No need to run millions of regressions - Sturm, Jan-Egbert,Haan, Jakob de (Univ., Center for Economic Studies, 2000)
The authors argue that in modelling cross-country growth models one should first identify so-called outlying observations. For the data set of Sali-i-Martin, they use the least median of squares (LMS) estimator to identify outliers. As LMS is not suited for inference, they then use reweighted least squares (RLS) for their cross-country growth models. They identify 27 variables that are significantly related to economic growth. Subsequently, applying Sala-i-Martin's approach to the data set without outliers hardly reveals any additional information. Variables that are insignificant according to the RLS method are generally not significantly related to economic growth under the Sala-i-Martin approach.
Auch im Internet unter der Adresse ftp://129.187.96.124/CESifo_WP/288.pdf verfügbar
Keywords: Arbeitspapier; Graue Literatur; Regressionsanalyse; Sensitivitätsanalyse; Wirtschaftswachstum; Theorie; Welt; Outlier