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Re: st: Fixed Effect Estimation Results


From   "Joana Quina" <joana.statalist@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Fixed Effect Estimation Results
Date   Wed, 5 Apr 2006 18:24:29 +0100

Mark and Bill,

Thank you for your answers - they were quite helpful.  The lpop
variable does seem to be problematic. What I still have some problems
with is that excluding it actually decreases the correlation.  I have
rechecked the lpop data just to make sure there wasn't some mistake
somewhere, but it seems fine.

Thanks again,
Joana

On 05/04/06, William Gould, Stata <wgould@stata.com> wrote:
> To rehash, Joana Quina <joana.statalist@gmail.com> reported,
>
>    1.  She has estimated the parameters of a model using -xtreg, fe- and
>        that the reported correlation between u_i and X_ij*b is .9249.
>
>    2.  She has estimated the parameters of the same same model on
>        the same data.  She then performs a Hausman test that fails to
>        reject random effects.
>
> I agree with Mark Schaffer <M.E.Schaffer@hw.ac.uk>, who wrote,
>
> > I wonder if this is being driven by the "omnibus" nature of your Hausman
> > test.  In your application, it has 12 degrees of freedom, one for each
> > coefficient.  I can imagine that, loosely speaking, if one coefficient is
> > "significantly different" between the 2 specifications, and the other 11 are
> > "very similar", then your Hausman test could fail to reject the null that
> > the specifications are both consistent.
>
> In Joana's case, one coefficient changed a lot.  The Hausman test is known
> to lack power in such cases.
>
> -- Bill
> wgould@stata.com
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