A New Ridge Regression Causality Test in the Presence of Multicollinearity |
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Authors: | Kristofer Månsson Ghazi Shukur |
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Affiliation: | 1. Department of Economics and Statistics , J?nk?ping University , Sweden;2. Department of Economics and Statistics , J?nk?ping University , Sweden;3. Department of Economics and Statistics , Linnaeus University , Sweden |
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Abstract: | The VAR lag structure applied for the traditional Granger causality (GC) test is always severely affected by multicollinearity due to autocorrelation among the lags. Therefore, as a remedy to this problem we introduce a new Ridge Regression Granger Causality (RRGC) test, which is compared to the GC test by means of Monte Carlo simulations. Based on the simulation study we conclude that the traditional OLS version of the GC test over-rejects the true null hypothesis when there are relatively high (but empirically normal) levels of multicollinearity, while the new RRGC test will remedy or substantially decrease this problem. |
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Keywords: | Granger causality test Multicollinearity Ridge parameters Size and power |
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