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On the County-Level Credit Outcome Beta

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  • Chintal Desai
  • Gregory Elliehausen
  • Edward Lawrence

Abstract

In their pioneering work, Musto and Souleles (Journal of Monetary Economics 53(1):59–84, 2006 ) apply portfolio theory to consumer lending. This paper extends their work by analyzing three county-level credit outcome betas. We use the probability of default calibrated from the credit score, the actual default rate, and the actual bankruptcy rate to compute ‘score’, ‘default’, and ‘bankruptcy’ betas for each U.S. county. The correlation between default and bankruptcy betas is quite low. Counties in states in which a borrower has a right to take action against aggressive collection practices tend to have higher default betas but lower bankruptcy betas. These findings suggest the possibility of an ‘informal bankruptcy’ option for consumers. The effects of county score, default, and bankruptcy betas on the county average revolving credit line per borrower are negative. For small lenders that do not have access to the detailed historical credit files on individual consumers, the county-level beta approach of this paper might be helpful for diversifying portfolios geographically and managing risk on existing accounts. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Chintal Desai & Gregory Elliehausen & Edward Lawrence, 2014. "On the County-Level Credit Outcome Beta," Journal of Financial Services Research, Springer;Western Finance Association, vol. 45(2), pages 201-218, April.
  • Handle: RePEc:kap:jfsres:v:45:y:2014:i:2:p:201-218
    DOI: 10.1007/s10693-012-0157-8
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    References listed on IDEAS

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    1. Musto, David K. & Souleles, Nicholas S., 2006. "A portfolio view of consumer credit," Journal of Monetary Economics, Elsevier, vol. 53(1), pages 59-84, January.
    2. Astrid A. Dick & Andreas Lehnert, 2010. "Personal Bankruptcy and Credit Market Competition," Journal of Finance, American Finance Association, vol. 65(2), pages 655-686, April.
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    4. White, Michelle J, 1998. "Why Don't More Households File for Bankruptcy?," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 14(2), pages 205-231, October.
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    9. Song Han & Wenli Li, 2007. "Fresh Start or Head Start? The Effects of Filing for Personal Bankruptcy on Work Effort," Journal of Financial Services Research, Springer;Western Finance Association, vol. 31(2), pages 123-152, June.
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    Cited by:

    1. Kim, Hyeongjun & Cho, Hoon & Ryu, Doojin, 2018. "An empirical study on credit card loan delinquency," Economic Systems, Elsevier, vol. 42(3), pages 437-449.
    2. Desai, Chintal Ajitbhai, 2017. "The cross-section of consumer lending risk," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 256-282.
    3. Sajjad Taghiyeh & David C Lengacher & Robert B Handfield, 2020. "Loss Rate Forecasting Framework Based on Macroeconomic Changes: Application to US Credit Card Industry," Papers 2006.07911, arXiv.org.
    4. Wenli Li & Ishani Tewari & Michelle J. White, 2019. "Using Bankruptcy to Reduce Foreclosures: Does Strip-Down of Mortgages Affect the Mortgage Market?," Journal of Financial Services Research, Springer;Western Finance Association, vol. 55(1), pages 59-87, February.

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    More about this item

    Keywords

    Beta; Default; Personal bankruptcy; Consumer credit; Portfolio theory; G21; E51;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers

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