Contribution of Climate-smart Agriculture to Farm Performance, Food and Nutrition Security and Poverty Reduction in Ghana

This study examines the drivers of individual and joint adoption of crop choice and soil and water conservation strategies and how adoption of these strategies impacts on farm performance and exposure to production risks, using a multinomial endogenous switching regression model to account for selectivity bias due to both observable and unobservable factors. The study also examines the determinants of climate-smart practices and how adoption affects food and nutrition security among farm households in Ghana, using an endogenous switching regression approach to account for selectivity bias. It also examines the impact of adoption of sustainable land management practices on consumption and poverty outcomes using multivalued treatment effects and generalized propensity score approaches, while considering adoption intensity within a continuum. Finally, the study assesses the impact of adoption of SLM on farm households’ technical efficiency and environmental inefficiency stochastic production frontier and data envelopment analysis models. The results revealed that farmers’ adoption of crop choice and soil and water conservation leads to higher crop yields and reduction in exposure to production risks, with the largest impact on yields coming from joint adoption, an indication of complementarity effects of crop choices and soil and water conservation strategies. The findings also showed that adoption of climate-smart practices had positive and significant impact on food and nutrition security in terms of household dietary diversity scores, household food insecurity access scores and farm revenues. Moreover, the effect of adoption of SLM on per capita consumption and poverty outcomes is nonlinear and differed among adopters at different intensity levels of adoption. Also, adopters of SLM exhibited higher levels of technical efficiency as compared to non-adopters, but they were also found to be using higher levels of herbicides that might have environmental implications.


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