Testing instantaneous causality in presence of non constant unconditional variance

Quentin Giai Gianetto (1) , Hamdi Raïssi (2)

1 ITI - Département Image et Traitement Information
2 IRMAR - Institut de Recherche Mathématique de Rennes

The problem of testing instantaneous causality between variables with time-varying unconditional variance is investigated. It is shown that the classical tests based on the assumption of stationary processes must be avoided in our non standard framework. More precisely we underline that the standard test does not control the type I errors, while the tests with White (1980) and Heteroscedastic Autocorrelation Consistent (HAC) corrections can suffer from a severe loss of power when the variance is not constant. Consequently a modified test based on a bootstrap procedure is proposed. The relevance of the modified test is underlined through a simulation study. The tests considered in this paper are also compared by investigating the instantaneous causality relations between US macroeconomic variables.

Mots clés: Instantaneous causality; Unconditionally heteroscedastic errors; VAR model

Domaines: Applications [stat.AP]; Méthodologie [stat.ME]

Quentin Giai Gianetto, Hamdi Raïssi. Testing instantaneous causality in presence of non constant unconditional variance. Journal of Business and Economic Statistics, 2015, 33 (1), pp.46-53. ⟨10.1080/07350015.2014.920614⟩. ⟨hal-00772479⟩