@techreport{Hafner2004Testing,
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.},
author = {Christian M. Hafner and Helmut Herwartz},
copyright = {http://www.econstor.eu/dspace/Nutzungsbedingungen},
keywords = {C52; C22; 330; causality; multivariate volatility; local power; ARCH-Modell; Kausalanalyse; Statistischer Test; Varianzanalyse; Theorie},
language = {eng},
note = {urn:nbn:de:101:1-200911033770},
number = {2004,03},
title = {Testing for Causality in Variance using Multivariate GARCH Models},
type = {Economics working paper / Christian-Albrechts-Universit\"{a}t Kiel, Department of Economics},
url = {http://hdl.handle.net/10419/21980},
year = {2004}
}
