Methodological Evaluation of Smallholder Farm Systems in Ghana using Difference-in-Differences for Adoption Rate Measurement

Smallholder farm systems in Ghana are critical for food security and environmental sustainability. Understanding their adoption of new technologies is essential to guide policy and investment. A DID model was employed, estimating the impact of a targeted extension programme on technology adoption. Data from to were analysed with robust standard errors accounting for spatial and temporal heterogeneity. The DID method showed significant increases in rice cultivation among treated farms (p < 0.05), indicating the effectiveness of targeted extension services. This study validates the use of DID for measuring adoption rates, providing a robust framework for future research and policy interventions in Ghana. Further research should explore other agricultural innovations and incorporate longitudinal data to enhance model accuracy. The empirical specification follows Y=β₀+β^ X+ε, and inference is reported with uncertainty-aware statistical criteria.