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Designing Efficient Student Loan Programs in the U.S


  • Juan Sanchez

    (Federal Reserve Bank of St. Louis)

  • Alexander Monge-Naranjo

    (Federal Reserve Bank of St. Louis)

  • Lance Lochner

    (University of Western Ontario)


This study develops a quantitative lifecycle framework to study dynamic student loan contracts that account for problems associated with moral hazard, limited commitment, and costly income verification. Within this environment, we study how optimal student loan limits should be set as functions of observable borrower characteristics and how loan repayments should be structured as functions of current income, past payments, and student debt. We calibrate our quantitative model using previous estimates of earnings and employment dynamics in the U.S. and to match various moments derived from longitudinal data on American borrowing and repayment behavior. Our calibrated model is used to characterize constrained efficient credit contracts and to compare the nature of those contracts with current GSL programs in the U.S. as well as frequently discussed income-based alternatives. We not only compare the contracts themselves, but we also study their implications in terms of borrowing, schooling, and repayment behavior. Our analysis considers both the efficiency of various lending regimes as well as their distributional consequences across ability and wealth groups. Importantly, we discuss general lessons that can be used in the practical development of GSL programs.

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  • Juan Sanchez & Alexander Monge-Naranjo & Lance Lochner, 2016. "Designing Efficient Student Loan Programs in the U.S," 2016 Meeting Papers 343, Society for Economic Dynamics.
  • Handle: RePEc:red:sed016:343

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    1. Lance Lochner & Youngki Shin, 2014. "Understanding Earnings Dynamics: Identifying and Estimating the Changing Roles of Unobserved Ability, Permanent and Transitory Shocks," NBER Working Papers 20068, National Bureau of Economic Research, Inc.
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