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Vector Autoregressive Models with Structural Changes in Regression Coefficients and in Variance-Covariance Matrices

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  • Jushan Bai

    ()
    (Department of Economics, Boston College)

Abstract

This paper analyzes vector autoregressive models (VAR) with multiple structural changes. One distinct feature of this paper is the explicit consideration of structural changes in the variance-covariance matrix, in addition to changes in the autoregressive coefficients. The model is estimated by the quasi-maximum likelihood method. It is shown that shifts in the covariance matrix help identify the change points. We obtain consistency, rate of convergence, and limiting distributions for the estimated change points and the estimated regression coefficients and variance-covariance matrix. We also show that the number of change points can be consistently estimated via the information criterion approach. The paper provides tools for constructing confidence intervals for change points in multiple time series. The result is also useful for analyzing volatility changes in economic time series.

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Bibliographic Info

Article provided by Society for AEF in its journal Annals of Economics and Finance.

Volume (Year): 1 (2000)
Issue (Month): 2 (November)
Pages: 303-339

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Handle: RePEc:cuf:journl:y:2000:v:1:i:2:p:303-339

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Keywords: Structural change; Multiple change points; QMLE; VAR; BIC;

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Cited by:
  1. Eiji Kurozumi & Purevdorj Tuvaandorj, 2010. "Model Selection Criteria in Multivariate Models with Multiple Structural Changes," Global COE Hi-Stat Discussion Paper Series gd10-144, Institute of Economic Research, Hitotsubashi University.
  2. Luca Benati, 2004. "Evolving post-World War II UK economic performance," Bank of England working papers 232, Bank of England.
  3. Bertrand Candelon & Gianluca Cubadda, 2006. "Testing for Parameter Stability in Dynamic Models Across Frequencies," CEIS Research Paper 82, Tor Vergata University, CEIS.
  4. Brian M. Doyle & Jon Faust, 2005. "Breaks in the Variability and Comovement of G-7 Economic Growth," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 721-740, November.
  5. Pierre Perron & Yohei Yamamoto, 2008. "Estimating and Testing Multiple Structural Changes in Models with Endogenous Regressors," Boston University - Department of Economics - Working Papers Series wp2008-017, Boston University - Department of Economics.
  6. Pitarakis, Jean-Yves, 2014. "A joint test for structural stability and a unit root in autoregressions," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 577-587.
  7. Oka, Tatsushi & Qu, Zhongjun, 2011. "Estimating structural changes in regression quantiles," Journal of Econometrics, Elsevier, vol. 162(2), pages 248-267, June.
  8. Paye, Bradley S. & Timmermann, Allan, 2006. "Instability of return prediction models," Journal of Empirical Finance, Elsevier, vol. 13(3), pages 274-315, June.
  9. Zijun Wang, 2006. "The joint determination of the number and the type of structural changes," Economics Letters, Elsevier, vol. 93(2), pages 222-227, November.
  10. Otavio Ribeiro de Medeiros and Vitor Leone, 2012. "Multiple Changes in Persistence vs. Explosive Behaviour: The Dotcom Bubble," Working Papers 2012/02, Nottingham Trent University, Nottingham Business School, Economics Division.
  11. Chen, Gongmeng & Choi, Yoon K. & Zhou, Yong, 2005. "Nonparametric estimation of structural change points in volatility models for time series," Journal of Econometrics, Elsevier, vol. 126(1), pages 79-114, May.
  12. Loredana Ureche-Rangau & Franck Speeg, 2011. "A simple method for variance shift detection at unknown time points," Economics Bulletin, AccessEcon, vol. 31(3), pages 2204-2218.
  13. Pierre Perron & Jing Zhou, 2008. "Testing Jointly for Structural Changes in the Error Variance and Coefficients of a Linear Regression Model," Boston University - Department of Economics - Working Papers Series wp2008-011, Boston University - Department of Economics.

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