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

Author

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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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    More about this item

    Keywords

    GDP forecasting; ARIMA; VAR; Linear Regression; UAE economy;
    All these keywords.

    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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