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Multiple imputation of missing values in the wave 2007 of the IAB Establishment Panel

Author

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  • Drechsler, Jörg

    () (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany])

Abstract

"The basic concept of multiple imputation is straightforward and easy to understand, but the application to real data imposes many implementation problems. To define useful imputation models for a dataset that consists of categorical and of continuous variables with distributions that are anything but normal, contains skip patterns and all sorts of logical constraints is a challenging task. In this paper, we review different approaches to handle these problems and illustrate their successful implementation for a complex imputation project at the German Institute for Employment Research (IAB): The imputation of missing values in one wave of the IAB Establishment Panel." (Author's abstract, IAB-Doku) ((en))

Suggested Citation

  • Drechsler, Jörg, 2010. "Multiple imputation of missing values in the wave 2007 of the IAB Establishment Panel," IAB Discussion Paper 201006, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  • Handle: RePEc:iab:iabdpa:201006
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    File URL: http://doku.iab.de/discussionpapers/2010/dp0610.pdf
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    Cited by:

    1. Friso Schlitte, 2012. "Local human capital, segregation by skill, and skill‐specific employment growth," Papers in Regional Science, Wiley Blackwell, vol. 91(1), pages 85-106, March.
    2. Breunig, Christoph & Kummer, Michael & Ohnemus, Jörg & Viete, Steffen, 2016. "IT outsourcing and firm productivity: Eliminating bias from selective missingness in the dependent variable," ZEW Discussion Papers 16-092, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.

    More about this item

    Keywords

    Missing Data-Technik; Datenqualität; IAB-Betriebspanel; statistische Methode; Imputationsverfahren;

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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