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The effects of scientific regional opportunities in science-technology flows: Evidence from scientific literature in firms patent data

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Listed author(s):
  • Daniel Coronado

    ()

  • Manuel Acosta

    ()

Abstract

Relevant scientific literature has demonstrated that in spaces of smaller scale than the national, the availability of scientific knowledge is also relevant for generating spillover effects that benefit the industrial sector. The proliferation of such literature consistently stressing the importance of physical proximity for the two-way flow of knowledge and for the development and fostering of innovation, together with the high degree of self-government of the Spanish regions (which have the competence to develop their own R&D policies), all suggest that the relationships between the scientific community and the industrial sector may be closer and more productive in the regions where the scientific potential is more relevant, in comparison with other regions. The basic objective of this article is to test for the possible differential effects of a favourable scientific environment on science-technology relationships, and more specifically, to determine if the considerable regional resources directed towards scientific research in local universities are being translated into economic results for industry, by way of better utilisation of scientific knowledge to enable companies to generate more and better innovations in processes and products. The methodology that we employ relates the scientific citations in patent documents - as a basic indicator of these science-technology flows- with various indicators of resources and results of academic research that reflect the scientific research environment. With caution, and recognising the limitations inherent in the NPC (non patent citation) methodology, different econometric specifications permit the conclusion to be drawn that companies of those regions with a more favourable scientific environment make greater use of scientific knowledge. JEL Classification: O31, O38, C21, R59.

(This abstract was borrowed from another version of this item.)

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File URL: http://hdl.handle.net/10.1007/s00168-004-0225-6
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Article provided by Springer & Western Regional Science Association in its journal The Annals of Regional Science.

Volume (Year): 39 (2005)
Issue (Month): 3 (09)
Pages: 495-522

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Handle: RePEc:spr:anresc:v:39:y:2005:i:3:p:495-522
DOI: 10.1007/s00168-004-0225-6
Contact details of provider: Web page: http://www.springer.com

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Order Information: Web: http://link.springer.com/journal/168

Keywords: O31; O38; C21; R59;

Other versions of this item:

Find related papers by JEL classification:
  • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
  • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy
  • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
  • R59 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Other

References listed on IDEAS
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  1. Hall, Bronwyn H. & Jaffee, Adam & Trajtenberg, Manuel, 2000. "Market Value and Patent Citations: A First Look," Department of Economics, Working Paper Series qt1rh8k6z2, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
  2. Jaffe, Adam B, 1989. "Real Effects of Academic Research," American Economic Review, American Economic Association, vol. 79(5), pages 957-970, December.
  3. Verspagen Bert & Schoenmakers Wilfred, 2000. "The Spatial Dimension of Knowledge Spillovers in Europe: Evidence from Firm Patenting Data," Research Memorandum 016, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
  4. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
  5. Zvi Griliches, 1998. "Issues in Assessing the Contribution of Research and Development to Productivity Growth," NBER Chapters,in: R&D and Productivity: The Econometric Evidence, pages 17-45 National Bureau of Economic Research, Inc.
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Cited by:

  1. Rui Baptista & Joana Mendonça, 2010. "Proximity to knowledge sources and the location of knowledge-based start-ups," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 45(1), pages 5-29, August.
  2. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2011. "A field-standardized application of DEA to national-scale research assessment of universities," Journal of Informetrics, Elsevier, vol. 5(4), pages 618-628.
  3. repec:elg:eechap:14395_24 is not listed on IDEAS
  4. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2012. "The dispersion of research performance within and between universities as a potential indicator of the competitive intensity in higher education systems," Journal of Informetrics, Elsevier, vol. 6(2), pages 155-168.
  5. Tsvetkova, Alexandra & Thill, Jean-Claude & Conroy, Tessa, 2016. "Firm patenting activity, metropolitan innovative environment and their effects on business survival in a high-tech industry," MPRA Paper 75783, University Library of Munich, Germany.

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