Summary In empirical studies often the values of some variables for some observations are much larger or smaller than the values for the other observations in the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses. Conclusions based...

The analysis of the empirical distribution of univariate data often includes the computation of location, scale, skewness, and tail-heaviness measures, which are estimates of specific parameters of the underlying population distribution. Several measures are available, but they differ by...

We define a new boxplot that can deal with skewed and/or heavy-tailed distributions and possible outliers. The methodology relies on a rank-preserving transformation that allows to fit a so-called Tukey   g   -and-h   distribution.

Using Baltagi and Li (2002)’s semi-parametric fixed effects regression estimator, we investigate the existence of an aggregate ‘Kuznets curve’ in a sample of 113 countries over the 1960–2000 period. Our results show that misspecification of the functional form in a panel model with...

In empirical studies often the values of some variables for some observations are much larger or smaller than the values for the other observations in the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses. Conclusions based on a...

In this article, we introduce a new Stata command, smultiv, that implements the S-estimator of multivariate location and scatter. Using simulated data, we show that smultiv outperforms mcd, an alternative robust estimator. Finally, we use smultiv to perform robust principal component analysis...

In this article, we describe http://www.stata-journal.com/software/Robinson’s (1988, Econometrica 56: 931– 954) double residual semiparametric regression estimator and H ̈ardle and Mam- men’s (1993, Annals of Statistics 21: 1926–1947) specification test implementation in Stata. We use...

F35, F22, C23 </AbstractSection> Copyright Ugarte Ontiveros and Verardi; licensee Springer. 2012

In regression analysis, classical estimations may be excessively influenced by a few atypical observations. We propose a Hausman-type test to balance robustness and efficiency and to check whether a robust method should be implemented. An economic application is presented.