Markov-Switching Models with Evolving Regime-Specific Parameters: Are Post-War Booms or Recessions All Alike?
In this paper, we relax the assumption of constant regime-specific mean growth rates in Hamilton's (1989) two-state Markov-switching model of the business cycle. We first present a benchmark model, in which each regime-specific mean growth rate evolves according to a random walk process over different episodes of booms or recessions. We then present a model with vector error correction dynamics for the regime-specific mean growth rates, by deriving and imposing a condition for the existence of a long-run equilibrium growth rate for real output. In the Bayesian Markov Chain Monte Carlo (MCMC) approach developed in this paper, the counterfactual priors, as well as the hierarchical priors for the regime-specific parameters, play critical roles. By applying the proposed approach to postwar U.S. real GDP growth (1947:Q4-2011:Q3), we uncover the evolving nature of the regime-specific mean growth rates of real output in the U.S. business cycle. An additional feature of the postwar U.S. business cycle that we uncover is a steady decline in the long-run equilibrium output growth. The decline started in the 1950s and ended in the 2000s. Our empirical results also provide partial, if not decisive, evidence that the central bank may have been more successful in restoring the economy back to its long-run equilibrium growth path after unusually severe recessions than after unusually good booms.
|Date of creation:||Feb 2012|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: 61 +2 9351 5055
Fax: 61 +2 9351 4341
Web page: http://sydney.edu.au/arts/economics
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Sangjoon Kim, Neil Shephard & Siddhartha Chib, .
"Stochastic volatility: likelihood inference and comparison with ARCH models,"
W26, revised version of W, Economics Group, Nuffield College, University of Oxford.
- Kim, Sangjoon & Shephard, Neil & Chib, Siddhartha, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," Review of Economic Studies, Wiley Blackwell, vol. 65(3), pages 361-93, July.
- Sangjoon Kim & Neil Shephard, 1994. "Stochastic volatility: likelihood inference and comparison with ARCH models," Economics Papers 3., Economics Group, Nuffield College, University of Oxford.
- Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1996. "Stochastic Volatility: Likelihood Inference And Comparison With Arch Models," Econometrics 9610002, EconWPA.
- Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
- Gary Koop & Simon M. Potter, 2007. "Estimation and Forecasting in Models with Multiple Breaks," Review of Economic Studies, Oxford University Press, vol. 74(3), pages 763-789.
- Giordani, Paolo & Kohn, Robert, 2006.
"Efficient Bayesian Inference for Multiple Change-Point and Mixture Innovation Models,"
Working Paper Series
196, Sveriges Riksbank (Central Bank of Sweden).
- Giordani, Paolo & Kohn, Robert, 2008. "Efficient Bayesian Inference for Multiple Change-Point and Mixture Innovation Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 66-77, January.
- Pesaran, M. Hashem & Pettenuzzo, Davide & Timmermann, Allan, 2004.
"Forecasting Time Series Subject to Multiple Structural Breaks,"
IZA Discussion Papers
1196, Institute for the Study of Labor (IZA).
- M. Hashem Pesaran & Davide Pettenuzzo & Allan Timmermann, 2006. "Forecasting Time Series Subject to Multiple Structural Breaks," Review of Economic Studies, Oxford University Press, vol. 73(4), pages 1057-1084.
- M. Hashem Pesaran & Davide Pettenuzzo & Allan Timmermann, 2004. "Forecasting Time Series Subject to Multiple Structural Breaks," CESifo Working Paper Series 1237, CESifo Group Munich.
- Pesaran, M Hashem & Pettenuzzo, Davide & Timmermann, Allan G, 2004. "Forecasting Time Series Subject to Multiple Structural Breaks," CEPR Discussion Papers 4636, C.E.P.R. Discussion Papers.
- Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2004. "‘Forecasting Time Series Subject to Multiple Structural Breaks’," Cambridge Working Papers in Economics 0433, Faculty of Economics, University of Cambridge.
- 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.
- 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.
- Olivier J. Blanchard & Mark W. Watson, 1987.
"Are Business Cycles All Alike?,"
NBER Working Papers
1392, National Bureau of Economic Research, Inc.
When requesting a correction, please mention this item's handle: RePEc:syd:wpaper:2123/8150. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Vanessa Holcombe)
If references are entirely missing, you can add them using this form.