Solomon Asfaw

Bio: Solomon Asfaw is an academic researcher from Food and Agriculture Organization. The author has contributed to research in topics: Food security & Productivity. The author has an hindex of 26, co-authored 63 publications receiving 2680 citations. Previous affiliations of Solomon Asfaw include United Nations & CGIAR.

Agricultural Technology Adoption, Seed Access Constraints and Commercialization in Ethiopia

Abstract: This article examines the driving forces behind farmers’ decisions to adopt agricultural technologies and the causal impact of adoption on farmers’ integration into output market using data obtained from a random cross-section sample of 700 farmers in Ethiopia. We estimate a Double-Hurdle model to analyze the determinants of the intensity of technology adoption conditional on overcoming seed access constraints. We estimate the impact of technology adoption on farmers’ integration into output market by utilizing treatment effect model, regression based on propensity score as well as matching techniques to account for heterogeneity in the adoption decision, and for unobservable characteristics of farmers and their farm. Results show that knowledge of existing varieties, perception about the attributes of improved varieties, household wealth (livestock and land) and availability of active labor force are major determinants for adoption of improved technologies. Our results suggest that the adoption of improved agricultural technologies has a significant positive impact on farmers’ integration into output market and the findings are consistent across the three models suggesting the robustness of the results. This confirms the potential direct role of technology adoption on market participation among rural households, as higher productivity from improved technology translates into higher output market integration.

Climate Smart Agriculture? Assessing the Adaptation Implications in Zambia

Abstract: We examine a set of potentially climate smart agricultural practices, including reduced tillage, crop rotation and legume intercropping, combined with the use of improved seeds and inorganic fertiliser, for their effects on maize yields in Zambia. We use panel data from the Rural Incomes and Livelihoods Surveys merged with a novel set of climatic variables based on geo-referenced historical rainfall and temperature data to explore the changing effects of these practices with climatic conditions. We estimate the impacts on maize yields, and also on the exhibition of very low yields and yield shortfalls from average levels, as indicators of resilience, while controlling for household characteristics. We find that minimum soil disturbance and crop rotation have no significant impact on these yield outcomes, but that legume intercropping significantly increases yields and reduces the probability of low yields even under critical weather stress during the growing season. We also find that the average positive impacts of modern input use (seeds and fertilisers) are significantly conditioned by climatic variables. Timely access to fertiliser emerges as one of the most robust determinants of yields and their resilience. These results have policy implications for targeted interventions to improve the productivity and the resilience of smallholder agriculture in Zambia in the face of climate change.

Mitigation and Adaptation Strategies for Global Change

Abstract: ▶ Addresses a wide range of timely environment, economic and energy topics ▶ A forum to review, analyze and stimulate the development, testing and implementation of mitigation and adaptation strategies at regional, national and global scales ▶ Contributes to real-time policy analysis and development as national and international policies and agreements are discussed and promulgated ▶ 94% of authors who answered a survey reported that they would definitely publish or probably publish in the journal again

Applied Linear Regression Models

Abstract: (1991). Applied Linear Regression Models. Journal of Quality Technology: Vol. 23, No. 1, pp. 76-77.