Robust Regression in Stata

In regression analysis, the presence of outliers in the data set can strongly distort the classical least squares estimator and lead to un- reliable 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 ef- fective robust estimators that we implemented in Stata. We also present a graphical tool that allows recognizing the type of detected outliers.