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
