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

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  • McCloskey, PJ
  • Malheiros Remor, Rodrigo

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.

Suggested Citation

  • McCloskey, PJ & Malheiros Remor, Rodrigo, 2024. "Comparative Analysis of ARIMA, VAR, and Linear Regression Models for UAE GDP Forecasting," MPRA Paper 122860, University Library of Munich, Germany, revised 01 Dec 2024.
    • Handle: RePEc:pra:mprapa:122860
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    References listed on IDEAS

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    1. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    2. Abdullah Ghazo, 2021. "Applying the ARIMA Model to the Process of Forecasting GDP and CPI in the Jordanian Economy," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 12(3), pages 70-77, May.
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    JEL classification:

    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

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