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Der Einsatz von Missing Data Techniken in der Arbeitsmarktforschung des IAB

Author

Listed:
  • Rässler, Susanne

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

Abstract

"Der Beitrag gibt einen Überblick über aktuelle Forschungsprojekte des Instituts für Arbeitsmarkt- und Berufsforschung (IAB), die sich alle auf unterschiedliche Weise mit der Behebung von Problemen mit Missing Data befassen. Hierzu gehören einerseits Projekte, die Stichproben verwenden wie das IAB-Betriebspanel, die IAB-Beschäftigtenstichprobe oder die Erhebung der offenen Stellen, die entweder wie alle Stichprobenerhebungen durch Antwortausfälle beeinträchtigt sind oder aber zensierte Beobachtungen aufweisen. Auf der anderen Seite zählen hierzu Forschungsprojekte, die versuchen, unterschiedliche Datengrundlagen vereinbar zu machen, die auf verschiedenen regionalen oder klassifikatorischen Abgrenzungen beruhen. Außerdem wird das Projekt TrEffeR des IAB und der Bundesagentur für Arbeit (BA) vorgestellt, das der oft ausgesprochenen Forderung gerecht wird, die Maßnahmen der aktiven Arbeitsmarktpolitik auf breiter Basis zu evaluieren und diese Erkenntnisse für das operative Geschäft der BA nutzbar macht." (Autorenreferat, IAB-Doku)

Suggested Citation

  • Rässler, Susanne, 2006. "Der Einsatz von Missing Data Techniken in der Arbeitsmarktforschung des IAB," IAB-Forschungsbericht 200618, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  • Handle: RePEc:iab:iabfob:200618
    as

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    File URL: http://doku.iab.de/forschungsbericht/2006/fb1806.pdf
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    References listed on IDEAS

    as
    1. Jensen, Uwe & Rässler, Susanne, 2005. "Where have all the data gone? Stochastic production frontiers with multiply imputed German establishment data," IAB Discussion Paper 200515, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    2. Gartner, Hermann & Rässler, Susanne, 2005. "Analyzing the changing gender wage gap based on multiply imputed right censored wages," IAB Discussion Paper 200505, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    3. Marco Caliendo & Reinhard Hujer, 2006. "The microeconometric estimation of treatment effects—An overview," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 199-215, March.
    4. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    5. Stephan, Gesine & Rässler, Susanne & Schewe, Torben, 2006. "Wirkungsanalyse in der Bundesagentur für Arbeit : Konzeption, Datenbasis und ausgewählte Befunde," IAB Discussion Paper 200607, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    6. Kölling, Arnd & Rässler, Susanne, 2004. "Editing and multiply imputing German establishment panel data to estimate stochastic production frontier models," IAB Discussion Paper 200405, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    7. Susanne Rässler & Regina Riphahn, 2006. "Survey item nonresponse and its treatment," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 217-232, March.
    8. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, pages 4-29.
    9. Chib, Siddhartha, 1992. "Bayes inference in the Tobit censored regression model," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 79-99.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Datengewinnung; Datenqualität; prozessproduzierte Daten; Arbeitsmarktforschung; Datenaufbereitung;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • J41 - Labor and Demographic Economics - - Particular Labor Markets - - - Labor Contracts

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