{ "background": "Municipal infrastructure asset systems in Nigeria face chronic inefficiencies, yet robust methodological frameworks for quantifying and analysing these inefficiencies across different administrative levels are lacking. Existing evaluations often fail to account for the hierarchical structure of data inherent in public asset management.", "purpose and objectives": "This case study aims to methodologically evaluate the application of multilevel regression modelling for measuring efficiency gains within municipal infrastructure systems. The objective is to demonstrate a replicable analytical framework that isolates variance attributable to state versus local government levels.", "methodology": "A longitudinal panel dataset for core infrastructure assets (water, roads, public buildings) was constructed. The methodological evaluation centres on fitting a three-level linear growth model: $y{ijt} = \\beta{0} + \\beta{1}Time{t} + u{0j} + u{0k} + \\epsilon_{ijt}$, where $j$ denotes local governments nested within states $k$. Model diagnostics, including intraclass correlation coefficients and robust standard errors, were used to assess the framework's utility.", "findings": "The methodological evaluation revealed that the multilevel model successfully partitioned significant variance in asset condition scores, with approximately 35% of the variance attributable to differences between states. The fixed effect for time indicated a positive but statistically non-significant average annual trend in efficiency scores (95% CI: -0.02 to 0.08) when hierarchical data structure was controlled for.", "conclusion": "The multilevel regression approach provides a superior methodological framework for infrastructure efficiency analysis by explicitly modelling clustered data, thereby preventing biased inference that can occur with conventional single-level models.", "recommendations": "Adopt multilevel modelling as a standard for infrastructure performance assessment across tiered governance systems. Future asset management information systems should be designed to capture data compatible with hierarchical analysis.", "key words": "asset management, hierarchical linear model, infrastructure efficiency, municipal engineering, public works", "contribution statement": "This study provides a novel methodological demonstration