"background": "Municipal infrastructure asset management in developing economies is often constrained by limited data and resources, making rigorous evaluation of cost-effectiveness challenging. Current approaches frequently rely on descriptive case studies lacking counterfactual analysis, which limits causal inference for investment decisions. ", "purpose and objectives": "This article presents a novel quasi-experimental framework designed to diagnose the cost-effectiveness of municipal infrastructure systems. The objective is to provide a robust methodological tool for comparing observed maintenance outcomes against a credible counterfactual, enabling causal attribution of efficiency gains or losses. ", "methodology": "The proposed framework employs a difference-in-differences design, leveraging phased implementation of asset management programmes across different municipalities. Infrastructure performance is modelled using a fixed-effects panel regression: Y{it = \ + \ (Tit) + \ + \ +, where Yit is a composite performance index, Tit is a treatment indicator, and \ and \ₜ are entity and time fixed effects. Inference is based on cluster-robust standard errors at the municipal level. ", "findings": "As a methodology article, this paper presents no empirical results from application. However, a pilot simulation using synthetic data demonstrates the framework's capability to isolate treatment effects, indicating that a key diagnostic output is the direction and magnitude of the coefficient \. The simulation suggests the model can detect a minimum cost-effectiveness improvement of 15% with 90% statistical power under plausible assumptions. ", "conclusion": "The developed framework provides a structured, statistically rigorous methodology for evaluating the cost-effectiveness of infrastructure asset systems where randomised controlled trials are impractical. It moves beyond descriptive analysis towards causal diagnosis. ", "recommendations": "Practitioners should adopt this quasi-experimental approach for periodic system audits. Future research should validate the framework through large-scale application and integrate it with lifecycle cost analysis modules. ", "key words": "quasi-experimental design, infrastructure asset management, cost-effectiveness
Mukamana et al. (Fri,) studied this question.