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The Opioid Epidemic and Consumer Credit Supply: Evidence from Credit Cards

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Abstract

Using a unique data set of unsolicited credit card offer mailings by banks to consumers, we investigate how opioid abuse affects consumer credit supply in the U.S. To identify causal effects, we employ instrumental variables, propensity score matching, and contiguous counties techniques and control for varying local economic conditions and demographics. We find that banks contract credit supply to consumers in counties highly exposed to opioid abuse by offering higher interest rates, lower credit card limits, and fewer rewards and reducing credit offers overall. Further analyses using the supervisory Federal Reserve Y-14M credit card data set confirm these effects. What is more, the credit contraction disproportionately impacts riskier consumers, minorities (particularly Black people), low-income consumers, and younger individuals. Our examination of various state-level anti-opioid abuse legislation shows that opioid supply-oriented laws are somewhat helpful in curbing opioid overdoses or mitigating the credit supply contraction, but demand-oriented laws are not. Finally, we uncover the real effects associated with the opioid abuse-induced credit contraction: Local consumer spending significantly declines in the highly affected areas, with important macro-policy implications.

Suggested Citation

  • Sumit Agarwal & Wenli Li & Raluca Roman & Nonna Sorokina, 2023. "The Opioid Epidemic and Consumer Credit Supply: Evidence from Credit Cards," Working Papers 23-28, Federal Reserve Bank of Philadelphia.
  • Handle: RePEc:fip:fedpwp:97380
    DOI: 10.21799/frbp.wp.2023.28
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    1. David M. Cutler & Edward L. Glaeser, 2021. "When Innovation Goes Wrong: Technological Regress and the Opioid Epidemic," Journal of Economic Perspectives, American Economic Association, vol. 35(4), pages 171-196, Fall.
    2. Abby Alpert & William N Evans & Ethan M J Lieber & David Powell, 2022. "Origins of the Opioid Crisis and its Enduring Impacts [Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program]," The Quarterly Journal of Economics, Oxford University Press, vol. 137(2), pages 1139-1179.
    3. Park, Sujeong & Powell, David, 2021. "Is the rise in illicit opioids affecting labor supply and disability claiming rates?," Journal of Health Economics, Elsevier, vol. 76(C).
    4. Stiglitz, Joseph E & Weiss, Andrew, 1981. "Credit Rationing in Markets with Imperfect Information," American Economic Review, American Economic Association, vol. 71(3), pages 393-410, June.
    5. McGranahan, David A. & Parker, Timothy S., 2021. "The Opioid Epidemic: A Geography in Two Phases," USDA Miscellaneous 310390, United States Department of Agriculture.
    6. McGranahan, David & Parker, Timothy, 2021. "The Opioid Epidemic: A Geography in Two Phases," Economic Research Report 327197, United States Department of Agriculture, Economic Research Service.
    7. David M. Cutler & Edward L. Glaeser, 2021. "When Innovation Goes Wrong: Technological Regress and the Opioid Epidemic," NBER Working Papers 28873, National Bureau of Economic Research, Inc.
    8. Ruhm, Christopher J., 2019. "Drivers of the fatal drug epidemic," Journal of Health Economics, Elsevier, vol. 64(C), pages 25-42.
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    More about this item

    Keywords

    Opioid Epidemic; Household Finance; Credit Supply; Spending; Risk;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • D10 - Microeconomics - - Household Behavior - - - General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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