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Lying About Borrowing

Author

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  • Dean Karlan
  • Jonathan Zinman

Abstract

We compare survey self-reports with administrative data and find that nearly 50% of recent borrowers do not report their high-interest consumer loans. Under-reporting appears to be correlated with several characteristics of interest, in particular gender: 62% of women interviewed by men underreport whereas 42% of women interviewed by women underreport. On the other hand, 40% of men underreport, irrespective of the gender of the interviewer. As such relying strictly on self-reported data may lead to biased inference, and we outline some methodological implications for identifying impacts of credit access on borrower behavior and outcomes. Matching female surveyors to female respondents appears to be a low-cost mitigating strategy, but clearly the best strategy is to make sure one has administrative data from a lender to measure actual borrowing history. (JEL: C81, D12, O12) (c) 2008 by the European Economic Association.

Suggested Citation

  • Dean Karlan & Jonathan Zinman, 2008. "Lying About Borrowing," Journal of the European Economic Association, MIT Press, vol. 6(2-3), pages 510-521, 04-05.
  • Handle: RePEc:tpr:jeurec:v:6:y:2008:i:2-3:p:510-521
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    Citations

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    Cited by:

    1. Greene, Claire & Schuh, Scott & Stavins, Joanna, 2017. "The 2015 Survey of Consumer Payment Choice: summary results," Research Data Report 17-3, Federal Reserve Bank of Boston.
    2. Blattman, Christopher & Jamison, Julian & Koroknay-Palicz, Tricia & Rodrigues, Katherine & Sheridan, Margaret, 2016. "Measuring the measurement error: A method to qualitatively validate survey data," Journal of Development Economics, Elsevier, vol. 120(C), pages 99-112.
    3. Shinsuke Ikeda & Myong-Il Kang, 2015. "Hyperbolic Discounting, Borrowing Aversion and Debt Holding," The Japanese Economic Review, Japanese Economic Association, vol. 66(4), pages 421-446, December.
    4. Stephan Meier & Charles Sprenger, 2010. "Present-Biased Preferences and Credit Card Borrowing," American Economic Journal: Applied Economics, American Economic Association, vol. 2(1), pages 193-210, January.
    5. Karlan, Dean S. & Zinman, Jonathan, 2012. "List randomization for sensitive behavior: An application for measuring use of loan proceeds," Journal of Development Economics, Elsevier, vol. 98(1), pages 71-75.
    6. Stephanie Moulton & Cäzilia Loibl & Anya Samak & J. Michael Collins, 2013. "Borrowing Capacity and Financial Decisions of Low-to-Moderate Income First-Time Homebuyers," Journal of Consumer Affairs, Wiley Blackwell, vol. 47(3), pages 375-403, November.
    7. Karlan, Dean & Osman, Adam & Zinman, Jonathan, 2016. "Follow the money not the cash: Comparing methods for identifying consumption and investment responses to a liquidity shock," Journal of Development Economics, Elsevier, vol. 121(C), pages 11-23.
    8. Dean Karlan & Jonathan Zinman, 2010. "Expanding Credit Access: Using Randomized Supply Decisions to Estimate the Impacts," Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 433-464, January.
    9. John Gibson & David McKenzie & Bilal Zia, 2014. "The Impact of Financial Literacy Training for Migrants," World Bank Economic Review, World Bank Group, vol. 28(1), pages 130-161.
    10. Brown, Meta & Haughwout, Andrew F. & Lee, Donghoon & Van der Klaauw, Wilbert, 2011. "Do we know what we owe? A comparison of borrower- and lender-reported consumer debt," Staff Reports 523, Federal Reserve Bank of New York, revised 01 Oct 2013.
    11. Gathergood, John, 2012. "Self-control, financial literacy and consumer over-indebtedness," Journal of Economic Psychology, Elsevier, vol. 33(3), pages 590-602.
    12. Leigh Ann Leung & Catherine Lau, 2017. "Effect of mortgage indebtedness on health of U.S. homeowners," Review of Economics of the Household, Springer, vol. 15(1), pages 239-264, March.
    13. Jonathan Zinman & Dean Karlan, 2009. "Expanding Microenterprise Credit Access: Using Randomized Supply Decisions to Estimate the Impacts in Manila," Working Papers 976, Economic Growth Center, Yale University.
    14. French, Declan & McKillop, Donal, 2016. "Financial literacy and over-indebtedness in low-income households," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 1-11.
    15. Andrea Bellucci & Alexander V. Borisov & Alberto Zazzaro, 2010. "Do Male and Female Loan Officers Differ in Small Business Lending?;A Review of the Literature," Mo.Fi.R. Working Papers 47, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
    16. Brown, Martin & Graf, Roman, 2013. "Financial Literacy, Household Investment and Household Debt: Evidence from Switzerland," Working Papers on Finance 1301, University of St. Gallen, School of Finance.
    17. René Bekkers & Pamala Wiepking, 2011. "Accuracy of self-reports on donations to charitable organizations," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(6), pages 1369-1383, October.
    18. Scott Carrell & Jonathan Zinman, 2014. "In Harm's Way? Payday Loan Access and Military Personnel Performance," Review of Financial Studies, Society for Financial Studies, vol. 27(9), pages 2805-2840.
    19. Clarke, George, 2012. "Do reticent managers lie during firm surveys?," MPRA Paper 37634, University Library of Munich, Germany.
    20. Asadul Islam & Chongwoo Choe, 2013. "Child Labor And Schooling Responses To Access To Microcredit In Rural Bangladesh," Economic Inquiry, Western Economic Association International, vol. 51(1), pages 46-61, January.
    21. Burks, Stephen & Carpenter, Jeffrey & Götte, Lorenz & Rustichini, Aldo, 2012. "Which measures of time preference best predict outcomes: Evidence from a large-scale field experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 84(1), pages 308-320.

    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development

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