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.

The Challenges Facing New York’s Tuition-Free College Program

Although tuition-free public college will not become a federal policy anytime soon, more states and local communities are considering different variations of free college. There are nearly 200 active college promise or free college programs in the United States, with two states (Arkansas and New York) enacting tuition-free programs in recent weeks.

New York’s Excelsior Scholarship program has garnered quite a bit of attention because it covers students at four-year colleges (most larger programs are limited to less-expensive two-year colleges), because of the conditions attached, and because New York governor Andrew Cuomo is likely to run for president in 2020. Yet the ambitious program (the legislation text starts on page 142 of this .pdf) also has to overcome a number of challenges in order to be truly effective. I discuss three of the key challenges with this program below.

Challenge 1: Will scholarship funds be available to all qualified students? The budget includes $163 million in funding for the program, which is probably far below the amount of money needed to fund all students. Judith Scott-Clayton of Teachers College estimated that an earlier version of the program could cost about $482 million per year. Even requirements that students complete 30 credits per year and clawbacks for students who leave the state after graduation (more on that later) may not bring the cost down enough—particularly if the program is successful in increasing enrollment at public colleges. The budget has a provision that allows awards to be cut or allocated via lottery if funds run short, which is a distinct possibility if the state faces another recession. Needless to say, this would be a PR nightmare for the state.

Challenge 2: Will colleges use fees as a tuition substitute? A full-tuition scholarship sounds great, but students and their families often forget about fees. Right now, fees are a sizable portion of direct educational prices. For example, at SUNY-Albany, tuition is $6,470 and fees are $2,793, while Hostos Community College charges $4,800 in tuition per year for a full-time student alongside $406 in fees. Since the scholarship only covers tuition, the state may pressure colleges to increase fees in an effort to reduce program costs. This happened in Massachusetts for years and still happens in Georgia, both states with large merit-based grant aid programs. Over time, it is quite possible that the value of the grant fails to keep up with inflation as a result—particularly if the state shifts funding from appropriations to student aid and colleges scramble for another revenue source.

Challenge 3: Will the state be able to manage a large “groan” program? Perhaps the most controversial portion of New York’s program is the requirement that students must live and work in the state after college for the same number of years that they received the grant; if they fail to do so, the grant converts to a loan (also known as a “groan” to financial aid wonks). Many people have raised concerns about the fairness of this idea, but here I’ll touch on the logistics of the program. Can the state of New York track students after graduation and see where they both live and work? Will they feel pressures to exempt students who live out of state but work in New York and pay state income taxes? What will the terms of the converted loans look like? There are a lot of unanswered questions here, but it is clear that the state must invest in a larger student loan agency in order to manage this complex of a program.

As Governor Cuomo prepares for a likely presidential bid in 2020, he is counting on the tuition-free college proposal to be one of his signature policy ideas. Some of the biggest concerns with this legislation may take years to develop, but even a period of two or three years may be enough to see whether the program can work effectively around some of the significant concerns noted here.

The Importance of Negative Expected Family Contributions

The Free Application for Federal Student Aid (FAFSA) has received a great deal of attention in the past year. From a much-needed change that allowed students to file the FAFSA in October instead of January for the following academic year to the pulling of the IRS Data Retrieval Tool that made FAFSA filing easier for millions of students, the federal financial aid system has had its ups and downs. But one criticism that has been consistent for years is that the FAFSA remains an extremely blunt—and complex—financial aid allocation instrument.

After students fill out the FAFSA, they receive an expected family contribution (EFC), which determines their eligibility for federal and other types of financial aid. EFCs are currently truncated at zero for reporting purposes, which lumps together millions of students with various levels of (high) financial need into the zero EFC category. In a previous article, I showed that more than one-third of undergraduate students have a zero EFC and how that rate has generally increased over time.

Yet the underlying FAFSA data allows for negative EFCs to be calculated, and these negative EFCs can be used for two different purposes. First, they could be used to give additional Pell Grant aid to the neediest students; there have been several proposals in the past to allow EFCs to go down to -$750 in order to boost Pell Grants by up to $750. Second, the sheer number of students classified in the zero EFC category makes identifying the very neediest students difficult when there are insufficient funds to help all students from lower-income families. Reporting negative EFCs would at least allow colleges to help target their often-scarce resources in the best possible manner.

In my newest article (just published in the Journal of Student Financial Aid, which is open-access!), I used five years of student-level FAFSA data from nine colleges to show how calculating negative EFCs can help identify students with the greatest levels of financial need. The graphics below give a rough idea of what the distributions of negative EFCs could look like under various scenarios and current FAFSA filing situations. (I show dependent students here, but the same story is generally true for independent students.)

I also looked at how much it might cost the federal Pell Grant program to fund EFCs of -$750 by increasing maximum Pell Grants by an additional $750 for the neediest students. I estimated that funding negative EFCs would have increased Pell Grant expenditures by between $5 billion and $7 billion per year, depending on the specification. This is far from a trivial change for a program that spent about $31.5 billion in 2013-14, but it would roughly return Pell spending to its high point following the Great Recession. To save money, additional Pell funds could be given just to students with an automatic zero EFC—students with low family incomes who are already receiving some kind of means-tested benefit (such as free lunches in high school). That sort of limited expansion could be funded out of the current Pell surplus (assuming it doesn’t get used for other purposes, as is currently proposed).

Regardless of whether students get more money from the federal government under a negative EFC, it is a no-brainer for Congress and the Department of Education to work together to at least release the negative EFC number alongside the current number. That way, states, colleges, and private foundations can better target their funds to students with the absolute greatest need. Until the FAFSA is simplified, it makes sense to better use all of the information that is collected on students so everyone can make better decisions on allocating scarce resources.

How Popular Was the IRS Data Retrieval Tool?

The financial aid application season for the 2017-18 academic year started out on a high note for current and prospective students. Thanks to the adoption of “prior prior year” or “early FAFSA,” students could file the FAFSA beginning October 1 instead of the following January 1 for the 2017-18 academic year. Students took advantage of this change in large numbers, with about 5.4 million students completing the FAFSA before the previous opening date of January 1.

But FAFSA filing hit a significant roadblock in early March when the federal government quietly pulled access to the IRS Data Retrieval Tool (DRT), which allowed students to quickly and seamlessly transfer their tax records from the IRS to the FAFSA. The tool was down for nearly a week before the IRS issued a statement explaining that the site had been taken offline due to security concerns—and now it looks like the Data Retrieval Tool will be down until next fall at the earliest. Students can still complete the FAFSA by inputting information from their 2015 tax returns, but this is an extra hurdle for many students to jump.

It is possible that the DRT outage is already affecting FAFSA filing rates. Nick Hillman of the University of Wisconsin-Madison (one of the best higher ed finance researchers out there) and his sharp grad students Valerie Crespin-Trujillo and Ellie Bruckner) have been tracking FAFSA filing trends among high school students since the start of this application cycle. Their latest look at filing trends (which they update every Friday) shows the following, which suggests a possible dip due to the DRT outage.

One question that hasn’t been addressed yet is how many students were actually using the DRT when it was pulled. Unlike the great data that Federal Student Aid makes available on FAFSA filing trends, far less data are available on DRT usage. But I was able to find two data points that provide some insights about how many FAFSA filers used the DRT. The first data point came from Federal Student Aid’s 2016 annual financial report, which listed the DRT as a priority for the department. As the highlighted text below shows, about half of all applicants who filed taxes used the DRT in the 2014-15 filing season.

A tidbit of more recent data comes from a presentation that Federal Student Aid made to a conference of financial aid professionals last fall. As shown below, 56% of the 2.2 million FAFSA filers in October 2016 used the DRT. Early FAFSA filers may have different characteristics than filers across the whole application cycle, but this again shows the popularity of the DRT.

Another important group of students use the Data Retrieval Tool—students who are enrolling in income-driven repayment plans. These students have to certify their income on an annual basis (and a majority of borrowers already struggle to do this on time), which becomes more time-consuming without the DRT. It’s still possible for students to do by submitting documentation of income, but the loss of the DRT makes that a lengthier process. I was unable to find any information about DRT usage among people in income-driven repayment programs, but my gut instinct is that it’s a fairly high percentage of borrowers.

The bottom line here—the lengthy outage of the IRS Data Retrieval Tool doesn’t mean that students can’t apply for federal financial aid or income-driven student loan repayment programs. But it does create an additional roadblock for millions of students, their families, and financial aid offices to navigate. Only time will tell whether the DRT outage is associated with lower FAFSA or income-driven repayment filing rates, but a small negative effect seems plausible.

Thanks to Carlo Salerno of Strada Education for inspiring me to dig into the numbers. Twitter conversations can be useful, after all!