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Identifying Age, Cohort and Period Effects in Scientific Research Productivity: Discussion and Illustration Using Simulated and Actual Data on French Physicists

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  • Bronwyn H. Hall
  • Jacques Mairesse
  • Laure Turner

Abstract

The identification of age, cohort (vintage), and period (year) effects in a panel of individuals or other units is an old problem in the social sciences, but one that has not been much studied in the context of measuring researcher productivity. In the context of a semi-parametric model of productivity where these effects are assumed to enter in an additive manner, we present the conditions necessary to identify and test for the presence of the three effects. In particular we show that failure to specify precisely the conditions under which such a model is identified can lead to misleading conclusions about the productivity-age relationship. We illustrate our methods using data on the publications 1986-1997 by 465 French condensed matter physicists who were born between 1936 and 1960.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 11739.

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Date of creation: Nov 2005
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Publication status: published as Bronwyn Hall & Jacques Mairesse & Laure Turner, 2007. "Identifying Age, Cohort, And Period Effects In Scientific Research Productivity: Discussion And Illustration Using Simulated And Actual Data On French Physicists," Economics of Innovation and New Technology, Taylor and Francis Journals, vol. 16(2), pages 159-177.
Handle: RePEc:nbr:nberwo:11739

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  1. Ernst R. Berndt & Zvi Griliches & Neal Rappaport, 1995. "Econometric Estimates of Prices Indexes for Personal Computers in the 1990s," NBER Working Papers 4549, National Bureau of Economic Research, Inc.
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  3. Andrea Bonaccorsi & Cinzia Daraio, 2003. "A robust nonparametric approach to the analysis of scientific productivity," Research Evaluation, Oxford University Press, vol. 12(1), pages 47-69, April.
  4. Paula E. Stephan, 1996. "The Economics of Science," Journal of Economic Literature, American Economic Association, vol. 34(3), pages 1199-1235, September.
  5. Ashish Arora & Alfonso Gambardella, 1996. "Reputation and competence in publicly funded scientific research," Industrial Organization 9605002, EconWPA.
  6. Blundell, Richard & Griffith, Rachel & Windmeijer, Frank, 2002. "Individual effects and dynamics in count data models," Journal of Econometrics, Elsevier, vol. 108(1), pages 113-131, May.
  7. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-38, July.
  8. Levin, Sharon G & Stephan, Paula E, 1991. "Research Productivity over the Life Cycle: Evidence for Academic Scientists," American Economic Review, American Economic Association, vol. 81(1), pages 114-32, March.
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