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Multiple imputation of right-censored wages in the German IAB Employment Sample considering heteroscedasticity

Author

Listed:
  • Büttner, Thomas
  • Rässler, Susanne

Abstract

"In many large data sets of economic interest, some variables, as wages, are top-coded or right-censored. In order to analyze wages with the German IAB employment sample we first have to solve the problem of censored wages at the upper limit of the social security system. We treat this problem as a missing data problem and derive new multiple imputation approaches to impute the censored wages by draws of a random variable from a truncated distribution based on Markov chain Monte Carlo techniques. In general, the variation of income is smaller in lower wage categories than in higher categories and the assumption of homoscedasticity in an imputation model is highly questionable. Therefore, we suggest a new multiple imputation method which does not presume homoscedasticity of the residuals. Finally, in a simulation study, different imputation approaches are compared under different situations and the necessity as well as the validity of the new approach is confirmed." (Author's abstract, IAB-Doku) ((en))

Suggested Citation

  • Büttner, Thomas & Rässler, Susanne, 2008. "Multiple imputation of right-censored wages in the German IAB Employment Sample considering heteroscedasticity," IAB-Discussion Paper 200844, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    • Handle: RePEc:iab:iabdpa:200844
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    References listed on IDEAS

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    3. Gartner, Hermann, 2005. "The imputation of wages above the contribution limit with the German IAB employment sample," FDZ-Methodenreport 200502 (en), Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    4. Gartner, Hermann, 2005. "The imputation of wages above the contribution limit with the German IAB employment sample," FDZ Methodenreport 200502_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    5. Bender, Stefan & Haas, Anette & Klose, Christoph, 2000. "IAB Employment Subsample 1975-1995 Opportunities for Analysis Provided by the Anonymised Subsample," IZA Discussion Papers 117, Institute of Labor Economics (IZA).
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    Cited by:

    1. Jorg Drechsler & Johannes Ludsteck, 2025. "Imputation Strategies for Rightcensored Wages in Longitudinal Datasets," Papers 2502.12967, arXiv.org.
    2. Hirsch, Boris & Jahn, Elke J. & Toomet, Ott & Hochfellner, Daniela, 2014. "Do better pre-migration skills accelerate immigrants' wage assimilation?," Labour Economics, Elsevier, vol. 30(C), pages 212-222.
    3. Kruppe, Thomas & Matthes, Britta & Unger, Stefanie, 2014. "Effectiveness of data correction rules in process-produced data : the case of educational attainment," IAB-Discussion Paper 201415, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    4. Kenneth Burdett & Carlos Carrillo-Tudela & Melvyn Coles, 2020. "The Cost of Job Loss," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 87(4), pages 1757-1798.
    5. Nicole Gürtzgen & André Nolte, 2017. "Imputation rules for the implementation of the pre-unification education variable in the BASiD Data Set [Imputationsregeln für die Generierung der Bildungsvariable in den BASiD-Daten vor der Wieder," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 50(1), pages 45-65, August.
    6. Jan Kluge & Michael Weber, 2018. "Decomposing the German East–West wage gap," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 26(1), pages 91-125, January.

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    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

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