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Endogenous R&D Spillovers and Industrial Research Productivity

  • James D. Adams

This paper explores the implications of a simple model of learning and innovation by firms. In this model R&D spillovers are partly determined by firms, rather than by the given economic environment. According to this approach the full effect of spillovers on research productivity of firms exceeds the structural effect because it includes an active learning' response of firms to new information. Furthermore, effective spillovers grow faster or slower than potential spillovers, depending on the returns to scale of production processes for learning and invention. The empirical work is based on a sample of R&D laboratories in the chemicals, machinery, electrical equipment, and transportation equipment industries. I estimate negative binomial regressions for the number of patents as a function of academic and industrial spillover pools, learning expenditures and internal research expenditures. The findings are consistent with the view that learning expenditures transmit the effect of spillovers. I also perform tobit, ordered probit and grouped probit estimation of learning effort. I find that learning effort increases in response to industrial and academic R&D spillovers. Lastly, academic spillovers appear to have a more pervasive effect on R&D than do industrial spillovers. Overall these results suggest a sequence of events underlying learning and innovation, with learning responding to opportunities, innovation responding to learning and own R&D, and a stream of innovations leading to the accumulation of new product introductions that ultimately are reflected in the value of enterprise.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 7484.

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Date of creation: Jan 2000
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Handle: RePEc:nbr:nberwo:7484
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  1. Dixit, Avinash K., 1990. "Optimization in Economic Theory," OUP Catalogue, Oxford University Press, edition 2, number 9780198772101.
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  8. Tor Jakob Klette, 1996. "R&D, Scope Economies, and Plant Performance," RAND Journal of Economics, The RAND Corporation, vol. 27(3), pages 502-522, Autumn.
  9. Jerry A. Hausman & Bronwyn H. Hall & Zvi Griliches, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," NBER Technical Working Papers 0017, National Bureau of Economic Research, Inc.
  10. Branstetter, Lee & Sakakibara, Mariko, 1998. "Japanese Research Consortia: A Microeconometric Analysis of Industrial Policy," Journal of Industrial Economics, Wiley Blackwell, vol. 46(2), pages 207-33, June.
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  13. Mansfield, Edwin, 1991. "Academic research and industrial innovation," Research Policy, Elsevier, vol. 20(1), pages 1-12, February.
  14. Zucker, Lynne G & Darby, Michael R & Brewer, Marilynn B, 1998. "Intellectual Human Capital and the Birth of U.S. Biotechnology Enterprises," American Economic Review, American Economic Association, vol. 88(1), pages 290-306, March.
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