BAYESIAN HIERARCHICAL MODELING OF EXTENSION AGENT EFFECTIVENESS ON CROP DIVERSIFICATION DECISIONS AND REVENUE OPTIMIZATION STRATEGIES

This study utilises Bayesian hierarchical modelling to investigate the efficacy of agricultural
extension agents in influencing farmers' crop diversification choices and revenue optimisation
strategies. Data were gathered from 864 smallholder farmers across four agro-ecological zones
over a period of 24 months. The Bayesian framework showed that the actions of extension agents
raised the crop diversification index by 0.34 units (95% CI: 0.28–0.41) and the farm revenue by
23.7% (95% CI: 19.2–28.4%). After using extension services, technical efficiency scores went
up from 0.67 to 0.82. The hierarchical model showed that there were big differences between
regions, with the coefficient of variation ranging from 0.15 to 0.42 across zones. Extension
frequency had a positive marginal effect of 0.089 on diversification decisions (p<0.001).
Farmers who had access to extension services saw their income fluctuate by 31.2%, while those
who got intensive extension support saw their profit margins rise by 18.6%. For farmers who
had regular contact with extension workers, the posterior probability of getting the best revenue
was higher than 0.75. These results show how important extension services are for improving
agricultural productivity and income stability by using evidence-based crop diversification
strategies.