Title

A new test of multivariate nonlinear causality

Document Type

Journal article

Source Publication

PLoS ONE

Publication Date

1-1-2018

Volume

13

Issue

1

First Page

1

Last Page

14

Publisher

Public Library of Science

Abstract

The multivariate nonlinear Granger causality developed by Bai et al. (2010) (Mathematics and Computers in simulation. 2010; 81: 5-17) plays an important role in detecting the dynamic interrelationships between two groups of variables. Following the idea of Hiemstra-Jones (HJ) test proposed by Hiemstra and Jones (1994) (Journal of Finance. 1994; 49(5): 1639-1664), they attempt to establish a central limit theorem (CLT) of their test statistic by applying the asymptotical property of multivariate U-statistic. However, Bai et al. (2016) (2016; arXiv: 1701.03992) revisit the HJ test and find that the test statistic given by HJ is NOT a function of U-statistics which implies that the CLT neither proposed by Hiemstra and Jones (1994) nor the one extended by Bai et al. (2010) is valid for statistical inference. In this paper, we re-estimate the probabilities and reestablish the CLT of the new test statistic. Numerical simulation shows that our new estimates are consistent and our new test performs decent size and power.

DOI

10.1371/journal.pone.0185155

E-ISSN

19326203

Publisher Statement

Copyright © 2018 Bai et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Access to external full text or publisher's version may require subscription.

Full-text Version

Publisher’s Version

Language

English

Recommended Citation

Bai, Z., Hui, Y., Jiang, D., Lv, Z., Wong, W.-K., & Zheng, S. (2018). A new test of multivariate nonlinear causality. PLoS ONE, 13(1), 1-14. doi: 10.1371/journal.pone.0185155

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