Climate-Smart Agriculture (CSA) and Crops Productivity in Tanzania

Abstract

Climate change hazards and impacts are exacerbating. They threaten crop productivity, farmers' resilience, and GHG emission mitigation. Understanding CSA and applying it in agriculture is crucial. However, the adaptation measures by smallholder farmers are still contextual, particularly whether small scale farmers adopting CSA boosts crop productivity and income is scanty. The study examines the drivers of CSA adoption and the impacts on farm performance. We used nationally representative data from a sample of 1862 farmers cultivating less than 2 hectares. The endogenous switching regression (ESR) was employed to address selection and endogeneity issues of CSA adoption. Propensity score matching (PSM) was adopted for comparisons purpose. The results in both models are consistent that CSA adoption augments productivity and income. Interestingly, if non-adopters had adopted, would have remarkably gained. Results imply that plausible programs, promotions, campaigns, or policy support measures to scale up CSA adoption can have significant contributions to food security and poverty reduction, build farmers' resilience, and mitigation of GHG in agricultural sector.

Keywords: Tanzania, climate change, climate-smart agriculture, resilience, income, crop productivity, endogenous switching regression model, propensity score matching, farmers, impact