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Measuring the welfare cost of asymmetric information in consumer credit markets

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  • DeFusco, Anthony A.
  • Tang, Huan
  • Yannelis, Constantine

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.

Suggested Citation

  • DeFusco, Anthony A. & Tang, Huan & Yannelis, Constantine, 2022. "Measuring the welfare cost of asymmetric information in consumer credit markets," LSE Research Online Documents on Economics 116693, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:116693
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    File URL: http://eprints.lse.ac.uk/116693/
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    Cited by:

    1. Braggion, Fabio & Manconi, Alberto & Zhu, Haikun, 2023. "Household credit and regulatory arbitrage: Evidence from online marketplace lending," Other publications TiSEM 9fbc0f2e-26f5-414f-8384-c, Tilburg University, School of Economics and Management.
    2. Tobias Berg & Andreas Fuster & Manju Puri, 2022. "FinTech Lending," Annual Review of Financial Economics, Annual Reviews, vol. 14(1), pages 187-207, November.
    3. Pan, Xiongfeng & Wang, Mengyang & Li, Mengna, 2023. "Low-carbon policy and industrial structure upgrading: Based on the perspective of strategic interaction among local governments," Energy Policy, Elsevier, vol. 183(C).
    4. Cheng, Haoyu & Chen, Zhijun & Qin, Meng & Su, Chi-Wei, 2024. "Mineral resources and Fintech: Catalyzing human capital and sustainable development," Resources Policy, Elsevier, vol. 92(C).
    5. Yannelis, Constantine & Zhang, Anthony Lee, 2023. "Competition and selection in credit markets," Journal of Financial Economics, Elsevier, vol. 150(2).
    6. Liran Einav & Amy Finkelstein, 2023. "Empirical analyses of selection and welfare in insurance markets: a self-indulgent survey," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 48(2), pages 167-191, September.

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    More about this item

    Keywords

    asymmetric information; consumer credit; experiment; Fintech; welfare;
    All these keywords.

    JEL classification:

    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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