A1924
Title: Testing for multiple structural breaks in multivariate long memory regression models
Authors: Vivien Less - Leibniz Universitaet Hannover (Germany) [presenting]
Philipp Sibbertsen - University of Hannover (Germany)
Abstract: Estimation and testing of multiple breaks are considered that occur at unknown dates in multivariate long-memory time series regression and allow for the possibility of a cointegrated system. A likelihood ratio-based approach is proposed for estimating breaks in the regression parameter and the covariance of a system of long-memory time series regression. The limiting distribution of these estimates as well as the consistency of the estimators are derived. A testing procedure to determine the unknown number of breakpoints is given based on iterative testing on the regression residuals. A Monte Carlo exercise shows the finite sample performance of the method.
