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Inference and prediction in a multiple-structural-break model

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  • Geweke, John
  • Jiang, Yu

Abstract

This paper develops a new Bayesian approach to structural break modeling. The focuses of the approach are the modeling of in-sample structural breaks and forecasting time series allowing out-of-sample breaks. The model has several desirable features. First, the number of regimes is not fixed but is treated as a random variable. Second, the model adopts a hierarchical prior for regime coefficients, which allows for the coefficients of one regime to contain information about coefficients of other regimes. Third, the regime coefficients can be integrated analytically in the posterior density; as a consequence the posterior simulator is fast and reliable. An application to US real GDP quarterly growth rates links groups of regimes to specific historical periods and provides forecasts of future growth rates.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 163 (2011)
Issue (Month): 2 (August)
Pages: 172-185

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Handle: RePEc:eee:econom:v:163:y:2011:i:2:p:172-185

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Web page: http://www.elsevier.com/locate/jeconom

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Cited by:
  1. Maheu, John M. & Song, Yong, 2014. "A new structural break model, with an application to Canadian inflation forecasting," International Journal of Forecasting, Elsevier, vol. 30(1), pages 144-160.
  2. Maheu, John & Song, Yong, 2012. "A new structural break model with application to Canadian inflation forecasting," MPRA Paper 36870, University Library of Munich, Germany.
  3. Kaufmann Sylvia, 2011. "K-state switching models with endogenous transition distributions," Working Papers 2011-13, Swiss National Bank.
  4. Song, Yong & Shi, Shuping, 2012. "Identifying speculative bubbles with an in finite hidden Markov model," MPRA Paper 36455, University Library of Munich, Germany.
  5. Huang, MeiChi, 2014. "Bubble-like housing boom–bust cycles: Evidence from the predictive power of households’ expectations," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(1), pages 2-16.

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