Multivariate Linear and Non-Linear Causality Tests

25 Pages Posted: 22 May 2009 Last revised: 22 Jul 2010

See all articles by Zhidong Bai

Zhidong Bai

Northeast Normal University

Bingzhi Zhang

Columbia University-Department of BioStatistics

Wing-Keung Wong

Asia University, Department of Finance

Date Written: May 22, 2009

Abstract

The traditional linear Granger test has been widely used to examine the linear causality among several time series in bivariate settings as well as multivariate settings. Hiemstra and Jones (1994) develop a nonlinear Granger causality test in a bivariate setting to investigate the nonlinear causality between stock prices and trading volume. In this paper, we first discuss linear causality tests in multivariate settings and thereafter develop a non-linear causality test in multivariate settings.

Keywords: linear Granger, causality, nonlinear Granger causality, U-statistics

JEL Classification: C01, C12, G10

Suggested Citation

Bai, Zhidong and Zhang, Bingzhi and Wong, Wing-Keung, Multivariate Linear and Non-Linear Causality Tests (May 22, 2009). Available at SSRN: https://ssrn.com/abstract=1408542 or http://dx.doi.org/10.2139/ssrn.1408542

Zhidong Bai

Northeast Normal University ( email )

Changchun
China

Bingzhi Zhang

Columbia University-Department of BioStatistics ( email )

3022 Broadway
New York, NY 10027
United States

Wing-Keung Wong (Contact Author)

Asia University, Department of Finance ( email )

Taiwan
Taiwan

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