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

Su, Dongwei and He, Xingxing (2010): A Hybrid Intelligent Early Warning System for Predicting Economic Crises: The Case of China.

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Computational intelligence; artificial neural networks; fuzzy optimization; early warning system; economic crises
• Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; E - Macroeconomics and Monetary Economics > E1 - General Aggregative Models > E17 - Forecasting and Simulation: Models and Applications

References

D. Beckmann, L. Menkhoff, and K. Sawischlewski, “Robust lessons about practical early warning systems,” Journal of Policy Modeling, vol. 28, no. 2, pp. 163-193, 2006.