Implications of the Presence of Large Scale Commercial Farmers on Small Scale Farming in Nigeria. The Case of Zimbabwean Farmers in Kwara State
This paper contributes to the debate on the impact `of large scale commercial farming on small scale farmers in developing countries. The study examined the technology spill-over effects on production efficiency of the small scale farming households prevalent in Nigeria. The Agricultural Development Project zone where the white farmers settled in Kwara State in 2007 was used as a case study. The characteristics of the white farmers were described using data collected from the thirteen foreign farmers. Primary data were collected from the local farmers on their situation before and after the arrival of the white farmers. The latent class stochastic production frontier was the major analytical tool used to classify the local farmers to different levels of technology adoption. There are evidences that the local production efficiency increased since the white farmers settled in the area. However, there are signs of dissatisfaction sporadically displayed by the local farmers. For sustainability of the performance of these local farmers, there is a need for policy options that will ensure peaceful co-existence between the local farmers and the foreign farmers.
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Volume (Year): 5 (2013)
Issue (Month): 4 (December)
Pages: 67-73
| Handle: | RePEc:khe:journl:v:5:y:2013:i:4:p:67-73 |
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References listed on IDEAS
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- Luis Orea & Subal C. Kumbhakar, 2004. "Efficiency measurement using a latent class stochastic frontier model," Empirical Economics, Springer, vol. 29(1), pages 169-183, January.
- 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 435-44, June.
- 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.
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