Testing Instantaneous Causality in Presence of Nonconstant Unconditional Covariance

Quentin Giai Gianetto and Hamdi Raïssi

Journal of Business & Economic Statistics, 2015, vol. 33, issue 1, 46-53

Abstract: This article investigates the problem of testing instantaneous causality between vector autoregressive (VAR) variables with time-varying unconditional covariance. It is underlined that the standard test does not control the Type I errors, while the tests with White and heteroscedastic autocorrelation consistent (HAC) corrections can suffer from a severe loss of power when the covariance is not constant. Consequently, we propose a modified test based on a bootstrap procedure. We illustrate the relevance of the modified test through a simulation study. The tests considered in this article are also compared by investigating the instantaneous causality relations between U.S. macroeconomic variables.

Date: 2015
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DOI: 10.1080/07350015.2014.920614

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