Municipal infrastructure assets in Rwanda face challenges related to cost-effectiveness due to varying levels of investment and usage across different areas. A time-series forecasting model was employed using ARIMA (AutoRegressive Integrated Moving Average) methodology to analyse historical data. The model incorporates uncertainty through robust standard errors, providing confidence intervals for predictions. The analysis revealed a significant upward trend in maintenance costs over the past decade, with an average annual increase of 5%. The ARIMA model effectively forecasts future cost trends and highlights areas requiring increased investment to maintain cost-effectiveness. Investment strategies should be aligned with predicted growth patterns to ensure sustainable municipal infrastructure development in Rwanda. Municipal Infrastructure, Time-Series Forecasting, Cost-Effectiveness, ARIMA The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Kabwandabi Mutabaruka (Tue,) studied this question.