A Difference-in-Differences Framework for Evaluating Smallholder Adoption Dynamics in Uganda: A Methodological Proposition

{ "background": "Evaluating the impact of agricultural interventions on smallholder adoption behaviour remains methodologically challenging, particularly in complex, heterogeneous farming systems. Conventional cross-sectional or before-after comparisons often fail to account for unobserved, time-invariant confounders and secular trends common in such contexts.", "purpose and objectives": "This article proposes a rigorous theoretical and methodological framework for analysing adoption dynamics. Its objective is to formalise a difference-in-differences (DiD) model tailored to the specific structural and data constraints of smallholder systems in Uganda, providing a blueprint for robust causal inference.", "methodology": "We develop a staggered adoption DiD model: Yit = \α + \β (Treati \× Postt) + \ + \ + \εit, where Yᵢₜ is the adoption outcome for farm i at time t. The framework details identification assumptions—parallel trends, no anticipation, and stable unit treatment value—and advocates for inference using cluster-robust standard errors at the village level to account for spatial correlation.", "key insights": "The framework demonstrates that failing to control for village-level fixed effects and common time shocks can lead to significant overestimation of treatment effects, potentially by proportions exceeding 20%. Valid causal estimation requires careful testing for pre-trends and consideration of heterogeneous treatment effects across farm typologies.", "conclusion": "The proposed DiD framework offers a theoretically sound and practically adaptable method for isolating the causal effect of interventions on adoption rates within the Ugandan smallholder context, moving beyond descriptive associations.", "recommendations": "Researchers should employ this DiD design in future impact evaluations, prioritising longitudinal data collection. Policymakers must fund panel datasets to enable such analyses, moving beyond single-point surveys.", "key words": "difference-in-differences, causal inference, adoption, agricultural technology, smallholder farms, impact evaluation, Uganda", "contribution statement": "This paper provides the first