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Testing for Multiple Structural Breaks in Multivariate Long Memory Time Series

Autor: Philipp Sibbertsen and Kai Wenger and Simon Wingert
Nummer: 676, Nov 2020, pp. 51
JEL-Class: C12, C22, C58, G15

This paper considers estimation and testing of multiple breaks that occur at unknown dates in multivariate long-memory time series. We propose a likelihood ratio based approach for estimating breaks in the mean and the covariance of a system of long-memory time series. The limiting distribution of these estimates as well as consistency of the estimators is derived. A testing procedure to determine the unknown number of break points is given based on iterative testing on the regression residuals. A Monte Carlo exercise shows the finite sample performance of our method. An empirical application to inflation series illustrates the usefulness of our procedures.


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