--- "M.C.D. van Damme" <[email protected]> wrote:
> I am estimating an OLS regression with variables on the individual
> and country level, correcting for intragroup correlation (,cl
> (country)). I have 13 countries.
> After correction, not only the standard error of the country level
> variable is corrected, but also the standard errors of some of the
> individual level variables are much higher. Normally, I do not find
> such big differences.
> What can be the reason for these large adjustments in standard errors
> on the individual level?
> In other words, what is the cluster option exactly doing?
Normally standard errors are based on the assumption that you have
drawn a simple random sample. The cluster option corrects the standard
errors (but not the coefficients) when your sample isn't random but
contains clusters. Robust standard errors (including -cluster-) are
discussed in the User's guide (for Stata 10) chapter 20.15. It was also
discussed in the User's guide of previous version but my Stata 9
manuals now reside in the office of my advisor, who is gone now, so I
can't give you the chapter.
If you are worried by this try estimating your model with -xtreg- or
-xtmixed- with the -re- option. 13 countries is not a lot, so you can't
enter a lot of country level variables, but that is as it should be: on
the country level you have only 13 observations, so more than 1 or 2
country level variables doesn't make sense in any model even if Stata
gives you results.
Hope this helps,
Maarten
-----------------------------------------
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
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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