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A Time Series Model of Multiple Structural changes in Level, Trend and Variance

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Author Info

  • Jiahui Wang

    (MathSoft)

  • Eric Zivot

    (University of Washington)

Abstract

We consider a deterministically trending dynamic time series model in which multiple changes in level, trend and error variance are modeled explicitly and the number but not the timing of the changes are known. Estimation of the model is made possible by the use of the Gibbs sampler. The determination of the number of structural breaks and the form of structural change is considered as a problem of model selection and we compare the use of marginal likelihoods, posterior odds ratios and Schwarz' BIC model selection criterion to select the most appropriate model from the data. We evaluate the efficacy of the Bayesian approach using a small Monte Carlo experiment. As empirical examples, we investigate structural changes in the U.S. ex-post real interest rate and in a long time series of U.S. GDP.

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Bibliographic Info

Paper provided by EconWPA in its series Econometrics with number 9903002.

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Length: 13 pages
Date of creation: 24 Mar 1999
Date of revision: 31 Mar 1999
Handle: RePEc:wpa:wuwpem:9903002

Note: Type of Document - Adobe Acrobat; prepared on PC using TeX; to print on Postscript; pages: 13 ; figures: included
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Web page: http://128.118.178.162

Related research

Keywords: BIC; Gibbs sampling; multiple structural changes; posterior odds ratio;

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  1. Charles Engel & Chang-Jin Kim, 1996. "The Long-Run U.S./U.K. Real Exchange Rate," NBER Working Papers 5777, National Bureau of Economic Research, Inc.
  2. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-56, July.
  3. Jushan Bai, 1997. "Estimation Of A Change Point In Multiple Regression Models," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 551-563, November.
  4. Charles Engel & Craig S. Hakkio, 1994. "The Distribution of Exchange Rates in the EMS," NBER Working Papers 4834, National Bureau of Economic Research, Inc.
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