No Need to Run Millions of Regressions
17 Pages Posted: 5 Nov 2000
Date Written: April 2000
We argue that in modelling cross-country growth models one should first identify so-called outlying observations. For the data set of Sala-i-Martin, we use the least median of squares (LMS) estimator to identify outliers. As LMS is not suited for inference, we then use reweighted least squares (RLS) for our cross-country growth models. We identify 27 variables that are significantly related to economic growth. Subsequently, applying Sala-i- Martin?s approach for 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.
Keywords: Sensitivity analysis, outliers, economic growth
JEL Classification: O4, C21, C52
Suggested Citation: Suggested Citation