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.
Department/s
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