How can we make the best use of agricultural technology to achieve food security? Is there still a role for older technologies and for traditional approaches? Or embracing industrial production systems should be the way forward? This brief is based on an online discussions held by the Global Forum on Food Security and Nutrition in 2010.
Solomon Asfaw, Bekele Shiferaw, Franklin Simtowe and Messia Hagos 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.
Mulubrhan Amare, Solomon Asfawb, Bekele Shiferaw This article examines the driving forces behind farmers’ decisions to adopt improved pigeonpea and maize and estimates the causal impact of technology adoption on household welfare using data obtained from a random cross-section sample of 613 small-scale farmers in Tanzania. We use seemingly unrelated and recursive bivariate probit regressions to test the endogeneity and joint decision making of pigeonpea–maize production. A double hurdle model is used to analyze the determinants of the intensity of technology adoption conditional on overcoming seed access constraints. To address the impact of adoption on welfare, the article employs both propensity score matching and switching regression techniques. Results from bivariate probit models show that unobservable factors cause both decisions to be correlated but the finding does not support the conjecture that both decisions are made jointly. Overall the analysis of the determinants of adoption identifies inadequate local supply of seed, access to information, human capital, and access to private productive asset as key constraints for pigeonpea technology adoption. The causal impact estimation from both the propensity score matching and switching regression suggests that maize/pigeonpea adoption has a positive and significant impact on income and consumption expenditure among sample households.