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
Authors registered in the RePEc Author Service: Fernando Rios-Avila ()

Journal of Applied Econometrics, 2021, vol. 36, issue 4, 474-483

Abstract: Meijer, Rohwedder, and Wansbeek (MRW, Journal of Business & Economic Statistics, 2012) developed methods for prediction of a single earnings figure per worker from mixture factor models fitted using earnings data from multiple linked data sources. MRW applied 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.

Date: 2021
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Citations: View citations in EconPapers (5)

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https://doi.org/10.1002/jae.2811

Related works:
Working Paper: 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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