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Testing Instantaneous Causality in Presence of Nonconstant Unconditional Covariance

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NIAID Data Ecosystem2026-03-07 收录
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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.

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2015-01-26
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