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The corrected VIF (CVIF)

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  • Jos� Dias Curto
  • Jos� Castro Pinto

Abstract

In this paper, we propose a new corrected variance inflation factor (VIF) measure to evaluate the impact of the correlation among the explanatory variables in the variance of the ordinary least squares estimators. We show that the real impact on variance can be overestimated by the traditional VIF when the explanatory variables contain no redundant information about the dependent variable and a corrected version of this multicollinearity indicator becomes necessary.

Suggested Citation

  • Jos� Dias Curto & Jos� Castro Pinto, 2011. "The corrected VIF (CVIF)," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(7), pages 1499-1507, June.
    • Handle: RePEc:taf:japsta:v:38:y:2011:i:7:p:1499-1507
    DOI: 10.1080/02664763.2010.505956
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    References listed on IDEAS

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    1. José Dias Curto & José Castro Pinto, 2007. "New Multicollinearity Indicators in Linear Regression Models," International Statistical Review, International Statistical Institute, vol. 75(1), pages 114-121, April.
    2. Spanos, Aris & McGuirk, Anya, 2002. "The problem of near-multicollinearity revisited: erratic vs systematic volatility," Journal of Econometrics, Elsevier, vol. 108(2), pages 365-393, June.
    3. Terry Gleason & Richard Staelin, 1975. "A proposal for handling missing data," Psychometrika, Springer;The Psychometric Society, vol. 40(2), pages 229-252, June.
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