Testing for Common Autocorrelation in Data Rich Environments
This paper proposes a strategy to detect the presence of common serial correlation in high-dimensional systems. We show by simulations that univariate autocorrelation tests on the factors obtained by partial least squares outperform traditional tests based on canonical correlations.
|Date of creation:||04 Dec 2009|
|Date of revision:||04 Dec 2009|
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- Jan J. J. Groen & George Kapetanios, 2008.
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- Gianluca Cubadda & Alain Hecq & Franz C. Palm, 2008.
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CEIS Research Paper
125, Tor Vergata University, CEIS, revised 14 Jul 2008.
- Cubadda, Gianluca & Hecq, Alain & Palm, Franz C., 2009. "Studying co-movements in large multivariate data prior to multivariate modelling," Journal of Econometrics, Elsevier, vol. 148(1), pages 25-35, January.
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Journal of Econometrics,
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