st: RE: difference between -xtreg, fe- and -areg, absorb- when adding the cluster option

["Jacobs, David" <jacobs.184@sociology.osu.edu>]

If you check the manuals, you'll see the -xtreg, fe- and -areg- use different methods to compute the standard errors.  I don't have my manuals here, but I recall that -xtreg, fe- employs a cluster correction when you specify "r", but -areg- does not.

Dave Jacobs 

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of natalie rebolledo
Sent: Monday, January 14, 2013 5:13 PM
To: statalist@hsphsun2.harvard.edu
Subject: st: difference between -xtreg, fe- and -areg, absorb- when adding the cluster option

Dear statalist users,

I'm trying to run a regression that accounts the influence of clusters on the standard errors. I have been researching and I saw that there are at least to basic solutions: one would be running an OLS with the cluster option (-reg, cluster (clustervar)-) and a second option would be -xtreg, fe i(groupvar)-. I have lots of clusters and observations so I'm not too much worried about the assumption of assymptotic consistency of this models.
The thing is that after my research I decided to go for the fixed effect model and found out that this is equivalent to do -areg, absorb(clustervar)-, but I obtained different results between the two when I add the cluster option, what I mean is that,

-xtreg, fe i(clustervar)- and -areg, absorb(clustervar)-  are equivalent, but when I run -xtreg, fe i(clustervar) cluster(clustervar)- and - areg,
absorb(clustervar) cluster(clustervar)-
I found the same coefficients but different standard errors, why is that? shouldn't the standard errors be equal too?
and also, between those two models which one is the best to account for the presence of clusters in my dataset?


Thanks in advance,
Natalie Rebolledo
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