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Determining factors of patent generation in Andalucia (Spain) - Does public policy support technological knowledge generation in universities?


  • Manuel Acosta


  • Daniel Coronado


  • Mª Dolores Leon


  • Mª Rosario Marin



Our objective in this paper is to explore in detail the second of the three essential functions of universities as elements of a system of innovation (Schartinger et al. 2002, Smith, 1995): the generation of a type of knowledge that is directly applicable to industrial production processes; we will use patents as indicator for this process. Several research studies have demonstrated that the analysis of patents is a sufficiently valid and objective method for determining technology transfer (Archibugi, 1992, Basberg, 1987, Boitani and Ciciotti, 1990, and Trajtenberg, 1990). For Meyer- Krahmer and Schmoch (1998). patents show the interest in commercial exploitation of a new technology (...) A high share of patents on the part of scientific institutions can be considered a good indicator for a close relationship of science and industrial laboratories in the technology field”. Also the accessibility of patents allows a more comprehensive treatment than surveys or case studies (Henderson et al., 1998). Unlike the previous studies on university patents that have utilised the university (Henderson et al. 1998; Coupe 2003) or university teachers (Agrawal and Henderson, 2002) as the unit of analysis in the output of patents, in this study we utilise the research group, as an intermediate unit between the university and the academic inventor. This is a realistic option considering that the majority of researchers are integrated into groups following common lines of research, which are also the basic unit for regional financing. With a sample of 1155 Research Groups from Andalucía (Spain), the questions to investigate are the following: What is the influence of the human resources (doctors, graduates and support personnel) on the generation of university patents? What influence does the scientific capacity of the research group have on the generation of university patents? What influence does external financing -public and private- have on the output of patents? To test for the factors that influence the output of patents by public research institutions, we follow the empirical tradition of the formulation of a "knowledge production function" begun with the work of Griliches (1979): Pati=f(Hi, If, Fi, Oi), Where Pat is the production of patents by the research group i, H is the human resources of the group, S is its scientific capacity, F is the financial resources and O represents other characteristics of the group. The empirical specification of this function, given the nature of patent data, suggests the formulation and calculation of two types of model: the first, utilising models of binary choice, will enable us to determine what characteristics are possessed by groups that obtain patents; the second, by means of a count model, will pick up the determinants of the production of patents by each research group (poisson/negative binomial o zero inflated posson/negative binomial models). Our working proposal is as follows. First we carry out a review of the literature on the production of technological knowledge in the universities, as measured by patents, and then we put forward the initial working hypotheses, the methodology and the data utilised. Next we present the results of testing our hypotheses. Finally we draw the principal conclusions and policy implications.

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  • Manuel Acosta & Daniel Coronado & Mª Dolores Leon & Mª Rosario Marin, 2005. "Determining factors of patent generation in Andalucia (Spain) - Does public policy support technological knowledge generation in universities?," ERSA conference papers ersa05p269, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa05p269

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    References listed on IDEAS

    1. Etzkowitz, Henry & Leydesdorff, Loet, 2000. "The dynamics of innovation: from National Systems and "Mode 2" to a Triple Helix of university-industry-government relations," Research Policy, Elsevier, vol. 29(2), pages 109-123, February.
    2. Coupe, Tom, 2003. "Science Is Golden: Academic R&D and University Patents," The Journal of Technology Transfer, Springer, vol. 28(1), pages 31-46, January.
    3. Keith Smith, "undated". "Interactions in knowledge systems: Foundations, policy implications and empirical methods," STEP Report series 199410, The STEP Group, Studies in technology, innovation and economic policy.
    4. Leydesdorff, Loet, 2000. "The triple helix: an evolutionary model of innovations," Research Policy, Elsevier, vol. 29(2), pages 243-255, February.
    5. Audretsch, David B & Feldman, Maryann P, 1996. "R&D Spillovers and the Geography of Innovation and Production," American Economic Review, American Economic Association, vol. 86(3), pages 630-640, June.
    6. Owen-Smith, Jason & Powell, Walter W., 2003. "The expanding role of university patenting in the life sciences: assessing the importance of experience and connectivity," Research Policy, Elsevier, vol. 32(9), pages 1695-1711, October.
    7. Jaffe, Adam B, 1989. "Real Effects of Academic Research," American Economic Review, American Economic Association, vol. 79(5), pages 957-970, December.
    8. Schartinger, Doris & Rammer, Christian & Fischer, Manfred M. & Frohlich, Josef, 2002. "Knowledge interactions between universities and industry in Austria: sectoral patterns and determinants," Research Policy, Elsevier, vol. 31(3), pages 303-328, March.
    9. Thursby, Jerry G. & Kemp, Sukanya, 2002. "Growth and productive efficiency of university intellectual property licensing," Research Policy, Elsevier, vol. 31(1), pages 109-124, January.
    10. Basberg, Bjorn L., 1987. "Patents and the measurement of technological change: A survey of the literature," Research Policy, Elsevier, vol. 16(2-4), pages 131-141, August.
    11. Meyer-Krahmer, Frieder & Schmoch, Ulrich, 1998. "Science-based technologies: university-industry interactions in four fields," Research Policy, Elsevier, vol. 27(8), pages 835-851, December.
    12. Jerry G. Thursby & Marie C. Thursby, 2002. "Who Is Selling the Ivory Tower? Sources of Growth in University Licensing," Management Science, INFORMS, vol. 48(1), pages 90-104, January.
    13. Thursby, Jerry G & Jensen, Richard & Thursby, Marie C, 2001. "Objectives, Characteristics and Outcomes of University Licensing: A Survey of Major U.S. Universities," The Journal of Technology Transfer, Springer, vol. 26(1-2), pages 59-72, January.
    14. Cameron, A Colin & Trivedi, Pravin K, 1986. "Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(1), pages 29-53, January.
    15. William H. Greene, 1994. "Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models," Working Papers 94-10, New York University, Leonard N. Stern School of Business, Department of Economics.
    16. Ajay Agrawal & Rebecca Henderson, 2002. "Putting Patents in Context: Exploring Knowledge Transfer from MIT," Management Science, INFORMS, vol. 48(1), pages 44-60, January.
    17. Thursby, Jerry G & Thursby, Marie C, 2003. "Industry/University Licensing: Characteristics, Concerns and Issues from the Perspective of the Buyer," The Journal of Technology Transfer, Springer, vol. 28(3-4), pages 207-213, August.
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