Measurement Error in Earnings Data: Replication of Meijer, Rohwedder, and Wansbeek's Mixture Model Approach to Combining Survey and Register Data

Stephen Jenkins and Fernando Rios-Avila ()

No 14172, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: Meijer, Rohwedder, and Wansbeek (MRW, Journal of Business & Economic Statistics, 2012) develop methods for prediction of a single earnings figure per worker from mixture factor models fitted using earnings data from multiple linked data sources. MRW apply their method using parameter estimates of Kapteyn and Ypma's mixture factor model (KY, Journal of Labour Economics 2007) fitted to earnings data for Swedish workers aged 50+. First, we replicate MRW's empirical analysis using the Swedish model estimates. Second, we check the generality of their empirical finding with a new application. Using estimates of a KY model fit to a linked dataset on earnings for UK employees of all ages, we confirm that MRW's principal findings about the performance of their various predictors of true earnings also hold in this different setting.

Keywords: labour earnings; earnings prediction; measurement error; mixture factor model; Kapteyn-Ypma model (search for similar items in EconPapers)
JEL-codes: C81 C83 D31 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2021-03
New Economics Papers: this item is included in nep-ltv and nep-ore
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Citations: View citations in EconPapers (6)

Published - published in: Journal of Applied Econometrics , 2021, 36 (4), 474 - 483

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Related works:
Journal Article: Measurement error in earnings data: Replication of Meijer, Rohwedder, and Wansbeek's mixture model approach to combining survey and register data (2021)
Working Paper: Measurement error in earnings data: replication of Meijer, Rohwedder, and Wansbeek’s mixture model approach to combining survey and register data (2021)
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