Who Is More Likely to Default on Student Loans?
Rajashri Chakrabarti, Nicole Gorton, Michelle Jiang, and Wilbert van der Klaauw
Liberty Street Economics November 20, 2017
This post seeks to understand how educational characteristics (school type and selectivity, graduation status, major) and family background relate to the incidence of student loan default. Student indebtedness has grown substantially, increasing by 170 percent between 2006 and 2016. In addition, the fraction of students who default on those loans has grown considerably. Of students who left college in 2010 and 2011, 28 percent defaulted on their student loans within five years, compared with 19 percent of those who left school in 2005 and 2006. Since defaulting on student loans can have serious consequences for credit scores and, by extension, the ability to purchase a home and take out other loans, it’s critical to understand how college and family characteristics correspond to default rates.
To better understand the determinants of student loan default, we ask the following questions in this blog post:
- Do default rates differ by college type?
- How do default rates of dropouts compare to those of graduates, and does this relationship vary by degree program?
- Does default vary with college major?
- Does college selectivity (defined below) matter for this relationship, and for student loan default more generally?
- Are students from less advantaged backgrounds more likely to default than students from more advantaged backgrounds?
To answer these questions, we utilize a unique data set that matches the New York Fed Consumer Credit Panel (CCP), based on Equifax data, to National Student Clearinghouse (NSC) education data, allowing us to track student debt and educational attainment over time for a representative sample of young adults. Throughout this discussion, it is important to note that our analysis is descriptive and, while suggestive, does not necessarily imply causation. For example, our results could partially reflect differences in the backgrounds and financial means of students who choose to attend various colleges.
As in our previous work with this data set, we focus on individuals born between 1980 and 1986 and track their college attendance and student loan default status by age. In this post, since we focus on determinants of student loan default, we limit our sample to students who took out student debt to finance their education. We focus on the characteristics associated with the highest degree-granting institution a student attended before age twenty-seven. We study default rates by age: out of all student loan holders in the 1980–86 birth cohorts, what fraction of people of a given age has defaulted on at least one of their student loans?
To examine differences in default rates by college type, we classify student debt holders by the type of college attended: did they attend a public, private not-for-profit, or private for-profit college, and was it a two-year institution or a four-year institution?
As seen in the chart below, students who attended private for-profit institutions have the highest default rates after their mid-twenties (shown in the blue lines). In contrast, at every age, four-year private not-for-profit students—the solid gold line—have the lowest default rates. For every college type (public, not-for-profit and for-profit), two-year students (dashed lines) have higher default rates than four-year students (solid lines). While this largely reflects the higher earnings prospects enjoyed by four-year students, it also partly reflects the earlier start of the loan repayment period for two-year students and inherent differences between two- and four-year students.
Interestingly, though the difference in default rates between two- and four-year private college students is not large (less than 5 percentage points at age thirty-three), this is not the case for public college students. Default rates for community college (two-year public college) students are nearly 25 percentage points higher than those for their counterparts in four-year public colleges. The chart below also shows that while for-profit students have the highest default rates, the default rates of community college students are not too different from those of for-profit students (36 percent versus 42 percent for two-year and 39 percent for four-year for-profit students, respectively, at age thirty‑three).
The next chart categorizes student debt holders by graduation status as well as by degree program. (Throughout this discussion, “bachelor’s” and “bachelor’s or higher” refer interchangeably to those with bachelor’s or higher-level degrees.) Regardless of degree program, dropouts have higher default rates at every age than graduates—likely because graduates enjoy the labor market benefits of having earned a degree, making it easier for them to find better jobs and repay their loans. However, among dropouts, the default comparison between associate and bachelor’s degree students changes over time. Bachelor-seeking students who did not graduate default at nearly the same rate as dropouts in associate programs until age twenty-nine, when the associate default rate climbs substantially, surpassing that of bachelor’s students.
Among graduates, those with associate degrees default at higher rates than those with bachelor’s degrees since their early twenties; the difference by age thirty-three is much larger among graduates (13 percentage points) than among dropouts (4 percentage points). This chart strongly suggests that graduation markedly reduces defaults, and the bachelor’s degree premium (as far as defaults are concerned) is considerably greater among graduates than dropouts. To put these numbers in perspective, 53 percent of debt holders graduate and 90 percent of those people earn a bachelor’s degree. Among loan holders who drop out, 28 percent were enrolled in an associate program.
In the next chart, we categorize student loan holders by the selectivity of the college they attended and by the major they pursued. Using Barron’s Profile of American Colleges (2001) ranking of college competitiveness, we classify four-year colleges into two categories: “selective” (colleges ranked “competitive” or above by Barron’s) and “nonselective.” In addition, we classify students into one of four fields, based on their major: “Arts and Humanities” (majors such as languages, sociology, theater), “Business and Law” (economics, legal studies, management), “STEM” (science, technology, engineering, mathematics), and “Vocational” (aviation, cosmetology, welding).
In analysis not reported here, we find that Arts majors have the highest overall default rates, while STEM majors default at the lowest rates. Both Business and Vocational majors default at higher rates than STEM majors, but at rates closer in magnitude to STEM majors than to Arts majors. Next, we separate students not only by major, but also by school selectivity; the chart below presents patterns at age thirty-three. We find that students attending nonselective colleges have higher default rates no matter what they study. Arts majors have the highest default rates regardless of college selectivity, but major matters much more among students at nonselective colleges: the gap in default rates between the best performing major and worst performing major is much smaller (3 percentage points by age thirty-three) among students at selective colleges than among students at nonselective colleges (8 percentage points by age thirty‑three).
Next, to analyze differences with respect to family background, we categorize individuals according to the average 2010 income in the zip code in which they resided at the youngest age we observe them in our data. We divide the panel between individuals from areas with an average income above $55,000 and those from areas with an average income below $55,000 (as measured in 2010). In analysis not reported here, we found that students from less advantaged family backgrounds have higher default rates. To understand this relationship, we investigate whether this correlation differs by college type.
In the chart below, we group debt holders by our family background measure, as well as by college type. We find that within each college type, students from less-advantaged backgrounds have higher default rates than their peers from a more-advantaged background. There is a nearly 30 percentage point difference in default rates between the group with the highest default rates (private for-profit students from less advantaged backgrounds) and the group with the lowest default rates (private not-for-profit students from more advantaged backgrounds). However, public college students from more advantaged backgrounds default at nearly the same rate as private not-for-profit students from less advantaged backgrounds (about 20 percent by age thirty-three). As before, at every age, for-profit students have the highest default rates, and students from less advantaged backgrounds attending for-profit colleges default at an even higher rate.
These stark differences in default rates with respect to school type, graduation status, college selectivity, major, and family background continue to hold even when we look at conditional correlations in a simple regression framework, introducing all these variables simultaneously. Attending a four-year private for-profit college correlates most strongly with increasing default, while dropping out is the second strongest predictor of default. These patterns are consistent with our finding that students from different educational and family backgrounds experience different returns on their academic investments. Our data show that students who drop out before earning a degree, enroll in an associate degree program as opposed to a bachelor’s degree program, major in the arts, attend a for-profit institution, community college or non-selective college, or come from a less advantaged family background are more likely to default by their late twenties compared to their peers. This represents preliminary evidence that later life outcomes—for example, the ability to buy a home and maintain a strong credit score—may vary widely among student loan holders based on their educational choices and backgrounds.
Disclaimer
The views expressed in this post are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.
Rajashri Chakrabarti a senior economist in the Federal Reserve Bank of New York’s Research and Statistics Group.
Nicole Gorton is a senior research analyst in the Bank’s Research and Statistics Group.
Michelle Jiang is a senior research analyst in the Bank’s Research and Statistics Group.
Wilbert van der Klaauw is a senior vice president in the Bank’s Research and Statistics Group.
