Extreme canonical correlations and high-dimensional cointegration analysis

Alexei Onatski () and Chen Wang

Journal of Econometrics, 2019, vol. 212, issue 1, 307-322

Abstract: We prove that the extreme squared sample canonical correlations between a random walk and its own innovations almost surely converge to the upper and lower boundaries of the support of the Wachter distribution when the sample size and the dimensionality go to infinity proportionally. This result is used to derive previously unknown analytic expressions for the Bartlett-type correction coefficients for Johansen’s trace and maximum eigenvalue tests in a high-dimensional VAR(1). An analysis of cointegration among a large number of log exchange rates illustrates the usefulness of our theoretical results.

Keywords: High-dimensional cointegration; Extreme canonical correlations; Trace statistic; Maximum eigenvalue statistic; Bartlett correction (search for similar items in EconPapers)
JEL-codes: C32 C38 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (9)

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Working Paper: Extreme canonical correlations and high-dimensional cointegration analysis (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:212:y:2019:i:1:p:307-322

DOI: 10.1016/j.jeconom.2019.04.032

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