department of Education under the current administration will propose how PIRS will be tied to aid before the clock runs out on the Obama presidency.

Comments on the CollegeNET-PayScale Social Mobility Index

The last two years have seen a great deal of attention being placed on the social mobility function that many people expect colleges to perform. Are colleges giving students from lower-income families the tools and skills they need in order to do well (and good) in society? The Washington Monthly college rankings (which I calculate) were the first entrant in this field nearly a decade ago, and we also put out lists of the Best Bang for the Buck and Affordable Elite colleges in this year’s issue. The New York Times put out a social mobility ranking in September, which essentially was a more elite version of our Affordable Elite list, which looked at only about 100 colleges with a 75% four-year graduation rate.

The newest entity in the cottage industry of social mobility rankings comes from PayScale and CollegeNET, an information technology and scholarship provider. Their Social Mobility Index (SMI) includes five components for 539 four-year colleges, with the following weights:

Tuition (lower is better): 126 points

Economic background (percent of students with family incomes below $48,000): 125 points

Graduation rate (apparently six years): 66 points

Early career salary (from PayScale data): 65 points

Endowment (lower is better): 30 points

The top five colleges in the rankings are Montana Tech, Rowan , Florida A&M, Cal Poly-Ponoma, and Cal State-Northridge, while the bottom five are Oberlin, Colby, Berklee College of music, Washington University, and the Culinary Institute of America.

Many people will critique the use of PayScale’s data in rankings, and I would partially agree—although it’s the best data that is available nationwide at this point until the ban on unit record data is eliminated. My two main critiques of these rankings are the following:

Tuition isn’t the best measure of college affordability. Judging by the numbers used in the rankings, it’s clear that the SMI uses posted tuition and fees for affordability. This doesn’t necessarily reflect what the typical lower-income student would actually pay for two reasons, as it excludes room, board, and other necessary expenses while also excluding any grant aid. The net price of attendance (the total cost of attendance less all grant aid) is a far better measure of what students from lower-income families may pay, even though the SMI measure does capture sticker shock.

The weights are justified, but still arbitrary. The SMI methodology includes the following howler of a sentence:

“Unlike the popular periodicals, we did not arbitrarily assign a percentage weight to the five variables in the SMI formula and add those values together to obtain a score.”

Not to put my philosopher hat on too tightly, but any weights given in college rankings are arbitrarily assigned. A good set of rankings is fairly insensitive to changes in the weighting methodology, while the SMI does not answer that question.

I’m pleased to welcome another college rankings website to this increasingly fascinating mix of providers—and I remain curious the extent to which these rankings (along with many others) will be used as either an accountability or a consumer information tool.

Do Student Loans Result in Tuition Increases? Why It’s So Hard to Tell

One of the longstanding questions in higher education finance is whether access to federal financial aid dollars is one of the factors behind tuition increases. This was famously stated by Education Secretary William Bennett in a 1987 New York Times editorial:

“If anything, increases in financial aid in recent years have enabled colleges and universities blithely to raise their tuitions, confident that Federal loan subsidies would help cushion the increase. In 1978, subsidies became available to a greatly expanded number of students. In 1980, college tuitions began rising year after year at a rate that exceeded inflation. Federal student aid policies do not cause college price inflation, but there is little doubt that they help make it possible.”

Since Secretary Bennett made his statement (now called the Bennett Hypothesis), more students are receiving federal financial aid. In 1987-1988, the average full-time equivalent student received $2,414 in federal loans, which rose to $6,374 in 2012-2013. The federal government has also increased spending on Pell Grants during this period, although the purchasing power of the grant has eroded due to large increases in tuition.

The Bennett Hypothesis continues to be popular in certain circles, as illustrated by comments by Dallas Mavericks owner and technology magnate Mark Cuban. In 2012, he wrote:

“The point of the numbers is that getting a student loan is easy. Too easy.

You know who knows that the money is easy better than anyone ? The schools that are taking that student loan money in tuition. Which is exactly why they have no problems raising costs for tuition each and every year.

Why wouldn’t they act in the same manner as real estate agents acted during the housing bubble? Raise prices and easy money will be there to pay your price. Good business, right ? Until its not.”

Recently, Cuban called for limiting student loans to $10,000 per year, as reported by Inc.:

“If Mark Cuban is running the economy, I’d go and say, ‘Sallie Mae, the maximum amount that you’re allowed to guarantee for any student in a year is $10,000, period, end of story.’  

We can talk about Republican or Democratic approaches to the economy but until you fix the student loan bubble–and that’s where the real bubble is–we don’t have a chance. All this other stuff is shuffling deck chairs on the Titanic.”

Cuban’s plan wouldn’t actually affect the vast majority of undergraduate students, as loan limits are often below $10,000 per year. Dependent students are limited to no more than $7,500 per year in subsidized and unsubsidized loans and independent students are capped at $12,500 per year. But this would affect graduate students, who can borrow $20,500 per year in unsubsidized loans, as well as students and their families taking out PLUS loans, which are only capped by the cost of attendance.

Other commentators do not believe in the Bennett Hypothesis. An example of this is from David Warren, president of the National Association of Independent Colleges and Universities (the professional association for private nonprofit colleges). In 2012, he wrote that “the hypothesis is nothing more than an urban legend,” citing federal studies that did not find a relationship.

The research on the Bennett Hypothesis can best be classified as mixed, with some studies finding a modest causal relationship between federal financial aid and tuition increases and others finding no relationship. (See this Wonkblog piece for a short overview or Donald Heller’s monograph for a more technical treatment.) But for data reasons, the studies of the Bennett Hypothesis either focus on all financial aid lumped together (which is broader than the original hypothesis) or just Pell Grants.

So do student loans result in tuition increases? There is certainly a correlation between federal financial aid availability and college tuition, but the first rule of empirical research is that correlation does not imply causation. And establishing causality is extremely difficult given the near-universal nature of student loans and the lack of change in program rules over time. It is essential to have some change in the program in order to identify effects separate from other types of financial aid.

In an ideal world (from a researcher’s perspective), some colleges would be randomly assigned to have lower loan limits than others and then longer-term trends in tuition could be examined. That, of course, is politically difficult to do. Another methodological possibility would be to look at the colleges that do not participate in federal student loan programs, which are concentrated among community colleges in several states. But the low tuition charges and low borrowing rates at community colleges make it difficult to even postulate that student loans could potentially drive tuition increases at community colleges.

A potential natural experiment (in which a change is introduced to a system unexpectedly) could have been the short-lived credit tightening of parent PLUS loans, which hit some historically black colleges hard. Students who could no longer borrow the full cost of attendance had to scramble to find other funding, which put pressure on colleges to find additional money for students. But the credit changes have partially been reversed before colleges had to make long-term decisions about pricing.

I’m not too concerned about student loans driving tuition increases at the vast majority of institutions. I think the Bennett Hypothesis is likely the strongest (meaning a modest relationship between loans and tuition) at the most selective undergraduate institutions and most graduate programs, as loan amounts can be substantial and access to credit is typically good. But, without a way to identify variations in loan availability across similar institutions, that will remain a postulation.

[NOTE (7/7/15): Since this piece was initially posted, more research has come out on the topic. See this updated blog post for my most up-to-date take.