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RE : st: a simple panel data question: FE and RE


From   Gaulé Patrick <patrick.gaule@epfl.ch>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   RE : st: a simple panel data question: FE and RE
Date   Sat, 2 Aug 2008 16:45:32 +0200

It might be useful to do a variance decomposition to see how much of the variance is due to the cross-sectional dimension and how much is due to the time dimension.

If much of the variance comes from the cross-sectional dimension, you could use the between estimator or simply pooled OLS with clustered standard errors.

Patrick Gaulé

________________________________________
De : owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] de la part de yjh jsh [jshyjh1@gmail.com]
Date d'envoi : samedi 2 août 2008 14:20
À : statalist@hsphsun2.harvard.edu
Objet : Re: st: a simple panel data question: FE and RE

This does helps. thanks
For me, it seems that different "levels" of Y in units are assumed to
be caused by those unobserved time-invariant variables. What if they
are not?

In my hypothetic case, for example, for both unit 1 and 2, we can't
see relationship between x and y if we only consider within-variation.
But this conceals the fact that Y takes higher value in unit 2 when 2
takes higher value in unit 2. That is, we do see a relationship that
higher x causes y. so, if FE a bad choice if we have a large between
variation compared to within variation in the data?

thanks

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