Comparative Analysis of ARIMA, VAR, and Linear Regression Models for UAE GDP Forecasting

Abstract

Forecasting GDP is crucial for economic planning and policymaking. This study compares the performance of three widely-used econometric models—ARIMA, VAR, and Linear Regression—using GDP data from the UAE. Employing a rolling forecast approach, we analyze the models’ accuracy over different time horizons. Results indicate ARIMA’s robust long-term forecasting capability, LR models perform better with short-term predictions, particularly when exogenous variable forecasts are accurate. These insights provide a valuable foundation for selecting forecasting models in the UAE’s evolving economy, suggesting ARIMA’s suitability for long-term outlooks and LR for short-term, scenario-based forecasts.