Default Rates Among Wisconsin Colleges and Universities

While previous posts in this series have focused on student borrowing, here we shift attention to one of the most pernicious outcomes student borrowers can experience: default, or failing to make agreed-upon payments towards their outstanding loans. Borrowers who default on their loans are likely to see credit scores plummet, and the federal government can garnish wages or withhold their federal tax refunds. Defaulted loans accumulate interest and often face additional collection fees and penalties, meaning borrowers owe more as a result of default.

To monitor and ultimately address these negative outcomes, the Higher Education Act requires colleges to report their Cohort Default Rate (CDR) to the U.S. Department of Education. These rates are based on federal loan borrowers who enter repayment in a given fiscal year and default within three years. A default occurs after 360 consecutive days of delinquency, so the current three-year CDR window captures only those borrowers who default shortly after leaving college. The CDR includes all leavers regardless of whether they earned a degree or not; and the rate only measures federal Direct Loans for undergraduate or graduate education and excludes PLUS, Perkins, and private loans.

The following chart uses College Scorecard data showing the official CDRs for individual colleges and universities going back to 2009. According to these data, 10% of borrowers nationwide default within three years of entering repayment; Wisconsin’s is slightly below the national average at 9%. Nationwide and in Wisconsin, these rates vary by individual colleges and sectors – public four-year and private non-profit colleges tend to have the lowest default rates while public two-year colleges and private for-profits tend to have the highest.

 

In the chart above, the horizontal axis shows the number of borrowers who defaulted within three years of entering repayment, which ranges between zero to over 1,000 in most years. The vertical axis shows the CDR for each institution, which ranges from zero to 30%. This 30% threshold is significant because federal accountability rules dictate that institutions must keep their CDR below that level in order to maintain access to federal student aid programs, and very few Wisconsin schools ever exceed this benchmark.

While the three-year CDR provides useful insights, it does not measure the full magnitude of the default problem. Borrowers can continue to default on their loans long after the three-year window. For this reason, the Center for American Progress published cohort default rates over a five-year period, finding that default rates rose from 10% to 16% for the 2012 repayment cohort. Better data are needed to measure and understand the full complexity of why borrowers default on their student loans. There is little public information on basic facts about default including: original and current loan balances; demographics of borrowers in default; length of time in default; default rates by loan repayment plans; and the amount of principal that has been repaid. These measures could help researchers and policymakers understand and ultimately improve loan repayment outcomes.

There are many reasons why borrowers end up defaulting on their student loans and more study is needed to understand the full extent of this problem. The field’s current thinking is that default is driven by borrowers who left colleges without earning a degree and who are unemployed. Additionally, there appear to be significant racial disparities in repayment outcomes, even among completers, that are likely rooted in labor market discrimination and wealth inequality. Still other explanations including administrative burdens (i.e., the paperwork to navigate repayment options) and information barriers are preventing borrowers from making more optimal repayment decisions. The reasons are varied and the CDR is a starting point for helping to pinpoint where the problems are concentrated. Considering the lasting negative consequences of default and its urgency as a policy problem, we will continue to examine the default picture for one of our next posts, using county level data to paint a picture of regional default situations.