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On the Use of Canonical Correlation Analysis in Testing Common Trends

In: Modelling and Prediction Honoring Seymour Geisser

Author

Listed:
  • N. H. Chan

    (Carnegie Mellon University, Department of Statistics)

  • Ruey S. Tsay

    (University of Chicago, Graduate School of Business)

Abstract

Motivated by the asymptotic uncorrelatedness between the stationary and nonstationary components of a vector time series, a statistic is constructed from the canonical correlations of these components to test for the number of common trends and, hence, the presence of co-integration. For univariate series, such a test statistic possesses direct relationships with the classical Dickey-Fuller test. An iterative testing procedure is then proposed which can handle unit roots of higher multiplicities as well as seasonal co-integrations. In applications, both bootstrap and simulation are used to obtain the empirical critical values of the test statistic. The proposed procedure is illustrated by two real examples.

Suggested Citation

  • N. H. Chan & Ruey S. Tsay, 1996. "On the Use of Canonical Correlation Analysis in Testing Common Trends," Springer Books, in: Jack C. Lee & Wesley O. Johnson & Arnold Zellner (ed.), Modelling and Prediction Honoring Seymour Geisser, pages 364-377, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4612-2414-3_23
    DOI: 10.1007/978-1-4612-2414-3_23
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