A Trillion Dollar Question: What Predicts Student Loan Delinquencies?

Abstract

The recent significant increase in student loan delinquencies has generated interest in understanding the key factors predicting the non-performance of these loans. However, despite the large size of the student loan market, existing analyses have been limited by data. This paper studies predictors of student loan delinquencies using a nationally representative panel dataset that anonymously combines individual credit bureau records with Pell Grant and Federal student loan recipient information, records on college enrollment, graduation and major, and school characteristics. We show that borrower-level credit characteristics are important predictors of student loan delinquencies. In particular, credit scores of young borrowers are highly predictive of future student loan delinquencies, even when measured well before borrowers enter repayment. In marked contrast, our results point to only a limited power of student debt levels in predicting future student loan credit events. Our findings have potentially useful practical implications. For example, access to credit file information when borrowers exit school could help to more effectively target student loan borrowers who might benefit from enrolling in income-driven repayment or loan modification plans.