{ "background": "Municipal infrastructure asset management in developing nations often lacks robust, data-driven methodologies for performance forecasting. This creates significant challenges for capital planning and maintenance prioritisation, particularly in sub-Saharan Africa where empirical longitudinal data is scarce.", "purpose and objectives": "This case study aims to methodologically evaluate existing municipal asset management systems and to develop a panel-data estimation model for forecasting infrastructure asset yield. The objective is to provide a replicable framework for measuring potential yield improvements in water supply and road networks.", "methodology": "The research employs a longitudinal panel-data analysis of asset registers and performance records from multiple urban municipalities. The core econometric model is a two-way fixed effects specification: $Y{it} = \\alpha + \\beta X{it} + \\mui + \\lambdat + \\epsilon{it}$, where $Y{it}$ is the infrastructure yield. Estimation uses robust standard errors clustered at the municipal level to account for heteroskedasticity and serial correlation.", "findings": "The methodological evaluation revealed systemic gaps in data collection, with over 60% of asset registers incomplete. The panel model indicates a statistically significant positive relationship between targeted maintenance expenditure and yield, with a coefficient of 0.15 (95% CI: 0.11, 0.19). This suggests that a 10% increase in such expenditure is associated with a 1.5% yield improvement, holding other factors constant.", "conclusion": "The proposed panel-data model offers a technically sound and practical method for estimating infrastructure yield trajectories, addressing a critical gap in municipal engineering asset management. The findings underscore the value of structured longitudinal data for informed decision-making.", "recommendations": "Municipalities should institutionalise standardised digital asset registers and adopt panel-data estimation for long-term performance forecasting. National policy should mandate minimum data standards to enable comparative analysis and benchmarking across regions.", "key words": "asset management, infrastructure yield, panel data, fixed effects model, municipal engineering, forecasting", "