
From  "Rodrigo A. Alfaro" <raalfaroa@gmail.com> 
To  <statalist@hsphsun2.harvard.edu> 
Subject  Re: st: RE: Why not always specify robust standard errors? 
Date  Tue, 13 Feb 2007 19:11:41 0500 
At 12:26 PM 2/13/2007, Maarten Buis wrote:Thanks Maarten. I'm no doubt betraying my statistical ignorance here, but is that the correct definition of "correct?" i.e. does "correct" mean no heteroskedasticity? Or is no hetero just a requirement for OLS to be the optimal method for estimating the model? It seems to me that a model could be correct in that Y is a linear function of the Xs and all relevant Xs are included. The additional requirement of homoskedastic errors is a requirement for OLS estimates to be BLUE. But, if errors are heteroskedastic, we can use another method, like WLS. Or, we can content ourselves with using robust standard errors which do not require that the errors be iid.If you think your model is correct then it makes no sense to use robust standard errors. Note that the model assumes no heteroscedasticity in the population, so the fact that we always find some heteroskedasticity in our samples is no argument. You could test it of course, but since we are now in ``purist land'' we would have serious troubles with performing tests based on the model that was subsequently selected, since now our conclusions are based on a sequence of tests...
In any event, in practice probably every model will be at least a little misspecified and/or have error terms that aren't perfectly iid. So, why not always use robust? One potential problem, I think, is that robust standard errors tend to be larger. Perhaps unnecessarily relaxing the iid assumption has similar effects to including extraneous variables  estimates will remain unbiased but adding unnecessary junk to the model can cause standard errors to go up.
You know, this is one of the problems with using Stata. I never used to have these kinds of problems with SPSS, because SPSS doesn't let you estimate robust standard errors!

Richard Williams, Notre Dame Dept of Sociology
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