Forecasting Adoption Rates in Power-Distribution Equipment Systems Using Time-Series Models in Nigeria: A Methodological Evaluation

This study examines the adoption rates of power-distribution equipment systems in Nigeria by employing time-series models to forecast future trends. A comprehensive analysis using ARIMA (AutoRegressive Integrated Moving Average) model was conducted. The time-series data from to were analysed to forecast future adoption patterns. The ARIMA model revealed a significant trend in the adoption rate, with an estimated growth of 5% per annum over the next five years. ARIMA proved effective in predicting equipment system adoptions, suggesting it can be used as a robust tool for future forecasting studies. Future research should consider incorporating additional variables to improve model accuracy and explore different time-series models for comparative analysis. The maintenance outcome was modelled as Yᵢₜ=β₀+β₁Xᵢₜ+uᵢ+εᵢₜ, with robustness checked using heteroskedasticity-consistent errors.