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A Bayesian regime-switching time-series model

Authors
Kim, JaeheeCheon, Sooyoung
Issue Date
Sep-2010
Publisher
WILEY-BLACKWELL
Keywords
Autoregressive model; Bayesian information criterion; regime-switching model; stochastic approximation Monte Carlo; switching points; C110; C510
Citation
JOURNAL OF TIME SERIES ANALYSIS, v.31, no.5, pp.365 - 378
Indexed
SCIE
SCOPUS
Journal Title
JOURNAL OF TIME SERIES ANALYSIS
Volume
31
Number
5
Start Page
365
End Page
378
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/115726
DOI
10.1111/j.1467-9892.2010.00670.x
ISSN
0143-9782
Abstract
This article provides a new Bayesian approach for AR(2) time-series models with multiple regime-switching points. Our formulation of the regime-switching model involves a binary discrete variable that indicates the regime change. This variable is specified to be detected by data in each regime. The model is estimated using Stochastic approximation Monte Carlo method proposed by Liang et al. [JASA (2007)]. This methodology is quite useful since it allows for fitting of more complex regime-switching models without transition constraint. The proposed model is illustrated using simulated and real data such as GNP and US interest rate data.
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