A Time-Series Forecasting Model for the Cost-Effectiveness of South African Municipal Infrastructure Asset Systems: A Methodological Evaluation (2000–2026)

{ "background": "Municipal infrastructure asset systems in South Africa face significant challenges in long-term financial planning and sustainability. Existing models often lack the temporal granularity and methodological rigour to forecast cost-effectiveness accurately, hindering strategic asset management.", "purpose and objectives": "This data descriptor presents a methodological evaluation of a novel time-series forecasting model designed to measure the cost-effectiveness of municipal infrastructure asset systems. The objective is to detail the model's architecture, data requirements, and validation protocol.", "methodology": "The methodology employs a seasonal autoregressive integrated moving average with exogenous variables (SARIMAX) model, specified as \φ(B)\Φ(Bˢ)\∇ᵈ yt = \θ(B)\Θ(Bˢ)\ + \β Xt, where Xₜ represents a vector of exogenous economic and demographic variables. Model parameters were estimated using maximum likelihood, with robust standard errors to account for heteroskedasticity.", "findings": "The methodological evaluation indicates that the integrated model provides a robust framework for forecasting, with out-of-sample validation showing a mean absolute percentage error (MAPE) of less than 8% for key cost indices. A principal finding is the model's sensitivity to exogenous economic variables, which account for approximately 60% of the forecast variance in long-term maintenance expenditure.", "conclusion": "The proposed time-series model constitutes a technically sound methodological advance for forecasting infrastructure cost-effectiveness, offering a structured and replicable approach for municipal engineers and planners.", "recommendations": "It is recommended that municipalities adopt this forecasting methodology within their asset management plans and that future work focuses on integrating spatially disaggregated data to enhance localised predictions.", "key words": "asset management, infrastructure economics, municipal engineering, SARIMAX, forecasting, cost-benefit analysis", "contribution statement": "This paper provides the first integrated SARIMAX forecasting model specifically configured for the South African municipal infrastructure context, detailing its complete methodological framework and validation data."