Smallholder farming systems in Tanzania play a crucial role in rural economies, particularly for food security and poverty reduction. However, understanding how these systems evolve over time is complex, requiring robust methodological approaches. Panel data regression analysis was employed, incorporating fixed effects models to control for unobserved heterogeneity across farms. Robust standard errors were used to account for potential serial correlation within farms over time. A significant proportion (35%) of smallholder farmers adopted energy-efficient technologies in the study period, with notable increases in adoption rates observed among younger farmers and those with higher education levels. The analysis highlights the importance of targeted interventions for accelerating technology diffusion in Tanzania's agricultural sector. The fixed effects model provided a nuanced understanding of adoption dynamics over time. Policy makers should focus on enhancing access to information, training programmes, and financial support to facilitate wider uptake of energy-efficient technologies among smallholder farmers. The empirical specification follows Y=₀+^ X+, and inference is reported with uncertainty-aware statistical criteria.
Chituwo et al. (Tue,) studied this question.