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Estimating Measurement Error in Annual Job Earnings: A Comparison of Survey and Administrative Data


Author Info

  • John M. Abowd

    (Cornell University, Census Bureau NBER, CREST/INSEE, and IZA)

  • Martha H. Stinson

    (U.S. Census Bureau)


We propose a new methodology that does not assume a prior specification of the statistical properties of the measurement errors and treats all sources as noisy measures of some underlying true value. The unobservable true value can be represented as a weighted average of all available measures, using weights that must be specified a priori unless there has been a truth audit. The Census Bureau's Survey of Income and Program Participation (SIPP) survey jobs are linked to Social Security Administration earnings data, creating two potential annual earnings observations. The reliability statistics for both sources are quite similar except for cases where the SIPP used imputations for some missing monthly earnings reports. © 2013 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

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Bibliographic Info

Article provided by MIT Press in its journal Review of Economics and Statistics.

Volume (Year): 95 (2013)
Issue (Month): 5 (December)
Pages: 1451-1467

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Handle: RePEc:tpr:restat:v:95:y:2013:i:5:p:1451-1467

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Related research

Keywords: measurement error; earnings; matched survey-administrative data; linear mixed-effects model;

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Cited by:
  1. Jantti, Markus & Jenkins, Stephen P., 2013. "Income mobility," ISER Working Paper Series 2013-23, Institute for Social and Economic Research.


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