"background": "The persistent inefficiency and high cost of power distribution in many African nations hinder economic development. In Uganda, ageing infrastructure and capital constraints necessitate rigorous, evidence-based policy to prioritise investments in distribution equipment. Existing evaluations often lack robust counterfactual analysis, leading to suboptimal resource allocation. ", "purpose and objectives": "This policy analysis aims to develop and apply a quasi-experimental difference-in-differences (DiD) model to evaluate the comparative cost-effectiveness of different power-distribution equipment systems. The objective is to provide a methodological framework for quantifying the causal impact of equipment choices on long-term economic and technical performance. ", "methodology": "A longitudinal panel dataset of utility operational and capital expenditures is analysed using a DiD model: Y{it = \0 + \1 + \2 + \ (\) +, where Yit is the cost-per-unit-delivered. Treatment groups are defined by equipment type (e. g. , conventional vs. modular transformers). Inference is based on cluster-robust standard errors at the regional level. ", "findings": "The analysis indicates that the adoption of modular transformer systems in treated regions yielded a statistically significant reduction in total life-cycle cost per kWh delivered, estimated at 18–22% compared to conventional systems. The DiD coefficient \ was negative and significant at the 1% level, with the result robust to multiple specifications. ", "conclusion": "The DiD model provides a credible framework for causal policy evaluation in infrastructure investment. The findings demonstrate that strategic equipment selection, informed by quasi-experimental analysis, can substantially improve the cost-effectiveness of power distribution networks. ", "recommendations": "National utilities and regulators should adopt quasi-experimental evaluation methods for major capital projects. Policy should incentivise procurement of equipment types with verified long-term cost-effectiveness, supported
Otieno et al. (Sun,) studied this question.
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