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The Agricultural Knowledge Production Function: An Empirical Look

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  • Pardey, Philip G.

Abstract

Economic analysis of the process of technical change has often involved macro-level studies of its causes and consequences. Relatively little attention has been given to the, more fundamental knowledge generation process itself. This stems in large part from the real difficulties of obtaining appropriate indicators of research output. The view that there exists a systematic relationship between research expenditures and knowledge increments has been taken up by numerous authors including Evenson (1968), Minasian (1969), Pakes (1978), Gri1iches (1979), and Kamien and Schwartz (1982). It follows naturally from the perception that, in general, science progresses by a sequence of marginal improvements rather than a series of discrete and essentially sporadic breakthroughs (see Burke [1978). Recent studies by Pakes and Gri1iches (1980), Hausman et a1. (1981), and Hall et a1. (1984) have sought direct estimates of the research input-output relationship for research performed by private firms in the non-agricultural sector. To date there appears to be no similar analysis of the public sector agricultural research process. The study reported here represents a first step in this direction. It develops some quantifiable indicators of agricultural knowledge production by the U.S. public sector research system and will also attempt to provide some clues as to the nature of the agricultural research spending-research output relationship.

Suggested Citation

  • Pardey, Philip G., 1987. "The Agricultural Knowledge Production Function: An Empirical Look," Evaluating Agricultural Research and Productivity, Proceedings of a Workshop, Atlanta, Georgia, January 29-30, 1987, Miscellaneous Publication 52 50022, University of Minnesota, Agricultural Experiment Station.
  • Handle: RePEc:ags:umae52:50022
    DOI: 10.22004/ag.econ.50022
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    9. Pardey, Philip G., 1986. "Public sector production of agricultural knowledge," Faculty and Alumni Dissertations 121800, University of Minnesota, Department of Applied Economics.
    10. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    11. Pakes, Ariel & Schankerman, Mark A., 1978. "The Rate of Obsolescence of Knowledge, Research Gestation Labs, and the Private Rate of Return to Research Resources," Working Papers 78-13, C.V. Starr Center for Applied Economics, New York University.
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    13. Fuller, Wayne A. & Battese, George E., 1974. "Estimation of linear models with crossed-error structure," Journal of Econometrics, Elsevier, vol. 2(1), pages 67-78, May.
    14. Wright, Brian Davern, 1983. "The Economics of Invention Incentives: Patents, Prizes, and Research Contracts," American Economic Review, American Economic Association, vol. 73(4), pages 691-707, September.
    15. McDowell, John M, 1982. "Obsolescence of Knowledge and Career Publication Profiles: Some Evidence of Differences among Fields in Costs of Interrupted Careers," American Economic Review, American Economic Association, vol. 72(4), pages 752-768, September.
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    Cited by:

    1. James Adams & Zvi Griliches, 1996. "Measuring Science: An Exploration," NBER Working Papers 5478, National Bureau of Economic Research, Inc.
    2. Paul Heisey & Sarah Adelman, 2011. "Research expenditures, technology transfer activity, and university licensing revenue," The Journal of Technology Transfer, Springer, vol. 36(1), pages 38-60, February.
    3. Lee, Yoo Hwan & Graff, Gregory D., 2015. "University Research Productivity and its Impact on the Regional Agricultural Economy: The Case of Colorado State University and the Colorado Economy," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205443, Agricultural and Applied Economics Association.
    4. Atul Nerkar, 2003. "Old Is Gold? The Value of Temporal Exploration in the Creation of New Knowledge," Management Science, INFORMS, vol. 49(2), pages 211-229, February.
    5. Qin, Lin & Buccola, Steven T., 2012. "Econometric Assessment of Research Programs: A Bayesian Approach," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124948, Agricultural and Applied Economics Association.
    6. Pardey, Philip G. & Craig, Barbara & Hallaway, Michelle L., 1989. "U.S. agricultural research deflators: 1890-1985," Research Policy, Elsevier, vol. 18(5), pages 289-296, October.
    7. Jens K. Perret, 2016. "A Spatial Knowledge Production Function Approach for the Regions of the Russian Federation," EIIW Discussion paper disbei217, Universitätsbibliothek Wuppertal, University Library.
    8. Jens K. Perret, 2019. "Re-Evaluating the Knowledge Production Function for the Regions of the Russian Federation," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(2), pages 670-694, June.
    9. Chen, Qiang & Naseem, Anwar & Pray, Carl E., 2004. "The Determinants of Research Productivity in Agricultural Biotechnology," 2004 Annual meeting, August 1-4, Denver, CO 20018, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Lee, Yoo Hwan & Graff, Gregory D., 2017. "The Production And Dissemination Of Agricultural Knowledge At U.S. Research Universities: The Role And Mission Of Land-Grant Universities," Journal of Rural Development/Nongchon-Gyeongje, Korea Rural Economic Institute, vol. 40(Special, ), December.
    11. Daniil G. Sandler & Dmitry A. Gladyrev & Dmitry M. Kochetkov & Anna D. Zorina, 2022. "Factors of research groups' productivity: The case of the Ural Federal University," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 8(2), pages 148-160.
    12. 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.
    13. Lee, Yoo Hwan & Graff, Gregory D., 2016. "Academic Knowledge Spillovers and the Role of Geographic Proximity in Regional Agriculture-related Sectors: The impact of agricultural research at Colorado State University on the Colorado economy, an," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235717, Agricultural and Applied Economics Association.
    14. Hock, Cricket & Naseem, Anwar & Hossain, Ferdaus & Pray, Carl E., 2003. "Impact of Biotechnology on Plant Breeding," 2003 Annual meeting, July 27-30, Montreal, Canada 22093, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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