{ "background": "Municipal infrastructure asset management (IAM) is critical for sustainable urban development, yet its systematic adoption in many developing nations remains poorly understood. In Ethiopia, despite national policy directives, the implementation of IAM systems across municipalities has been inconsistent and inadequately evaluated.", "purpose and objectives": "This policy analysis evaluates the adoption rates of municipal IAM systems and identifies the key institutional, technical, and financial factors influencing their uptake. The objective is to provide an evidence base for refining national infrastructure policy.", "methodology": "A multilevel regression analysis was conducted using a novel panel dataset from a stratified sample of municipalities. The model, $y{ij} = \\beta{0} + \\beta{1}X{ij} + \\gamma Z{j} + u{j} + e_{ij}$, where $i$ denotes municipality and $j$ denotes region, accounted for clustered data structures. Inference was based on robust standard errors.", "findings": "Adoption rates are strongly associated with dedicated municipal revenue streams and technical staff capacity. A one-unit increase in standardised technical capacity score was associated with a 0.37 increase in the adoption index (95% CI: 0.28 to 0.46). Regional policy enforcement mechanisms explained a significant portion of the variance between clusters.", "conclusion": "The adoption of IAM systems is a multilevel problem, driven by local capacity and conditioned by higher-level governance frameworks. Current policy has been partially effective but requires more targeted support mechanisms.", "recommendations": "National policy should mandate minimum staffing and training standards for municipal engineering units. Furthermore, fiscal decentralisation policies must be strengthened to ensure municipalities have predictable capital and operational funding for IAM systems.", "key words": "asset management, infrastructure policy, multilevel modelling, municipal engineering, urban services", "contribution statement": "This study provides the first application of multilevel regression to quantify IAM adoption in the Ethiopian context, introducing a novel composite index for measuring system maturity