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Editing and multiply imputing German establishment panel data to estimate stochastic production frontier models

Author

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  • Kölling, Arnd
  • Rässler, Susanne

Abstract

"This paper illustrates the effects of item-nonresponse in surveys on the results of multivariate statistical analysis when estimation of productivity is the task. To multiply impute the missing data a data augmentation algorithm based on a normal/Wishart model is applied. Data of the German IAB Establishment Panel from waves 2000 and 2001 are used to estimate the establishment's productivity. The processes of constructing, editing, and transforming the variables needed for the analyst's as well as the imputer's models are described. It is shown that standard multiple imputation techniques can be used to estimate sophisticated econometric models from large-scale panel data exposed to item-nonresponse. Basis of the empirical analysis is a stochastic production frontier model with labour and capital as input factors. The results show that a model of technical inefficiency is favoured compared to a case where we assume different production functions in East and West Germany. Also we see that the effect of regional setting on technical inefficiency increases when inference is based on multiply imputed data sets. This could have influence on the economic and regional policies in Germany in the future." (Author's abstract, IAB-Doku) ((en))

Suggested Citation

  • 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].
    • Handle: RePEc:iab:iabdpa:200405
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    References listed on IDEAS

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    1. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    2. Ragnitz, Joachim, 2001. "Produktivitätsrückstand der ostdeutschen Wirtschaft: Eine zusammenfassende Bewertung," Wirtschaft im Wandel, Halle Institute for Economic Research (IWH), vol. 7(7-8), pages 181-189.
    3. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    Cited by:

    1. 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].
    2. Holger Alda & Lutz Bellmann & Hermann Gartner, 2009. "Wage Structure and Labor Mobility in the West German Private Sector, 1993-2000," NBER Chapters, in: The Structure of Wages: An International Comparison, pages 261-313, National Bureau of Economic Research, Inc.
    3. Jensen, Uwe & Rässler, Susanne, 2007. "The effects of collective bargaining on firm performance : new evidence based on stochastic production frontiers and multiply imputed German establishment data," IAB-Forschungsbericht 200703, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].

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    More about this item

    Keywords

    Bundesrepublik Deutschland ; Ostdeutschland ; Westdeutschland ; Befragung ; Datenanalyse ; IAB-Betriebspanel ; Imputationsverfahren ; Markov-Ketten ; Modell ; Monte-Carlo-Methode ; multivariate Analyse ; Ökonometrie ; Antwortverhalten ; Produktivität ; regionale Disparität ; Schätzung ; statistische Methode ; technischer Fortschritt ; Unternehmen ; 2000-2001;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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