st: Why not always specify robust standard errors?

[Richard Williams <Richard.A.Williams.5@ND.edu>]

A student asked me a question the other day that I couldn't think of 
a definitive answer for: Why not always specify -robust- when using 
OLS regression?  My initial reaction is to say that you shouldn't 
relax restrictions unnecessarily; and there are various 
post-estimation commands where Stata will at least whine at you if 
you've used robust standard errors (e.g. -lrtest-).  But in practice, 
your model is probably at least a little mis-specified and/or there 
may be some degree of heteroskedasticity, so maybe robust is a good 
idea.  Any thoughts on the matter?

Incidentally, my own experience is that robust standard errors 
usually aren't all that different from non-robust standard errors. Is 
that what other people have found as well, or is just me?



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Richard Williams, Notre Dame Dept of Sociology
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