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Re: st: Re: Adjusted R2 using IVREG2


From   "Clive Nicholas" <Clive.Nicholas@newcastle.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Re: Adjusted R2 using IVREG2
Date   Fri, 18 Aug 2006 18:57:01 +0100 (BST)

Heather Milkiewicz wrote:

[...]

> Using IVREG, after running the regression I can use the following
> command, outreg using table4b.xls, nolabel replace bdec(2) se adjr2, to
> get the results with adjusted R2 in a table, but I cannot figure out how
> to do it for the IVREG2, GMM command.
>
> If you could let me know how to view the adjusted R2 results, and
> possibly a command to transfer them into a table, that would be great.

[...]

Allow me to be blunt, Heather, but frankly, stuff -outreg-! Use Ben Jann's
far superior -estout- (downloadable from -ssc-) and you'll obtain exactly
what you need (and more, if needed).

Adapting from the example given along the bottom of -whelp ivreg2-:

. clear

. use http://fmwww.bc.edu/ec-p/data/macro/abdata.dta

. ivreg2 n (w k ys = d.w d.k d.ys d2.w d2.k d2.ys), gmm cluster(id)

GMM estimation
--------------

Number of clusters (id) = 140                       Number of obs =      751
                                                    F(  3,   139) =    61.06
                                                    Prob > F      =   0.0000
Total (centered) SS     =  1350.891752              Centered R2   =   0.8255
Total (uncentered) SS   =  2122.555626              Uncentered R2 =   0.8890
Residual SS             =  235.6866628              Root MSE      =    .5602
----------------------------------------------------------------------------
           |               Robust
         n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------+----------------------------------------------------------------
         w |  -.3349211   .2904668    -1.15   0.249    -.9042255    .2343834
         k |   .7156264   .0863561     8.29   0.000     .5463715    .8848813
        ys |  -.0538032   .4875811    -0.11   0.912    -1.009445    .9018382
     _cons |    2.69377   3.041579     0.89   0.376    -3.267615    8.655155
----------------------------------------------------------------------------
Anderson canon. corr. LR statistic (identification/IV relevance test): 9.839
                                                   Chi-sq(4) P-val =  0.0432
----------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):       7.540
                                                   Chi-sq(3) P-val =  0.0565
----------------------------------------------------------------------------
Instrumented:         w k ys
Excluded instruments: D.w D.k D.ys D2.w D2.k D2.ys
----------------------------------------------------------------------------

. est store model

. estout model, stats(F r2_a N) cells(b(star fmt(%9.2f)) t(par))
varwidth(50) modelwidth(10)

                                                             model
                                                               b/t
w                                                            -0.33
                                                           (-1.15)
k                                                             0.72***
                                                            (8.29)
ys                                                           -0.05
                                                           (-0.11)
_cons                                                         2.69
                                                            (0.89)
F                                                            61.06
r2_a                                                          0.82

Hope this helps.

CLIVE NICHOLAS        |t: 0(044)7903 397793
Politics              |e: clive.nicholas@ncl.ac.uk
Newcastle University  |http://www.ncl.ac.uk/geps

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