Does the Adoption of Climate-Smart Agricultural Practices Impact Farmers’ Income? Evidence from Ghana

Abstract

People’s lives, particularly farmers’, have been affected by extreme weather conditions that have reduced the yield of numerous crops due to climate change. Climate-smart agriculture practices can reduce or eliminate greenhouse gas emissions and have the propensity to increase farm income and productivity. Therefore, the purpose of this study is to ascertain whether CSA practices impact farmers’ income. This study includes all cocoa farmers in the selected districts in the Ashanti Region. The population includes those who live in the six cocoa production villages. The multistage sampling procedure was considered based on the dominants of literature. The study used an endogenous switching regression framework to examine the effects of the adoption of climate-smart agricultural practices (CSAPs) on farmers’ income. While estimating treatment effects, telasso uses lasso techniques to select the appropriate variable sets. The results revealed that gender, farm experience, age, household size, and farm size do not significantly influence the adoption of irrigation and crop insurance. The study revealed a significant positive impact of access to credit on adopting irrigation and crop insurance. The adoption of climate-smart practices has a positive coefficient. This indicates that if all respondents in each region adopts these practices, their income would increase significantly. This study shows that adopting irrigation practices leads to an increase in household income of 8.6% and 11.1%, respectively, for cocoa farmers. Crop insurance has a positive coefficient and is statistically significant on household income, on-farm, and off-farm. This paper shows that climate-smart practices such as crop insurance can positively influence farmers’ income in Ghana. We also conjecture that crop insurance is the most effective and efficient climate-smart practice among the various agricultural practices. The study suggests that access to credit and mass awareness should be compulsory modules coupled with the consistent training of farmers on new technologies for effective policy implementation. Expanding access to extension officers could enhance farmers’ adaptive capacity and warrant the efficiency of implemented practices.

The Determinants of Adoption and Intensity of Climate-Smart Agricultural Practices among Smallholder Maize Farmers

“…These results imply that more people in the household means more labour and exposure to information sources and hence more ideas about climate change adaptation strategies. This is in line with Adeagbo et al [5] and Agbenyo et al [41], who found that household size positively influences the likelihood of CSA practices adoption. On the contrary, Musafiri et al [42] found that large families were less likely to adopt labor-intensive CSA practices, and small family sizes adopted and hired labor to implement the innovations.…”

Distributional impact of climate-smart villages on access to savings and credit and adoption of improved climate-smart agricultural practices in the Nyando Basin, Kenya

“…In case savings are inadequate or allocated for other household expenditures in the future, such as school fees, smallholders have to resort to credit to meet their liquid financial needs (Simtowe and Zeller 2006). Access to credit (and land titles as collateral) therefor can have a positive impact on CSA adoption (Agbenyo et al 2022;Tanti et al 2022;Teklu et al 2023;Yiridomoh et al 2022). Credit market failure is a frequently cited reason for low adoption rates (Carter 1989;Makate et al 2019;Ogada et al 2014).…”

Study on the influence mechanism of adoption of smart agriculture technology behavior

“…The research shows that farmers’ behavioural decisions are influenced by a combination of internal and external factors, which leads to an in-depth exploration of the logic of farmers’ behaviour. Farmers’ behavioural preferences vary by gender and age 23 – 25 , which is a root factor for the differences in farmers’ perceptions 26 – 28 . Behaviour is also influenced by a combination of other individual characteristics such as literacy, part-time employment, access to information, risk perception, social networks and other household characteristics 29 – 31 .…”