# Re: st: R2-within(xtreg,fe) and R2_adj(areg)?

 From "Clive Nicholas" To statalist@hsphsun2.harvard.edu Subject Re: st: R2-within(xtreg,fe) and R2_adj(areg)? Date Fri, 11 Jun 2004 22:02:39 +0100 (BST)

```Mark Schaffer wrote:

> The R2s depend on the coefficient estimates but not on the estimated
> variance-covariance matrix.  It looks like you are using xtreg,fe and areg
> to estimate the same model, and so the coefficients reported by the two
> estimators should be the same.  If they are, then you can simply use the
> R2s reported by xtreg,fe.

Whilst I was perfecting my LSDV models, I assumed (both from Mark's and
Kit Baum's comments) that the coefficients from them would indeed be the
same as FE. Not from my data. An example:

. areg edconch lagconch laglabch lagldmch if edmarker==1, absorb(region)

Number of obs =
2187
F(  3,  2173) =
89.91
Prob > F      =
0.0000
R-squared     =
0.1379
0.1328
Root MSE      =
10.752

------------------------------------------------------------------------------
edconch |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+----------------------------------------------------------------
lagconch |  -1.145137   .1207652    -9.48   0.000    -1.381964
-.9083096
laglabch |  -.7120315   .1372847    -5.19   0.000    -.9812545
-.4428084
lagldmch |  -.8160474   .1272037    -6.42   0.000    -1.065501
-.5665938
_cons |  -12.85246   .2432762   -52.83   0.000    -13.32953
-12.37538
-------------+----------------------------------------------------------------
region |       F(10, 2173) =      7.705   0.000          (11
categories)

. xtreg edconch lagconch laglabch lagldmch region if edmarker==1, fe

Fixed-effects (within) regression               Number of obs      =
2187
Group variable (i): pano                        Number of groups   =
304

R-sq:  within  = 0.1970                         Obs per group: min =
1
between = 0.0000                                        avg =
7.2
overall = 0.1049                                        max =
11

F(3,1880)          =
153.72
corr(u_i, Xb)  = -0.0409                        Prob > F           =
0.0000

------------------------------------------------------------------------------
edconch |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+----------------------------------------------------------------
lagconch |  -1.351399   .1029873   -13.12   0.000    -1.553381
-1.149418
laglabch |  -.9368757   .1180488    -7.94   0.000    -1.168396
-.7053552
lagldmch |  -1.048965   .1090272    -9.62   0.000    -1.262792
-.8351383
region |  (dropped)
_cons |  -12.95549   .1934802   -66.96   0.000    -13.33495
-12.57603
-------------+----------------------------------------------------------------
sigma_u |  8.0146543
sigma_e |  8.4675555
rho |  .47254255   (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0:     F(303, 1880) =     5.76           Prob > F =
0.0000

Exactly the same results occur if I use individual dummy variables in
-xtreg, fe-.

As they might say in the UK's "Private Eye" magazine, is any difference
between them a coincidence? I think we should be told.

CLIVE NICHOLAS        |t: 0(044)191 222 5969
Politics              |e: clive.nicholas@ncl.ac.uk
Newcastle University  |http://www.ncl.ac.uk/geps
*
*   For searches and help try:
*   http://www.stata.com/support/faqs/res/findit.html
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/
```