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Identify regimes in post-war US GDP growth

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  • Yu Jiang
  • Xianming Fang

Abstract

This article attempts to simultaneously investigate different regimes in both mean and volatility of post-war US GDP growth using a four-regime Bayesian Markov switching model. Bayesian approach suffers from the label switching problem that leads to the failure of identifying regimes. We introduce two methods to deal with the label switching problem in posterior simulations of parameters. The four regimes identified by either of the two methods capture different characteristics in mean and volatility of US GDP growth.

Suggested Citation

  • Yu Jiang & Xianming Fang, 2014. "Identify regimes in post-war US GDP growth," Applied Economics Letters, Taylor & Francis Journals, vol. 21(6), pages 397-401, April.
    • Handle: RePEc:taf:apeclt:v:21:y:2014:i:6:p:397-401
    DOI: 10.1080/13504851.2013.861582
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    References listed on IDEAS

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    1. Matthew Stephens, 2000. "Dealing with label switching in mixture models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 795-809.
    2. 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 357-384, March.
    3. Geweke, John, 2007. "Interpretation and inference in mixture models: Simple MCMC works," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3529-3550, April.
    4. Geweke, John & Jiang, Yu, 2011. "Inference and prediction in a multiple-structural-break model," Journal of Econometrics, Elsevier, vol. 163(2), pages 172-185, August.
    5. Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November.
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