Abstract:
Agriculture is the backbone of the Ethiopian economy because it constitutes almost half of the GDP and
more than 85 % of the population still depends on it for their livelihood. As a result, the government has
given attention to the development of agriculture. The key challenge here is how to increase the
productivity of smallholder farmers so that they would increasingly benefit from the small plot of land,
and surplus labor could increasingly move to industrial sector. Agricultural output can be increased
either through introduction of modern technologies or by improving the efficiency of inputs such as labor
and management given the existing level of technology. The main inspiration of efficiency and
productivity studies are the need to investigate and understand the forces that drive finger millet technical
efficiency. Thus, this study was aimed to measure the level of technical efficiency and identify the factors
that influence the efficiency levels of finger millet in Guangua district during the production year of
2016/17(2009). A three stage sampling technique was employed to select 134 finger millet growing
sample households. Primary and secondary data was collected through interview schedule from the
sampled households and reviewing secondary sources, respectively descriptive statistics, inferential
statistics and stochastic production functions were employed to analyze the collected data. The Stochastic
Production Frontier (SPF) result revealed that plot size, labor and DAP were found to be significantly
influencing finger millet production at 1 %, 5 % and 10 % significance level, respectively. The coefficient
of the Cobb-Douglas production function interpreted as elasticity and summing the individual elasticity,
yields a scale elasticity of 0.806 this indicated that farmers’ scale of production belongs to decreasing
returns to scale. The result of the study further showed that there was difference in technical efficiency
among finger millet producers of the area. The estimated gamma parameters (discrepancy ratio γ), which
measures the relative deviation of output from the frontier level due to inefficiency, was about 50%. This
implies that about 50% of the total variation in finger millet output was due to technical inefficiency
effects. The estimated mean level of technical efficiency of finger millet producers was about 73%. Based
on the results, it was concluded that there existed room for increasing finger millet output by 27%
through efficient use of existing resources and technology. The study found that family size, credit access,
education and age of household head contributed significantly and positively to TE, while off-farm
activity and slope affected negatively
