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The paper employed a Heckman selectivity model to determine factors influencing the adoption of irrigation and its effect on rice yield in Benin. Results from probit estimates indicate that farmer's age, gender, extension services, access to credit, market participation, distance to irrigation scheme, use of tractor and fertilizer are factors affecting the probability of irrigation adoption. Results from Heckman second stage estimates show that the adoption of irrigation contributes significantly to rice yield improvement by 57 per cent. For robustness checks of the estimated effect of adoption of irrigation, the propensity score matching method was used. The results indicate that the percentage increase in rice yield due to irrigation adoption varies between 55 per cent and 60 per cent. This confirms the finding of the Heckman estimates. Other variables explaining rice yield are education, extension services, access to credit, market participation, off farm income, use of tractor, labour, and fertilizer. These results imply that besides the adoption of irrigation the provision of complementary services are needed to achieve the objective of productivity improvement.

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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.

Adoption of agricultural technologies in Benin remains at a very low level. This paper analyzes the factors that determine the adoption of agricultural technologies by rice producers in Benin. It employs a simple probit and Poisson regression models, as well as a multivariate probit model to account for the unobserved interaction between technology adoption decisions. Results reveal that variables such as education, access to extension services, membership of a farmers‐based organization, access to credit, media and use of a mobile phone are important in the process of increasing adoption of agricultural technologies. These variables must be taken into consideration in the elaboration of the agricultural modernization policy.