Methodological Evaluation and Panel-Data Estimation of Municipal Infrastructure Asset Efficiency in Rwanda, 2000–2026

Municipal infrastructure asset management in developing nations often lacks robust, data-driven methodologies for assessing long-term efficiency. This creates challenges for capital planning and sustainable service delivery. This study aims to develop and evaluate a panel-data econometric methodology for measuring technical efficiency gains in municipal infrastructure systems. The objective is to provide a replicable framework for asset performance analysis. A balanced panel dataset for key municipal asset classes was constructed. Technical efficiency was estimated using a stochastic frontier analysis model: (Output₈ₓ) = (Input₈ₓ) + v₈ₓ - u₈ₓ, where u₈ₓ represents inefficiency. Estimation used maximum likelihood with robust standard errors clustered at the municipal level. The methodological evaluation confirmed the model's robustness, with inefficiency effects significant at the 1% level. Estimated mean technical efficiency across the panel showed a statistically significant upward trend, increasing by approximately 17 percentage points over the study period. The panel-data approach provides a rigorous, quantitative foundation for tracking infrastructure asset efficiency. It moves beyond descriptive analysis to isolate measurable efficiency gains attributable to management practices. Infrastructure agencies should adopt panel-data estimation for periodic asset efficiency reviews. This requires institutionalising standardised data collection on asset inputs and service outputs. asset management, stochastic frontier analysis, technical efficiency, municipal engineering, panel data This paper provides a novel application of stochastic frontier analysis to longitudinal infrastructure asset data, generating the first panel-data estimates of technical efficiency for municipal assets in the region.