Robust Regression in Stata
14 Pages Posted: 27 Mar 2009
Date Written: October 2008
In regression analysis, the presence of outliers in the data set can strongly distort the classical least squares estimator and lead to unreliable results. To deal with this, several robust-to-outliers methods have been proposed in the statistical literature. In Stata, some of these methods are available through the commands rreg and qreg. Unfortunately, these methods only resist to some specific types of outliers and turn out to be ineffective under alternative scenarios. In this paper we present more effective robust estimators that we implemented in Stata. We also present a graphical tool that allows recognizing the type of existing outliers.
Keywords: S-estimators, MM-estimators, Outliers, Robustness
JEL Classification: C12, C21, C87
Suggested Citation: Suggested Citation