Is Double Trouble? How to Combine Cointegration Tests

27 Pages Posted: 19 May 2008 Last revised: 20 May 2008

See all articles by Christian Bayer

Christian Bayer

Bocconi University

Christoph Hanck

University of Dortmund - Department of Statistics

Date Written: May 13, 2008

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 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 arbitrary decision which test to use if single test results conflict. Moreover it avoids the size distortion inherent in separately applying multiple tests for cointegration to the same data set. We apply our test to 143 data sets from published cointegration studies. There, in one third of all cases single tests give conflicting results whereas our meta tests provides an unambiguous test decision.

Keywords: Cointegration, Meta Test, Multiple Testing

JEL Classification: C12, C22

Suggested Citation

Bayer, Christian and Hanck, Christoph, Is Double Trouble? How to Combine Cointegration Tests (May 13, 2008). Ruhr Economic Papers No. 48, Available at SSRN: https://ssrn.com/abstract=1133444 or http://dx.doi.org/10.2139/ssrn.1133444

Christian Bayer (Contact Author)

Bocconi University ( email )

Via Sarfatti, 25
Milan, MI 20136
Italy

Christoph Hanck

University of Dortmund - Department of Statistics ( email )

D-44221 Dortmund
Germany

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