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A Bayesian regime‐switching time‐series model
Author(s) -
Kim Jaehee,
Cheon Sooyoung
Publication year - 2010
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.2010.00670.x
Subject(s) - series (stratigraphy) , mathematics , monte carlo method , variable (mathematics) , bayesian probability , constraint (computer aided design) , time series , statistical physics , econometrics , statistics , mathematical analysis , paleontology , physics , geometry , biology
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.