Evaluating the cost-effectiveness of water treatment infrastructure in resource-constrained settings is critical for sustainable development, yet robust methodological frameworks for such assessments are lacking. This study aimed to develop and apply a novel quasi-experimental design to diagnose the cost-effectiveness of different water treatment systems in a Tanzanian context, moving beyond descriptive analysis to causal inference. A quasi-experimental design compared intervention facilities with matched control sites. Cost data were collected via engineering audits, and effectiveness was measured through consistent water quality testing. The primary analysis used a difference-in-differences model: Y₈ₓ = ₀ + ₁ Treatᵢ + ₂ Postₜ + ₃ (Treatᵢ Postₜ) + ₈ₓ, with inference based on cluster-robust standard errors. The methodological application revealed that membrane-based systems showed a statistically significant improvement in cost-effectiveness compared to conventional coagulation plants, with a calculated differential effect of 22% (95% CI: 15 to 29). The design successfully isolated the effect of technology choice from confounding regional factors. The proposed quasi-experimental design provides a rigorous, transferable framework for cost-effectiveness diagnostics in infrastructure engineering, yielding actionable insights for system selection. Infrastructure planners should adopt quasi-experimental principles during project appraisal and monitoring. Future research should apply this methodology to a broader range of technologies and geographical settings. cost-effectiveness analysis, quasi-experimental design, water treatment infrastructure, difference-in-differences, engineering economics This paper provides a novel methodological framework for causal cost-effectiveness analysis of engineered systems, demonstrating its utility through a comprehensive field study.
Mwambene et al. (Fri,) studied this question.