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The Knowledge Production Function For University Patenting

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  • SHIFERAW GURMU
  • GRANT C. BLACK
  • PAULA E. STEPHAN

Abstract

We estimate a knowledge production function for university patenting using an individual effects negative binomial model. We control for Research and Development expenditures, research field, and the presence of a Technology Transfer Office. We distinguish between three kinds of researchers: faculty, postdoctoral scholars (postdocs), and PhD students. For the latter two, we also distinguish by visa status. We find patent counts to relate positively and significantly to the number of PhD students and number of postdocs. Our results also suggest that not all graduate students and postdocs contribute equally to patenting but that contribution is mediated by citizenship and visa status. (JEL C25, O31, O32, O34, O38)

Suggested Citation

  • Shiferaw Gurmu & Grant C. Black & Paula E. Stephan, 2010. "The Knowledge Production Function For University Patenting," Economic Inquiry, Western Economic Association International, vol. 48(1), pages 192-213, January.
    • Handle: RePEc:bla:ecinqu:v:48:y:2010:i:1:p:192-213
    DOI: 10.1111/j.1465-7295.2008.00172.x
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    Cited by:

    1. Candelaria Barrios & Esther Flores & M. Ángeles Martínez & Marta Ruiz-Martínez, 2023. "Are the Major Knowledge-producing Countries Converging in Science and Technology Capabilities?," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(4), pages 4534-4560, December.
    2. Jeongsik Lee & Eric Stuen, 2016. "University reputation and technology commercialization: evidence from nanoscale science," The Journal of Technology Transfer, Springer, vol. 41(3), pages 586-609, June.
    3. Junbing Xu & Zhongmei Wei & Haitang Yao, 2022. "Can international students help enhance China's urban innovation?," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(6), pages 2421-2433, September.
    4. John V. Winters, 2017. "Do Native STEM Graduates Increase Innovation? Evidence from U.S. Metropolitan Areas," Economics Working Paper Series 1714, Oklahoma State University, Department of Economics and Legal Studies in Business.
    5. Ejermo, Olof & Toivanen, Hannes, 2018. "University invention and the abolishment of the professor's privilege in Finland," Research Policy, Elsevier, vol. 47(4), pages 814-825.
    6. Manuel Acosta & Daniel Coronado & M. Ángeles Martínez, 2018. "Does technological diversification spur university patenting?," The Journal of Technology Transfer, Springer, vol. 43(1), pages 96-119, February.
    7. Olivier Brossard & Inès Moussa, 2014. "The French cluster policy put to the test with differences-in-differences estimates," Economics Bulletin, AccessEcon, vol. 34(1), pages 520-529.
    8. Soares, Thiago J. & Torkomian, Ana L.V. & Nagano, Marcelo Seido, 2020. "University regulations, regional development and technology transfer: The case of Brazil," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    9. Manuel Acosta & Daniel Coronado & Mª Dolores León & Pedro Jesús Moreno, 2020. "The Production of Academic Technological Knowledge: an Exploration at the Research Group Level," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 11(3), pages 1003-1025, September.
    10. Paula E. Stephan, 2010. "The "I"s Have It: Immigration and Innovation, the Perspective from Academe," Innovation Policy and the Economy, University of Chicago Press, vol. 10(1), pages 83-127.
    11. Kathleen Carroll & Lisa M. Dickson & Jane E. Ruseski, 2013. "Do Faculty Matter? Effects of Faculty Participation in University Decisions," UMBC Economics Department Working Papers 13-06, UMBC Department of Economics.
    12. Daniel Coronado & Esther Flores & M. Ángeles Martínez, 2017. "The role of regional economic specialization in the production of university-owned patents," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 59(2), pages 513-533, September.
    13. Chatterjee, Diti & Dinar, Ariel & González-Rivera, Gloria, 2018. "An empirical knowledge production function of agricultural research and extension: The case of the University of California Cooperative Extension," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 290-297.
    14. Julien Pénin, 2009. "On the consequences of university patenting: What can we learn by asking directly to academic inventors?," Working Papers of BETA 2009-04, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    15. Davide Antonioli & Francesco Nicolli & Laura Ramaciotti & Ugo Rizzo, 2016. "The Effect of Intrinsic and Extrinsic Motivations on Academics’ Entrepreneurial Intention," Administrative Sciences, MDPI, vol. 6(4), pages 1-18, November.
    16. Fouarge, D. & Özer, M.N., 2014. "International mobility of students - Its impact on labour market forecasts and its contribution to the Dutch economy," ROA Technical Report 006, Maastricht University, Research Centre for Education and the Labour Market (ROA).
    17. Patrick Gaule & Mario Piacentini, 2015. "Immigration and Innovation: Chinese Graduate Students in U.S. Universities," CERGE-EI Working Papers wp529, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    18. Margaret E. Blume-Kohout, 2023. "The case of the interrupting funder: dynamic effects of R&D funding and patenting in U.S. universities," The Journal of Technology Transfer, Springer, vol. 48(4), pages 1221-1242, August.
    19. Olof Ejermo & John Källström, 2016. "What is the causal effect of R&D on patenting activity in a “professor’s privilege” country? Evidence from Sweden," Small Business Economics, Springer, vol. 47(3), pages 677-694, October.
    20. Winters, John V., 2014. "Foreign and Native-Born STEM Graduates and Innovation Intensity in the United States," IZA Discussion Papers 8575, Institute of Labor Economics (IZA).
    21. Aydemir, Nisa Yazici & Huang, Wan-Ling & Welch, Eric W., 2022. "Late-stage academic entrepreneurship: Explaining why academic scientists collaborate with industry to commercialize their patents," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    22. Alexander Whalley & Justin Hicks, 2014. "Spending Wisely? How Resources Affect Knowledge Production In Universities," Economic Inquiry, Western Economic Association International, vol. 52(1), pages 35-55, January.

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    More about this item

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy

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