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Worker-firm Matching and Unemployment in Transition to a Market Economy: (Why) Are the Czechs More Successful than Others?

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  • Daniel Munich
  • Jan Svejnar
  • Katherine Terrell

Abstract

In this paper we compare the nature and determinants of outflows from unemployment in the case of the Czech and Slovak Republics which in early 1990’s experienced a process close to a controlled experiment. Overall, our study suggests that the exceptionally low unemployment rate in the Czech Republic as compared to Slovakia and the other Central and East European economies has been brought about principally by (1) a rapid increase in vacancies along with unemployment, resulting in a balanced unemployment-vacancy situation at the aggregate as well as district level, (2) a major part played by vacancies and the newly unemployed in the outflow from unemployment, (3) a matching process with strongly increasing returns to scale throughout (rather than only in parts of) the transition period, and (4) ability to keep the long term unemployed at relatively low levels. Using the framework of matching functions we find that in many years the usual Cobb-Douglas specification and the hypothesis of constant returns to scale are rejected. A translog matching function with weak separability between the existing and newly unemployed is found to be the functional form best supported by the data. Our theoretical analysis also indicates that by not adjusting data for the varying size of districts or regions, previous studies may have generated estimates of the returns to scale of the matching function that were biased toward unity.

Suggested Citation

  • Daniel Munich & Jan Svejnar & Katherine Terrell, 1999. "Worker-firm Matching and Unemployment in Transition to a Market Economy: (Why) Are the Czechs More Successful than Others?," CERGE-EI Working Papers wp141, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
  • Handle: RePEc:cer:papers:wp141
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    Cited by:

    1. Aki Kangasharju & Jaakko Pehkonen & Sari Pekkala, 2003. "Matching in thin labour markets: panel data evidence from Finland, 1991-2002," ERSA conference papers ersa03p208, European Regional Science Association.
    2. Christopher A. Pissarides & Barbara Petrongolo, 2001. "Looking into the Black Box: A Survey of the Matching Function," Journal of Economic Literature, American Economic Association, vol. 39(2), pages 390-431, June.
    3. Martin Guzi, 2014. "An Empirical Analysis of Welfare Dependence in the Czech Republic," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(5), pages 407-431, November.
    4. Aki Kangasharju & Jaakko Pehkonen & Sari Pekkala, 2005. "Returns to scale in a matching model: evidence from disaggregated panel data," Applied Economics, Taylor & Francis Journals, vol. 37(1), pages 115-118.
    5. Tito Boeri, 1999. "Transition with Labour Supply," William Davidson Institute Working Papers Series 274, William Davidson Institute at the University of Michigan.
    6. Elzbieta Antczak & Ewa Galecka-Burdziak & Robert Pater, 2016. "Efficiency in spatially disaggregated labour market matching," KAE Working Papers 2016-010, Warsaw School of Economics, Collegium of Economic Analysis.
    7. Kamil Galušèák & Daniel Münich, 2007. "Structural and Cyclical Unemployment: What Can Be Derived from the Matching Function? (in English)," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 57(3-4), pages 102-125, June.
    8. Jekaterina Dmitrijeva & Mihails Hazans, 2007. "A Stock–Flow Matching Approach to Evaluation of Public Training Programme in a High Unemployment Environment," LABOUR, CEIS, vol. 21(3), pages 503-540, September.
    9. Jan Babecky & Kamil Galuscak & Lubomir Lizal, 2011. "Firm-Level Labour Demand: Adjustment in Good Times and During the Crisis," Working Papers 2011/15, Czech National Bank.
    10. Joanna Tyrowicz & Tomasz Jeruzalski, 2013. "(In)Efficiency of matching: the case of a post-transition economy," Economic Change and Restructuring, Springer, vol. 46(2), pages 255-275, May.
    11. Kosfeld Reinhold, 2007. "Regional Spillovers and Spatial Heterogeneity in Matching Workers and Employers in Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 227(3), pages 236-253, June.
    12. Jekaterina Dmitrijeva, 2008. "Matching and Labour Market Efficiency across Space and through EU accession: Evidence from Latvia, Estonia and Slovenia," Documents de recherche 08-05, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    13. Tito Boeri & Katherine Terrell, 2002. "Institutional Determinants of Labor Reallocation in Transition," Journal of Economic Perspectives, American Economic Association, vol. 16(1), pages 51-76, Winter.
    14. Joanna Tyrowicz & Piotr Wojcik, 2010. "Active Labour Market Policies and Unemployment Convergence in Transition," Review of Economic Analysis, Digital Initiatives at the University of Waterloo Library, vol. 2(1), pages 46-72, January.
    15. Gerard Rpland, 2001. "The Political Economy of Transition," William Davidson Institute Working Papers Series 413, William Davidson Institute at the University of Michigan.
    16. Kamil Galuscak & Daniel Munich, 2005. "Structural and Cyclical Unemployment: What Can We Derive from the Matching Function?," Working Papers 2005/02, Czech National Bank.
    17. Kenjiro Hori, 2005. "Job Matching with Multiple-Hiring Firms and Heterogeneous Workers: A Microfoundation," Birkbeck Working Papers in Economics and Finance 0514, Birkbeck, Department of Economics, Mathematics & Statistics.

    More about this item

    JEL classification:

    • P2 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies
    • J4 - Labor and Demographic Economics - - Particular Labor Markets
    • J6 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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