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RE: st: RE: Why not always specify robust standard errors?

From   "Maarten Buis" <>
To   <>
Subject   RE: st: RE: Why not always specify robust standard errors?
Date   Tue, 13 Feb 2007 18:26:54 +0100

--- Richard Williams wrote: 
> So, I think his cautions and concerns are pretty valid; robust
> standard errors are not a panacea for a model that is "seriously in
> error" .  But, it still seems to leave open the question of whether
> always using robust would be a good idea if your model is "nearly
> correct" or hetero is an issue.

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...

So it depends on how much faith you have in your model. On the other 
hand I think it is good that Stata forces us to make a conscious 
decision to declare that there is something wrong with the error but 
that we don't care about it. Since trying to understand why there is 
something wrong with the errors improves our understanding of the data 
even if we finally choose to ignore it by specifying the robust option.
Maarten L. Buis
Department of Social Research Methodology 
Vrije Universiteit Amsterdam 
Boelelaan 1081 
1081 HV Amsterdam 
The Netherlands

visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434 

+31 20 5986715

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