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Re: st: fixed vs random effect model


From   David Jacobs <jacobs.184@sociology.osu.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: fixed vs random effect model
Date   Sun, 04 Jul 2010 12:51:05 -0400

If the Haussman test rejects random-effects, that test is telling you a random-effects approach would not produce consistent results. And this would be a deadly flaw.

A reasonable answer to your question depends on how small your over-time (or within) variances actually are (which you don't tell us). Given the limited information you've provided, I'd go with fixed-effects, but tell the reader the degree to which specific explanatory variables approach time invariance. One source on this is the Wooldrige econometrics book on cross-sectional and pooled time-series models (sorry but the book's at home, so I don't have a complete citation) on about page 270 (I think).

One way to assess this problem is to use the Stata routine -xtsum- as it provides over time (or within) standard deviations for variables in a pooled time-series model.

Dave Jacobs

At 10:42 AM 7/4/2010, you wrote:
Good day Stata-listers,
I'm apoloziging is the question may seems elementary for many of you,
but i really need to check this before going on in my analysis. i'm
running a panel data regression and after performing the haussman test
the conclusion was that my model is a fixed effect one. The problem is
located on my explanatory variables which display week variations, and
as it is well known fixed effect model gives weak results in a such
case. So should 'i use the random effect instead???

Thanks a lot in advance.

Ama.
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