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International R&D Spillovers: An Empirical Study

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  • Charbel Macdissi
  • Syoum Negassi

Abstract

The existence of R&D spillovers or externalities i.e. the effects of firms' research activities on others firms activities was theoretically established by Arrow 1962a, but few empirical studies have addressed their effects on firm's economic performance ( i.e. productivity growth) and technological performance. In an open economy, firms' economic and technological performance depends on the position of these firms in their national and international technological environment. The main focus of this paper is on identifying the different channels through which international technology spillovers occurs between firms. Our statistical and econometric analysis determine that spillovers drive the productivity growth rates of individual firms. Thus, using a pooling method based on segmentation of bunched (or grouped by industry) individuals rather than those of usual individuals panel models, this empirical study shows that the international spillovers account for a substantial fraction of the variation in firm productivity growth. The estimated coefficients obtained for the classical variables (R&D and Human capital) are comparable to those obtained in the literature.

Suggested Citation

  • Charbel Macdissi & Syoum Negassi, 2002. "International R&D Spillovers: An Empirical Study," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 11(2), pages 77-91.
  • Handle: RePEc:taf:ecinnt:v:11:y:2002:i:2:p:77-91
    DOI: 10.1080/10438590210897
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    Cited by:

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    2. Daniela Cagno & Andrea Fabrizi & Valentina Meliciani, 2014. "The impact of participation in European joint research projects on knowledge creation and economic growth," The Journal of Technology Transfer, Springer, vol. 39(6), pages 836-858, December.
    3. Valentina Meliciani & Daniela Cagno & Andrea Fabrizi & Marco Marini, 2022. "Knowledge networks in joint research projects, innovation and economic growth across European regions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 68(3), pages 549-586, June.
    4. Yoonjung An & Mintak Han & Yongtae Park, 2017. "Identifying dynamic knowledge flow patterns of business method patents with a hidden Markov model," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 783-802, November.
    5. Oliviero Carboni, 2013. "Spatial and industry proximity in collaborative research: evidence from Italian manufacturing firms," The Journal of Technology Transfer, Springer, vol. 38(6), pages 896-910, December.
    6. Oliviero A. Carboni, 2013. "A spatial analysis of R&D: the role of industry proximity," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 22(8), pages 820-839, November.

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