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Does the Hartz IV Reform have an Effect on Matching Efficiency in Germany? A Stochastic Frontier Approach

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  • Hillmann, Katja

Abstract

In the course of a comprehensive labor market reform started in 2002 and finished through the implementation of the most radical measure Hartz IV in 2005, I exploit its impact on matching processes in Germany. I use disaggregated data for 178 local employment agencies to examine the effects of stocks and flows of vacancies and unemployed on the hiring rate as well as on the matching efficiency. Building on the work of Ibourk et al. (2004) and Fahr and Sunde (2006), I employ a stochastic frontier analysis. As a functional framework I choose the translog function to address the interactions of stocks and flows in generating new hires. Furthermore, the twofold structure of a stochastic frontier allows for a modeling of potential sources (e.g. Hartz IV) expected to induce an increased or decreased matching efficiency. My results suggest that Hartz IV exhibits a significantly positive impact on the hiring rate and the matching efficiency. Compared to 1998, on average matching efficiency experienced an increase in 2007.

Suggested Citation

  • Hillmann, Katja, 2009. "Does the Hartz IV Reform have an Effect on Matching Efficiency in Germany? A Stochastic Frontier Approach," MPRA Paper 22295, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:22295
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    File URL: https://mpra.ub.uni-muenchen.de/22295/1/MPRA_paper_22295.pdf
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    References listed on IDEAS

    as
    1. Sanna-Mari Hynninen, 2009. "Matching in local labor markets: a stochastic frontier approach," Journal of Productivity Analysis, Springer, vol. 31(1), pages 15-26, February.
    2. René Fahr & Uwe Sunde, 2009. "Did the Hartz Reforms Speed-Up the Matching Process? A Macro-Evaluation Using Empirical Matching Functions," German Economic Review, Verein für Socialpolitik, vol. 10, pages 284-316, August.
    3. Jacobi, Lena & Kluve, Jochen, 2006. "Before and After the Hartz Reforms: The Performance of Active Labour Market Policy in Germany," RWI Discussion Papers 41, RWI - Leibniz-Institut für Wirtschaftsforschung.
    4. Coles, Melvyn G & Smith, Eric, 1996. "Cross-Section Estimation of the Matching Function: Evidence from England and Wales," Economica, London School of Economics and Political Science, vol. 63(252), pages 589-597, November.
    5. Melvyn Coles & Barbara Petrongolo, 2008. "A Test Between Stock-Flow Matching And The Random Matching Function Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 49(4), pages 1113-1141, November.
    6. Eran Yashiv, 2000. "The Determinants of Equilibrium Unemployment," American Economic Review, American Economic Association, vol. 90(5), pages 1297-1322, December.
    7. Rene Fahr & Uwe Sunde, 2006. "Regional dependencies in job creation: an efficiency analysis for Western Germany," Applied Economics, Taylor & Francis Journals, vol. 38(10), pages 1193-1206.
    8. Coles, Melvyn G & Smith, Eric, 1998. "Marketplaces and Matching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(1), pages 239-254, February.
    9. Jacobi, Lena & Kluve, Jochen, 2006. "Before and After the Hartz Reforms: The Performance of Active Labour Market Policy in Germany," IZA Discussion Papers 2100, Institute for the Study of Labor (IZA).
    10. Warren, Ronald Jr., 1996. "Returns to scale in a matching model of the labor market," Economics Letters, Elsevier, vol. 50(1), pages 135-142, January.
    11. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    12. 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. Michael Stops, 2016. "Revisiting German labour market reform effects—a panel data analysis for occupational labour markets," IZA Journal of European Labor Studies, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-43, December.
    2. Baas, Timo & Belke, Ansgar, 2017. "Oil price shocks, monetary policy and current account imbalances within a currency union," CEPS Papers 13334, Centre for European Policy Studies.

    More about this item

    Keywords

    Labor Market Reform; Matching Models; Stochastic Frontier Analysis; Germany;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy

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