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{ "background": "Municipal infrastructure asset management in Nigeria is characterised by systemic inefficiencies and a lack of robust diagnostic tools. Current evaluation methods often rely on descriptive analyses, which fail to isolate the causal impact of management interventions on asset performance.", "purpose and objectives": "This article presents a novel quasi-experimental framework designed to measure efficiency gains within municipal infrastructure systems. Its primary objective is to provide a rigorous methodological tool for diagnosing causal improvements in asset management practices.", "methodology": "The proposed framework employs a difference-in-differences design, comparing treated asset cohorts (e.g., those under a new maintenance regime) with matched control groups over time. The core statistical model is a fixed-effects panel regression: $Y{it} = \\alpha + \\beta (Treati \\times Postt) + \\gamma X{it} + \\mui + \\lambdat + \\epsilon{it}$, where $Y{it}$ is an infrastructure condition index. Inference is based on cluster-robust standard errors to account for serial correlation within asset groups.", "findings": "As a methodology article, this paper presents no empirical results from field application. However, simulation studies of the framework indicate its capacity to detect a minimum detectable effect of a 15% improvement in the condition index with 80% power, assuming plausible levels of inter-asset correlation. The diagnostic output effectively distinguishes between programme effect and secular trends.", "conclusion": "The framework provides a viable and technically sound approach for causal inference in infrastructure management evaluation, where randomised controlled trials are often impractical. It translates econometric techniques directly into the engineering asset management domain.", "recommendations": "Municipal engineers and policymakers should adopt quasi-experimental designs for programme evaluation. Future research should focus on validating the framework through large-scale field trials and developing standardised asset condition indices for consistent measurement.", "key words": "asset management, causal inference, difference-in-differences, infrastructure efficiency, quasi-experiment, municipal engineering", "contribution statement": "