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Collinearity: revisiting the variance inflation factor in ridge regression

Author

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  • C.B. Garc�a
  • J. Garc�a
  • M.M. L�pez Mart�n
  • R. Salmer�n

Abstract

Ridge regression has been widely applied to estimate under collinearity by defining a class of estimators that are dependent on the parameter k . The variance inflation factor (VIF) is applied to detect the presence of collinearity and also as an objective method to obtain the value of k in ridge regression. Contrarily to the definition of the VIF, the expressions traditionally applied in ridge regression do not necessarily lead to values of VIFs equal to or greater than 1. This work presents an alternative expression to calculate the VIF in ridge regression that satisfies the aforementioned condition and also presents other interesting properties.

Suggested Citation

  • C.B. Garc�a & J. Garc�a & M.M. L�pez Mart�n & R. Salmer�n, 2015. "Collinearity: revisiting the variance inflation factor in ridge regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(3), pages 648-661, March.
    • Handle: RePEc:taf:japsta:v:42:y:2015:i:3:p:648-661
    DOI: 10.1080/02664763.2014.980789
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    Cited by:

    1. Salmerón Gómez, Román & Rodríguez Martínez, Eduardo, 2017. "Métodos cuantitativos para un modelo de regresión lineal con multicolinealidad. Aplicación a rendimientos de letras del tesoro || Quantitative Methods for a Linear Regression Model with Multicollinear," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 24(1), pages 169-189, Diciembre.
    2. Lei, Heng & Xue, Minggao & Liu, Huiling & Ye, Jing, 2023. "Precious metal as a safe haven for global ESG stocks: Portfolio implications for socially responsible investing," Resources Policy, Elsevier, vol. 80(C).

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