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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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    1. Altonji, Joseph G & Segal, Lewis M, 1996. "Small-Sample Bias in GMM Estimation of Covariance Structures," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 353-366, July.
    2. John M. Abowd & Martha H. Stinson, 2013. "Estimating Measurement Error in Annual Job Earnings: A Comparison of Survey and Administrative Data," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1451-1467, December.
    3. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318, Elsevier.
    4. 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.
    5. Bound, John & Krueger, Alan B, 1991. "The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right?," Journal of Labor Economics, University of Chicago Press, vol. 9(1), pages 1-24, January.
    6. Dean R. Hyslop, 2001. "Rising U.S. Earnings Inequality and Family Labor Supply: The Covariance Structure of Intrafamily Earnings," American Economic Review, American Economic Association, vol. 91(4), pages 755-777, September.
    7. Lillard, Lee A & Weiss, Yoram, 1979. "Components of Variation in Panel Earnings Data: American Scientists, 1960-70," Econometrica, Econometric Society, vol. 47(2), pages 437-454, March.
    8. MaCurdy, Thomas E., 1982. "The use of time series processes to model the error structure of earnings in a longitudinal data analysis," Journal of Econometrics, Elsevier, vol. 18(1), pages 83-114, January.
    9. Meghir, Costas & Pistaferri, Luigi, 2011. "Earnings, Consumption and Life Cycle Choices," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 9, pages 773-854, Elsevier.
    10. Peter Gottschalk & Minh Huynh, 2010. "Are Earnings Inequality and Mobility Overstated? The Impact of Nonclassical Measurement Error," The Review of Economics and Statistics, MIT Press, vol. 92(2), pages 302-315, May.
    11. Pischke, Jorn-Steffen, 1995. "Measurement Error and Earnings Dynamics: Some Estimates from the PSID Validation Study," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 305-314, July.
    12. Hause, John C, 1980. "The Fine Structure of Earnings and the On-the-Job Training Hypothesis," Econometrica, Econometric Society, vol. 48(4), pages 1013-1029, May.
    13. Costas Meghir & Luigi Pistaferri, 2004. "Income Variance Dynamics and Heterogeneity," Econometrica, Econometric Society, vol. 72(1), pages 1-32, January.
    14. Arie Kapteyn & Jelmer Y. Ypma, 2007. "Measurement Error and Misclassification: A Comparison of Survey and Administrative Data," Journal of Labor Economics, University of Chicago Press, vol. 25(3), pages 513-551.
    15. Abowd, John M & Card, David, 1989. "On the Covariance Structure of Earnings and Hours Changes," Econometrica, Econometric Society, vol. 57(2), pages 411-445, March.
    16. Bound, John & Brown, Charles & Duncan, Greg J & Rodgers, Willard L, 1994. "Evidence on the Validity of Cross-Sectional and Longitudinal Labor Market Data," Journal of Labor Economics, University of Chicago Press, vol. 12(3), pages 345-368, July.
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    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. 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.
    4. 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).
    5. 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).
    6. Okamura, Kazuaki & Islam, Nizamul, 2021. "Multinomial employment dynamics with state dependence and heterogeneity: Evidence from Japan," Economic Modelling, Elsevier, vol. 101(C).
    7. 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.
    8. 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.
    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. 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.

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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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