TY - JOUR
T1 - Bayesian inference for periodic regime-switching models
AU - Ghysels, Eric
AU - Mcculloch, Robert E.
AU - Tsay, Ruey S.
PY - 1998
Y1 - 1998
N2 - We present a general class of nonlinear time-series Markov regime-switching models for seasonal data which may exhibit periodic features in the hidden Markov process as well as in the laws of motion in each of the regimes. This class of models allows for non-trivial dependencies between seasonal, cyclical and long-term patterns in the data. To overcome the computational burden we adopt a Bayesian approach to estimation and inference. This paper contains two empirical examples as illustration, one uses housing starts data while the other employs US post-Second World War industrial production.
AB - We present a general class of nonlinear time-series Markov regime-switching models for seasonal data which may exhibit periodic features in the hidden Markov process as well as in the laws of motion in each of the regimes. This class of models allows for non-trivial dependencies between seasonal, cyclical and long-term patterns in the data. To overcome the computational burden we adopt a Bayesian approach to estimation and inference. This paper contains two empirical examples as illustration, one uses housing starts data while the other employs US post-Second World War industrial production.
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U2 - 10.1002/(SICI)1099-1255(199803/04)13:2<129::AID-JAE466>3.0.CO;2-2
DO - 10.1002/(SICI)1099-1255(199803/04)13:2<129::AID-JAE466>3.0.CO;2-2
M3 - Article
AN - SCOPUS:0032366065
SN - 0883-7252
VL - 13
SP - 129
EP - 143
JO - Journal of Applied Econometrics
JF - Journal of Applied Econometrics
IS - 2
ER -