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A Quantitative Theory of the Credit Score

Author

Listed:
  • Satyajit c

    (Federal Reserve Bank of Philadelphia)

  • Dean Corbae

    (University of Wisconsin-Madison and NBER)

  • Kyle Dempsey

    (Ohio State University)

  • Jose-Victor Rios-Rull

    (University of Pennsylvania, UCL, CAERP, CEPR and NBER)

Abstract

What is the role of credit scores in credit markets? We argue that it is a stand in for a market assessment of a person’s unobservable type (which here we take to be patience). We pose a model of persistent hidden types where observable actions shape the public assessment of a person’s type via Bayesian updating. We show how dynamic reputation can incentivize repayment without monetary costs of default beyond the administrative cost of filing for bankruptcy. Importantly we show how an economy with credit scores implements the same equilibrium allocation. We estimate the model using both credit market data and the evolution of individual’s credit scores. We find a 3% di?erence in patience in almost equally sized groups in the population with significant turnover and a shift towards becoming more patient with age. If tracking of individual credit actions is outlawed, the benefits of bankruptcy forgiveness are outweighed by the higher interest rates associated with lower incentives to repay.

Suggested Citation

  • Satyajit c & Dean Corbae & Kyle Dempsey & Jose-Victor Rios-Rull, 2020. "A Quantitative Theory of the Credit Score," PIER Working Paper Archive 20-030, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  • Handle: RePEc:pen:papers:20-030
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    Cited by:

    1. Manuel Amador & Christopher Phelan, 2021. "Reputation and Sovereign Default," Econometrica, Econometric Society, vol. 89(4), pages 1979-2010, July.
    2. Mark Aguiar & Satyajit Chatterjee & Harold Cole & Zachary Stangebye, 2022. "Self-Fulfilling Debt Crises, Revisited," Journal of Political Economy, University of Chicago Press, vol. 130(5), pages 1147-1183.
    3. Tertilt, Michèle & Exler, Florian & Livshits, Igor & MacGee, Jim, 2020. "Consumer Credit with Over-Optimistic Borrowers," CEPR Discussion Papers 15570, C.E.P.R. Discussion Papers.
    4. Mallucci, Enrico, 2022. "Natural disasters, climate change, and sovereign risk," Journal of International Economics, Elsevier, vol. 139(C).
    5. Kyle Dempsey & Felicia Ionescu, 2021. "Lending Standards and Borrowing Premia in Unsecured Credit Markets," Finance and Economics Discussion Series 2021-039, Board of Governors of the Federal Reserve System (U.S.).
    6. Laura Blattner & Scott Nelson & Jann Spiess, 2021. "Unpacking the Black Box: Regulating Algorithmic Decisions," Papers 2110.03443, arXiv.org, revised Jul 2023.
    7. Laura Blattner & Scott Nelson, 2021. "How Costly is Noise? Data and Disparities in Consumer Credit," Papers 2105.07554, arXiv.org.
    8. Bulent Guler & Yasin Kursat Onder & Temel Taskin, 2022. "Asymmetric Information and Sovereign Debt Disclosure," CAEPR Working Papers 2022-004 Classification-E, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.

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    More about this item

    Keywords

    Credit Scores; Unsecured Consumer Credit; Bankruptcy; Persistent Private Information;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • G51 - Financial Economics - - Household Finance - - - Household Savings, Borrowing, Debt, and Wealth

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