Testing Instantaneous Causality in Presence of Nonconstant Unconditional Covariance

Quentin Giai Gianetto, Hamdi Raïssi

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


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.

Original languageEnglish
Pages (from-to)46-53
Number of pages8
JournalJournal of Business and Economic Statistics
Issue number1
StatePublished - 2 Jan 2015
Externally publishedYes


  • Unconditionally heteroscedastic errors
  • VAR model
  • Wild bootstrap


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