This study was undertaken with the objective of analyzing the economic efficiency of common bean producers in Burji district of Southern Nation National Regional State of Ethiopia. The study area was selected purposively based on the level of common bean production in the region. The study employed FRONTIER 4.1 software and both primary and secondary data were used. Primary data were collected through household survey from a sample of 313 households using structured questionnaire. Secondary data were collected from relevant sources to supplement the primary data. Data analysis was carried out using descriptive statistics and econometric techniques.
According to findings, farm input variables such as labor force, oxen, DAP, seed, land and chemical application were influenced by common bean output by different percent of significant level. From these labor, land and DAP are significant at 1 percent probability level. And the rest oxen, seed and chemical are significant at 5 percent probability level. A contribution of labor and oxen was positive and indicating that motivate and mobilize the farm labor and oxen power in agricultural activities would be likely to lead to higher common bean output. DAP and chemical also appeared to be the major underling determinants of common bean output. However, farmer's uses of these inputs have challenged by shortage of supply and high prices.
The study also indicated that 63.7%, 77.2% and 50.0% were the mean levels of TE, AE and EE, respectively. This in turn implies that farmers can increase their common bean production on average by 36.3% when they were technically efficient. Similarly, they can reduce their cost by 50.0%without any change from optimum level of output. This implies that, using the subsisting resource base, improved efficiency can still be achieved and there was a great potential for increasing the gross output and profit with the existing level of resource base.
In the second step of the analysis, relationships between TE, AE, and EE, and various variables that expected to have effect on farm efficiency were examined. This was relied on two limit Tobit regression techniques, where TE, AE, and EE were expressed as functions of 13 independent variables. Among them all were found to be statistically significant except land preparation and access to credit to affect the level of technical efficiency. The model showed that family size, education, land size, frequency of extension contact, training, credit access, TLU, sex, crop pest and off farm income were important factors that affect economic efficiency of farmers in the study area. The results also revealed that educational level of the household, training, credit access, TLU, sex, crop pest and off farm income significantly influence the allocative efficiency of smallholders in the study area.
Thus, the results of the study give information to policy makers and extension workers on how to better aim efforts to improve farm efficiency as the level and specific determinant for specific efficiency types are identified. This could contribute to compensation of high production cost, hence improve farm revenue, welfare and generally help agricultural as well as economic development. These findings stresses the need for appropriate policy formulation and implementation to enable farmers reduce their inefficiency in production as this is expected to have multiplier effects ranging from farm productivity growth to economic growth and poverty reduction at macro level.