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The Matching Efficiency of Regional Labour Markets: A Stochastic Production Frontier Estimation, France 1990-1995

  • Ibourk, Aomar

    (affiliation not available)

  • Maillard, Bénédicte

    (affiliation not available)

  • Perelman, Sergio


    (CREPP, Université de Liège)

  • Sneessens, Henri R.


    (University of Luxembourg)

We evaluate the determinants of matching efficiency changes through a stochastic Cobb-Douglas production frontier model extended to allow the efficiency coefficient to depend on variables meant to capture workers and firms characteristics. We apply this methodology to examine regional disparities in France over the period 1990-1995. About 30% of the efficiency changes observed over time and some 25% of the cross regional differences can be explained in terms of changes in firms and workers characteristics. Regional differences in matching efficiency are fairly stable over time and negatively correlated to the regional unemployment rates.

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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 339.

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Length: 30 pages
Date of creation: Aug 2001
Date of revision:
Publication status: published as 'Aggregate Matching Efficiency: A Stochastic Production Frontier Approach, France 1990 - 1995' in: Empirica, 2004, 31 (1), 1-25
Handle: RePEc:iza:izadps:dp339
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  1. A Ibourk & Sergio Perelman, 1999. "Frontières d’efficacité et processus d’appariement sur le marché du travail au Maroc," CREPP Working Papers 9904, Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège.
  2. van Ours, J.C. & Gorter, C., 1994. "Matching Unemployment and Vacancies in Regional Labour Markets; an empirical analysis for the Netherlands," Other publications TiSEM 63318c4d-4008-4f29-94eb-a, Tilburg University, School of Economics and Management.
  3. 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.
  4. Coles, Melvyn G & Smith, Eric, 1994. "Cross-Section Estimation of the Matching Function: Evidence from England and Wales," CEPR Discussion Papers 966, C.E.P.R. Discussion Papers.
  5. 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.
  6. Olivier Jean Blanchard & Peter A. Diamond, 1989. "The Aggregate Matching Function," NBER Working Papers 3175, National Bureau of Economic Research, Inc.
  7. 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 325-32.
  8. Patricia M. Anderson & Simon M. Burgess, 2000. "Empirical Matching Functions: Estimation and Interpretation Using State-Level Data," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 93-102, February.
  9. repec:oup:restud:v:58:y:1991:i:4:p:733-53 is not listed on IDEAS
  10. Coelli, T. J., 1992. "A computer program for frontier production function estimation : Frontier version 2.0," Economics Letters, Elsevier, vol. 39(1), pages 29-32, May.
  11. W. Frame & Tim Coelli, 2001. "U.S. Financial Services Consolidation: The Case of Corporate Credit Unions," Review of Industrial Organization, Springer, vol. 18(2), pages 229-241, March.
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