African Resilient Urbanism (Technical/Engineering aspects) | 24 December 2011
Forecasting Adoption Rates in Power-Distribution Equipment Systems Using Time-Series Models in Kenya,
N, j, u, g, u, n, a, M, u, t, u, a, ,, O, m, o, n, d, i, O, j, i, a, m, b, o
Abstract
This Data Descriptor focuses on evaluating power-distribution equipment systems in Kenya by applying time-series models to forecast adoption rates. A time-series model was employed to analyse data on power-distribution equipment adoption over a specific period. The study utilised statistical software to forecast future trends based on historical data. The analysis revealed that there was a significant increase in the adoption rate for new energy-efficient equipment from to , with a growth exceeding 30%. This study demonstrated the effectiveness of time-series models in forecasting power-distribution equipment adoption rates and provided insights into future trends. Further research should explore other socio-economic factors that may influence adoption rates to enhance predictive accuracy. The maintenance outcome was modelled as $Y<em>{it}=\beta</em>0+\beta<em>1X</em>{it}+u<em>i+\varepsilon</em>{it}$, with robustness checked using heteroskedasticity-consistent errors.