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Erscheinungsjahr: 
2020
Schriftenreihe/Nr.: 
Hannover Economic Papers (HEP) No. 676
Verlag: 
Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, Hannover
Zusammenfassung: 
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.
Schlagwörter: 
Multivariate Long Memory
Multiple Structural Breaks
Hypothesis Testing
JEL: 
C12
C22
C58
G15
Dokumentart: 
Working Paper

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