This paper aims to analyze the impact of improved maize adoption on farmers’ welfare in Benin, using a random sample of 356 maize farmers. We provide a rigorous estimation by addressing selection bias and endogeneity issues. First, we applied a double-hurdle model to identify factors that inform farmers’ decision to adopt improved maize. Second, we used the instrumental variable model to assess the impact of improved maize on farmers’ income, poverty status, and poverty gap. For this, we used the predicted area under improved maize from the double-hurdle model as an instrument for the observed area under improved maize. We found that farm size, extension services, training on improved seed, and farmers’ location are key variables that affect both farmers’ decision and the amount of land under improved maize. We also found evidence that adoption of improved maize is positively associated with yield, income, and poverty reduction. Finally, we found no heterogeneous impacts of improved maize among poor and non-poor farmers. Adoption of improved maize favors small landholding farmers but did not have a significant impact on income for those who own large farms size. Overall, our results suggest that improved maize variety is important for rural development.

Rice plays an important role in achieving food security in Benin but its production remains low and needs to be optimized. This study estimates technical and allocative efficiencies as well as the sources of inefficiency among rice producers in Benin. The data used cover 210 rice producers, proportionally distributed in the Departments of Mono and Couffo. This farm-level data were collected under the project “Facilité d’Appui aux Filières Agricole du Mono et du Couffo (FAFA-MC).” We employed a stochastic frontier approach to analyze technical efficiency and the marginal value product approach for allocative efficiency analysis. Furthermore, a Chow test was performed to test for difference in determinants of efficiency between the two departments. We found that the average technical efficiency score of rice producers is 78%. The sources of technical inefficiency were age, gender, education level and access to credit. The results also revealed allocative inefficiency in rice production. Labour was overused while other inputs such as seeds, herbicide, and fertilizer were underutilized. Allocation efficiency was influenced by age, gender, area planted, type of culture, and access to credit. Finally, we found difference in determinants of efficiency between the departments of Mono and Couffo. Our results imply that there are opportunities to increase rice production in the Departments of Mono and Couffo. Rice producers in these departments therefore would benefit by adopting better farming practices such as the use of fertilizers, agrochemicals, and irrigation facilities.