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Production Analysis: A Non‐Parametric Time Series Application To Us Agriculture

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  • Jean‐Paul Chavas
  • Thomas L. Cox
Abstract
The paper investigates production analysis using non‐parametric methods. When all data are not consistent with profit maximisation, we propose a method relying on the concept of ‘effective inputs and outputs’ to evaluate technology and economic behaviour. The approach is illustrated in a time series application to US agriculture. The results provide empirical measures of productivity growth. They also generate useful information on the ‘bias in technical change’ in US agriculture.

Suggested Citation

  • Jean‐Paul Chavas & Thomas L. Cox, 1997. "Production Analysis: A Non‐Parametric Time Series Application To Us Agriculture," Journal of Agricultural Economics, Wiley Blackwell, vol. 48(1‐3), pages 330-348, January.
    • Handle: RePEc:bla:jageco:v:48:y:1997:i:1-3:p:330-348
    DOI: 10.1111/j.1477-9552.1997.tb01158.x
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    References listed on IDEAS

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    1. Forsund, Finn R. & Lovell, C. A. Knox & Schmidt, Peter, 1980. "A survey of frontier production functions and of their relationship to efficiency measurement," Journal of Econometrics, Elsevier, vol. 13(1), pages 5-25, May.
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    4. Chavas, Jean-Paul & Cox, Thomas L, 1990. "A Non-parametric Analysis of Productivity: The Case of U.S. and Japanese Manufacturing," American Economic Review, American Economic Association, vol. 80(3), pages 450-464, June.
    5. Hanoch, Giora & Rothschild, Michael, 1972. "Testing the Assumptions of Production Theory: A Nonparametric Approach," Journal of Political Economy, University of Chicago Press, vol. 80(2), pages 256-275, March-Apr.
    6. Afriat, Sidney N, 1972. "Efficiency Estimation of Production Function," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 13(3), pages 568-598, October.
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    8. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    9. Cox, Thomas L & Chavas, Jean-Paul, 1990. "A Nonparametric Analysis of Productivity: The Case of U.S. Agriculture," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 17(4), pages 449-464.
    10. V. Eldon Ball, 1985. "Output, Input, and Productivity Measurement in U.S. Agriculture 1948–79," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 67(3), pages 475-486.
    11. Banker, Rajiv D & Maindiratta, Ajay, 1988. "Nonparametric Analysis of Technical and Allocative Efficiencies in Production," Econometrica, Econometric Society, vol. 56(6), pages 1315-1332, November.
    12. Seiford, Lawrence M. & Thrall, Robert M., 1990. "Recent developments in DEA : The mathematical programming approach to frontier analysis," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 7-38.
    13. Varian, Hal R, 1984. "The Nonparametric Approach to Production Analysis," Econometrica, Econometric Society, vol. 52(3), pages 579-597, May.
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    17. Chavas, Jean-Paul & Aliber, Michael, 1993. "An Analysis Of Economic Efficiency In Agriculture: A Nonparametric Approach," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 18(1), pages 1-16, July.
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    Cited by:

    1. Morrison Paul, Catherine J., 2000. "Productivity And Efficiency In The U.S. Food System, Or, Might Cost Factors Support Increasing Mergers And Concentration?," Working Papers 11983, University of California, Davis, Department of Agricultural and Resource Economics.
    2. Hailu, Atakelty & Veeman, Terrence S., 2001. "Alternative methods for environmentally adjusted productivity analysis," Agricultural Economics, Blackwell, vol. 25(2-3), pages 211-218, September.

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