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Economic sustainability is particularly important in agriculture. It is related to the basic economic goal of farmers and the reason for their economic activities. Household-level adaptation and mitigation measures reflect the relative importance of economic goals for sustainability. Researchers collected data via a questionnaire designed to include household demographics, farm-specific variables, inputs, and outputs. The empirical model uses stochastic frontier and technical inefficiency models to analyze economic sustainability. Bered and Teleta were the two most economically sustainable and unsustainable regions. Differences in levels of economic sustainability have been attributed to characteristics that are expected to vary from household to household and from region to region. Output-oriented and input-oriented measures of inefficiency loss show that agriculture can be more economically sustainable as long as it is less efficient. Farmers could expand production with existing inputs, or they could reduce their inputs without lowering production levels. In addition, the return to scale was compared with the growth potential in each region. The political decision makers, therefore, seem to emphasize efforts to improve efficiency instead of investing in new technologies and inputs for the greater economic sustainability of the Koga Irrigation and Watershed Project.

Climate change and variability adversely affect smallholder farmers in developing countries, including Ethiopia. In response, farmers are adopting various adaptation strategies. However, there is a paucity of studies examining whether or not these responses benefit farmers in increasing crop productivity. Cognizant of this fact and its policy importance, this study empirically analyzes the impact of adaptation strategies on crop productivity in northwest Ethiopia. We collected data through household survey questionnaire, focus group discussion and key informant interview. We also analyzed time-series climate data to see how crop yield responds to climate variability. The empirical model employs the endogenous switching regression. Climate information and distance to market are validated as instrumental variables. The model revealed that farmers who adopted adaptation strategies would have gained lower yield if they had not adopted them; and those who did not adopt a strategy would have gained higher yield than if they had. Improved seed, contact with development agents (DAs), urea, compost and rainfall are significantly associated with the likelihood of increasing yield. The results also show systematic difference where age is inversely related with adapters and vice versa for non-adapters. Hence, adaptation interventions should consider these heterogeneities.