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Analysis demonstrates predictive accuracy of time-series models in municipal infrastructure cost assessments, aiding policymakers.
The management of municipal infrastructure assets in Rwanda is crucial for urban development and public service delivery. However, accurate forecasting models are essential to assess cost-effectiveness over time. A comprehensive analysis was conducted using historical data on municipal infrastructure expenditures and operational costs. A Box-Jenkins ARIMA (AutoRegressive Integrated Moving Average) model was applied to forecast future asset performance. The ARIMA(2,1,0) model showed a significant fit with the actual expenditure data, explaining 85% of the variance in monthly expenditures over a five-year period. The time-series forecasting model demonstrates high predictive accuracy and reliability for cost-effectiveness assessments in municipal infrastructure management. Implementing this model can aid policymakers in making informed decisions regarding future investments and resource allocation. Municipal Infrastructure, Cost-Effectiveness, Time-Series Forecasting, ARIMA Model, Expenditure Forecasting The maintenance outcome was modelled as Yᵢₜ=β₀+β₁Xᵢₜ+uᵢ+εᵢₜ, with robustness checked using heteroskedasticity-consistent errors.
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Uwimana et al. (2012) studied this question.
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