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Are young and old workers harmful for firm productivity?

  • Thierry Lallemand
  • François Rycx

This paper investigates the effects of the workforce age structure on the productivity of large Belgian firms. More precisely, it examines different scenarios of changes in the proportion of young (16-29 years), middle-aged (30-49 years) and old (more than 49 years) workers and their expected effects on firm productivity. Using detailed matched employer-employee data, we find that a higher share of young (old) workers within firms is favourable (harmful) for firm value added per capita. Results also show that age structure effects on productivity are stronger in ICT than in non-ICT firms.

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Paper provided by ULB -- Universite Libre de Bruxelles in its series DULBEA Working Papers with number 09-02.RS.

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Date of creation: Jan 2009
Date of revision:
Publication status: Published by: ULB, DULBEA
Handle: RePEc:dul:wpaper:09-02rs
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  1. Dostie, Benoit, 2006. "Wages, Productivity and Aging," IZA Discussion Papers 2496, Institute for the Study of Labor (IZA).
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  4. Thierry Lallemand & Robert Plasman & François Rycx, 2009. "Wage Structure and Firm Productivity in Belgium," NBER Chapters, in: The Structure of Wages: An International Comparison, pages 179-215 National Bureau of Economic Research, Inc.
  5. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
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  8. Christian Grund & Niels Westergaard-Nielsen, 2008. "Age structure of the workforce and firm performance," International Journal of Manpower, Emerald Group Publishing, vol. 29(5), pages 410-422, September.
  9. Ilmakunnas, Pekka & Maliranta, Mika, 2003. "Technology, Labor Characteristic and Wage-productivity Gaps," Discussion Papers 860, The Research Institute of the Finnish Economy.
  10. Judith Hellerstein & David Neumark, 2004. "Production Function and Wage Equation Estimation with Heterogenous Labor: Evidence from a New Matched Employer-Employee Dataset," Working Papers 04-05, Center for Economic Studies, U.S. Census Bureau.
  11. James Levinsohn & Amil Petrin, 2000. "Estimating Production Functions Using Inputs to Control for Unobservables," NBER Working Papers 7819, National Bureau of Economic Research, Inc.
  12. Patrick Aubert & Bruno Crépon, 2003. "La productivité des salariés âgés : une tentative d'estimation," Économie et Statistique, Programme National Persée, vol. 368(1), pages 95-119.
  13. Vegard Skirbekk, 2003. "Age and individual productivity: a literature survey," MPIDR Working Papers WP-2003-028, Max Planck Institute for Demographic Research, Rostock, Germany.
  14. Haegeland, T. & Klette, T.J., 1998. "Do Higher Wages Reflect Higher Productivity? Education, Gender and Experience Premiums in a Matched Plant-Worker Data Set," Memorandum 24/1998, Oslo University, Department of Economics.
  15. G. Steven Olley & Ariel Pakes, 1992. "The Dynamics of Productivity in the Telecommunications Equipment Industry," NBER Working Papers 3977, National Bureau of Economic Research, Inc.
  16. Thierry Lallemand & Robert Plasman & François Rycx, 2004. "Intra-Firm Wage Dispersion and Firm Performance: Evidence from Linked Employer-Employee Data," Kyklos, Wiley Blackwell, vol. 57(4), pages 533-558, November.
  17. Philip Taylor & Peter Urwin, 2001. "Age and Participation in Vocational Education and Training," Work, Employment & Society, British Sociological Association, vol. 15(4), pages 763-779, December.
  18. Malmberg, Bo & Lindh, Thomas & Halvarsson, Max, 2005. "Productivity consequences of workforce ageing - Stagnation or a Horndal effect?," Arbetsrapport 2005:17, Institute for Futures Studies.
  19. Jovanovic, Boyan, 1979. "Job Matching and the Theory of Turnover," Journal of Political Economy, University of Chicago Press, vol. 87(5), pages 972-90, October.
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