"background": "Evaluating the cost-effectiveness of power-distribution infrastructure investments in developing economies is complex, requiring robust methods to isolate causal effects from confounding factors. Existing engineering-economic analyses often lack rigorous counterfactual frameworks, limiting their utility for policy and investment decisions. ", "purpose and objectives": "This article presents a methodological framework for the causal evaluation of power-distribution equipment systems. Its objective is to detail a quasi-experimental difference-in-differences (DiD) model tailored to assess the cost-effectiveness of infrastructure upgrades in the power sector. ", "methodology": "We specify a two-way fixed effects DiD model: Y{it = \ + \ (Treati \ Postt) + \ + \ +, where Y₈ₓ is a cost-effectiveness metric for region i at time t. The coefficient \ captures the average treatment effect. Inference relies on cluster-robust standard errors at the regional level to account for serial correlation. ", "findings": "As a methodology article, this paper presents no empirical results. The primary finding is the detailed specification of a DiD model, which includes a concrete adjustment for heterogeneous treatment timing and a procedure for testing the parallel trends assumption—a critical prerequisite for causal validity. ", "conclusion": "The proposed DiD model provides a statistically rigorous framework for evaluating infrastructure projects, moving beyond descriptive comparisons to estimate causal impacts on cost-effectiveness. ", "recommendations": "Researchers and planners should adopt quasi-experimental designs for infrastructure evaluation. We recommend pre-registration of analysis plans and rigorous testing of model assumptions, particularly parallel trends, before applying this methodology. ", "key words": "causal inference, difference-in-differences, infrastructure economics, power distribution, quasi-experimental design, cost-benefit analysis", "contribution statement": "This paper provides the first formalised difference-in-differences framework specifically designed for cost-effectiveness analysis of electrical distribution equipment, offering a novel tool for
Adebayo et al. (Wed,) studied this question.