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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.

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  • 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. Stephen P. Jenkins & Fernando Rios-Avila, 2023. "Finite mixture models for linked survey and administrative data: Estimation and postestimation," Stata Journal, StataCorp LP, vol. 23(1), pages 53-85, March.
    2. Hyslop, Dean R. & Townsend, Wilbur, 2017. "Employment misclassification in survey and administrative reports," Economics Letters, Elsevier, vol. 155(C), pages 19-23.
    3. 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).
    4. Okamura, Kazuaki & Islam, Nizamul, 2021. "Multinomial employment dynamics with state dependence and heterogeneity: Evidence from Japan," Economic Modelling, Elsevier, vol. 101(C).
    5. Dean Hyslop & Wilbur Townsend, 2017. "The longer term impacts of job displacement on labour market outcomes," Working Papers 17_12, Motu Economic and Public Policy Research.
    6. 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.
    7. 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.
    8. 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, Institute of Labor Economics (IZA).
    9. 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).
    10. Park, Seonyoung & Shin, Donggyun, 2019. "Inflation and wage rigidity/flexibility in the short run," Working Paper Series 20917, Victoria University of Wellington, School of Economics and Finance.

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    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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