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A Hybrid Intelligent Early Warning System for Predicting Economic Crises: The Case of China

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  • Su, Dongwei
  • He, Xingxing

Abstract

This paper combines artificial neural networks (ANN), fuzzy optimization and time-series econometric models in one unified framework to form a hybrid intelligent early warning system (EWS) for predicting economic crises. Using quarterly data on 12 macroeconomic and financial variables for the Chinese economy during 1999 and 2008, the paper finds that the hybrid model possesses strong predictive power and the likelihood of economic crises in China during 2009 and 2010 remains high.

Suggested Citation

  • Su, Dongwei & He, Xingxing, 2010. "A Hybrid Intelligent Early Warning System for Predicting Economic Crises: The Case of China," MPRA Paper 19962, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:19962
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Computational intelligence; artificial neural networks; fuzzy optimization; early warning system; economic crises;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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