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Earnings Dynamics and Measurement Error in Matched Survey and Administrative Data

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  • Dean R. Hyslop
  • Wilbur Townsend

Abstract

This article analyzes earnings dynamics and measurement error using a matched longitudinal sample of individuals’ survey and administrative earnings. In line with previous literature, the reported differences are characterized by both persistent and transitory factors. Estimating a model consistent with past results, survey errors are mean-reverting when administrative reports are assumed correct, but not when this assumption is relaxed. Although most reported earnings variation is true, we conclude that measurement errors dominate observed changes, and that transitory earnings contribute little to overall earnings inequality. The results imply the reliability of matched administrative data should be treated with caution.

Suggested Citation

  • Dean R. Hyslop & Wilbur Townsend, 2020. "Earnings Dynamics and Measurement Error in Matched Survey and Administrative Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 457-469, April.
    • Handle: RePEc:taf:jnlbes:v:38:y:2020:i:2:p:457-469
    DOI: 10.1080/07350015.2018.1514308
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    Cited by:

    1. Bergstrom, Katy & Dodds, William & Lacoste, Nicholas & Rios, Juan, 2026. "Estimating the welfare cost of labor supply frictions," Journal of Public Economics, Elsevier, vol. 253(C).
    2. Daniel L. Millimet & Christopher F. Parmeter, 2025. "The impact of measurement error on trends in earnings inequality in the USA," Empirical Economics, Springer, vol. 69(5), pages 2727-2753, November.
    3. Chris Ball & Judd Ormsby, 2017. "Comparing the Household Economic Survey to administrative records: An analysis of income and benefit receipt," Treasury Analytical Papers Series ap17/01, New Zealand Treasury.
    4. Ferreira, Francisco H. G. & Brunori, Paolo, 2024. "Inherited inequality, meritocracy, and the purpose of economic growth," LSE Research Online Documents on Economics 126263, London School of Economics and Political Science, LSE Library.
    5. Emmanuel Flachaire & Nora Lustig & Andrea Vigorito, 2023. "Underreporting of Top Incomes and Inequality: A Comparison of Correction Methods using Simulations and Linked Survey and Tax Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(4), pages 1033-1059, December.
    6. Jenkins, Stephen P. & Rios-Avila, Fernando, 2020. "Modelling errors in survey and administrative data on employment earnings: Sensitivity to the fraction assumed to have error-free earnings," Economics Letters, Elsevier, vol. 192(C).
    7. Stephen P. Jenkins & Fernando Rios-Avila, 2023. "Finite mixture models for linked survey and administrative data: Estimation and postestimation," Stata Journal, StataCorp LLC, vol. 23(1), pages 53-85, March.
    8. Hyslop, Dean R. & Townsend, Wilbur, 2017. "Employment misclassification in survey and administrative reports," Economics Letters, Elsevier, vol. 155(C), pages 19-23.
    9. Schmillen, Achim & Umkehrer, Matthias & Wachter, Till von, 2024. "Measurement error in longitudinal earnings data: evidence from Germany," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 58, pages 1-008.
    10. Nico Thurow, 2025. "Characterizing Measurement Error in the German Socio-Economic Panel Using Linked Survey and Administrative Data," Papers 2501.03015, arXiv.org, revised Aug 2025.
    11. Nora Lustig & Andrea Vigorito, 2025. "The "Missing Rich" in Household Surveys: Causes and Correction Approaches. Extended Version with Technical Appendixes," Documentos de Trabajo (working papers) 25-03, Instituto de Economía - IECON.
    12. 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).
    13. Seonyoung Park & Donggyun Shin, 2019. "Inflation And Wage Rigidity/Flexibility In The Short Run," Economic Inquiry, Western Economic Association International, vol. 57(3), pages 1675-1697, July.
    14. Okamura, Kazuaki & Islam, Nizamul, 2021. "Multinomial employment dynamics with state dependence and heterogeneity: Evidence from Japan," Economic Modelling, Elsevier, vol. 101(C).
    15. Dean Hyslop & Wilbur Townsend, 2017. "The longer term impacts of job displacement on labour market outcomes," Motu Working Papers 17_12, Motu Economic and Public Policy Research.
    16. Seonyoung Park & Donggyun Shin, 2019. "Inflation And Wage Rigidity/Flexibility In The Short Run," Economic Inquiry, Western Economic Association International, vol. 57(3), pages 1675-1697, July.
    17. Jenkins, Stephen P. & Rios-Avila, Fernando, 2021. "Reconciling Reports: Modelling Employment Earnings and Measurement Errors Using Linked Survey and Administrative Data," IZA Discussion Papers 14405, IZA Network @ LISER.
    18. Nora Lustig, 2019. "The “Missing Rich” in Household Surveys: Causes and Correction Approaches," Commitment to Equity (CEQ) Working Paper Series 75, Tulane University, Department of Economics.

    More about this item

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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