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A Dynamic Analysis of University Agricultural Biotechnology Patent Production

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  • Jeremy D. Foltz
  • Kwansoo Kim
  • Bradford Barham
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    Abstract

    This article examines the factors that account for agricultural biotechnology patenting success among universities using a dynamic count data model. It builds a theoretical and econometric model to capture the inherently dynamic and nonlinear process of technological innovation, wherein a feedback mechanism from previous success partially determines current patent counts. The econometric estimates reveal the importance to agricultural biotechnology patent production of land grant infrastructure, quality faculty, patent-oriented technology transfer offices, as well as dynamic feedback effects. Copyright 2003, Oxford University Press.

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    File URL: http://hdl.handle.net/10.1111/1467-8276.00112
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    Bibliographic Info

    Article provided by Agricultural and Applied Economics Association in its journal American Journal of Agricultural Economics.

    Volume (Year): 85 (2003)
    Issue (Month): 1 ()
    Pages: 187-197

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    Handle: RePEc:oup:ajagec:v:85:y:2003:i:1:p:187-197

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    Cited by:
    1. Xia, Yin & Yuan, Yiyong, 2005. "Privatization of Agricultural Biotechnology Research at U.S. Universities," 2005 Annual meeting, July 24-27, Providence, RI 19276, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Acosta, Manuel & Coronado, Daniel & Martínez, M. Ángeles, 2012. "Spatial differences in the quality of university patenting: Do regions matter?," Research Policy, Elsevier, vol. 41(4), pages 692-703.
    3. Meissner Cornelia, 2011. "Academic Patenting: Opportunity, Support or Attitude?," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201107, University of Turin.
    4. Boardman, P. Craig & Corley, Elizabeth A., 2008. "University research centers and the composition of research collaborations," Research Policy, Elsevier, vol. 37(5), pages 900-913, June.
    5. Klaus Moeltner & James J. Murphy & John K. Stranlund & Maria Alejandra Velez, 2007. "Processing Data from Social Dilemma Experiments: A Bayesian Comparison of Parametric Estimators," Working Papers 07-013, University of Nevada, Reno, Department of Economics & University of Nevada, Reno , Department of Resource Economics.
    6. Xia, Yin, 2004. "University Basic Research And Applied Agricultural Biotechnology," 2004 Annual meeting, August 1-4, Denver, CO 20187, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Fernando, Estrada, 2013. "Ronald Coase 1910-2013, In memoriam," MPRA Paper 49558, University Library of Munich, Germany.

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