A new biased estimation method in tobit regression: theory and application

In this study, the effects of multicollinearity on the maximum likelihood estimator are analyzed in the tobit regression model. It is known that the near-linear dependencies in the design matrix affect the maximum likelihood estimation negatively, namely, the standard errors become so large so that the estimations are said to be inconsistent. Therefore, a new biased estimator being a generalization of the well-known Liu estimator is introduced …