Payday Loans, Uncertainty, and Discounting: Explaining Patterns of Borrowing, Repayment, and Default

Joint with: Paige Marta Skiba

Ten million American households borrowed on payday loans in 2002. Typically, to receive two weeks of liquidity from these loans households paid annualized (compounded) interest rates over 7000%. Using an administrative dataset from a payday lender, we seek to explain demand-side behavior in the payday loan market. We estimate a structural dynamic programming model that includes standard features like liquidity constraints and stochastic income, and we also incorporate institutionally realistic payday loans, default opportunities, and generalizations of the discount function. Method of Simulated Moments estimates of the key parameters are identified by two novel pieces of evidence. First, over half of payday borrowers default on a payday loan within one year of their first loans. Second, defaulting borrowers have on average already repaid or serviced five payday loans, making interest payments of 90% of their original loan's principal. Such costly delay of default, we find, is most consistent with partially naive quasi-hyperbolic discounting, and we statistically reject nested benchmark alternatives.

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