Asymmetric Information, Reputation, and Welfare in Online Credit Markets

Abstract

This paper studies the welfare impact of reputation/feedback systems in markets where both adverse selection and moral hazard are present. Using a transaction-level dataset from an online credit market, I estimate a dynamic model of borrowers and lenders, in which borrowers are subject to reputational incentives. I quantify the welfare loss from adverse selection and moral hazard separately and find that 78 percent of overall inefficiency is induced by moral hazard. When the reputation system is implemented, I find that 95 percent of total welfare loss from asymmetric information is eliminated. I also consider a policy intervention that protects borrowers from accidental loss of reputation. My results suggest that introducing a payment protection insurance into the market further improves total welfare.

Keywords: asymmetric information, reputation/feedback systems, credit markets

JEL Classification: L14, D82, G21, C14