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Disaggregate Matching Functions

Author

Listed:
  • Fahr, René

    (University of Paderborn)

  • Sunde, Uwe

    (University of Munich)

Abstract
This paper deals with empirical matching functions. The paper is innovative in several ways. First, unlike in most of the existing literature, matching functions are estimated not only on aggregate, but also on disaggregate levels which is unusual due to the scarcity of appropriate data. Moreover, the unique data set used allows to distinguish inflows into jobs by sources. Results for different measures of flows found in the literature can therefore be replicated using a single data set. Labor markets can be disaggregated by occupations, rather than by industries or regions. Furthermore, disaggregation is possible for age and educational groups. The paper allows detailed insights into the pattern of frictions in labor markets, on mismatch and labor market tightness, and therefore provides valuable information necessary for the conduct of labor market policies.

Suggested Citation

  • Fahr, René & Sunde, Uwe, 2001. "Disaggregate Matching Functions," IZA Discussion Papers 335, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp335
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. Brown, Alessio & Merkl, Christian & Snower, Dennis, 2015. "An Incentive Theory Of Matching," Macroeconomic Dynamics, Cambridge University Press, vol. 19(3), pages 643-668, April.
    2. 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.
    3. Brown, Alessio J.G. & Merkl, Christian & Snower, Dennis J., 2011. "Comparing the effectiveness of employment subsidies," Labour Economics, Elsevier, vol. 18(2), pages 168-179, April.
    4. 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.
    5. Philip Schuster, 2010. "Labor Market Policy Instruments and the Role of Economic Turbulence," University of St. Gallen Department of Economics working paper series 2010 2010-29, Department of Economics, University of St. Gallen.
    6. Christoffel, Kai & Kuester, Keith & Linzert, Tobias, 2009. "The role of labor markets for euro area monetary policy," European Economic Review, Elsevier, vol. 53(8), pages 908-936, November.
    7. Lottmann, Franziska, 2012. "Spatial dependencies in German matching functions," Regional Science and Urban Economics, Elsevier, vol. 42(1-2), pages 27-41.
    8. Schüssler, Reinhard & Seidel, Christian, 2010. "Gale Shapley auf dem Arbeitsmarkt," EconStor Preprints 55829, ZBW - Leibniz Information Centre for Economics.
    9. Sanna-Mari Hynninen & Jukka Lahtonen, 2007. "Does population density matter in the process of matching heterogeneous job seekers and vacancies?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 34(5), pages 397-410, December.
    10. Oskamp, Frank & Snower, Dennis J., 2007. "Interactions between employment and training policies," Kiel Working Papers 1389, Kiel Institute for the World Economy (IfW Kiel).
    11. René Fahr & Uwe Sunde, 2002. "On the Effects of Career Choice: Matching Efficiency of Different Occupations and Education Levels," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 B1-1, International Conferences on Panel Data.
    12. Fahr, Rene & Sunde, Uwe, 2005. "Job and vacancy competition in empirical matching functions," Labour Economics, Elsevier, vol. 12(6), pages 773-780, December.
    13. Elżbieta Antczak & Ewa Gałecka‐Burdziak & Robert Pater, 2019. "What Affects Efficiency In Labour Market Matching At Different Territorial Aggregation Levels In Poland?," Bulletin of Economic Research, Wiley Blackwell, vol. 71(2), pages 160-179, April.
    14. Jukka Petteri Lahtonen & Sanna-Mari Hynninen, 2005. "Does population density matter in the matching process of heterogeneous job seekers and vacancies?," ERSA conference papers ersa05p438, European Regional Science Association.
    15. Patacchini, E., 2002. "Unobservable factors and panel data sets: an investigation in the labour market," Discussion Paper Series In Economics And Econometrics 202, Economics Division, School of Social Sciences, University of Southampton.

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    More about this item

    Keywords

    vacancies; empirical matching functions; Matching; unemployment; occupational structure;
    All these keywords.

    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J41 - Labor and Demographic Economics - - Particular Labor Markets - - - Labor Contracts
    • J42 - Labor and Demographic Economics - - Particular Labor Markets - - - Monopsony; Segmented Labor Markets
    • J62 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Job, Occupational and Intergenerational Mobility; Promotion
    • J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs

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