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

Dongwei Su and Xingxing He

MPRA Paper from University Library of Munich, Germany

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.

Keywords: Computational intelligence; artificial neural networks; fuzzy optimization; early warning system; economic crises (search for similar items in EconPapers)
JEL-codes: C53 E17 (search for similar items in EconPapers)
Date: 2010-01-11
New Economics Papers: this item is included in nep-cmp, nep-for and nep-tra
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:19962

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