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Forecast performance of nonlinear error‐correction models with multiple regimes
Author(s) -
Psaradakis Zacharias,
Spagnolo Fabio
Publication year - 2005
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.946
Subject(s) - disequilibrium , nonlinear system , error detection and correction , focus (optics) , markov chain , computer science , error correction model , econometrics , mathematics , algorithm , cointegration , physics , machine learning , medicine , quantum mechanics , optics , ophthalmology
In this paper we investigate the forecast performance of nonlinear error‐correction models with regime switching. In particular, we focus on threshold and Markov switching error‐correction models, where adjustment towards long‐run equilibrium is nonlinear and discontinuous. Our simulation study reveals that the gains from using a correctly specified nonlinear model can be considerable, especially if disequilibrium adjustment is strong and/or the magnitude of parameter changes is relatively large. Copyright © 2005 John Wiley & Sons, Ltd.