"background": "Municipal infrastructure asset management in South Africa faces systemic challenges, including ageing assets, fiscal constraints, and inconsistent performance measurement. Existing frameworks often lack robust, forward-looking quantitative tools to evaluate the efficiency of asset management systems and inform capital investment policy. ", "purpose and objectives": "This policy analysis develops and evaluates a novel time-series forecasting model to quantify efficiency gains within municipal infrastructure asset management systems. The objective is to provide a replicable methodological tool for benchmarking performance and informing strategic infrastructure investment policy. ", "methodology": "A vector autoregressive (VAR) model, Yt = A1Y{t-1 +. . . + ApYt-p + \, was specified using panel data on asset condition, maintenance expenditure, and service delivery outputs. Model parameters were estimated using feasible generalised least squares, with inference based on heteroskedasticity-robust standard errors to account for cross-sectional volatility. ", "findings": "The model forecasts a persistent, albeit slow, upward trend in aggregate technical efficiency of approximately 1. 2% per annum under current policy settings. A key finding is that maintenance expenditure shocks have a greater and more sustained positive impact on forecast asset health than equivalent capital replacement shocks, with impulse response functions indicating effects lasting over eight periods. ", "conclusion": "The forecasting model provides a statistically robust instrument for policy simulation, demonstrating that targeted operational expenditure can yield significant long-term efficiency dividends for municipal infrastructure portfolios. ", "recommendations": "Policy should prioritise ring-fenced funding for preventative maintenance. National treasury guidelines should incorporate forward-looking efficiency metrics from such models into municipal infrastructure grant conditions. A centralised asset performance data repository should be established to refine forecasts. ", "key words": "infrastructure asset management, time-series forecasting, vector autoregression, municipal engineering, policy analysis, efficiency measurement", "contribution statement": "This paper introduces a novel application of a panel VAR model to forecast and decompose efficiency gains in infrastructure management, providing a quantitative tool for evidence
Nkosi et al. (Thu,) studied this question.