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Technical inefficiency of commercial maize producers in South Africa: A stochastic frontier production function approach

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  • von Bach, Helmke J. Sartorius
  • Townsend, Rob F.
  • van Zyl, Johan

Abstract

A stochastic frontier production function is defined for panel data on maize producing regions of South Africa. Technical inefficiency effects are assumed to be a function of climatic conditions, time and the terms of trade facing maize producers. The model is derived using nine years of data for the six major maize production regions of South Africa. The results demonstrate how maize farmers have increased their efficiency in the face of a cost-squeeze. The increased efficiency seems to be driven by lower levels of intermediate input use when facing higher costs and uncertain weather conditions.

Suggested Citation

  • von Bach, Helmke J. Sartorius & Townsend, Rob F. & van Zyl, Johan, 1998. "Technical inefficiency of commercial maize producers in South Africa: A stochastic frontier production function approach," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 37(2), pages 1-9, June.
    • Handle: RePEc:ags:agreko:54787
    DOI: 10.22004/ag.econ.54787
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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. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    3. 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.
    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.
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