College on Credit: Student and Institutional Factors Associated With Student Loan Default

• In Event: Understanding Student Loan Default and the Impact of Compulsory Remediation

Abstract

Using a nationally-representative sample from Beginning Postsecondary Students survey (2003-2009), this study employs a multilevel logistic regression model to estimate the student and institutional factors associated with student loan default. Interestingly, a relatively small amount of research has been conducted on the topic and previous studies have yet to utilize multilevel techniques. Considering the ongoing policy debates over student loan default, this is a timely analysis that takes advantage of recently-released national dataset. Preliminary results suggest students’ demographic and socio-economic backgrounds are strong predictors of default. After accounting for these factors, the for-profit sector still has a systematically higher probability of default, suggesting that default is not a “pre-existing condition” as some observers have argued.

Authors

• Natalie Jane Brown, University of Utah

• Nicholas Hillman, University of Wisconsin - Madison