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Measurement Error and Misclassification: A Comparison of Survey and Administrative Data

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Author Info
Arie Kapteyn
Jelmer Y. Ypma

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Abstract

We provide both a theoretical and empirical analysis of the relation between administrative and survey data. By distinguishing between different sources of deviations between survey and administrative data we are able to reproduce several stylized facts. We illustrate the implications of different error sources for estimation in (simple) econometric models and find potentially very substantial biases. This article shows the sensitivity of some findings in the literature for the assumption that administrative data represent the truth. In particular, the common finding of substantial mean reversion in survey data largely goes away once we allow for a richer error structure.

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File URL: http://www.journals.uchicago.edu/cgi-bin/resolve?id=doi:10.1086/513298
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Publisher Info
Article provided by University of Chicago Press in its journal Journal of Labor Economics.

Volume (Year): 25 (2007)
Issue (Month): ()
Pages: 513-551
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Handle: RePEc:ucp:jlabec:v:25:y:2007:p:513-551

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  1. Jesse Bricker & Gary V. Engelhardt, 2007. "Measurement Error in Earnings Data in the Health and Retirement Study," Working Papers, Center for Retirement Research at Boston College wp2007-16, Center for Retirement Research, revised Oct 2007. [Downloadable!]
  2. Erik Meijer & Susann Rohwedder & Tom Wansbeek, 2008. "Prediction of Latent Variables in a Mixture of Structural Equation Models, with an Application to the Discrepancy Between Survey and Register Data," Working Papers 584, RAND Corporation Publications Department. [Downloadable!]
  3. repec:ese:iserwp: is not listed on IDEAS
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This page was last updated on 2009-11-21.


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