Bayesian Inference in Regime-Switching ARMA Models With Absorbing States: The Dynamics of the Ex-Ante Real Interest Rate Under Regime Shifts

Chang-Jin Kim and Jaeho Kim

Journal of Business & Economic Statistics, 2015, vol. 33, issue 4, 566-578

Abstract: One goal of this article is to develop an efficient Metropolis-Hastings (MH) algorithm for estimating an ARMA model with a regime-switching mean, by designing a new efficient proposal distribution for the regime-indicator variable. Unlike the existing algorithm, our algorithm can achieve reasonably fast convergence to the posterior distribution even when the latent regime-indicator variable is highly persistent or when there exist absorbing states. Another goal is to appropriately investigate the dynamics of the latent ex-ante real interest rate (EARR) in the presence of structural breaks, by employing the econometric tool developed. We show that excluding the theory-implied moving-average terms may understate the persistence of the observed EPRR dynamics. Our empirical results suggest that, even though we rule out the possibility of a unit root in the EARR, it may be more persistent and volatile than has been documented in some of the literature.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlbes:v:33:y:2015:i:4:p:566-578

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DOI: 10.1080/07350015.2014.979995

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