Uptake of Climate-Smart Agricultural Technologies and Practices: Actual and Potential Adoption Rates in the Climate-Smart Village Site of Mali

Mathieu Ouédraogo, Prosper Houessionon, Robert B. Zougmoré, Samuel Tetteh Partey
2019 Sustainability  
Understanding the level of adoption of Climate-Smart Agriculture (CSA) technologies and practices and its drivers is needed to spur large-scale uptake of CSA in West Africa. This paper used the Average Treatment Effect framework to derive consistent parametric estimators of the potential adoption rates of eight CSA technologies and practices in the Climate-Smart Village (CSV) site of Mali. A total of 300 household heads were randomly selected within the CSV site for data collection. Results
more » ... ection. Results showed significant differences in the observed and potential adoption rates of the CSA technologies and practices (drought tolerant crop varieties, micro-dosing, organic manure, intercropping, contour farming, farmer managed natural regeneration, agroforestry and climate information service). The most adopted technology was the organic manure (89%) while the least adopted was the intercropping (21%). The observed adoption rate varied from 39% to 77% according to the CSA options while the potential adoption rates of the technologies and practices ranged from 55% to 81%. This implies an adoption gap of 2% to 16% due to the incomplete diffusion (lack of awareness) of CSA technologies and practices which must be addressed by carrying out more actions to disseminate these technologies in the CSV. Results showed that education, number of workers in the household, access to subsidies, and training have a positive effect on the adoption of most of the CSA technologies and practices. The adoption of drought tolerant varieties and micro-dosing are positively correlated with access to subsidies and training. The study suggests that efforts should be focused concomitantly on the diffusion of CSA options as well as the lifting of their adoption barriers.
doi:10.3390/su11174710 fatcat:hwfold4pivgnrcuflp3jjji3aq