IMPACT OF WHEAT CLUSTER FARMING ON PRODUCTIVITY, TECHNICAL EFFICIENCY, AND ASSET BUILDING OF SMALLHOLDER FARMERS IN ARSI ZONE, OROMIA REGION OF ETHIOPIA

Abstract

Agriculture is the main focus of Ethiopia's economic development. Wheat is one of the major cereal crops produced by smallholder farmers in Ethiopia. Wheat demand is rising quickly in Ethiopia despite efforts to improve wheat production. Recently, to curb this problem, the government of Ethiopia has implemented a cluster farming system for high-potential agricultural commodities like wheat as a means of poverty reduction and smallholders’ income maximization. In light of the problems and research gaps identified, this study seeks to address the impact of wheat cluster farming practices on wheat productivity, technical efficiency, and asset building among smallholder wheat producers in the Arsi zone, Oromia Region of Ethiopia. Data were collected from a total of 383 sample wheat producer households that were randomly selected through a multi-stage sampling technique. Both descriptive statistics and econometric techniques were used to meet the objectives of the study. The factors affecting wheat cluster farming participation were identified using the logit model. The result reveals that education level, credit access, extension contacts, off/non-farm income, and mechanization access were positively associated with wheat cluster farming adoption, while the age of the household head and wheat farming experience were negatively associated with wheat cluster farming adoption. The Endogenous Switching Regression model result indicates that mechanization use, labour, extension contact, credit use, off/non-farm income, improved seed use, urea, NPS and row planting positively and significantly affect wheat productivity of cluster farming participants, while labour, off/non-farm income, NPS and row planting positively and significantly affect wheat productivity of non-participants. Moreover, a one-step stochastic frontier production model was used to identify determinants of technical efficiency. The result reveals that extension contact, household head education level, off/non farm income, and credit accesses were factors that positively and significantly influenced the TE of wheat producers. However, wheat production experience negatively and significantly affected the TE of wheat producers. The ESR model's findings showed that smallholder wheat xviii productivity was significantly impacted by cluster farming participation. As a result, cluster participants increased their wheat production by about 13 qt, which is equivalent to a 42% rise in productivity, which was also confirmed by the Propensity Score Matching result. The ATT result indicates that the average wheat TE gain due to participation in cluster farming ranges from 14 to 17.5%. It shows the production of wheat under cluster farming has a promising average treatment effect. Wheat cluster farming participation has increased smallholders' asset building ranges from ETB 8374.29 (PSM) to ETB 11664.30 (ESR) for wheat cluster participant households as compared to non-participant wheat producer households. The findings emanating from this study suggest that improving the supply of agricultural input packages and providing continuous training on input utilization and wheat farm management may improve wheat production and productivity through better implementation of wheat cluster farming in Ethiopia, which in turn improves wheat producer’s asset building. In addition, policymakers and stakeholders should develop strategies that help promote and scale up wheat cluster farming implementation