Parameter Estimation in Marketing Models in the Presence of Multicollinearity: An Application of Ridge Regression

Abstract

In the presence of multicollinearity in data, the estimation of parameters or regression coefficients in marketing models by means of ordinary least squares may give inflated estimates with a high variance and wrong signs. The authors demonstrate the potential usefulness of the ridge regression analysis to handle multicollinearity in marketing data.