Statalist The Stata Listserver

[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

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

From   Richard Williams <>
Subject   RE: st: RE: Why not always specify robust standard errors?
Date   Tue, 13 Feb 2007 17:59:30 -0500

At 12:26 PM 2/13/2007, Maarten Buis wrote:
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...
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.

In any event, in practice probably every model will be at least a little mis-specified 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
OFFICE: (574)631-6668, (574)631-6463
FAX: (574)288-4373
HOME: (574)289-5227
EMAIL: Richard.A.Williams.5@ND.Edu
WWW (personal):
WWW (department):
* For searches and help try:

© Copyright 1996–2017 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index