Estimating Technical Efficiency and Yield Losses Among Smallholder Coffee Farmers in Uganda: A Stochastic Frontier Analysis

This study examines technical efficiency (TE) and identifies determinants of inefficiency among smallholder Robusta and Arabica coffee farmers in Uganda while quantifying yield losses associated with inefficiency. The study utilized pooled cross-sectional data from 1,283 smallholder coffee farmers drawn from three survey waves (2015/2016, 2018/2019 and 2019/2020) of the Uganda National Panel Survey (UNPS). A one-step Stochastic Frontier Analysis (SFA) with a translog production frontier is applied to jointly estimate technical efficiency and its determinants. The approach further quantifies yield losses attributable to inefficiency, disaggregated by coffee farmer type. Mean technical efficiency is 76.5 percent for Robusta and 73.1 percent for Arabica, implying potential output gains of 23.5 percent and 26.9 percent, respectively, using existing inputs. Efficiency variations are associated with group membership, off-farm income, cropping systems, soil type, and plot proximity, with effects differing by coffee type. Yield losses due to inefficiency averaged 113.0 kilograms for Robusta and 138.6 kilograms for Arabica per farmer. Policies should promote location-specific agronomic practices like intercropping and soil fertility management tailored to coffee type and ecological conditions. Capacity-building initiatives including input use, pest and disease management, and sustainable farming can reinforce efficiency gains. Supporting farmer groups and cooperatives could enhance knowledge sharing, coordinated input use, and market access, thereby reducing transaction costs and improving resource-use efficiency. The study employs a one-step SFA to estimate technical efficiency separately for Robusta and Arabica farmers, incorporating farm-level, institutional, and environmental factors to examine efficiency differentials across coffee types in Uganda.