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Tools for non-linear time series forecasting in economics - An empirical comparison of regime switching vector autoregressive models and recurrent neural networks

Author

Summary, in English

The purpose of this study is to contrast the forecasting performance of two non-linear models, a regime-switching vector autoregressive model (RS-VAR) and a recurrent neural network (RNN), to that of a linear benchmark VAR model. Our specific forecasting experiment is U.K. inflation and we utilize monthly data from 1969 to 2003. The RS-VAR and the RNN perform approximately on par over both monthly and annual forecast horizons. Both non-linear models perform significantly better than the VAR model.

Publishing year

2004

Language

English

Pages

71-91

Publication/Series

Advances in Econometrics

Volume

19

Document type

Journal article

Publisher

Elsevier

Topic

  • Economics

Status

Published

ISBN/ISSN/Other

  • ISSN: 0731-9053