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st: RE: SE's in Fixed Effects Model


From   "Boylan, Richard" <rboylan@cba.ua.edu>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: SE's in Fixed Effects Model
Date   Wed, 23 Jun 2004 10:54:42 -0500

In method (i) you need to adjust the degree of freedom.  If you compare
the standard errors in the two estimates you will notice that they are
identical up to a scalar (approx = 1.46).
Richard

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Tim R. Sass
Sent: Wednesday, June 23, 2004 10:45 AM
To: statalist@hsphsun2.harvard.edu
Subject: st: SE's in Fixed Effects Model


I am estimating a fixed-effects panel model using two methods: (i)
manually 
demeaning the data and running regress, (ii) running areg on the
original 
data.  I am able to get identical estimated slope coefficients from both

models.  However, the standard errors are very different.  The standard 
errors should be asymptotically equivalent, so given my large sample
size 
(21,000+ observations) the reported standard errors ought to be quite 
close.  I tried applying the standard error correction noted by Wiggins
and 
Gould in the Stata 6 FAQ "How can I estimate a fixed-effects regresion
with 
instrumental variables?", but as one would expect (given my large sample

size) it made very little difference.  Any ideas what may be going on 
here?  My output is given below.

Tim



. areg  nrtrgain nschools chgschl, absorb(student) ;

                                                        Number of obs =
21601
                                                        F(  2, 10062) =
219.77
                                                        Prob > F      =
0.0000
                                                        R-squared     =
0.3732
                                                        Adj R-squared =
-0.3455
                                                        Root MSE      =
31.382

------------------------------------------------------------------------
------
     nrtrgain |      Coef.         Std. Err.          t        P>|t|
-------------+----------------------------------------------------------
-------------+------
    nschools |  -2.487567   1.967418      -1.26   0.206
      chgschl |  -11.67239   .5572808    -20.95   0.000
         _cons |   20.07552   2.067988       9.71   0.000


. reg   de_nrtrgain de_nschools de_chgschl;

       Number of obs =   21601
       F(  2, 21598) =  471.74
       Prob > F      =  0.0000
       R-squared     =  0.0419
       Adj R-squared =  0.0418

------------------------------------------------------------------------
------
    de_nrtrgain |      Coef.        Std. Err.         t        P>|t|
-------------+----------------------------------------------------------
-------------+------
  de_nschools |  -2.487567   1.342864     -1.85   0.064
    de_chgschl |  -11.67239   .3803728   -30.69   0.000
             _cons |   20.07552   1.411508     14.22   0.000
------------------------------------------------------------------------
------

. display _se[de_chgschl]*sqrt(e(df_r)/(e(df_r)-3+1));
.38039039




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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