Measuring the poverty reduction effects of adopting agricultural technologies in rural Ethiopia: findings from an endogenous switching regression approach.

The purpose of this study is to understand how the adoption of different agricultural technologies can reduce poverty in rural regions of Ethiopia. To attain this objective, this paper uses a comprehensive socio-economic survey of Ethiopia, which allows us to securitize the household level information. The paper uses a multinomial endogenous switching regression model to estimate the impact of alternative technologies adoption on poverty reduction on a sample of 2316 farm households, and a multinomial logit model to estimate the determinants of alternative agricultural technologies adoption. The results showed that the decision to adopt alternative agricultural technologies depends on several variables such as education, regional heterogeneity, remittance income, extension visit, credit access, off-farm activity, soil quality, farm size, tropical livestock unit, distance, plot's potential wetness, and ownership certification. The impact results of the study show that household consumption increases when households adopt alternative agricultural technologies, thereby reducing their poverty. Furthermore, adoption of a package of technologies can result in higher food and total consumption per adult than single technology adoption. The paper recommends strategies for further disseminating and scaling up these technologies to help reduce poverty in Ethiopia.