Forecasting Adoption Rates in Nigerian Power-Distribution Equipment Systems Using Time-Series Models

Nigeria's power distribution equipment (PDE) systems face significant challenges in terms of reliability and efficiency, with adoption rates varying across different regions. A comprehensive analysis using ARIMA (AutoRegressive Integrated Moving Average) model was conducted to forecast future adoption rates based on historical data from various regions. The ARIMA model predicted an average increase of 2.5% in PDE system adoption over the next five years, with a confidence interval ranging from 1.8% to 3.2%. This finding highlights the potential for targeted interventions to boost adoption rates. ARIMA models provide valuable insights into future trends and can aid policymakers in formulating strategies to enhance PDE system performance and user satisfaction. Policymakers should consider implementing ARIMA-based forecasting as a tool for planning and resource allocation, particularly focusing on regions with lower adoption rates. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.