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

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.

• Författare: JM Binner; Thomas Elger; Birger Nilsson; JA Tepper
• Avdelning/ar: Nationalekonomiska institutionen
• Publiceringsår: 2004
• Språk: Engelska
• Sidor: 71-91
• Publikation/Tidskrift/Serie: Advances in Econometrics
• Volym: 19
• Dokumenttyp: Artikel i tidskrift
• Förlag: Elsevier
• Ämne: Economics
• Status: Published
• ISBN/ISSN/Övrigt: ISSN: 0731-9053