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Worker flows in Germany: Inspecting the time aggregation bias

Author

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  • Nordmeier, Daniela

    (Institute for Employment Research (IAB), Nuremberg, Germany)

Abstract

"This paper analyzes the importance of time aggregation in the measurement of worker flows by exploiting daily information from German administrative data. Time aggregation caused by comparing monthly labor market states leads to an underestimation of total worker flows by around 10%. Contrary to the claim of Shimer (2005, 2012), the time aggregation bias in the separation rate is relatively unaffected by business cycle fluctuations, whereas the time aggregation bias in the job finding rate is procyclical. Nevertheless, monthly time aggregation does not have notable effects on the relative contributions to steady-state unemployment dynamics. The reconsideration of German worker flows reveals that both the job finding rate and the separation rate play an important role for German unemployment dynamics, but the job finding rate dominates in the long run." (Author's abstract, IAB-Doku) ((en))

Suggested Citation

  • Nordmeier, Daniela, 2012. "Worker flows in Germany: Inspecting the time aggregation bias," IAB-Discussion Paper 201212, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    • Handle: RePEc:iab:iabdpa:201212
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    References listed on IDEAS

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    Cited by:

    1. Kohlbrecher, Britta & Merkl, Christian & Nordmeier, Daniela, 2016. "Revisiting the matching function," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 350-374.
    2. Schoiswohl, Florian & Wüger, Michael, 2016. "A Representative Matched Cross-section Survey for Austria - Measuring Worker Flow Dynamics with the Austrian Labour Force Survey," Department of Economics Working Paper Series 223, WU Vienna University of Economics and Business.
    3. Klinger, Sabine & Weber, Enzo, 2014. "Decomposing Beveridge curve dynamics by correlated unobserved components: The impact of labour market reforms in Germany," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100499, Verein für Socialpolitik / German Economic Association.
    4. Gartner, Hermann & Merkl, Christian & Rothe, Thomas, 2012. "Sclerosis and large volatilities: Two sides of the same coin," Economics Letters, Elsevier, vol. 117(1), pages 106-109.
    5. Sabine Klinger & Enzo Weber, 2016. "Decomposing Beveridge Curve Dynamics By Correlated Unobserved Components," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(6), pages 877-894, December.
    6. Rahn, Daniela & Weber, Enzo, 2019. "Patterns Of Unemployment Dynamics In Germany," Macroeconomic Dynamics, Cambridge University Press, vol. 23(1), pages 322-357, January.
    7. Matthias S. Hertweck & Oliver Sigrist, 2012. "The Aggregate Effects of the Hartz Reforms in Germany," Working Paper Series of the Department of Economics, University of Konstanz 2012-38, Department of Economics, University of Konstanz.
    8. Wolfgang Nagl & Michael Weber, 2014. "Unemployment compensation and unemployment duration before and after the German Hartz IV reform," ifo Working Paper Series 186, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    9. Wolfgang Nagl & Michael Weber, 2016. "Stuck in a trap? Long-term unemployment under two-tier unemployment compensation schemes," ifo Working Paper Series 231, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    10. Nordmeier, Daniela & Weber, Enzo, 2013. "Conditional Patterns of Unemployment Dynamics in Germany," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79958, Verein für Socialpolitik / German Economic Association.
    11. Mark Trede & Michael Zimmermann, 2020. "Regional labour migration - Stylized facts for Germany," CQE Working Papers 9320, Center for Quantitative Economics (CQE), University of Muenster.

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