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Signaling in Online Credit Markets

Author

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  • Kei Kawai
  • Ken Onishi
  • Kosuke Uetake

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 & Weiss (1981).

Suggested Citation

  • Kei Kawai & Ken Onishi & Kosuke Uetake, 2021. "Signaling in Online Credit Markets," NBER Working Papers 29268, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:29268
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    Cited by:

    1. Kai Lu & Zaiyan Wei & Tat Y. Chan, 2022. "Information Asymmetry Among Investors and Strategic Bidding in Peer-to-Peer Lending," Information Systems Research, INFORMS, vol. 33(3), pages 824-845, September.

    More about this item

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality

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