This study analyzes the impact of beans produced under joint multiple agricultural technologies (Improved beans variety, soil carbon management, integrated pest control, and use of compost manure) on nutrition outcome of stunting, underweight, and wasting in Kenya, Uganda, and Tanzania. Adoption of technologies in East Africa has been in isolation only focusing on single technologies. However, farmers typically adopt joint multiple agricultural technologies as complements or substitutes thus technologies to be adopted dependent on early technology choices. The objective of the study was to analyze the impact of the nutrition outcome variables in terms of stunting, wasting, and underweight for the best joint multiple agricultural technology combinations as a set of explanatory variables (z). This study adopts the multinomial endogenous switching regression model to correct for the selection bias and endogeneity. Results indicate that joint multiple agricultural technologies had a significant impact on the overall nutrition outcome in East Africa households. It is concluded that households in East Africa rarely use a single agricultural technology but rather a combination of different joint technologies in order to improve their nutrition outcome. The findings recommend that households should adopt joint multiple agricultural technologies rather than focusing on single technologies.

This paper analyses factors that influence the adoption of multiple agricultural technology. That is: improved beans variety, biofortified maize variety, grafted fruit trees, and garden vegetable techniques in East Africa. The endogenous switching regression (ESR) framework was modeled where the farmer's choice of alternative technologies was estimated using a multinomial logit selection (MNLS) model accounting for unobserved heterogeneity. There were four major joint multiple technologies that were adopted by households in East Africa for the production of the crop that are; improved beans variety, grafted fruit trees, biofortified maize variety, and use of garden vegetables techniques. The results show that the only factor that affects the probability of adoption of the four joint multiple agricultural technology combinations apart from education level was the regional diffusion of technology in comparison to base category. A household located in the East Africa region increases the chances of adopting the four joint technology innovation by TC1 (21%), TC2 (31%), TC3 (30%), and TC4 (23%). The factors that were found to be positive and significantly influenced the adoption of a combination of three joint technologies were the education level of the household head, the general participation in community meetings, and barazas and diseases that cause problems. Given region there may be a variety of economic and political factors with different relevant agronomic characteristics that might be specific in adopting technologies. The results from the study generally conclude that theirs a potential subsistence-oriented factors that influence the adoption of multiple agricultural technologies through the link of the household's own production and, therefore recommended that more households be encouraged and influenced to embrace this factors.