This study provides estimates of smallholder household＇s production efficiency and its determinants, and separately analyses the technical efficiency of dairy technology adopting and non-adopting farmers using data f...This study provides estimates of smallholder household＇s production efficiency and its determinants, and separately analyses the technical efficiency of dairy technology adopting and non-adopting farmers using data from Ethiopia. Cobb-Douglas stochastic frontier production function was modeled in the context of local level agricultural innovation systems framework and estimated using 2011 milk production data on 304 dairy farmers. Results show that the mean level of technical efficiency among the sampled farmers was about 26%. This result suggests that there is room for significant increases of production through reallocation of existing resources. Despite significant variation among farmers, these results also indicate only 19% of farmers have mean efficiency scores （_〉 50%）, implying a need to focus on creating innovation capacity that pushes the production frontier outward in the dairy production system. It is also revealed that individual farm households＇ efficiency varied widely across dairy technology adoption status, gender and districts. The significant gamma （g） statistic, of 0.9985 in the analysis indicates that about 99.85% variation in the output of milk production would be attributed to technical inefficiency effects （those under farmer＇s control） while only 0.0015% would be due to random effects, i.e., beyond the farmers control and hence calling for a focus on efficiency enhancing investments. Education, farm size, extension visit and off-farm income opportunity were found to be efficiency enhancing. The study recommends that different components of an agricultural innovation system have to interact to improve the innovation capacity of different actors and thereby improve the estimated technical inefficiencies.展开更多
文摘This study provides estimates of smallholder household＇s production efficiency and its determinants, and separately analyses the technical efficiency of dairy technology adopting and non-adopting farmers using data from Ethiopia. Cobb-Douglas stochastic frontier production function was modeled in the context of local level agricultural innovation systems framework and estimated using 2011 milk production data on 304 dairy farmers. Results show that the mean level of technical efficiency among the sampled farmers was about 26%. This result suggests that there is room for significant increases of production through reallocation of existing resources. Despite significant variation among farmers, these results also indicate only 19% of farmers have mean efficiency scores （_〉 50%）, implying a need to focus on creating innovation capacity that pushes the production frontier outward in the dairy production system. It is also revealed that individual farm households＇ efficiency varied widely across dairy technology adoption status, gender and districts. The significant gamma （g） statistic, of 0.9985 in the analysis indicates that about 99.85% variation in the output of milk production would be attributed to technical inefficiency effects （those under farmer＇s control） while only 0.0015% would be due to random effects, i.e., beyond the farmers control and hence calling for a focus on efficiency enhancing investments. Education, farm size, extension visit and off-farm income opportunity were found to be efficiency enhancing. The study recommends that different components of an agricultural innovation system have to interact to improve the innovation capacity of different actors and thereby improve the estimated technical inefficiencies.
