Robustness for Dummies
Marjorie Gassner and
Darwin Ugarte ()
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Darwin Ugarte: Center for Research in the Economics of Development, University of Namur
No 1206, Working Papers from University of Namur, Department of Economics
In the robust statistics literature, a wide variety of models have been developed to cope with outliers in a rather large number of scenarios. Nevertheless, a recurrent problem for the empirical implementation of these estimators is that optimization algorithms generally do not perform well when dummy variables are present. What we propose in this poper is a simple solution to this involving the replacement of the sub-sampling step of the maximization procedure by a projection-based method. This allows us to propose robust estimators involving categorical variables, be they explanatory of dependent. Some Monte Carlo simulations are presented to illustrate the good behavior of the method.
Keywords: S-estimators; robust regression; dummy variable; outliers (search for similar items in EconPapers)
Pages: 27 pages
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http://www.fundp.ac.be/eco/economie/recherche/wpseries/wp/1206 First version, 2012 (application/pdf)
Working Paper: Robustness for dummies (2012)
Working Paper: Robustness for Dummies (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:nam:wpaper:1206
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