Collinearity diagnostic applied in ridge estimation through the variance inflation factor Salmerón Gómez, Román García Pérez, José López Martín, María Del Mar García García, Catalina Multicolinealidad Multicollinearity Multiple linear regression Collinearity Ridge Regression Multivariables The variance inflation factor (VIF) is used to detect the presence of linear relationships between two or more independent variables (i.e. collinearity) in the multiple linear regression model. However, the traditionally used VIF definitions encounter some problems when extended to the case of the ridge estimation (RE). This paper presents an extension of the VIF in RE by providing two alternative VIF expressions that overcome these problems in the general case. Some characteristics of these expressions are also presented and compared with the traditional expression. The results are illustrated with an economic example in the case of three independent variables and with a Monte Carlo simulation for the general case. 2024-02-29T09:16:43Z 2024-02-29T09:16:43Z 2016 journal article Published version: Roman Salmerón Gómez, José García Pérez, María Del Mar López Martín & Catalina García García (2016) Collinearity diagnostic applied in ridge estimation through the variance inflation factor, Journal of Applied Statistics, 43:10, 1831-1849. http://dx.doi.org/10.1080/02664763.2015.1120712 https://hdl.handle.net/10481/89669 10.1080/02664763.2015.1120712 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Taylor and Francis