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dc.contributor.authorBayer, Christianen
dc.contributor.authorHanck, Christophen
dc.date.accessioned2009-05-19-
dc.date.accessioned2010-07-15T10:08:00Z-
dc.date.available2010-07-15T10:08:00Z-
dc.date.issued2008-
dc.identifier.urihttp://hdl.handle.net/10419/36613-
dc.description.abstractThis paper suggests a combination procedure to exploit the imperfect correlation of cointegration tests to develop a more powerful meta test. To exemplify, we combine Engle and Granger (1987) and Johansen (1988) tests. Either of these underlying tests can be more powerful than the other one depending on the nature of the data-generating process. The new meta test is at least as powerful as the more powerful one of the underlying tests irrespective of the very nature of the data generating process. At the same time, our new meta test avoids the size distortion inherent in separately applying multiple tests for cointegration to the same data set.en
dc.language.isoengen
dc.publisher|aTechnische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen |cDortmunden
dc.relation.ispartofseries|aTechnical Report |x2008,10en
dc.subject.jelC12en
dc.subject.jelC22en
dc.subject.ddc519en
dc.subject.keywordCointegrationen
dc.subject.keywordMeta Testen
dc.subject.keywordMultiple Testingen
dc.titleIs double trouble? How to combine cointegration tests-
dc.typeWorking Paperen
dc.identifier.ppn600066878en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:zbw:sfb475:200810en

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