Non-Markovian Regime Switching with Endogenous States and Time-Varying State Strengths
AbstractThis article presents a non-Markovian regime switching model in which the regime states depend on the sign of an autoregressive latent variable. The magnitude of the latent variable indexes the `strength' of the state or how deeply the system is embedded in the current regime. The autoregressive nature of this non-Markovian regime switching implies time-varying state transition probabilities, even in the absence of an exogenous covariate. Furthermore, with time-varying regime strengths, the expected duration of a regime is time-varying. In this framework, it is natural to allow the autoregressive latent variable to be endogenous so that regimes are determined jointly with the observed data. We apply the model to GDP growth, as in Hamilton (1989), Albert and Chib (1993) and Filardo and Gordon (1998) to illustrate the relation of the regimes to NBER-dated recessions and the time-varying expected durations of regimes
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Bibliographic InfoPaper provided by Econometric Society in its series Econometric Society 2004 Latin American Meetings with number 34.
Date of creation: 11 Aug 2004
Date of revision:
Publication status: published in The B.E. Journal of Macroeconomics, 2011, vol. 11, issue 1.
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Regime switching; Markov Chain Monte Carlo;
Other versions of this item:
- Siddhartha Chib & Michael J. Dueker, 2004. "Non-Markovian regime switching with endogenous states and time-varying state strengths," Working Papers 2004-030, Federal Reserve Bank of St. Louis.
- Chib & Siddhartha; Dueker, 2004. "Non-Markovian Regime Switching with Endogenous States and Time-Varying State Strengths," Econometric Society 2004 North American Summer Meetings 600, Econometric Society.
- F42 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Policy Coordination and Transmission
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-10-30 (All new papers)
- NEP-ECM-2004-10-30 (Econometrics)
- NEP-ETS-2004-10-30 (Econometric Time Series)
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