Predictors of Student Loan Repayments: A Comparison Between Public, Private For-Profit and Private Nonprofit Schools
by Mannat Bakshi and Arjun Ahluwalia
Using a sample of over 3,500 colleges from the College Scorecard Dataset , we investigate the association of average federal student loan repayment rates with institutional, regional, and student demographic characteristics of colleges. We consider educational cohorts from 2010 to 2016 at public, private for-profit, and private non-profit institutions. Our data do not allow us to see individual student characteristics, hence we control for traits of the average student in each college and focus on institutional traits that impact repayment rates. Our controls for demographics are consistent with prior research on student loan repayment rates (Lochner and Monge-Naranjo, 2014; Kelchen and Li, 2017).
We ran a Random Effects panel regression to determine how institutional, regional, and student demographic characteristics impact repayment rates. We see an important influence of the institution attended. Institution selectivity (lower admission and withdrawal rates) is associated with higher average repayment. Furthermore, the highest degree awarded is a more significant variable when it comes to describing the variation in repayment rates for public schools; private for-profit schools exhibit lower repayment rates and private nonprofit schools exhibit higher repayment rates regardless of the highest degree awarded. This could be due to a combination of signaling and screening effects. Local income and unemployment impact repayment for the average student in public and for-profit schools, but not in private non-profit schools.
A noticeable institutional finding is that, even after controlling for average school demographics, for-profit schools exhibit lower repayment rates across all types of degree-granting programs. Attending a for-profit school may be a negative signal of ability or value to potential employers. Median family income positively affects repayment twice as much for for-profit schools compared to other school types. These finding on for-profit institutions help explain Obama’s “crack down on for-profit career training colleges” (Simon & Emma, 2014).
Advisor: Professor Genna Miller | JEL Codes: I2, I22, I26
Analyzing Student and Family-Level Effects on a Family’s Contributions to Fund a College Education
By Justin T. Rosenblum and John H. Zipf
We investigate the efficiency of the current financial aid system for prospective college students. The Free Application for Federal Student Aid (FAFSA) form reviews a family’s financial information and universities review a student’s academic prowess, but neither fully examines students and their family’s qualitative factors such as parents’ highest education level or intended major. Using the National Center for Education Statistics’ National Postsecondary Student Aid Study, we investigate academic, financial, and familial characteristics to determine if they impact a student’s level of private loans relative to their total cost of attendance. We find that students with parents who did not receive a college degree are adversely affected by the current financial aid system. In particular, these students take out a greater amount of private loans relative to their total cost of attendance all else equal. Our finding has wider policy implications; changing the current financial aid system to assist disadvantaged students could help reduce intergenerational education inequalities. In addition, colleges could reach a broader range of students by helping
the students that currently struggle the most to pay tuition.
Advisors: Michelle Connolly, Hugh Macartney and Kent Kimbrough | JEL Codes: I2, I22, I23
Benefit Spillovers and Higher Education Financing: An Empirical Analysis of Brain Drain and State-Level Investment in Public Universities
By Chinmany G. Pandit
This paper analyzes the impact of out-migration of college graduates on state higher education investment. A three-stage least squares regression model with state and year fixed effects is developed and estimated, addressing the relationship between state legislative appropriations, tuition, and educated out-migration across 49 U.S. states from 2006-2015. The results support the notion that states respond negatively to benefit spillovers in higher education: for every one percent increase in the rate of educated out-migration, state appropriations decrease by 1.92 percent (roughly $140 per student). These findings suggest that an education subsidy
provided to states may be necessary to prevent underinvestment in higher education.
Advisor: Thomas Nechyba | JEL Codes: H7, H75, I22, I28, R23