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Modelling Errors in Survey and Administrative Data on Employment Earnings: Sensitivity to the Fraction Assumed to Have Error-Free Earnings

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  • Jenkins, Stephen P.

    (London School of Economics)

  • Rios-Avila, Fernando

    (Levy Economics Institute)

Abstract

Kapteyn and Ypma (Journal of Labour Economics 2007) is an influential study of errors in survey and administrative data on employment earnings. To fit their mixture models, Kapteyn and Ypma assume a specific fraction of their sample have error-free earnings. Using a new UK dataset, we assess the sensitivity of model estimates and post-estimation statistics to variations in this fraction and find some lack of robustness.

Suggested Citation

  • 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," IZA Discussion Papers 13196, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp13196
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. repec:taf:jnlbes:v:30:y:2012:i:2:p:191-201 is not listed on IDEAS
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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. Stephen P. Jenkins & Fernando Rios‐Avila, 2021. "Measurement error in earnings data: Replication of Meijer, Rohwedder, and Wansbeek's mixture model approach to combining survey and register data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(4), pages 474-483, June.
    3. Apostolos Davillas & Victor Hugo Oliveira & Andrew M. Jones, 2024. "A model of errors in BMI based on self-reported and measured anthropometrics with evidence from Brazilian data," Empirical Economics, Springer, vol. 67(5), pages 2371-2410, November.
    4. Crossley, Thomas F. & Fisher, Paul & Hussein, Omar, 2023. "Assessing data from summary questions about earnings and income," Labour Economics, Elsevier, vol. 81(C).
    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, 2021. "Reconciling Reports: Modelling Employment Earnings and Measurement Errors Using Linked Survey and Administrative Data," IZA Discussion Papers 14405, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    Kapteyn-Ypma model; measurement error; misclassification error; labour earnings;
    All these keywords.

    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
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

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