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Firms' Productivity Growth and R&D Spillovers: An Analysis of Alternative Technological Proximity Measures

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  • Cincera, Michele

Abstract

This paper aims at assessing the impact of R&D spillovers on firms’ economic performance as measured by productivity growth. The construction of R&D spillovers is based on Jaffe’s methodology (1986, 1988), which associates econometrics and data analysis. The main objective of the paper is to extend Jaffe’s methodology by examining alternative methods for measuring R&D spillovers and to test their impacts in terms of the robustness of results. In particular, the method used to classify firms into technological clusters as well as the metrics implemented to appreciate firms’ technological proximities which enter the construction of spillovers are further investigated. In addition to R&D spillovers, firms’ own R&D capital, labour and physical capital are estimated by means of a Cobb-Douglas production function. The data set consists of a representative sample of 625 worldwide R&D-intensive firms over the period 1987-1994.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 4894.

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Date of creation: Feb 2005
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Handle: RePEc:cpr:ceprdp:4894

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Keywords: clustering; panel data; productivity growth; R&D Spillovers;

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References

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Citations

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Cited by:
  1. Aiello, Francesco & Cardamone, Paola, 2012. "Regional economic divide and the role of technological spillovers in Italy. Evidence from microdata," Structural Change and Economic Dynamics, Elsevier, vol. 23(3), pages 205-220.
  2. Luigi Aldieri & Michele Cincera, 2009. "Geographic and technological R&D spillovers within the triad: micro evidence from US patents," The Journal of Technology Transfer, Springer, vol. 34(2), pages 196-211, April.
  3. Chyi, Yih-Luan & Lai, Yee-Man & Liu, Wen-Hsien, 2012. "Knowledge spillovers and firm performance in the high-technology industrial cluster," Research Policy, Elsevier, vol. 41(3), pages 556-564.
  4. Anne Plunket, 2009. "Firms' inventiveness and localized vertical R&D spillovers," Journal of Innovation Economics, De Boeck Université, vol. 0(2), pages 147-170.
  5. McNamee, Robert C., 2013. "Can’t see the forest for the leaves: Similarity and distance measures for hierarchical taxonomies with a patent classification example," Research Policy, Elsevier, vol. 42(4), pages 855-873.
  6. Alvaro Escribano & Szabolcs Blazsek, 2012. "Patents, secret innovations and firm's rate of return : differential effects of the innovation leader," Economics Working Papers we1202, Universidad Carlos III, Departamento de Economía.
  7. Paola Cardamone, 2012. "A micro-econometric analysis of the role of R&D spillovers using a nonlinear translog specification," Journal of Productivity Analysis, Springer, vol. 37(1), pages 41-58, February.
  8. Capolupo, Rosa, 2009. "The New Growth Theories and Their Empirics after Twenty Years," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 3(1), pages 1-72.
  9. Schmidt, Tobias, 2006. "An Empirical Analysis of the Effects of Patents and Secrecy on Knowledge Spillovers," ZEW Discussion Papers 06-48, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  10. Sabine Visser, 2007. "R&D in Worldscan," CPB Memorandum 189, CPB Netherlands Bureau for Economic Policy Analysis.

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