Research, Innovation, and Productivity: An Econometric Analysis at the Firm Level
AbstractThis paper studies the links between productivity, innovation and research at th level. We introduce three new features: (i) A structural model that explains pro by innovation output, and innovation output by research investment; (ii) New dat manufacturing firms, including the number of European patents and the percentage sales, as well as firm-level demand pull and technology push indicators; (iii) E which correct for selectivity and simultaneity biases and take into account the features of the available data: only a small proportion of firms engage in resea apply for patents; productivity, innovation and research are endogenously determ investment and capital are truncated variables, patents are count data and innov We find that using the more widespread methods, and the more usual data and mode may lead to sensibly different estimates. We find in particular that simultaneit with selectivity, and that both sources of biases must be taken into account tog results are consistent with many of the stylized facts of the empirical literatu of engaging in research (R&D) for a firm increases with its size (number of empl share and diversification, and with the demand pull and technology push indicato capital intensity) of a firm engaged in research increases with the same variabl research capital being strictly proportional to size). The firm innovation outpu patent numbers or innovative sales, rises with its research effort and with the indicators, either directly or indirectly through their effects on research. Fin correlates positively with an higher innovation output, even when controlling fo the skill composition of labor as well as for physical capital intensity.
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Bibliographic InfoPaper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 6696.
Date of creation: Aug 1998
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Other versions of this item:
- Bruno Crepon & Emmanuel Duguet & Jacques Mairessec, 1998. "Research, Innovation And Productivi[Ty: An Econometric Analysis At The Firm Level," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 7(2), pages 115-158.
- 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.
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
- L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
- O31 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
- O33 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-TID-1998-08-31 (Technology & Industrial Dynamics)
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- Crepon, B. & Duguet, E. & Kabla, I., 1995. "A Moderate Support to Schumpeterian Conjectures from Various Innovation Measures," Papiers d'Economie MathÃÂ©matique et Applications 95.06, UniversitÃ© PanthÃ©on-Sorbonne (Paris 1).
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97-30, Centre de Recherche en Economie et Statistique.
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- Zvi Griliches & Jacques Mairesse, 1995. "Production Functions: The Search for Identification," Harvard Institute of Economic Research Working Papers 1719, Harvard - Institute of Economic Research.
- repec:fth:inseep:9730 is not listed on IDEAS
- Jacques Mairesse & Philippe Cunéo, 1985. "Recherche-développement et performances des entreprises : une étude économétrique sur données individuelles," Revue Économique, Programme National Persée, vol. 36(5), pages 1001-1042.
- Chamberlain, Gary, 1982. "Multivariate regression models for panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 5-46, January.
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