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The credit card debt puzzle: the role of preferences, credit risk, and financial literacy

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Abstract

We use the 1979 National Longitudinal Survey of Youth to revisit what is termed the credit card debt puzzle: why consumers simultaneously co-hold high-interest credit card debt and low-interest assets that could be used to pay down this debt. This dataset contains unique information on intelligence, financial literacy, and preferences, while also providing a complete picture of households? balance sheets. Relative to individuals with no credit card debt but positive liquid assets, individuals in the puzzle group have higher discount rates, slightly lower financial literacy scores, and very different perceptions on future credit risk: many individuals are using credit cards for precautionary motives.

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  • Olga Gorbachev & María Jose Luengo-Prado, 2016. "The credit card debt puzzle: the role of preferences, credit risk, and financial literacy," Working Papers 16-6, Federal Reserve Bank of Boston.
    • Handle: RePEc:fip:fedbwp:16-6
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    1. Irina A. Telyukova & Randall Wright, 2008. "A Model of Money and Credit, with Application to the Credit Card Debt Puzzle," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 75(2), pages 629-647.
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    6. Shawn Cole & Anna Paulson & Gauri Kartini Shastry, 2014. "Smart Money? The Effect of Education on Financial Outcomes," The Review of Financial Studies, Society for Financial Studies, vol. 27(7), pages 2022-2051.
    7. Nathaniel Hendren, 2015. "Knowledge of Future Job Loss and Implications for Unemployment Insurance," NBER Working Papers 21819, National Bureau of Economic Research, Inc.
    8. Carol C. Bertaut & Michael Haliassos & Michael Reiter, 2009. "Credit Card Debt Puzzles and Debt Revolvers for Self Control," Review of Finance, European Finance Association, vol. 13(4), pages 657-692.
    9. John Gathergood & Joerg Weber, 2012. "Self-Control, Financial Literacy and Co-Holding Puzzle," Discussion Papers 2012-02, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    10. Olga Gorbachev, 2016. "Has the Increased Attachment of Women to the Labor Market Changed a Family's Ability to Smooth Income Shocks?," American Economic Review, American Economic Association, vol. 106(5), pages 247-251, May.
    11. Feigenbaum James A. & Li Geng, 2012. "Life Cycle Dynamics of Income Uncertainty and Consumption," The B.E. Journal of Macroeconomics, De Gruyter, vol. 12(1), pages 1-49, May.
    12. Fulford, Scott L., 2015. "How important is variability in consumer credit limits?," Journal of Monetary Economics, Elsevier, vol. 72(C), pages 42-63.
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    Cited by:

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    2. Ben-David, Itzhak & Fermand, Elyas & Kuhnen, Camelia M. & Li, Geng, 2018. "Expectations Uncertainty and Household Economic Behavior," Working Paper Series 2018-25, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    3. Kyle Dempsey & Felicia Ionescu, 2019. "Lending Standards and Consumption Insurance over the Business Cycle," 2019 Meeting Papers 1428, Society for Economic Dynamics.

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    More about this item

    Keywords

    household finances; risk aversion; time preferences; precautionary motives; bankruptcy; foreclosures;
    All these keywords.

    JEL classification:

    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles

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