Signaling in Online Credit Markets

56 Pages Posted: 13 Dec 2012 Last revised: 24 Aug 2021

See all articles by Kei Kawai

Kei Kawai

University of California at Berkeley

Ken Onishi

Board of Governors of the Federal Reserve System

Kosuke Uetake

Yale School of Management

Multiple version iconThere are 2 versions of this paper

Date Written: August 24, 2021

Abstract

We study how signaling affects equilibrium outcomes and welfare in an online credit market using detailed data on loan characteristics and borrower repayment. We build and estimate an equilibrium model in which a borrower may signal her default risk through the reserve interest rate. Comparing a market with and without signaling relative to the benchmark with no asymmetric information, we find that adverse selection destroys as much as 34\% of total surplus, up to 78\% of which can be restored with signaling. We also estimate backward-bending supply curves for some markets, consistent with the prediction of Stiglitz and Weiss (1981).

Keywords: Signaling, Adverse Selection, Credit Markets, Structural Model

JEL Classification: D82, G14

Suggested Citation

Kawai, Kei and Onishi, Ken and Uetake, Kosuke, Signaling in Online Credit Markets (August 24, 2021). Available at SSRN: https://ssrn.com/abstract=2188693 or http://dx.doi.org/10.2139/ssrn.2188693

Kei Kawai

University of California at Berkeley ( email )

Berkeley, CA 94720
United States

Ken Onishi

Board of Governors of the Federal Reserve System ( email )

20th St and C Ave, NW
Washington, DC 20551
United States

Kosuke Uetake (Contact Author)

Yale School of Management ( email )

135 Prospect Street
P.O. Box 208200
New Haven, CT 06520-8200
United States

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