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

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  • Chang-Jin Kim
  • Jaeho Kim

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.

Suggested Citation

  • Chang-Jin Kim & Jaeho Kim, 2015. "Bayesian Inference in Regime-Switching ARMA Models With Absorbing States: The Dynamics of the Ex-Ante Real Interest Rate Under Regime Shifts," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 566-578, October.
    • Handle: RePEc:taf:jnlbes:v:33:y:2015:i:4:p:566-578
    DOI: 10.1080/07350015.2014.979995
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    Cited by:

    1. Yacouba Boubacar Maïnassara & Landy Rabehasaina, 2020. "Estimation of weak ARMA models with regime changes," Statistical Inference for Stochastic Processes, Springer, vol. 23(1), pages 1-52, April.
    2. Zhao-Hua Lu & Sy-Miin Chow & Nilam Ram & Pamela M. Cole, 2019. "Zero-Inflated Regime-Switching Stochastic Differential Equation Models for Highly Unbalanced Multivariate, Multi-Subject Time-Series Data," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 611-645, June.
    3. Roberto Casarin & Domenico Sartore & Marco Tronzano, 2018. "A Bayesian Markov-Switching Correlation Model for Contagion Analysis on Exchange Rate Markets," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 101-114, January.

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