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Re: st: Fixed effects vs. Random effects
you should defenitely run a Hausman test first to test whether the strict
exogeneity assumption of RE is met. otherwise RE is anyway not appropriate
and produces biased estimates and you should do a FE model. at least this
would be econometrically sound.
however, problem with FE is that it produces very inefficient and
therefore unreliable estimates if the between variation of (some of) your
right hand side variables is much larger than the within variation since
FE does not use the between variance because variables are demeaned.
there is a whole discussion going on (see Beck and Katz vs. Green, Kim and
Yoon in IO 2001) whether FE "throws out the baby with the bath water"
especially in binary choice models...
however if hausman test reveals that RE is producing biased estimates
because orthogonality between x and the unit specific effects is not given
(and this is almost always the case with real data - there is correlation
between the ui and at least some x), then there is no choice than using
Vera E. Troeger
Lecturer in Political Science
University of Exeter
Department of Politics
Exeter, Devon EX4 4QJ
Topsham, Exeter EX3 0AQ
> I don't think there is a minimum. Since it is a within firm (in your
> case) regression, you could technically estimate a fixed effects model
> with one panel, as long as there is 2 or more time observations within
> that panel.
> Of course, you want a large number of panels for precise estimation of
> the parameters, but there is any magic number on the smallest number of
> panels you would need for that. The more the better. The size of your
> dataset seems plenty large enough to run the model you propose.
> Justin Smith
> On Fri, 21 Jul 2006 07:56:27 -0700 (PDT)
> ILR School <firstname.lastname@example.org> wrote:
>> Does anyone know where I can find out the minimum
>> number of panels one needs to run a fixed-effects
>> model? I have a dataset of 800 firms with only 3 time
>> periods using a xtlogit regression model. I am
>> currently using a random effects model.
>> Thank you,
>> Shon R.
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> Justin Smith
> PhD Candidate
> Department of Economics
> McMaster University
> Phone: (905) 962-0353
> E-mail: email@example.com
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