Non-Markovian Regime-Switching Models

37 Pages Posted: 27 Apr 2018

See all articles by Chang-Jin Kim

Chang-Jin Kim

Dept. of Economics, University of Washington

Jaeho Kim

Korea Development Institute; University of Oklahoma

Date Written: March 2018

Abstract

This paper revisits the non-Markovian regime switching model considered by Chib and Dueker (2004), who employ an autoregressive continuous latent variable in order to specify the dynamics of the latent regime-indicator variable. We show that, in spite of the non-Markovian nature of the regime indicator variable, the Markovian property of this continuous latent variable allows us to easily estimate the model within the Bayesian framework without any approximations. In particular, we show that the conventional Gibbs sampling is enough in generating the regime indicator variable as well as the continuous latent variable conditional on all the parameters of the model and data. For an application to business cycle modeling of postwar US real GDP, a modified version of Hamilton’s (1989) Markovian switching model is slightly preferred to a non-Markovian switching model by the Bayesian model selection criterion. For an application to volatility modeling of the weekly stock return, a non-Markovian switching model with endogenous switching or the leverage effect is strongly preferred to Markovian switching models.

Keywords: Non-Markovian Regime Switching, Markovian Regime Switching, Exogenous Switching, Endogenous Switching

JEL Classification: C11, C13, C22, C25

Suggested Citation

Kim, Chang-Jin and Kim, Jaeho, Non-Markovian Regime-Switching Models (March 2018). Available at SSRN: https://ssrn.com/abstract=3159530 or http://dx.doi.org/10.2139/ssrn.3159530

Chang-Jin Kim

Dept. of Economics, University of Washington ( email )

Department of Economics (Box 353330)
University of Washington
Seattle, WA 98195-3330
United States

HOME PAGE: http://https://econ.washington.edu/people/chang-jin-kim

Jaeho Kim (Contact Author)

Korea Development Institute ( email )

P.O. Box 113
Cheongryangri
Seoul 130-012
United States

University of Oklahoma ( email )

729 Elm Avenue
Norman, OK 73019-2103
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
56
Abstract Views
480
rank
451,066
PlumX Metrics