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A Theory of Credit Scoring and the Competitive Pricing of Default Risk

Author

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  • Victor Rios-Rull

    (University of Minnesota)

  • Dean Corbae:

    (University of Texas at Austin)

  • Satyajit Chatterjee

    (FRB Philadelphia)

Abstract

We propose a theory of unsecured consumer credit where: (i) borrowers have the legal option to default; (ii) defaulters are not exogenously excluded from future borrowing; (iii) there is free entry of lenders; and (iv) lenders cannot collude to punish defaulters. In our framework, limited credit or credit at higher interest rates following default arises from the lenderâs optimal response to limited information about the agentâs type and earnings realizations. The lender learns froman individualâs borrowing and repayment behavior about his type and encapsulates his reputation for not defaulting in a credit score. We take the theory to data choosing the parameters of the model to match key data moments such as the overall and subprime delinquency rates. We test the theory by showing that our underlying framework is broadly consistent with the way credit scores affect unsecured consumer credit market behavior. The framework can be used to shed light on household consumption smoothing with respect to transitory income shocks and to examine the welfare consequences of legal restrictions on the length of time adverse events can remain on one's credit record.

Suggested Citation

  • Victor Rios-Rull & Dean Corbae: & Satyajit Chatterjee, 2011. "A Theory of Credit Scoring and the Competitive Pricing of Default Risk," 2011 Meeting Papers 1115, Society for Economic Dynamics.
  • Handle: RePEc:red:sed011:1115
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    References listed on IDEAS

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    1. Chatterjee, Satyajit & Corbae, Dean & Ríos-Rull, José-Víctor, 2008. "A finite-life private-information theory of unsecured consumer debt," Journal of Economic Theory, Elsevier, vol. 142(1), pages 149-177, September.
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    5. Satyajit Chatterjee & Dean Corbae & Makoto Nakajima & José-Víctor Ríos-Rull, 2007. "A Quantitative Theory of Unsecured Consumer Credit with Risk of Default," Econometrica, Econometric Society, vol. 75(6), pages 1525-1589, November.
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    11. Geng Li & Song Han & Benjamin J. Keys, 2015. "Information, Contract Design, and Unsecured Credit Supply: Evidence from Credit Card Mailings," Finance and Economics Discussion Series 2015-103, Board of Governors of the Federal Reserve System (U.S.), revised 16 Nov 2015.
    12. David K. Musto, 2004. "What Happens When Information Leaves a Market? Evidence from Postbankruptcy Consumers," The Journal of Business, University of Chicago Press, vol. 77(4), pages 725-748, October.
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    Cited by:

    1. Ordoñez, Guillermo L., 2013. "Fragility of reputation and clustering of risk-taking," Theoretical Economics, Econometric Society, vol. 8(3), September.
    2. Jeon, Kiyoung & Kabukcuoglu, Zeynep, 2018. "Income inequality and sovereign default," Journal of Economic Dynamics and Control, Elsevier, vol. 95(C), pages 211-232.
    3. Dean Corbae & Andrew Glover, 2018. "Employer Credit Checks: Poverty Traps versus Matching Efficiency," NBER Working Papers 25005, National Bureau of Economic Research, Inc.
    4. Chatterjee, Satyajit & Gordon, Grey, 2012. "Dealing with consumer default: Bankruptcy vs garnishment," Journal of Monetary Economics, Elsevier, vol. 59(S), pages 1-16.
    5. Geng Li & Song Han & Benjamin J. Keys, 2015. "Information, Contract Design, and Unsecured Credit Supply: Evidence from Credit Card Mailings," Finance and Economics Discussion Series 2015-103, Board of Governors of the Federal Reserve System (U.S.), revised 16 Nov 2015.
    6. Patrick Bajari & Chenghuan Sean Chu & Minjung Park, 2008. "An Empirical Model of Subprime Mortgage Default From 2000 to 2007," NBER Working Papers 14625, National Bureau of Economic Research, Inc.
    7. Gajendran Raveendranathan, 2018. "Improved Matching, Directed Search, and Bargaining in the Credit Card Market," 2018 Meeting Papers 112, Society for Economic Dynamics.
    8. Sharma, Priyanka, 2017. "Is more information always better? A case in credit markets," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 269-283.
    9. Igor Livshits & Ariel Zetlin-Jones & Natalia Kovrijnykh, 2017. "Building Credit Histories with Competing Lenders," 2017 Meeting Papers 807, Society for Economic Dynamics.
    10. Rodney Ramcharan & Christopher Crowe, 2013. "The Impact of House Prices on Consumer Credit: Evidence from an Internet Bank," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(6), pages 1085-1115, September.
    11. Davis, Andrew & Kim, Jiseob, 2017. "Explaining changes in the US credit card market: Lenders are using more information," Economic Modelling, Elsevier, vol. 61(C), pages 76-92.
    12. Juan M. Sanchez, 2009. "The role of information in the rise in consumer bankruptcies," Working Paper 09-04, Federal Reserve Bank of Richmond, revised 2009.
    13. Kim, Jiseob, 2019. "How foreclosure delays impact mortgage defaults and mortgage modifications," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 18-37.
    14. Martin Dumav, 2013. "Health Insurance over the Life Cycle with Adverse Selection," 2013 Meeting Papers 1138, Society for Economic Dynamics.

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