Stein-rule estimator under inclusion of superfluous variables in linear regression models

Abstract

Stein-rule estimation is a well-known method to improve the unbiased OLSE in the sense of smaller Mean-Square-Error. The paper is investigating the behaviour of this efficiency relation in case of misspecification of the linear model caused by inclusion of superfluous variables

Keywords:

• Regression
• Stein-rule estimation
• MSE-superiority