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Abstract

We investigate business cycle asymmetries in the real GDP of eleven selected Asian economies using nonlinear switching time series models and artificial neural networks. Results based on neural network linearity tests show evidence of business cycle asymmetries in all series. Results based on switching and augmented time series models also reveal business cycle asymmetries in most series studied.

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Bibliographic Info

Article provided by College of Business, and College of Finance, Feng Chia University, Taichung, Taiwan in its journal International Journal of Business and Economics.

Volume (Year): 8 (2009)
Issue (Month): 1 (April)
Pages: 37-54

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Handle: RePEc:ijb:journl:v:8:y:2009:i:1:p:37-54

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Postal: 100 Wenhwa Road, Seatwen, Taichung
Web page: http://www.ijbe.org/
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Related research

Keywords: real GDP growth rates; fat tails; stable distributions; neural networks; out-of-sample forecasts; long memory; nonlinearities; business cycles;

Find related papers by JEL classification:

• C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
• C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
• C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
• C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

References

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