I have read 10 but like any other rule of thumb its arbitrary.

As per Hair et al., 2016, the value should be below 5. When it exceeded from 5, there is the chances of collinearity. VIF value 10 or above means perfect collinearity.

Hi,

I found A Caution Regarding Rules of Thumb for Variance Inflation Factors (O’Brien, 2007) article helpful when I struggled with issue of VIF value.

Maybe it will be helpful for you.

A citation from abstract (O’Brien, 2007) :

"Unfortunately, several rules of thumb – most commonly the rule of 10 – associated with VIF are regarded by many practitioners as a sign of severe or serious multi-collinearity (this rule appears in both scholarly articles and advanced statistical textbooks). When VIF reaches these threshold values researchers often attempt to reduce the collinearity by eliminating one or more variables from their analysis; using Ridge Regression to analyze their data; or combining two or more independent variables into a single index. These techniques for curing problems associated with multi-collinearity can create problems more serious than those they solve. Because of this, we examine these rules of thumb and find that threshold values of the VIF (and tolerance) need to be evaluated in the context of several other factors that influence the variance of regression coefficients"

O’Brien, R. M. (2007). A Caution Regarding Rules of Thumb for Variance Inflation Factors. Quality & Quantity, 41(5), 673–690. https://doi.org/10.1007/s11135-006-9018-6

Article A Caution Regarding Rules of Thumb for Variance Inflation Factors

Thanks Konrad

VIF values of just over 1.0 are desirable, with the floor VIF value being 1.0. A VIF value of 1.007 would be considered very good and indicative of no collinearity.

https://quantifyinghealth.com/vif-threshold/

Thank you.