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Measurement error and misclassification in linked earnings data: Estimation of the Kapteyn and Ypma model

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Listed:
  • Stephen Jenkins

    (London School of Economics and Political Science)

  • Fernando Rios-Avila

    (Levy Economics Institute)

Abstract

Kapteyn and Ypma (KY; 2007, https://doi.org/10.1086/513298) is an influential study for the analysis of linked administrative and survey earnings data that was the first to allow for measurement errors in both sources of data. Allowing for measurement errors in administrative data, they find evidence that the oft-cited feature of mean-reversion errors in survey data virtually disappeared. In this talk, I introduce a new set of commands that facilitates the estimation of the KY measurement error model, expanding on the theoretical model proposed by KY, and incorporating insights from Meijer, Rohwedder, and Wansbeek (2012, https://doi.org/10.1198/jbes.2011.08166). These commands are ky_fit, a command that can be used to fit the KY model, including the proposed extensions; ky_estat, an add-on for estat that allows the user to obtain summary statistics of important features of the KY model, including measurements of data reliability; ky_p, an add-on for predict and margins that allows obtaining model predictions and marginal effects of the model; and ky_sim, a command that can simulate data based on the fitted models.

Suggested Citation

  • Stephen Jenkins & Fernando Rios-Avila, 2021. "Measurement error and misclassification in linked earnings data: Estimation of the Kapteyn and Ypma model," 2021 Stata Conference 33, Stata Users Group.
    • Handle: RePEc:boc:scon21:33
    as

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    File URL: http://fmwww.bc.edu/repec/scon2021/US21_Rios-Avila.pdf
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    References listed on IDEAS

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    1. repec:taf:jnlbes:v:30:y:2012:i:2:p:191-201 is not listed on IDEAS
    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.
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