Forecasting urbanization and electricity consumption dynamics in Somalia using ARIMA modeling

Abstract

Somalia is experiencing rapid urban expansion alongside rising electricity demand, posing significant challenges for sustainable development and infrastructure planning in a context characterized by severe data limitations. Empirical evidence on the urban–energy nexus in Somalia remains scarce, particularly studies employing formal time-series forecasting techniques. This study addresses this gap by applying Autoregressive Integrated Moving Average (ARIMA) models to forecast urbanization and electricity consumption using quarterly data obtained from international statistical sources. Following the Box–Jenkins methodology and information criteria, ARIMA (4,1,2) and ARIMA (5,1,2) are identified as the optimal models for urbanization and electricity consumption, respectively. Diagnostic tests confirm model adequacy and stability. The forecasts indicate a sustained increase in both urbanization and electricity consumption through 2030, reflecting rising population density and escalating energy needs. The study establishes a robust univariate forecasting benchmark for Somalia and provides empirical insights to inform integrated urban–energy policies and sustainable infrastructure investment. Future research may extend this analysis by incorporating multivariate or hybrid forecasting approaches to enhance policy relevance.