What Causes The Forecasting Failure of Markov-Switching Models? A Monte Carlo Study
Marie Bessec () and
Bouabdallah Othman ()
Additional contact information
Bouabdallah Othman: EUREQua, University of Paris 1 Panthéon Sorbonne
Studies in Nonlinear Dynamics & Econometrics, 2005, vol. 9, issue 2, 1-24
This paper explores the forecasting abilities of Markov-Switching models. Although MS models generally display a superior in-sample fit relative to linear models, the gain in prediction remains small. We confirm this result using simulated data for a wide range of specifications by applying several tests of forecast accuracy and encompassing robust to nested models. In order to explain this poor performance, we use a forecasting error decomposition. We identify four components and derive their analytical expressions in different MS specifications. The relative contribution of each source is assessed through Monte Carlo simulations. We find that the main source of error is due to the misclassification of future regimes.
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10) Track citations by RSS feed
Downloads: (external link)
For access to full text, subscription to the journal or payment for the individual article is required.
Working Paper: What causes the forecasting failure of Markov-Switching models? A Monte Carlo study (2005)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:bpj:sndecm:v:9:y:2005:i:2:n:6
Ordering information: This journal article can be ordered from
Access Statistics for this article
Studies in Nonlinear Dynamics & Econometrics is currently edited by Bruce Mizrach
More articles in Studies in Nonlinear Dynamics & Econometrics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().