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How Well Do Survey Self-Reports Align with Administrative Data? The Case of U.S. Consumer Credit Records

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This paper assesses how closely consumers’ self-reported credit and debt attributes (such as credit account ownership and balances) align with administrative credit bureau records for mortgages, auto loans, and credit cards. Understanding the contents of one’s credit report can be critical to consumers’ ability to obtain affordable credit and to their ability to manage their finances generally. Surveys often ask respondents to report the types and amounts of credit they have, but it is often difficult or impossible to determine if the reported information is accurate. In this paper, we examine how well individuals’ self-reported credit activities in surveys correspond to the administrative data in their credit bureau files. We use anonymized survey data linked with individual-level administrative credit records to assess the levels of agreement between the two data sources for key credit-related attributes — such as credit seeking, credit account ownership, and outstanding balances — across several widely used credit products, such as credit cards, mortgages, and auto loans. We find that survey self-reports generally align well with administrative data, with a large majority of respondents reporting the composition and balances of their existing credit accounts as well as new credit applications in a manner consistent with their credit records. Agreement between the two data sources is generally higher for credit seeking and account ownership than for account balances, higher for installment loans than for revolving credit, and higher for credit products used more frequently than those used less often. When there is disagreement, there is a greater tendency to underreport rather than overreport in surveys, especially for account balances. Additionally, more often than not, demographic characteristics do not explain the level of agreement or disagreement between self-reports and credit records.

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  • Tom Akana & Amber Lee, 2025. "How Well Do Survey Self-Reports Align with Administrative Data? The Case of U.S. Consumer Credit Records," Consumer Finance Institute discussion papers 101848, Federal Reserve Bank of Philadelphia.
  • Handle: RePEc:fip:fedpdp:101848
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    1. Celhay, Pablo & Meyer, Bruce D. & Mittag, Nikolas, 2024. "What leads to measurement errors? Evidence from reports of program participation in three surveys," Journal of Econometrics, Elsevier, vol. 238(2).
    2. Meta Brown & Andrew F. Haughwout & Donghoon Lee & Wilbert Van der Klaauw, 2015. "Do we know what we owe? Consumer debt as reported by borrowers and lenders," Economic Policy Review, Federal Reserve Bank of New York, issue 21-1, pages 19-44.
    3. L. Douglas Smith & Michael Staten & Thomas Eyssell & Maureen Karig & Beth A. Freeborn & Andrea Golden, 2013. "Accuracy of Information Maintained by US Credit Bureaus: Frequency of Errors and Effects on Consumers' Credit Scores," Journal of Consumer Affairs, Wiley Blackwell, vol. 47(3), pages 588-601, November.
    4. 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.
    5. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843, Elsevier.
    6. Jonathan Zinman, 2009. "Where Is The Missing Credit Card Debt? Clues And Implications," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 55(2), pages 249-265, June.
    7. Madeira, Carlos & Margaretic, Paula, 2022. "The impact of financial literacy on the quality of self-reported financial information," Journal of Behavioral and Experimental Finance, Elsevier, vol. 34(C).
    8. Stefan Angel & Franziska Disslbacher & Stefan Humer & Matthias Schnetzer, 2019. "What did you really earn last year?: explaining measurement error in survey income data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(4), pages 1411-1437, October.
    9. Bruce D. Meyer & Nikolas Mittag & Robert M. Goerge, 2022. "Errors in Survey Reporting and Imputation and Their Effects on Estimates of Food Stamp Program Participation," Journal of Human Resources, University of Wisconsin Press, vol. 57(5), pages 1605-1644.
    10. Parminder Raina & Vicki Torrance-Rynard & Micheline Wong & Christel Woodward, 2002. "Agreement between Self-Reported and Routinely Collected Health Care Utilisation Data among Seniors," Social and Economic Dimensions of an Aging Population Research Papers 81, McMaster University.
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