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Are Young and Old WorkersS Harmful for Firm Productivity ?

Listed author(s):
  • 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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File URL: https://dipot.ulb.ac.be/dspace/bitstream/2013/53967/1/RePEc_sol_wpaper_09-002.pdf
File Function: RePEc_sol_wpaper_09-002
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Paper provided by ULB -- Universite Libre de Bruxelles in its series Working Papers CEB with number 09-002.RS.

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Length: 33 p.
Date of creation: 2009
Publication status: Published by:
Handle: RePEc:sol:wpaper:09-002
Contact details of provider: Postal:
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Phone: +32 (0)2 650.48.64
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Web page: http://difusion.ulb.ac.be
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  1. Benoit Dostie, 2011. "Wages, Productivity and Aging," De Economist, Springer, vol. 159(2), pages 139-158, June.
  2. Susana Iranzo & Fabiano Schivardi & Elisa Tosetti, 2008. "Skill Dispersion and Firm Productivity: An Analysis with Employer-Employee Matched Data," Journal of Labor Economics, University of Chicago Press, vol. 26(2), pages 247-285, 04.
  3. Malmberg, Bo & Lindh, Thomas & Halvarsson, Max, 2005. "Productivity consequences of workforce ageing - Stagnation or a Horndal effect?," Arbetsrapport 2005:17, Institute for Futures Studies.
  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.
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  8. Judith K. Hellerstein & David Neumark, 1995. "Are Earnings Profiles Steeper Than Productivity Profiles? Evidence from Israeli Firm-Level Data," Journal of Human Resources, University of Wisconsin Press, vol. 30(1), pages 89-112.
  9. Julia I. Lane & John C. Haltiwanger & James Spletzer, 1999. "Productivity Differences across Employers: The Roles of Employer Size, Age, and Human Capital," American Economic Review, American Economic Association, vol. 89(2), pages 94-98, May.
  10. Judith K. Hellerstein & David Neumark, 2007. "Production Function and Wage Equation Estimation with Heterogeneous Labor: Evidence from a New Matched Employer-Employee Data Set," NBER Chapters,in: Hard-to-Measure Goods and Services: Essays in Honor of Zvi Griliches, pages 31-71 National Bureau of Economic Research, Inc.
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  16. Christian Grund, 2008. "Age structure of the workforce and firm performance," International Journal of Manpower, Emerald Group Publishing, vol. 29(5), pages 410-422, August.
  17. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
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  19. Pekka Ilmakunnas & Mika Maliranta, 2005. "Technology, Labour Characteristics and Wage-productivity Gaps," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(5), pages 623-645, October.
  20. Torbjørn Hægeland & Tor Jakob Klette, 1997. "Do Higher Wages Reflect Higher Productivity? Education, Gender and Experience Premiums in a Matched Plant-Worker Data Set," Discussion Papers 208, Statistics Norway, Research Department.
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  22. William R. Johnson, 1978. "A Theory of Job Shopping," The Quarterly Journal of Economics, Oxford University Press, vol. 92(2), pages 261-277.
  23. 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.
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