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A New Ridge Regression Causality Test in the Presence of Multicollinearity
Jönköping University.
Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University. (Statistik)ORCID iD: 0000-0002-3416-5896
Jönköping University.
2014 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 43, no 2, p. 235-248Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Taylor & Francis, 2014. Vol. 43, no 2, p. 235-248
National Category
Probability Theory and Statistics
Research subject
Statistics/Econometrics
Identifiers
URN: urn:nbn:se:lnu:diva-17268DOI: 10.1080/03610926.2012.659825ISI: 000328930900002Scopus ID: 2-s2.0-84891588520OAI: oai:DiVA.org:lnu-17268DiVA, id: diva2:490152
Available from: 2012-02-03 Created: 2012-02-03 Last updated: 2019-08-07Bibliographically approved

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