Multivariate causality tests with simulation and application

Zhidong Bai, Heng Li, Wing-Keung Wong*, Bingzhi Zhang

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

34 Citations (Scopus)
15 Downloads (Pure)


This paper extends the test established by Hiemstra and Jones (1994) to develop a nonlinear causality test in a multivariate setting. A Monte Carlo simulation is conducted to demonstrate the superiority of our proposed multivariate test over its bivariate counterpart. In addition, we illustrate the applicability of our proposed test for analyzing the relationships among different Chinese stock market indices.

Original languageEnglish
Pages (from-to)1063-1071
Number of pages9
JournalStatistics and Probability Letters
Issue number8
Early online date2 Mar 2011
Publication statusPublished - Aug 2011

Scopus Subject Areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

User-Defined Keywords

  • Linear Granger causality
  • Nonlinear Granger causality
  • U-statistics
  • Simulation
  • Stock markets


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