HUI Working Papers, HUI Research
Kristofer Månsson, Ghazi Shukur
A New Ridge Regression Causality Test in the Presence of Multicollinearity
() and Pär Sjölander
Abstract: This paper analyzes and compares the properties of the
most commonly applied versions of the Granger causality (GC) test to a new
ridge regression GC test (RRGC), in the presence of multicollinearity. The
investigation has been carried out using Monte Carlo simulations. A large
number of models have been investigated where the number of observations,
strength of collinearity, and data generating processes have been varied.
For each model we have performed 10000 replications and studied seven
different versions of the test. The main conclusion from our study is that
the traditional OLS version of the GC test over-rejects the true null
hypothesis when there are relatively high (but empirically common levels
of) multicollinearity, while it is established that the new RRGC test will
remedy or substantially decrease this problem.
Keywords: Granger causality test; multicollinearity; ridge parameters; size and power; (follow links to similar papers)
JEL-Codes: C32; (follow links to similar papers)
17 pages, February 1, 2010
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