Measuring and Explaining Technical Efficiency of Dairy Farms: A Case Study of Smallholder Farms in East Africa

This paper measures and explains technical efficiency of 371 dairy farms located in seventeen districts in East African Countries. Four output and nine input types were used to calculate the efficiency scores for each farm. A two-stage analysis was conducted to measure and explain the efficiency scores. First, the efficiency scores were measured by using a data envelopment analysis (DEA) approach which was implemented with a linear programming method. About 18% of the farms were fully productive, each with efficiency scores of unity, which meant this group is currently operating on the production possibility frontier. On the other hand, about 32% of the farms have efficiency scores below 0.25, which means about a third of the dairy farms would need to expand dairy production by at least 75% from the current level without any increase in the level of inputs. Second, a fractional regression method was used to explain the efficiency scores by relating then to a range of explanatory variables. The findings indicate that technology adoption factors such as the existence of improved breeds; feed and fodder innovations (e.g. growing legumes) have positive and statistically significant effects on the level of efficiency. Similarly, zero-grazing seem have positive and highly significant effects. As far as marketing variables are concerned, interestingly selling milk to individual consumers or organizations seems to contribute to dairy efficiency positively and significantly than other marketing outlets such as traders of chilling plants. Membership of dairy cooperative has a positive effect but this is not statistically significant.

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Replaced with revised version of paper 11/18/10.

 Record created 2017-04-01, last modified 2018-01-22

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