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A Count Panel Data Study Of The Schumpeterian Hypothesis

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  • James J. Jozefowicz

Abstract

This study estimates the patent-R&D relationship using count panel data. The data is an original panel of 318 firms making R&D investments and applying for patents during the period from 1984 to 1993. A negative binomial model with fixed effects is estimated, taking into account both the discrete nature of the count dependent variable and firm-specific unobserved heterogeneity as well as overdispersion in the data. Firm-level R&D capital, concentration ratios, and various firm size proxies are used as independent variables. Analysis of the data fails to reveal support for the basic tenets of the Schumpeterian Hypothesis. In particular, firm size has a significant negative impact on innovation while industry concentration is statistically insignificant.

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Bibliographic Info

Article provided by New York State Economics Association (NYSEA) in its journal New York Economic Review.

Volume (Year): 34 (2003)
Issue (Month): 1 ()
Pages: 21-37

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Handle: RePEc:nye:nyervw:v:34:y:2003:i:1:p:21-37

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  1. Emmanuel DUGUET & Isabelle KABLA, 1998. "Appropriation Strategy and the Motivations to Use the Patent System: An Econometric Analysis at the Firm Level in French Manufacturing," Annales d'Economie et de Statistique, ENSAE, issue 49-50, pages 289-327.
  2. Bruno Crépon & Emmanuel Duguet & Jacques Mairesse, 1998. "Research, Innovation and Productivity : An Econometric Analysis at the Firm Level," Working Papers 98-33, Centre de Recherche en Economie et Statistique.
  3. Georg LICHT & Konrad ZOZ, 1998. "Patents and R&D, An Econometric Investigation Using Applications for German, European and US Patents by German Companies," Annales d'Economie et de Statistique, ENSAE, issue 49-50, pages 329-360.
  4. Crepon, B. & Duguet, E., 1995. "Research and Development, Competition and Innovation; Pseudo Maximum Likelihood and Simulated Maximum Likelihood Methods Applied to Count Data Models with Heterogeneity," Papiers d'Economie Mathématique et Applications 95.08, Université Panthéon-Sorbonne (Paris 1).
  5. Richard Blundell & Rachel Griffith & John Van Reenen, 1994. "Dynamic count data models of technological innovation," IFS Working Papers W94/10, Institute for Fiscal Studies.
  6. Richard Blundell & Rachel Griffith & John Van Reenen, 1993. "Knowledge stocks, persistent innovation and market dominance: evidence from a panel of British manufacturing firms," IFS Working Papers W93/19, Institute for Fiscal Studies.
  7. Richard Blundell & Rachel Griffith & Frank Windmeijer, 1999. "Individual effects and dynamics in count data models," IFS Working Papers W99/03, Institute for Fiscal Studies.
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