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

John Abowd () and Martha H. Stinson
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Martha H. Stinson: U.S. Census Bureau

The Review of Economics and Statistics, 2013, vol. 95, issue 5, 1451-1467

Abstract: 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.

Keywords: measurement error; earnings; matched survey-administrative data; linear mixed-effects model (search for similar items in EconPapers)
JEL-codes: C18 C33 J3 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (94)

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The Review of Economics and Statistics is currently edited by Pierre Azoulay, Olivier Coibion, Will Dobbie, Raymond Fisman, Benjamin R. Handel, Brian A. Jacob, Kareen Rozen, Xiaoxia Shi, Tavneet Suri and Yi Xu

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