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Abstract This study examines the determinants of farmers’ climate adaptation strategies across agro-climatic zones, with particular focus on education, household characteristics, and income. A multi-stage random sample of 200 farmers was analyzed using a stochastic frontier model to assess production efficiency and a logit model to evaluate adaptation choices. Results reveal substantial heterogeneity in productivity, with mean 0.619 technical efficiency scores ranging from 0.378 to 0.961. The variance parameter (γ = 0.723) indicates that most performance differences arise from inefficiency rather than random shocks. Among production inputs, tractor use (0.182) and urea application (0.160) significantly increase yield, whereas cultivated area is negatively associated with output (− 0.943), reflecting land fragmentation and managerial constraints. Labor and DAP were not significant contributors. In the logit model (Pseudo-R2 = 0.528), farmers’ age and education significantly increase the likelihood of adopting adaptation measures, while larger household size reduces it; agricultural income shows a modest positive effect. These findings suggest that productivity gains are more likely to come from intensification through improved timing, mechanization services, and nutrient management rather than from expanding cultivated area. Policy priorities should focus on three areas: (i) knowledge and extension support, including zone-specific advisories and training; (ii) improved access to mechanization and soil and water management technologies; and (iii) financial tools such as credit and insurance to reduce adoption barriers. Strengthening education and skills, particularly for labor-constrained households, can accelerate the uptake of effective practices, narrow the efficiency gap, and enhance the resilience of maize systems under a warming climate.
Ali et al. (Thu,) studied this question.
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