|
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.
|