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Does the Use of Worker Flows Improve the Analysis of Establishment Turnover? Evidence from German Administrative Data

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  • Tanja Hethey-Maier
  • Johannes F. Schmieder

Abstract

Administrative datasets provide an excellent source for detailed analysis of establishment entries and exits on a fine and disaggregate level. However, administrative datasets are not without problems: restructuring and relabeling of firms is often poorly measured and can create large biases. Information on worker flows between establishments can potentially alleviate these measurement issues, but it is typically hard to judge how well correction algorithms based on this methodology work. This paper evaluates the use of the worker flow methodology using a dataset from Germany, the Establishment History Panel. We first document the extent of misclassification that stems from relying solely on the first and last appearance of the establishment identifier (EID) to identify openings and closings: Only about 35 to 40 percent of new and disappearing EIDs with more than 3 employees are likely to correspond to real establishment entries and exits. We provide 3 pieces of evidence that using a classification system based on worker flows is superior to using EIDs only: First, establishment birth years generated using the worker flow methodology are much higher correlated with establishment birth years from an independent survey. Second, establishment entries and exits which are identified using the worker flow methodology move closely with the business cycle, while events which are identified as simple ID changes are not. Third, new establishment entries are small and show rapid growth, unlike new EIDs that correspond to ID changes.

Suggested Citation

  • Tanja Hethey-Maier & Johannes F. Schmieder, 2013. "Does the Use of Worker Flows Improve the Analysis of Establishment Turnover? Evidence from German Administrative Data," NBER Working Papers 19730, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:19730
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    References listed on IDEAS

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    1. Lars Vilhuber, 2009. "Adjusting Imperfect Data: Overview and Case Studies," NBER Chapters,in: The Structure of Wages: An International Comparison, pages 59-80 National Bureau of Economic Research, Inc.
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    Citations

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    Cited by:

    1. Fackler, Daniel & Müller, Steffen & Stegmaier, Jens, 2016. "Plant-level employment development before collective displacements: Comparing mass layoffs, plant closures, and bankruptcies," IWH Discussion Papers 27/2016, Halle Institute for Economic Research (IWH).
    2. Neffke, Frank & Otto, Anne & Weyh, Antje, 2017. "Skill-relatedness matrices for Germany : Data method and access," FDZ Methodenreport 201704_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    3. Deborah Goldschmidt & Wolfram Klosterhuber & Johannes F Schmieder, 2017. "Identifying couples in administrative data
      [Identifizierung von Ehepaaren in Administrativen Daten]
      ," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 50(1), pages 29-43, August.
    4. repec:bla:ecinqu:v:55:y:2017:i:2:p:757-777 is not listed on IDEAS
    5. Baumgarten, Daniel & Irlacher, Michael & Koch, Michael, 2018. "Offshoring and non-monotonic employment effects across industries in general equilibrium," Discussion Papers in Economics 43049, University of Munich, Department of Economics.
    6. Geurts, Karen & Van Biesebroeck, Johannes, 2016. "Firm creation and post-entry dynamics of de novo entrants," International Journal of Industrial Organization, Elsevier, vol. 49(C), pages 59-104.
    7. Daniel Fackler & Claus Schnabel & Alexandra Schmucker, 2016. "Spinoffs in Germany: characteristics, survival, and the role of their parents," Small Business Economics, Springer, vol. 46(1), pages 93-114, January.
    8. vom Berge, Philipp & Schmillen, Achim, 2015. "Direct and indirect effects of mass layoffs : evidence from geo-referenced data," IAB Discussion Paper 201511, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    9. Andrew Kerr, 2016. "Job flows, worker flows, and churning in South Africa," WIDER Working Paper Series 037, World Institute for Development Economic Research (UNU-WIDER).
    10. Fackler, Daniel & Müller, Steffen & Stegmaier, Jens, 2017. "Explaining wage losses after job displacement: Employer size and lost firm rents," IWH Discussion Papers 32/2017, Halle Institute for Economic Research (IWH).
    11. Fackler, Daniel & Hank, Eva & Müller, Steffen & Stegmaier, Jens, 2017. "Identifying bankruptcies in German social security data," FDZ Methodenreport 201710_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    12. Eliason, Marcus & Hensvik, Lena & Kramarz, Francis & Nordstrom Skans, Oskar, 2017. "The Causal Impact of Social Connections on Firms' Outcomes," CEPR Discussion Papers 12135, C.E.P.R. Discussion Papers.
    13. Thomas Brenner & Matthias Dorner, 2015. "The Cyclical Dynamics of Industries in West Germany- Testing the Industry Life Cycle Hypothesis," Papers on Economics and Evolution 2015-05, Philipps University Marburg, Department of Geography.
    14. Schäffler, Johannes, 2014. "ReLOC linkage: a new method for linking firm-level data with the establishment-level data of the IAB," FDZ Methodenreport 201405_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    15. Bossler, Mario & Oberfichtner, Michael, 2014. "The employment effect of deregulating shopping hours: Evidence from German retailing," Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100506, Verein für Socialpolitik / German Economic Association.
    16. repec:spr:qualqt:v:52:y:2018:i:2:d:10.1007_s11135-017-0495-6 is not listed on IDEAS
    17. Otto, Anne & Weyh, Antje, 2014. "Industry space and skill-relatedness of economic activities : comparative case studies of three eastern German automotive regions," IAB-Forschungsbericht 201408, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    18. Eliason, Marcus & Hensvik, Lena & Kramarz, Francis & Nordstrom Skans, Oskar, 2017. "The Causal Impact of Social Connections on Firms' Outcomes," CEPR Discussion Papers 12135, C.E.P.R. Discussion Papers.
    19. Karen Geurts, 2016. "Longitudinal firm-level data: problems and solutions," Small Business Economics, Springer, vol. 46(3), pages 425-445, March.
    20. Dorner, Matthias & Bender, Stefan & Harhoff, Dietmar & Hoisl, Karin & Scioch, Patrycja, 2014. "The MPI-IC-IAB-Inventor data 2002 (MIID 2002): Record-linkage of patent register data with labor market biography data of the IAB," FDZ Methodenreport 201406_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].

    More about this item

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms

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