The problem of testing instantaneous causality in the important case where the unconditional covariance is time-varying is considered. It is underlined that the standard test does not control the Type I errors, while the tests with White (Ref. 1) and heteroscedastic autocorrelation consistent (HAC) corrections can suffer from a severe loss of power when the covariance is not constant. It is found that the Wald tests based on the assumption of constant unconditional covariance may have no power in this nonstandard framework. Therefore, in this article a modified test based on a bootstrap procedure is proposed. The relevance of the modified test is illustrated through a simulation study. The tests considered in this article are also compared by investigating the instantaneous causality relations between U.S. macroeconomic variables. It is shown that the tests based on the stationary assumption are outperformed by the bootstrap test. The outcomes obtained from macroeconomic datasets suggest that the classical Wald tests may deliver results which are quite different from the bootstrap test. (53 refs.)
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