Testing for a break in persistence under long-range dependencies
AbstractWe show that tests for a break in the persistence of a time series in the classical I(0) - I(1) framework have serious size distortions when the actual data generating process exhibits long-range dependencies. We prove that the limiting distribution of a CUSUM of squares based test depends on the true memory parameter if the DGP exhibits long memory. We propose adjusted critical values for the test and give finite sample response curves which allow the practitioner to easily implement the test and to compute the relevant critical values. We furthermore prove consistency of the test and prove consistency for a simple break point estimator also under long memory. We show that the test has satisfying power properties when the correct critical values are used.
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Bibliographic InfoPaper provided by Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät in its series Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät der Leibniz Universität Hannover with number dp-381.
Length: 23 pages
Date of creation: Nov 2007
Date of revision:
break in pesistence; long memory; CUSUM of squares based test;
Other versions of this item:
- Philipp Sibbertsen & Robinson Kruse, 2009. "Testing for a break in persistence under long-range dependencies," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(3), pages 263-285, 05.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-11-24 (All new papers)
- NEP-ECM-2007-11-24 (Econometrics)
- NEP-ETS-2007-11-24 (Econometric Time Series)
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