Measuring the welfare cost of asymmetric information in consumer credit markets

Anthony DeFusco, Huan Tang and Constantine Yannelis

Journal of Financial Economics, 2022, vol. 146, issue 3, 821-840

Abstract: Information asymmetries are known in theory to lead to inefficiently low credit provision, yet empirical estimates of the resulting welfare losses are scarce. This paper leverages a randomized experiment conducted by a large fintech lender to estimate welfare losses arising from asymmetric information in the market for online consumer credit. Building on methods from the insurance literature, we show how exogenous variation in interest rates can be used to estimate borrower demand and lender cost curves and recover implied welfare losses. While asymmetric information generates large equilibrium price distortions, we find only small overall welfare losses, particularly for high-credit-score borrowers.

Keywords: Asymmetric information; Welfare; Consumer credit; Fintech; Experiment (search for similar items in EconPapers)
JEL-codes: D14 D82 G10 G23 G5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Related works:
Working Paper: Measuring the welfare cost of asymmetric information in consumer credit markets (2022)
Working Paper: Measuring the Welfare Cost of Asymmetric Information in Consumer Credit Markets (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jfinec:v:146:y:2022:i:3:p:821-840

DOI: 10.1016/j.jfineco.2022.09.001

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