African Peace and Conflict Studies (Broader - Interdisciplinary) | 23 March 2005
Time-Series Forecasting Model for Evaluating Off-Grid Community Systems in Kenya,
N, a, i, k, a, i, N, a, n, y, a, k, i, ,, K, i, p, r, u, t, o, M, u, r, i, u, k, i, ,, O, k, o, t, h, O, p, i, y, o, ,, W, a, m, b, u, g, u, K, i, b, e, t
Abstract
Off-grid community systems in Kenya have evolved significantly over recent years, yet their cost-effectiveness remains a subject of debate and evaluation. A time-series forecasting model was developed using historical data on electricity usage, cost structures, and technological advancements within off-grid community systems. Robust statistical techniques were employed to account for uncertainties in the data. The forecast indicated a steady decline in per capita system costs over five years, with an average reduction of approximately 10% annually, reflecting improved efficiency and economies of scale. The time-series model provided valuable insights into cost-effectiveness trends but acknowledged limitations such as data variability and potential technological obsolescence. Further research should focus on incorporating real-time data inputs to enhance the predictive accuracy of future forecasting models. Model estimation used $\hat{\theta}=argmin<em>{\theta}\sum</em>i\ell(y<em>i,f</em>\theta(x<em>i))+\lambda\lVert\theta\rVert</em>2^2$, with performance evaluated using out-of-sample error.