Technical Efficiency in Agriculture

Abstract

Resource limitations in the agricultural sector for achieving food production is one of the most critical challenges for planners and policymakers in many countries including Iran. Optimal use of available resources is one of the ways to overcome these limitations. This study aims to investigate the factors affecting technical efficiency of resource use in the agricultural sector. Classic Regression Robust (CLR) and Two Limit Tobit (TLT), M, MM and S regression were used to explore the effects of estimation techniques and study characteristics on Mean Technical Efficiency (MTE) level. The results are based on a total of 55 studies covering the 1994–2015 period. The econometric results indicate that year of publication, agronomic production, the functional form assumed for estimation (such as Stochastic Frontier production Function, Cobb–Douglas and Translog function) have a positive effect on the estimated MTE. On the other hand, livestock production, sample size and some model variables and cross-section have an adverse impact. Farms with livestock production have their MTE lowered by 0.03–0.06 units. Similarly, farms located in cold and humid climate regions had a lower MTE by 0.08–0.12 units. However, studies for the cold and mountainous regions reported higher MTE by 0.03–0.06. According to research results, we suggest that to achieve an overall result, policymakers and researchers can use Meta-regression analysis along with other models.