📄 Abstract
This study examines trends and forecasts of access to electricity in Uganda using data from 1995 to 2022 via a quantitative approach based on ARIMA modelling. Balanced time-series data from World Bank is analyzed, with access to electricity as dependent variable, incorporating autoregressive (AR) and moving average (MA) components as independent variables. Parameter estimation is conducted using Maximum Likelihood Estimation (MLE). Results indicate that MA(4) coefficient (0.5847) is positive and statistically significant, suggesting that short-term fluctuations in electricity access are influenced by prior trends, with 58.5% of variations explained by past values. Estimated ARIMA (1, 1, 4) model is both covariance stationary and invertible, making it reliable for forecasting future patterns in electricity access. Projections reveal a steady upward trend, with electricity access expected to increase from 47.1% in 2022 to approximately 65.9% by 2042. These findings highlight the role of sustained infrastructure investment and policy interventions in improving electrification rates. The study recommends prioritizing rural electrification programs, expanding grid infrastructure, and leveraging renewable energy sources.
🏷️ Keywords
📚 How to Cite:
Nahabwe Patrick Kagambo John, Kagarura Willy Rwamparagi , MODELLING ACCESS TO ELECTRICITY IN UGANDA , Volume 12 , Issue 1, january 2025, EPRA International Journal of Environmental Economics, Commerce and Educational Management(ECEM) ,