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st: RE: Re: egen and computing fixed effects


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Re: egen and computing fixed effects
Date   Tue, 22 Jun 2004 20:54:47 +0100

This hits the nail on the head. To get the same sample, 

egen nmiss = rmiss(nrtrgain charter nschools chgschl student) 

and work with observations for which nmiss == 0 

(unless -areg- can cope with missing -student-). 

Nick 
n.j.cox@durham.ac.uk 

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of Michael
> Blasnik
> Sent: 22 June 2004 20:46
> To: statalist@hsphsun2.harvard.edu
> Subject: st: Re: egen and computing fixed effects
> 
> 
> The problem isn't how egen calculates the mean, the means are 
> calculated as
> you would expect -- for all non-missing observations for each 
> variable.
> These means will include observations that may be missing on 
> other variables
> in your regression.  You need to calculate the means only for 
> the estimation
> sample (excluding observations with missing values on any of 
> the variables)
> if you want the same answer.
> 
> Michael Blasnik
> michael.blasnik@verizon.net
> 
> 
> ----- Original Message ----- 
> From: "Tim R. Sass" <tsass@coss.fsu.edu>
> To: <statalist@hsphsun2.harvard.edu>
> Sent: Tuesday, June 22, 2004 3:25 PM
> Subject: st: egen and computing fixed effects
> 
> 
> > Statalisters -
> >
> > I am trying to "manually" compute a fixed-effects estimator 
> by taking the
> > differences from means of all variables and then running reg on the
> > demeaned data.  You may ask why in the world I would want 
> to do that, but
> > that's for another post.
> >
> > I have a panel of student-level data over three years.  I 
> demean the data
> > as follows:
> >
> > bysort student:egen nrtrgain_m = mean(nrtrgain);
> > bysort student:egen charter_m = mean(charter);
> > bysort student:egen nschools_m = mean(nschools);
> > bysort student:egen chgschl_m = mean(chgschl);
> >
> > gen d2_nrtrgain = nrtrgain - nrtrgain_m;
> > gen d2_charter = charter - charter_m;
> > gen d2_nschools = nschools - nschools_m;
> > gen d2_chgschl = chgschl - chgschl_m;
> >
> > I then run the following models:
> >
> > areg  nrtrgain charter nschools chgschl,
> >                   absorb(student) ;
> >
> > reg   d2_nrtrgain d2_charter d2_nschools d2_chgschl ;
> >
> > xtdata  nrtrgain charter nschools chgschl, fe clear;
> > reg  nrtrgain charter nschools chgschl;
> >
> >
> > The first and third models yield the same estimated 
> coefficients (except
> > for the constant, of course), but the coefficients for the 
> second model
> > (using reg on the demeaned variables) yields different 
> results.  However,
> > when I eliminate all observations with missing values for any of the
> > variables in the model, all three models yield identical 
> estimated slope
> > coefficients.
> >
> > I'm guessing the problem has something to do with how egen 
> computes the
> > mean for each student when there are missing observations.  
> I have read
> > through the manual and searched the archives, but still 
> can't figure out
> > what is going on.  Any help would be greatly appreciated.
> >
> > Tim
> >
> >
> > Tim R. Sass
> > Professor                               Voice:   (850)644-7087
> > Department of Economics         Fax:      (850)644-4535
> > Florida State University                E-mail:   tsass@coss.fsu.edu
> > Tallahassee, FL  32306-2180     Internet:
> http://garnet.acns.fsu.edu/~tsass
> 
> 
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