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

Author

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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.

Suggested Citation

  • Jushan Bai, 1999. "Vector Autoregressive Models with Structural Changes in Regression Coefficients and in Variance-Covariance Matrices," CEMA Working Papers 24, China Economics and Management Academy, Central University of Finance and Economics, revised Oct 2000.
    • Handle: RePEc:cuf:wpaper:24
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    Keywords

    Structural change; Multiple change points; QMLE; VAR; BIC;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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