To improve the national average yield of potato in Ethiopia, which is very low as compared to its potential, factors that influence technical efficiency of potato production need to be determined. Therefore, the objective of this study was to investigate the determinants of technical efficiency using a cross-sectional data collected from 368 randomly selected potato producers in Northern Ethiopia using a multi-stage sampling technique. The study employed Cobb–Douglas stochastic frontier model to get farm-level technical efficiency scores. Tobit model and principal component analysis were used to determine the factors that influence technical efficiency of farm households. The results revealed that chemical fertiliser, seed potato, plot size and labour are statistically significant factors that affect potato yield. The average technical efficiency score was estimated to be 75%; and education, experience, off-farm income, household size, membership in a farmers’ association, use of irrigation water, extension contact, use of improved seed, access to product market and weak coordination of stakeholders’ were significant factors influencing technical efficiency. The findings of the study suggest that there is a need for government intervention to create strong market linkage between producers and buyers and to give appropriate training to agricultural extension agents.

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There is an enormous potential for beekeeping practices to generate income, create jobs, and alleviate poverty. However, in Ethiopia, there are many constraints that hinder rural households to expand and adopt beekeeping practices. The objective of this study was to analyze the determinants of beekeeping adoption in Northwest Ethiopia. To achieve the objective, cross-sectional data were collected from 369 rural households and analyzed using a nonlinear econometric (binary logistic regression) model. The maximum likelihood estimation results revealed that sex, marital status, household size, and the educational status of the household head, number of extension visits, membership in a farmers' association, and access to credit were the statistically significant variables determining beekeeping adoption in the study area. The beekeeping constraints that had statistically significant influence on beekeeping adoption were grouped as marketing, natural, and financial. To reap the benefits from the huge potential of honeybee colonies, the government of Ethiopia and other associated actors and stakeholders should work together to solve the constraints faced by rural households in adopting beekeeping practices that could result in improving their livelihoods.