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Payday Loans and Credit Cards: New Liquidity and Credit Scoring Puzzles?

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Listed:
  • Sumit Agarwal
  • Paige M. Skiba
  • Jeremy Tobacman

Abstract

Using a unique dataset matched at the individual level from two administrative sources, we examine household choices between liabilities and assess the informational content of prime and subprime credit scores in the consumer credit market. First, more specifically, we assess consumers' effectiveness at prioritizing use of their lowest-cost credit option. We find that most borrowers from one payday lender who also have a credit card from a major credit card issuer have substantial credit card liquidity on the days they take out their payday loans. This is costly because payday loans have annualized interest rates of at least several hundred percent, though perhaps partly explained by the fact that borrowers have experienced substantial declines in credit card liquidity in the year leading up to the payday loan. Second, we show that FICO scores and Teletrack scores have independent information and are specialized for the types of lending where they are used. Teletrack scores have eight times the predictive power for payday loan default as FICO scores. We also show that prime lenders should value information about their borrowers' subprime activity. Taking out a payday loan predicts nearly a doubling in the probability of serious credit card delinquency over the next year.

Suggested Citation

  • Sumit Agarwal & Paige M. Skiba & Jeremy Tobacman, 2009. "Payday Loans and Credit Cards: New Liquidity and Credit Scoring Puzzles?," NBER Working Papers 14659, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:14659
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    References listed on IDEAS

    as
    1. Sumit Agarwal & Paige Marta Skiba & Jeremy Tobacman, 2009. "Payday Loans and Credit Cards: New Liquidity and Credit Scoring Puzzles?," American Economic Review, American Economic Association, vol. 99(2), pages 412-417, May.
    2. William Adams & Liran Einav & Jonathan Levin, 2009. "Liquidity Constraints and Imperfect Information in Subprime Lending," American Economic Review, American Economic Association, vol. 99(1), pages 49-84, March.
    3. Agarwal, Sumit & Chomsisengphet, Souphala & Liu, Chunlin & Souleles, Nicholas S., 2005. "Do consumers choose the right credit contracts?," CFS Working Paper Series 2005/32, Center for Financial Studies (CFS).
    4. David B. Gross & Nicholas S. Souleles, 2002. "Do Liquidity Constraints and Interest Rates Matter for Consumer Behavior? Evidence from Credit Card Data," The Quarterly Journal of Economics, Oxford University Press, vol. 117(1), pages 149-185.
    5. Irina A. Telyukova & Randall Wright, 2008. "A Model of Money and Credit, with Application to the Credit Card Debt Puzzle," Review of Economic Studies, Oxford University Press, vol. 75(2), pages 629-647.
    6. Zinman, Jonathan, 2009. "Debit or credit?," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 358-366, February.
    7. Borzekowski, Ron & Kiser, Elizabeth K., 2008. "The choice at the checkout: Quantifying demand across payment instruments," International Journal of Industrial Organization, Elsevier, vol. 26(4), pages 889-902, July.
    8. Sumit Agarwal & John C Driscoll & Xavier Gabaix & David Laibson, 2008. "Learning in the Credit Card Market," Levine's Working Paper Archive 122247000000002028, David K. Levine.
    9. Sumit Agarwal & Souphala Chomsisengphet & Chunlin Liu & Nicholas S. Souleles, 2010. "Benefits of relationship banking: evidence from consumer credit markets," Working Paper Series WP-2010-05, Federal Reserve Bank of Chicago.
    10. Michael A. Stegman, 2007. "Payday Lending," Journal of Economic Perspectives, American Economic Association, vol. 21(1), pages 169-190, Winter.
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    More about this item

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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