{ "background": "Evaluating the cost-effectiveness of large-scale water infrastructure in developing nations remains a significant challenge, often relying on cross-sectional or before-after comparisons that inadequately account for confounding trends and selection bias.", "purpose and objectives": "This study develops and applies a quasi-experimental difference-in-differences (DiD) model to rigorously assess the cost-effectiveness of water treatment facility systems, aiming to isolate the causal impact of infrastructure investments from other temporal changes.", "methodology": "A panel dataset was constructed for treatment and control groups of communities. The core DiD model is specified as $Y{it} = \\beta0 + \\beta1 \\text{Treat}i + \\beta2 \\text{Post}t + \\delta (\\text{Treat}i \\times \\text{Post}t) + \\epsilon{it}$, where $Y{it}$ is the cost-per-cubic-metre metric. Inference is based on cluster-robust standard errors at the regional level.", "findings": "The DiD estimator ($\\delta$) indicates a statistically significant reduction in average unit costs of 18.2% (95% CI: 12.5% to 23.9%) attributable to the new infrastructure programme, after controlling for underlying trends common to both groups.", "conclusion": "The DiD framework provides a more robust methodological approach for cost-effectiveness analysis in civil engineering projects than conventional methods, effectively accounting for unobserved confounders that evolve linearly over time.", "recommendations": "Infrastructure planning authorities should adopt quasi-experimental evaluation designs, particularly DiD models, for the ex-post assessment of major capital projects to inform future investment prioritisation and improve accountability.", "key words": "cost-benefit analysis, quasi-experimental design, infrastructure evaluation, water treatment, econometric modelling", "contribution statement": "This paper provides the first application of a difference-in-differences model to evaluate the cost-effectiveness of water treatment infrastructure in a