Despite the availability of improved maize varieties in Ethiopia, adoption among smallholder farmers remains uneven, contributing to persistent yield gaps. This study investigates the determinants of improved maize variety adoption and its impact on smallholder farm productivity in Gesha Woreda, Southwest Ethiopia. Using cross-sectional household survey data, a binary logit model is employed to identify factors influencing farmers’ adoption decisions. To address potential selection bias arising from observable differences between adopters and non-adopters, Propensity Score Matching (PSM) were applied to estimate the causal effect of adoption on maize productivity. Multiple matching algorithms, including nearest neighbor, radius, and kernel matching, are used to assess the robustness of the estimated treatment effects. Descriptive results indicate significant differences between adopters and non-adopters in age, education, farm size, farming experience, and credit access. Logit model results show that the sex of the household head, education level, farm size, farming experience, access to credit, and distance to markets significantly affect adoption decisions. PSM results revealed that adopters produce significantly higher maize yields than non-adopters, confirming the positive effect of IMV adoption. The results underscore the need for policies that expand farmer access to extension services and rural credit, strengthen dissemination of improved seed technologies, and enhance farmers’ human capital through education and training programs to accelerate adoption and improve smallholder productivity.
Gizaw et al. (Mon,) studied this question.
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