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| From | "JVerkuilen (Gmail)" <jvverkuilen@gmail.com> |
| To | statalist@hsphsun2.harvard.edu |
| Subject | Re: st: OLS assumptions not met: transformation, gls, or glm as solutions? |
| Date | Mon, 17 Dec 2012 11:37:29 -0500 |
On Mon, Dec 17, 2012 at 10:27 AM, Maarten Buis <maartenlbuis@gmail.com> wrote: The whole point of robust standard errors is not that it > "solves" in some way for heteroskedasticity, it just makes that > "assumption" irrelevant. For more, see section 20.20 of the User's > Guide. I think I'm vehemently agreeing with you Maarten, but "sort of irrelevant" is probably a better characterization. Heteroscedasticity is often the sign of a very bad model. There's a temptation to "white wash" a bad model by using remedial measures such as one of the various heteroscedasticity-consistent VCE estimates, bootstrap, jackknife, etc., but if the model is not appropriate all the remedial measures in the world won't truly fix it up. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/