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st: Hausman test for clustered random vs. fixed effects (again)


From   Steven Archambault <archstevej@gmail.com>
To   statalist@hsphsun2.harvard.edu, austinnichols@gmail.com, Alfred.Stiglbauer@oenb.at
Subject   st: Hausman test for clustered random vs. fixed effects (again)
Date   Fri, 26 Jun 2009 17:25:36 -0600

Hi all,

I know this has been discussed before, but in STATA 10 (and versions
before 9 I understand) the canned procedure for Hausman test when
comparing FE and RE models cannot be run when the data analysis uses
clustering (and by default corrects for robust errors in STATA 10).
This is the error received

"hausman cannot be used with vce(robust), vce(cluster cvar), or p-weighted data"

My question is whether or not the approach of using xtoverid to
compare FE and RE models (analyzed using the clustered and by default
robust approach in STATA 10) is accepted in the literature. This
approach produces the Sargan-Hansen stat, which is typically used with
analyses that have instrumentalized variables and need an
overidentification test. For the sake of publishing I am wondering if
it is better just not to worry about heteroskedaticity, and avoid
clustering in the first place (even though heteroskedaticity likely
exists)? Or, alternatively one could just calculate the Hausman test
by hand following the clustered analyses.

Thanks for your insight.
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