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Smallholder Technical Efficiency With Stochastic Exogenous Production Conditions

Author

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  • Sherlund, Shane M.
  • Barrett, Christopher B.
  • Adesina, Akinwumi A.

Abstract

There is a large literature on the estimation of frontier production functions, much of it applied to low-income agriculture. However, much of this literature largely ignores nature's role in agricultural production. Because exogenous, natural production conditions (e.g., rainfall, soil quality, pest infestation, plant disease, weed growth) are rarely uniform or symmetrically distributed within a population or a sample thereof, this omission generally leads to downward bias in producers' estimated efficiency and to biased estimates of both the parameters of the production frontier and the correlates of true technical inefficiency. Using panel data from 464 traditional rice plots in Cote d'Ivoire, we show that controlling for stochastic, exogenous, natural production conditions in estimating the production frontier significantly increases smallholder rice farmers' estimated efficiency, whether estimated using parametric, stochastic or nonparametric, nonstochastic methods. The resulting frontier parameter estimates are also more consistent with theoretical predictions than are those of a frontier estimated without controlling for exogenous production conditions. Conventional estimates of technical efficiency may then mislead policymakers' perceptions of overall efficiency levels and of the sources of such inefficiency.

Suggested Citation

  • Sherlund, Shane M. & Barrett, Christopher B. & Adesina, Akinwumi A., 1998. "Smallholder Technical Efficiency With Stochastic Exogenous Production Conditions," Working Papers 14760, Cornell University, Department of Applied Economics and Management.
  • Handle: RePEc:ags:cudawp:14760
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    File URL: http://purl.umn.edu/14760
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    References listed on IDEAS

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    1. 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.
    2. Pollak, Robert A. & Wales, Terence J., 1991. "The likelihood dominance criterion : A new approach to model selection," Journal of Econometrics, Elsevier, pages 227-242.
    3. Kumbhakar, Subal C., 1987. "The specification of technical and allocative inefficiency in stochastic production and profit frontiers," Journal of Econometrics, Elsevier, vol. 34(3), pages 335-348, March.
    4. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    5. Christpher B. Barrett, 1997. "How credible are estimates of peasant allocative scale, or scope efficiency? A commentary," Journal of International Development, John Wiley & Sons, Ltd., vol. 9(2), pages 221-229.
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    Cited by:

    1. Kelemework, D., 2008. "A comparative analysis of the technical efficiency of irrigated and rainfed agriculture: a case of Awash and Rift valleys of Ethiopia," Conference Papers h044137, International Water Management Institute.
    2. Yongil Jeon & Ishak Haji Omar & K. Kuperan & Dale Squires & Indah Susilowati, 2006. "Developing country fisheries and technical efficiency: the Java Sea purse seine fishery," Applied Economics, Taylor & Francis Journals, vol. 38(13), pages 1541-1552.

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    Keywords

    Production Economics;

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