Granger Causality Test in the Presence of Spillover Effects

被引:5
|
作者
Mansson, Kristofer [1 ,2 ]
Shukur, Ghazi [1 ,2 ,3 ]
机构
[1] Jonkoping Univ, Dept Econ, Jonkoping, Sweden
[2] Jonkoping Univ, Dept Stat, Jonkoping, Sweden
[3] Vaxjo Univ, Ctr Labour Market Policy Res CAFO, Vaxjo, Sweden
关键词
GARCH; Granger causality test; Power; Size; Spillover; HETEROSKEDASTICITY;
D O I
10.1080/03610910903243695
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this article, we investigate the effect of spillover (i.e., causality in variance) on the reliability of Granger causality test based on ordinary least square estimates. We studied eight different versions of the test both, with and without Whites heteroskedasticity consistent covariance matrix (HCCME). The properties of the tests are investigated by means of a Monte Carlo experiment where 21 different data generating processes (DGP) are used and a number of factors that might affect the test are varied. The result shows that the best choice to test for Granger causality under the presence of spillover is the Lagrange Multiplier test with HCCME.
引用
收藏
页码:2039 / 2059
页数:21
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