Cogent Social Sciences (Aug 2024)
Impact of integrated land management technology adoption on rural livelihoods in the Goyrie watershed, Southern Ethiopia: Endogenous switching regression modeling estimation
Abstract
Integrated land management (ILM) technology adoption is crucial for enhancing yield production and households’ income, which are indispensable to sustainable development objectives. This research analyzes the impact of ILM technology adoptions on rural livelihoods by focusing on yield production and net farm income in the Goyrie watershed, southern Ethiopia. Deploying random sampling techniques, cross-sectional data was collected from 291 households’. Quantitative data was analyzed using percent, mean, standard deviation and independent t-test, while qualitative data was presented in a narrative forms. The Full Information Maximum Likelihood (FIML) methods and Endogenous Switching Regression Modeling (ESRM) were utilized to estimate the impact of ILM technology adoptions on yield production and net farm income. The result exhibited that the average treatment effect for technology adopters increased their yield production by 4.71% and net farm income by 2.81%. Under counterfactual scenarios, the average treatment effect on untreated control groups would increase yield production and net farm income by 5.73% and 3.71%, respectively, if they preferred to adopt the technology. The study found that adoption of ILM technologies significantly and positively impacts yield production and net farm income in Goyrie watershed. Thus, we suggest that agricultural experts and academics should assist early adopters to scale up and encourage the non-adopters to adopt combined technologies through training and enhancing extension services. Educational status, land size, livestock and membership had positive impacts on yield production and income, suggesting that policies that encourage livelihood asset indicators can enable households to boost their yield production and income.
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