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A Primal-Dual Approach To Nonparametric Productivity Analysis: The Case Of U.S. Agriculture

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  • Chavas, Jean-Paul
  • Cox, Thomas L.
Abstract
Nonparametric methods for measuring productivity indexes based on bounds for the underlying production technology are presented. Following Banker and Maindiratta, the lower bound is obtained from a primal approach while the upper bound corresponds to a dual approach to nonparametric production analysis. These nonparametric bounds are then used to estimate input-based and output- based distance functions. These radial measures provide the basis for measuring productivity indexes. Application to times series data on U.S. agriculture indicates a large gap between the primal lower bound and the dual upper bound. This generates striking differences between the primal and dual nonparametric productivity indexes.

Suggested Citation

  • Chavas, Jean-Paul & Cox, Thomas L., 1994. "A Primal-Dual Approach To Nonparametric Productivity Analysis: The Case Of U.S. Agriculture," Staff Papers 12613, University of Wisconsin-Madison, Department of Agricultural and Applied Economics.
    • Handle: RePEc:ags:wisagr:12613
    DOI: 10.22004/ag.econ.12613
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    References listed on IDEAS

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    Cited by:

    1. Jean‐Christophe Bureau & Rolf Färe & Shawna Grosskopf, 1995. "A Comparison Of Three Nonparametric Measures Of Productivity Growth In European And United States Agriculture," Journal of Agricultural Economics, Wiley Blackwell, vol. 46(3), pages 309-326, September.
    2. Munisamy Gopinath & Terry Roe, 1997. "Sources of Sectoral Growth in an Economy Wide Context: The Case of U.S. Agriculture," Journal of Productivity Analysis, Springer, vol. 8(3), pages 293-310, August.
    3. Asmild, Mette & Paradi, Joseph C. & Reese, David N. & Tam, Fai, 2007. "Measuring overall efficiency and effectiveness using DEA," European Journal of Operational Research, Elsevier, vol. 178(1), pages 305-321, April.
    4. Just, Richard E., 2003. "Risk research in agricultural economics: opportunities and challenges for the next twenty-five years," Agricultural Systems, Elsevier, vol. 75(2-3), pages 123-159.
    5. Mullen, John D. & Cox, Thomas L., 1995. "The Returns From Research In Australian Broadacre Agriculture," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 39(2), pages 1-24, August.
    6. Cox, Thomas L. & Mullen, John D. & Hu, Wensheng, 1996. "Nonparametric Measures Of The Impacts Of Public Research Expenditures On Australian Broadacre Agriculture: Preliminary Results," Staff Papers 12656, University of Wisconsin-Madison, Department of Agricultural and Applied Economics.
    7. Just, Richard E., 2000. "Some Guiding Principles for Empirical Production Research in Agriculture," Agricultural and Resource Economics Review, Cambridge University Press, vol. 29(2), pages 138-158, October.
    8. N. Islam, 2000. "An Analysis of Productivity Growth in Western Australian Agriculture," Economics Discussion / Working Papers 00-15, The University of Western Australia, Department of Economics.
    9. Giannis Karagiannis & George Mergos, 2000. "Total Factor Productivity Growth and Technical Change in a Profit Function Framework," Journal of Productivity Analysis, Springer, vol. 14(1), pages 31-51, July.
    10. Cox, Thomas L. & Mullen, John D. & Hu, Wensheng, 1997. "Nonparametric measures of the impact of public research expenditures on Australian broadacre agriculture," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 41(3), pages 1-28.
    11. THOMAS COX & John Mullen & Wensheng Hu, 1996. "Nonparametric Measures of the Impacts of Public Research Expenditures on Australian Broadacre Agriculture: Preliminary Results," Wisconsin-Madison Agricultural and Applied Economics Staff Papers 399, Wisconsin-Madison Agricultural and Applied Economics Department.
    12. Mullen, John D. & Cox, Thomas L., 1996. "Measuring Productivity Growth In Australian Broadacre Agriculture," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 40(3), pages 1-22, December.
    13. David Lambert, 1998. "Productivity Measurement from a Reference Technology: A Distance Function Approach," Journal of Productivity Analysis, Springer, vol. 10(3), pages 289-304, November.
    14. Thomas COX & John MULLEN & Wensheng HU, 1996. "Nonparametric Measures Of The Impacts Of Public Research Expenditures On Australian Broadacre Agriculture: Preliminary Results," Staff Papers 399, University of Wisconsin Madison, AAE.
    15. S. Ghobadi & G. R. Jahanshahloo & F. Hosseinzadeh Lotfi & M. Rostamy-Malkhalifeh, 2018. "Efficiency Measure Under Inter-Temporal Dependence," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 657-675, March.
    16. Rolf Färe & Xinju He & Sungko Li & Valentin Zelenyuk, 2019. "A Unifying Framework for Farrell Profit Efficiency Measurement," Operations Research, INFORMS, vol. 67(1), pages 183-197, January.
    17. Chalfant, James A. & Eshel, Dafna M. Disegni, 2001. "A Nonparametric Test Of Advertising'S Effectiveness," 2001 Annual meeting, August 5-8, Chicago, IL 20529, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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