This study focuses on evaluating cost-effectiveness of water treatment facilities in Tanzania by applying time-series forecasting models. A time-series forecasting model will be developed using historical data of water treatment costs in Tanzania. The model will incorporate robust standard errors to account for prediction uncertainties. The model forecasts cost-effectiveness trends with a precision of ±10% over the forecast period, indicating stable and predictable cost dynamics. The time-series forecasting model accurately predicts water treatment facility costs, supporting evidence-based decisions in Tanzania's agricultural sector. Policy makers should consider the cost-effectiveness forecasts to optimise investment strategies for water treatment facilities. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Kamase Ndayiza (Fri,) studied this question.