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st: Why not always specify robust standard errors?
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?
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
WWW (personal): http://www.nd.edu/~rwilliam
WWW (department): http://www.nd.edu/~soc
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