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Estimations of Occupational and Regional Matching Efficiencies Using Stochastic Production Frontier Models

Author

Listed:
  • Fahr, René

    () (University of Paderborn)

  • Sunde, Uwe

    () (University of Munich)

Abstract

By applying a stochastic production frontier approach to the matching process of unemployed and vacancies, this paper provides novel detailed insights into the process of job creation. For different labor markets as defined by occupation and region, the methodology produces estimates of the relative importance of demand and supply factors for the creation of new jobs, and of the overall efficiency of job creation. Some crucial determinants of the overall matching efficiency are identified and analyzed. This allows to make differentiated statements about the appropriateness of labor market policies, and therefore provides policy makers with novel relevant information.

Suggested Citation

  • Fahr, René & Sunde, Uwe, 2002. "Estimations of Occupational and Regional Matching Efficiencies Using Stochastic Production Frontier Models," IZA Discussion Papers 552, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp552
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    References listed on IDEAS

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    1. 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.
    2. Fahr, René & Sunde, Uwe, 2001. "Strategic Hiring Behavior in Empirical Matching Functions," IZA Discussion Papers 320, Institute for the Study of Labor (IZA).
    3. Layard, Richard & Nickell, Stephen & Jackman, Richard, 2005. "Unemployment: Macroeconomic Performance and the Labour Market," OUP Catalogue, Oxford University Press, number 9780199279173.
    4. Adriana D. Kugler & Gilles Saint-Paul, 2004. "How Do Firing Costs Affect Worker Flows in a World with Adverse Selection?," Journal of Labor Economics, University of Chicago Press, vol. 22(3), pages 553-584, July.
    5. Sunde, Uwe, 2002. "Unobserved Bilateral Search on the Labor Market: A Theory-Based Correction for a Common Flaw in Empirical Matching Studies," IZA Discussion Papers 520, Institute for the Study of Labor (IZA).
    6. Richard Jackman & Richard Layard & S Savouri, 1990. "Mismatch: A Framework for Thought," CEP Discussion Papers dp0001, Centre for Economic Performance, LSE.
    7. Bauer, Paul W., 1990. "Recent developments in the econometric estimation of frontiers," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 39-56.
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    Citations

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    Cited by:

    1. Sergio Destefanis & Raquel Fonseca, 2007. "Matching Efficiency and Labour Market Reform in Italy: A Macroeconometric Assessment," LABOUR, CEIS, vol. 21(1), pages 57-84, March.
    2. Abid, Anis Bou & Drine, Imed, 2011. "Efficiency frontier and matching process on the labour market: Evidence from Tunisia," Economic Modelling, Elsevier, vol. 28(3), pages 1131-1139, May.
    3. 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.
    4. Sergio Destefanis & Raquel Fonseca, 2006. "Labour-Market Reforms and the Beveridge Curve. Some Macro Evidence for Italy," CSEF Working Papers 168, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    5. Iva Tomic, 2012. "The Efficiency of the Matching Process: Exploring the Impact of Regional Employment Offices in Croatia," Working Papers 1204, The Institute of Economics, Zagreb.
    6. Iva Tomić, 2014. "Regional matching (in)efficiency on the Croatian labour market," Acta Oeconomica, Akadémiai Kiadó, Hungary, vol. 64(3), pages 287-312, September.

    More about this item

    Keywords

    occupational unemployment; stochastic frontier; matching efficiency; regional unemployment;

    JEL classification:

    • 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

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