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Productivity consequences of workforce ageing - Stagnation or a Horndal effect?

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  • Malmberg, Bo

    ()
    (Institute for Futures Studies)

  • Lindh, Thomas

    ()
    (Institute for Futures Studies)

  • Halvarsson, Max

    (Institute for Futures Studies)

Abstract

Data linking the production of value-added at the plant level to the individual employees provide an opportunity to deepen the understanding of how the labor force composition relates to productivity performance. In view of the anticipated aging of the workforce in industrialised economies a body of research has emerged that indicate that individual productivity has a more pronounced hump-shape than the wage profile. This paper studies these issues by examining the composition of the workforce at the plant level in relation to the productivity performance of the plants. Our data cover the Swedish mining and manufacturing industries 1985-1996. The fact that older workers selectively work with older capital may have biased results found in the literature. Endogeneity of workforce composition poses serious estimation problems, but our attempts to cope with these problems tend to indicate that biases in general go in the direction that productivity of the young is overestimated and the productivity of the old is underestimated.

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Bibliographic Info

Paper provided by Institute for Futures Studies in its series Arbetsrapport with number 2005:17.

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Length: 43 pages
Date of creation: 12 Dec 2005
Date of revision:
Handle: RePEc:hhs:ifswps:2005_017

Note: ISSN 1652-120X ISBN 91-89655-75-3
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Postal: Institute for Futures Studies, Box 591, SE-101 31 Stockholm, Sweden
Phone: 08-402 12 00
Fax: 08-24 50 14
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Web page: http://www.framtidsstudier.se
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Keywords: workforce ageing; productivity growth;

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  1. John Shea, 1997. "Instrument Relevance in Multivariate Linear Models: A Simple Measure," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 348-352, May.
  2. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2002. "Instrumental variables and GMM: Estimation and testing," North American Stata Users' Group Meetings 2003 05, Stata Users Group.
  3. Lindh, Thomas & Malmberg, Bo, 2007. "Demographically based global income forecasts up to the year 2050," International Journal of Forecasting, Elsevier, vol. 23(4), pages 553-567.
  4. 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.
  5. Bruno Crépon & Nicolas Deniau & Sébastien Pérez-Duarte, 2003. "Wages, Productivity and Worker Characteristics : A French Perspective," Working Papers 2003-04, Centre de Recherche en Economie et Statistique.
  6. James Feyrer, 2007. "Demographics and Productivity," The Review of Economics and Statistics, MIT Press, vol. 89(1), pages 100-109, February.
  7. McMillan, Henry M. & Baesel, Jerome B., 1990. "The macroeconomic impact of the baby boom generation," Journal of Macroeconomics, Elsevier, vol. 12(2), pages 167-195.
  8. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  9. Rafael Gómez & Pablo Hernández de Cos, 2003. "Demographic Maturity and Economic Performance: The Effect of Demographic Transitions on Per Capita GDP Growth," Banco de Espa�a Working Papers 0318, Banco de Espa�a.
  10. Paul M. Romer, 1987. "Crazy Explanations for the Productivity Slowdown," NBER Chapters, in: NBER Macroeconomics Annual 1987, Volume 2, pages 163-210 National Bureau of Economic Research, Inc.
  11. Bjorn Andersson, 2001. "Scandinavian Evidence on Growth and Age Structure," Regional Studies, Taylor & Francis Journals, vol. 35(5), pages 377-390.
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