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A Bayesian Analysis of Unit Roots and Structural Breaks in the Level, Trend, and Error Variance of Autoregressive Models of Economic Series

Author

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  • Loukia Meligkotsidou
  • Elias Tzavalis
  • Ioannis Vrontos

Abstract

In this article, a Bayesian approach is suggested to compare unit root models with stationary autoregressive models when the level, the trend, and the error variance are subject to structural changes (known as breaks) of an unknown date. Ignoring structural breaks in the error variance may be responsible for not rejecting the unit root hypothesis, even if allowance is made in the inferential procedures for breaks in the mean. The article utilizes analytic and Monte Carlo integration techniques for calculating the marginal likelihoods of the models under consideration, in order to compute the posterior model probabilities. The performance of the method is assessed by simulation experiments. Some empirical applications of the method are conducted with the aim to investigate if it can detect structural breaks in financial series, especially with changes in the error variance.

Suggested Citation

  • Loukia Meligkotsidou & Elias Tzavalis & Ioannis Vrontos, 2011. "A Bayesian Analysis of Unit Roots and Structural Breaks in the Level, Trend, and Error Variance of Autoregressive Models of Economic Series," Econometric Reviews, Taylor & Francis Journals, vol. 30(2), pages 208-249.
    • Handle: RePEc:taf:emetrv:v:30:y:2011:i:2:p:208-249
    DOI: 10.1080/07474938.2011.534046
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    Citations

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    Cited by:

    1. Karavias, Yiannis & Tzavalis, Elias, 2013. "The Power Performance of Fixed-T Panel Unit Root Tests allowing for Structural Breaks," MPRA Paper 46012, University Library of Munich, Germany.
    2. Varun Agiwal & Jitendra Kumar, 2020. "Bayesian estimation for threshold autoregressive model with multiple structural breaks," METRON, Springer;Sapienza Università di Roma, vol. 78(3), pages 361-382, December.
    3. Yiannis Karavias & Elias Tzavalis, 2017. "Local power of panel unit root tests allowing for structural breaks," Econometric Reviews, Taylor & Francis Journals, vol. 36(10), pages 1123-1156, November.
    4. Loukia Meligkotsidou & Elias Tzavalis & Ioannis D. Vrontos, 2012. "A Bayesian panel data framework for examining the economic growth convergence hypothesis: do the G7 countries converge?," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 1975-1990, May.

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