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Activity Number:
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137
- On Structural Changes
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Type:
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Invited
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Date/Time:
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Tuesday, August 4, 2020 : 10:00 AM to 11:50 AM
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Sponsor:
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Business and Economic Statistics Section
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Abstract #308158
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Title:
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Testing for Multiple Structural Breaks in Multivariate Long Memory Time Series
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Author(s):
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Philipp Sibbertsen* and Kai Wenger and Simon Wingert
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Companies:
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Leibniz Universitaet Hannover and Leibniz University of Hannover and Leibniz University of Hannover
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Keywords:
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Multivariate Long Memory;
Multiple Structural Breaks;
Hypothesis Testing
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Abstract:
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This paper considers estimation and testing of multiple unknown breaks 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 test to determine the unknown number of break points is given based on sequential testing on the regression residuals. A Monte Carlo exercise shows the finite sample performance of our method. An empirical application to real exchange rates is provided.
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Authors who are presenting talks have a * after their name.
