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Regional Matching Frictions and Aggregate Unemployment

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  • Sanna-Mari Hynninen
  • Aki Kangasharju
  • Jaakko Pehkonen

Abstract

The study shows that a stochastic frontier approach applied to regional level data offers a convenient and interesting method to examine how regional differences in matching efficiency and structural factors contribute to aggregate unemployment. The study finds notable and time-wise stable differences in the matching efficiency across travel-to-work areas in Finland. If all areas were as efficient as the most efficient one, the number of hires would increase about 40 per cent. This would decrease the aggregate unemployment rate from the current 8.5 percent level to 6.0 per cent. If all the areas shared the same structural characteristics as the most favourable area, the aggregate unemployment rate would drop to 7.1 per cent.

Suggested Citation

  • Sanna-Mari Hynninen & Aki Kangasharju & Jaakko Pehkonen, 2006. "Regional Matching Frictions and Aggregate Unemployment," ERSA conference papers ersa06p416, European Regional Science Association.
    • Handle: RePEc:wiw:wiwrsa:ersa06p416
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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. Pekka Ilmakunnas & Hanna Pesola, 2003. "Regional Labour Market Matching Functions and Efficiency Analysis," LABOUR, CEIS, vol. 17(3), pages 413-437, September.
    3. Robert Shimer, 2005. "The Cyclical Behavior of Equilibrium Unemployment and Vacancies," American Economic Review, American Economic Association, vol. 95(1), pages 25-49, March.
    4. Karsten Albæk & Henrik Hansen, 2004. "The Rise in Danish Unemployment: Reallocation or Mismatch?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(4), pages 515-536, September.
    5. Peter Diamond (ed.), 1990. "Growth / Productivity / Unemployment," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262041103, April.
    6. Tim Coelli & Sergio Perelman & Elliot Romano, 1999. "Accounting for Environmental Influences in Stochastic Frontier Models: With Application to International Airlines," Journal of Productivity Analysis, Springer, vol. 11(3), pages 251-273, June.
    7. repec:bla:scandj:v:91:y:1989:i:2:p:371-96 is not listed on IDEAS
    8. Steinar Holden & Ragnar Nymoen, 2002. "Measuring Structural Unemployment: NAWRU Estimates in the Nordic Countries," Scandinavian Journal of Economics, Wiley Blackwell, vol. 104(1), pages 87-104, March.
    9. van Ours, J. C. & Burdett, K. & Coles, M., 1994. "Temporal Aggregation Bias in Stock-Flow Models," Other publications TiSEM 993a7da0-0d67-4900-b529-6, Tilburg University, School of Economics and Management.
    10. Burgess, Simon & Turon, Hélène, 2003. "Unemployment Equilibrium and On-the-Job Search," IZA Discussion Papers 753, Institute of Labor Economics (IZA).
    11. 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.
    12. Burgess, Simon M, 1993. "A Model of Competition between Unemployed and Employed Job Searchers: An Application to the Unemployment Outflow Rate in Britain," Economic Journal, Royal Economic Society, vol. 103(420), pages 1190-1204, September.
    13. Olivier Jean Blanchard & Peter A. Diamond, 1989. "The Aggregate Matching Function," NBER Working Papers 3175, National Bureau of Economic Research, Inc.
    14. Aomar IBOURK & Béatrice MAILLARD & Serge PERELMAN & Henri R. SNEESSENS, 2001. "Aggregate Matching Efficiency : A Stochastic Production Frontier Approach, France 1990-1994," LIDAM Discussion Papers IRES 2001034, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    15. 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.
    16. Oliver Jean Blanchard & Peter Diamond, 1989. "The Beveridge Curve," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 20(1), pages 1-76.
    17. 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.
    18. Christopher A. Pissarides, 1992. "Loss of Skill During Unemployment and the Persistence of Employment Shocks," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(4), pages 1371-1391.
    19. 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.
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    Cited by:

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    2. Berger, Johannes & Strohner, Ludwig, 2020. "Documentation of the PUblic Policy Model for Austria and other European countries (PUMA)," Research Papers 11, EcoAustria – Institute for Economic Research.

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