Multivariate out-of-sample tests for Granger causality

Authors:
Sarah Gelper;Christophe Croux
Affiliations:
K.U.Leuven, Faculty of Economics and Applied Economics, Naamsestraat 69, 3000 Leuven, Belgium;K.U.Leuven, Faculty of Economics and Applied Economics, Naamsestraat 69, 3000 Leuven, Belgium
Venue:
Computational Statistics & Data Analysis
Year:
2007

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Abstract

A time series is said to Granger cause another series if it has incremental predictive power when forecasting it. While Granger causality tests have been studied extensively in the univariate setting, much less is known for the multivariate case. Multivariate out-of-sample tests for Granger causality are proposed and their performance is measured by a simulation study. The results are graphically represented by size-power plots. It emerges that the multivariate regression test is the most powerful among the considered possibilities. As a real data application, it is investigated whether the consumer confidence index Granger causes retail sales in Germany, France, the Netherlands and Belgium.