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

Jushan Bai

No 24, CEMA Working Papers from China Economics and Management Academy, Central University of Finance and Economics

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.

Keywords: Structural change; Multiple change points; QMLE; VAR; BIC (search for similar items in EconPapers)
JEL-codes: C12 C13 C22 C52 (search for similar items in EconPapers)
Pages: 37 pages
Date: 1999-11, Revised 2000-10
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Citations: View citations in EconPapers (69)

Published in Annals of Economics and Finance, Nov 2000, pages 303-339

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Journal Article: Vector Autoregressive Models with Structural Changes in Regression Coefficients and in Variance-Covariance Matrices (2000)
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Persistent link: https://EconPapers.repec.org/RePEc:cuf:wpaper:24

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