Is double trouble? How to combine cointegration tests
| dc.contributor.author | Bayer, Christian | |
| dc.contributor.author | Hanck, Christoph | |
| dc.date.accessioned | 2008-11-26T14:41:51Z | |
| dc.date.available | 2008-11-26T14:41:51Z | |
| dc.date.issued | 2008-11-26T14:41:51Z | |
| dc.description.abstract | This 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 un- derlying 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.identifier.uri | http://hdl.handle.net/2003/25873 | |
| dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-14131 | |
| dc.language.iso | en | de |
| dc.subject | Cointegration | en |
| dc.subject | Meta test | en |
| dc.subject | Multiple testing | en |
| dc.subject.ddc | 004 | |
| dc.title | Is double trouble? How to combine cointegration tests | en |
| dc.type | Text | de |
| dc.type.publicationtype | report | en |
| dcterms.accessRights | open access |