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Determinants of Short-term Lender Location and Interest Rates

Author

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  • Taylor J. Canann

    (Department of Economics, Brigham Young University)

  • Richard W. Evans

    (Department of Economics, Brigham Young University)

Abstract

This study tests the degree to which payday and title lenders differentiate their store location and interest rates based on the socioeconomic characteristics of the areas in which they operate. We use store-level lender data, geographically matched IRS income data, and Census Bureau demographic data to answer these questions. In the case of lender location, we find that payday and title lenders tend to locate in areas with lower median age, a larger population of not married households, more restaurants, and more pawn shops. We also find a nonlinear relationship between lender location and individual incomes in the surrounding area. Regarding lender interest rates, we find that competition among lenders reduces average interest rates and that riskiness of borrowers, as measured by defaults, increases average interest rates. We also find that payday and title lenders have higher interest rates in areas with lower educational attainment, smaller proportions of Black residents, and fewer married households. This evidence seems to contradict the argument that payday and title lenders prey on minorities.

Suggested Citation

  • Taylor J. Canann & Richard W. Evans, 2013. "Determinants of Short-term Lender Location and Interest Rates," BYU Macroeconomics and Computational Laboratory Working Paper Series 2013-06, Brigham Young University, Department of Economics, BYU Macroeconomics and Computational Laboratory.
    • Handle: RePEc:byu:byumcl:201306
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    References listed on IDEAS

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    1. Cameron,A. Colin & Trivedi,Pravin K., 2013. "Regression Analysis of Count Data," Cambridge Books, Cambridge University Press, number 9781107667273.
    2. Brian T. Melzer, 2011. "The Real Costs of Credit Access: Evidence from the Payday Lending Market," The Quarterly Journal of Economics, Oxford University Press, vol. 126(1), pages 517-555.
    3. 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.
    4. Burkey, Mark L. & Simkins, Scott P., 2004. "Factors Affecting the Location of Payday Lending and Traditional Banking Services in North Carolina," The Review of Regional Studies, Southern Regional Science Association, vol. 34(2), pages 191-205.
    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.
    6. Victor Stango, 2012. "Some New Evidence On Competition In Payday Lending Markets," Contemporary Economic Policy, Western Economic Association International, vol. 30(2), pages 149-161, April.
    7. H. Damar, 2009. "Why Do Payday Lenders Enter Local Markets? Evidence from Oregon," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 34(2), pages 173-191, March.
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    10. Morse, Adair, 2011. "Payday lenders: Heroes or villains?," Journal of Financial Economics, Elsevier, vol. 102(1), pages 28-44, October.
    11. Robert DeYoung & Ronnie J. Phillips, 2009. "Payday loan pricing," Research Working Paper RWP 09-07, Federal Reserve Bank of Kansas City.
    12. Donald P. Morgan & Michael R. Strain & Ihab Seblani, 2012. "How Payday Credit Access Affects Overdrafts and Other Outcomes," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44, pages 519-531, March.
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    15. Joshua Shackman & Glen Tenney, 2006. "The Effects of Government Regulations on the Supply of Pawn Loans: Evidence from 51 Jurisdictions in the U.S," Journal of Financial Services Research, Springer;Western Finance Association, vol. 30(1), pages 69-91, August.
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    More about this item

    Keywords

    Consumer lending; interest rates; payday lending; lender location;

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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