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A Stochastic Frontier Production Function with Flexible Risk Properties

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  • Battese, George E.
  • Rambaldi, A. N.
  • Wan, G. H.

Abstract

This paper considers a stochastic frontier production function which has additive, heteroscedastic error structure. The model allows for negative or positive marginal production risks of inputs, as originally proposed by Just and Pope (1978). The technical efficiencies of individual firms in the sample are a function of the levels of the input variables in the stochastic frontier, in addition to the technical inefficiency effects. These are two features of the model which are not exhibited by the commonly used stochastic frontiers with multiplicative error structures. An empirical application is presented using cross-sectional data on Ethiopian peasant farmers. The null hypothesis of no technical inefficiencies of production among these farmers is accepted. Further, the flexible risk models do not fit the data on peasant farmers as well as the traditional stochastic frontier model with multiplicative error structure. Copyright Kluwer Academic Publishers 1997
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Suggested Citation

  • Battese, George E. & Rambaldi, A. N. & Wan, G. H., 1995. "A Stochastic Frontier Production Function with Flexible Risk Properties," 1995 Conference (39th), February 14-16, 1995, Perth, Australia 148840, Australian Agricultural and Resource Economics Society.
    • Handle: RePEc:ags:aare95:148840
    DOI: 10.22004/ag.econ.148840
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    References listed on IDEAS

    as
    1. John M. Antle, 1983. "Incorporating Risk in Production Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 65(5), pages 1099-1106.
    2. Gourieroux, Christian & Holly, Alberto & Monfort, Alain, 1982. "Likelihood Ratio Test, Wald Test, and Kuhn-Tucker Test in Linear Models with Inequality Constraints on the Regression Parameters," Econometrica, Econometric Society, vol. 50(1), pages 63-80, January.
    3. Coelli, T. J., 1992. "A computer program for frontier production function estimation : Frontier version 2.0," Economics Letters, Elsevier, vol. 39(1), pages 29-32, May.
    4. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    5. Kumbhakar, Sabul C., 1993. "Production risk, technical efficiency, and panel data," Economics Letters, Elsevier, vol. 41(1), pages 11-16.
    6. Antle, John M., 1983. "Incorporating Risk In Production Analysis," 1983 Annual Meeting, July 31-August 3, West Lafayette, Indiana 279106, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Just, Richard E. & Pope, Rulon D., 1978. "Stochastic specification of production functions and economic implications," Journal of Econometrics, Elsevier, vol. 7(1), pages 67-86, February.
    8. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    9. Asmcrom Kidane & David G. Abler, 1994. "Production technologies in Ethiopian agriculture," Agricultural Economics, International Association of Agricultural Economists, vol. 10(2), pages 179-191, April.
    10. Wan, G.H. & Griffiths, William E. & Anderson, Jock R., 1989. "Estimation of Marginal Risks with Seemingly Unrelated Regression and Panel Data," 1989 Conference (33rd), February 7-9, 1989, Christchurch, New Zealand 144886, Australian Agricultural and Resource Economics Society.
    11. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
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