Governments and development agencies increasingly promote agro-clusters as a pathway to improving smallholder incomes and ensuring inclusive rural development through mitigating production and market risks. However, there is very limited empirical evidence to support this promise. We use a large farm household survey of about 4000 smallholder farmers in Ethiopia growing cereals like teff, maize, wheat, maltbarley and sesame to examine the relationship between agro-clusters and smallholder welfare and poverty. Using instrumental variable estimators, we establish a positive association between agro-clusters, household income and per capita income. Agro-clusters are also shown to reduce poverty and poverty gaps. Our results are robust over different agro-cluster proxies and alternative estimators, such as the augmented inverse probability weighting estimator. We also show that our findings are unlikely to be driven by omitted variable bias. Moving beyond average effects and in the interest of understanding heterogeneous effects, we use quantile regressions at different income levels. We find that agroclusters are associated with welfare gains for all households. However, the most significant gains are observed for the wealthier households. Despite this regressive association, our findings suggest that agro-clusters may be useful in making farming more profitable with significant welfare implications.

Cluster farming is increasingly recognized as a viable means of improving smallholder economic integration and commercialization in many developing countries. However, little is known about its impact on smallholder welfare and livelihoods. We examine the relationship between cluster farming and smallholder commercialization using a large‐scale survey of 3969 farm households in Ethiopia cultivating high‐acreage crops such as teff, wheat, maize, barley, and sesame. Using switching regressions and instrumental variable estimators, we show that cluster farming is associated with commercialization measured as commercialization index, market surplus value, and market price. To further deal with endogeneity concerns, we also employ some pseudo‐panel models where we observe similar insights. Beyond this, we account for heterogeneities by disaggregating households based on farm scales and crops cultivated. Our findings show that cluster farming is positively associated with commercialization for all farms and crop types despite this disaggregation. However, the related gains are higher among medium and large farms and vary per crop type. These findings imply that cluster farming is crucial in improving smallholder commercialization and may be a critical entry and leveraging point for policy. We thus lend support to initiatives and plans that seek to upscale cluster farming as they can potentially improve smallholder commercialization with ensuing impacts on rural livelihoods and welfare.