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.

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