Determinants of common bean productivity and efficiency a case of smallholder farmers in Eastern Uganda

Abstract

Agriculture sustains the livelihoods of about 70.8% of Ugandans, while common bean has emerged to be an important cash crop as well as a staple food for the majority of farmers and consumers. Although Uganda’s bean output has more than doubled, average bean yields in the country have been between 0.6 and 0.8 Mt Ha“, even though yields higher than 1.5 Mt l-la” can be realized with improved varieties. Thus the objective of this study was to detem-tine the factors influencing common bean productivity and efficiency among smallholder farmers in Eastem Uganda. The study was conducted in Busia, Mbale, Budaka and Tororo districts in Eastern Uganda based on a sample of 280 households selected using a multi-stage sampling technique. For the data collection, a personally administered structured questionnaire was used to conduct interviews, with a focus on household heads. ln the analyses, descriptive statistics, a stochastic frontier model and a two-limit Tobit regression model were employed. It was established that bean productivity was positively influenced by plot size, ordinary seeds, certified seeds and planting fertilizers. The mean technical efficiency among bean farms was 48.2%, mean economic efficiency was 59.94% and mean allocative efficiency was 29.37%. Finally, Tobit model estimation revealed that technical efficiency was positively influenced by value of assets at 1% level and extension service and group membership at 5% level; while age and distance to the factor market negatively influenced technical efficiency at 10% and 5% levels respectively. Economic efficiency was positively influenced by value of assets at 1% level and off-farm income and credit at 5% level. However, farmers’ primary occupation negatively influenced economic efficiency at 5% level. Allocative efficiency ‘was positively influenced by value of assets at 1% level and farm size and off-farm income at 10% level; while distance to the factor market negatively influenced allocative efficiency at 5% level. Hence the study recommended on the need for increased provision of extension service and training on correct input application and improved farming technologies to increase bean productivity. lt also suggested on the need for policy to discourage land fragmentation, develop road and market infrastructure in rural areas and provide affordable and easily available credit facilities to improve production efficiency of bean fanns.