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Title:Testing for Causality in Variance using Multivariate GARCH Models PDF Logo
Authors:Hafner, Christian M.
Herwartz, Helmut
Issue Date:2004
Series/Report no.:Economics working paper / Christian-Albrechts-Universität Kiel, Department of Economics 2004,03
Abstract:Tests of causality in variance in multiple time series have been proposed recently, based on residuals of estimated univariate models. Although such tests are applied frequently little is known about their power properties. In this paper we show that a convenient alternative to residual based testing is to specify a multivariate volatility model, such as multivariate GARCH (or BEKK), and construct a Wald test on noncausality in variance. We compare both approaches to testing causality in variance in terms of asymptotic and finite sample properties. The Wald test is shown to have superior power properties under a sequence of local alternatives. Furthermore, we show by simulation that the Wald test is quite robust to misspecification of the order of the BEKK model, but that empirical power decreases substantially when asymmetries in volatility are ignored.
Subjects:causality
multivariate volatility
local power
JEL:C52
C22
Persistent Identifier of the first edition:urn:nbn:de:101:1-200911033770
Document Type:Working Paper
Appears in Collections:Economics Working Papers, Department of Economics, CAU Kiel

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