Assessing the Dynamics of kilowatt per capita in Nigeria; Evidence from Non-Seasonal ARIMA modeling

Using data from 1990 to 2023, this study examines the suitability of a non-seasonal ARIMA (0,1,1) model with drift for short-term forecasting of Nigeria's annual per-capita electricity consumption (kWh). ACF/PACF analysis was used to determine the model specification, which was ARIMA (0,1,1) with drift (μ = 1.6456). The mean of the first differences was subtracted to estimate the drift. A moving average coefficient (θ = -0.2246) was obtained by maximum likelihood estimation, and a Ljung–Box test (p = 0.2941) verified the model's adequacy and showed no discernible residual autocorrelation. Per-capita electricity use is expected to rise gradually between 2024 and 2026, with prediction intervals increasing over time to reflect growing uncertainty. These findings imply that the parsimonious ARIMA (0,1,1) with drift is a useful and interpretable tool for policy and planning in situations with limited data since it accurately captures the central trend in Nigeria's per-capita electricity consumption and offers trustworthy short-term forecasts.

Abstract licence: CC BY-NC

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.