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A Stochastic Frontier Production Function Approach to Technical Efficiency among Cassava Farmers in Rivers State, Nigeria

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  • Anyanwu, S. O.
  • Kalio, A. E.
  • Olatunji, S. O.
  • Akonye, L.

Abstract

In this study the stochastic frontier production function approach was employed in the empirical analysis of technical efficiency among smallholder cassava farmers in Rivers State, Nigeria. Multistage random sampling technique was used in the data generation exercise. A total of 94 cassava farmers were randomly selected from ten out of the fifteen Upland Local Government Areas of Rivers State, Nigeria, for interview using structured questionnaire. The results showed that there was a significant positive and elastic relationship between output of cassava and farm sizes, family labour, cassava stem cuttings, and depreciated values of implements among cassava farmers in Rivers State. Production elasticity estimates showed that the farmers were experiencing increasing returns to scale (1.27). The significant determinants of technical inefficiency among these farmers include Age, household size and farming experience. The mean technical efficiency of the farms was 70%. This shows that there is still room for the farmers to increase their technical efficiency as they grow older in age. Furthermore, incentives on cassava farming such as subsidized inputs from the governments should be skewed in favor of the older and more experienced farmers.

Suggested Citation

  • Anyanwu, S. O. & Kalio, A. E. & Olatunji, S. O. & Akonye, L., 2014. "A Stochastic Frontier Production Function Approach to Technical Efficiency among Cassava Farmers in Rivers State, Nigeria," Asian Journal of Agricultural Extension, Economics & Sociology, Asian Journal of Agricultural Extension, Economics & Sociology, vol. 3(6).
    • Handle: RePEc:ags:ajaees:357440
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    References listed on IDEAS

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    1. 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.
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