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

  • Chang-Jin Kim

    ()

    (Department of Economics, University ofWashington, and Department of Economics, Korea University)

  • Jaeho Kim

    ()

    (Dept. of Economics, Univ. of Washington, Seattle, WA)

One goal of this paper is to develop an efficient Markov-Chain Monte Carlo (MCMC) algorithm for estimating an ARMA model with a regime-switching mean, based on a multimove sampler. Unlike the existing algorithm of Billio et al. (1999) based on a single-move sampler, 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 argue Garcia and Perron¡¯s (1996) conclusion that the EARR rate is a constant subject to occasional jumps may be sample-specific. For an extended sample that includes recent data, Garcia and Perron¡¯s (1996) AR(2) model of EPRR may be misspecified,and we show that excluding the theory-implied moving-average terms may understate the persistence of the observed ex-post real interest rate (EPRR) dynamics. Our empiricalresults 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 including Garcia and Perron (1996).

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Paper provided by Institute of Economic Research, Korea University in its series Discussion Paper Series with number 1306.

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Date of creation: 2013
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Handle: RePEc:iek:wpaper:1306
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  1. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
  2. Albert, James H & Chib, Siddhartha, 1993. "Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 1-15, January.
  3. René Garcia & Pierre Perron, 1995. "An Analysis of the Real Interest Rate Under Regime Shifts," CIRANO Working Papers 95s-05, CIRANO.
  4. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1996. "Stochastic Volatility: Likelihood Inference And Comparison With Arch Models," Econometrics 9610002, EconWPA.
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  7. Rose, Andrew Kenan, 1988. " Is the Real Interest Rate Stable?," Journal of Finance, American Finance Association, vol. 43(5), pages 1095-1112, December.
  8. Rapach, David E. & Weber, Christian E., 2004. "Are real interest rates really nonstationary? New evidence from tests with good size and power," Journal of Macroeconomics, Elsevier, vol. 26(3), pages 409-430, September.
  9. Koustas, Z., Serletis, A., 1998. "On the Fisher Effect," Papers 98-09, Calgary - Department of Economics.
  10. Caporale, Tony & Grier, Kevin B, 2000. "Political Regime Change and the Real Interest Rate," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 32(3), pages 320-34, August.
  11. BAI, Jushan & PERRON, Pierre, 1998. "Computation and Analysis of Multiple Structural-Change Models," Cahiers de recherche 9807, Universite de Montreal, Departement de sciences economiques.
  12. Frederic S. Mishkin, 1991. "Is the Fisher Effect for Real? A Reexamination of the Relationship Between Inflation and Interest Rates," NBER Working Papers 3632, National Bureau of Economic Research, Inc.
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  14. Gali, Jordi, 1992. "How Well Does the IS-LM Model Fit Postwar U.S. Data," The Quarterly Journal of Economics, MIT Press, vol. 107(2), pages 709-38, May.
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  18. Fama, Eugene F, 1975. "Short-Term Interest Rates as Predictors of Inflation," American Economic Review, American Economic Association, vol. 65(3), pages 269-82, June.
  19. Crowder, William J & Hoffman, Dennis L, 1996. "The Long-Run Relationship between Nominal Interest Rates and Inflation: The Fisher Equation Revisited," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 28(1), pages 102-18, February.
  20. Cosslett, Stephen R. & Lee, Lung-Fei, 1985. "Serial correlation in latent discrete variable models," Journal of Econometrics, Elsevier, vol. 27(1), pages 79-97, January.
  21. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  22. Nakatsuma, Teruo, 2000. "Bayesian analysis of ARMA-GARCH models: A Markov chain sampling approach," Journal of Econometrics, Elsevier, vol. 95(1), pages 57-69, March.
  23. Scott S. L., 2002. "Bayesian Methods for Hidden Markov Models: Recursive Computing in the 21st Century," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 337-351, March.
  24. Antoncic, Madelyn, 1986. "High and Volatile Real Interest Rates: Where Does the Fed Fit In?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 18(1), pages 18-27, February.
  25. Billio, M. & Monfort, A. & Robert, C. P., 1999. "Bayesian estimation of switching ARMA models," Journal of Econometrics, Elsevier, vol. 93(2), pages 229-255, December.
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