Department of Economics
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.
Linear Granger causality, Nonlinear Granger causality, U-statistics, Simulation, Stock markets
Source Publication Title
Statistics & Probability Letters
Link to Publisher's Edition
Bai, Z., Wong, W., & Zhang, B. (2011). Multivariate causality tests with simulation and application. Statistics & Probability Letters, 81 (8). https://doi.org/10.1016/j.spl.2011.02.031