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Re: st: help with R-square of xtreg,fe and areg (fwd)


From   JAYESH KUMAR <[email protected]>
To   <[email protected]>
Subject   Re: st: help with R-square of xtreg,fe and areg (fwd)
Date   Sat, 25 Oct 2003 19:21:20 +0530 (IST)

Thanks a lot!

It's of great help, as I can defend the R-sq I am reporting in my results,
by giving their construction.
Thanks,
-Jayesh


On Sat, 25 Oct 2003, alopca2002 wrote:

:Date: Sat, 25 Oct 2003 10:18:41 -0000
:From: alopca2002 <[email protected]>
:Reply-To: [email protected]
:To: statalist
:Subject: Re: st: help with R-square of xtreg,fe and areg (fwd)
:
:Dear Jayesh
:
:I have asked myself the same question just a week ago and i think i
:can give you an interpretation.
:
:I runned the same model in Stata and in LIMDEP because the
:differences found in the R squared. In LIMDEP the R squared was
:bigger but coeficientes and t ratios were the same!!!
:
:The R-squared provided by STATA with xtreg responds only to the
:effects of the independient variables, nor the fixed effects. The
:overall R-squared reported by STATA correponds to the R-squared (no
:adjusted)in LIMDEP in other models.
:
:I renember to read a text on the official STATA website explaining
:the differences in the xtreg and areg R squared, but i cant find it.
:In the construction of the R squared of xtreg fixed effects impact is
:droped.
:
:So, what is the most suitable R squared???? I think that it depends
:on your results. In my model i am gonna use the areg R squared and
:explain the composition of it.
:
:Hope it helps.
:
:Alfredo L�pez
:Universidad de Zaragoza
:Zaragoza (Spain)
:
:--- In [email protected], JAYESH KUMAR <jayesh@i...> wrote:
:> Dear Statalisters,
:> I have posted this mail a week before, but didn't get any response.
:> I am sending it again in the hope someone may help me.
:> -Jayesh
:>
:> ---------- Forwarded message ----------
:> Date: Fri, 17 Oct 2003 23:20:49 +0530 (IST)
:> From: JAYESH KUMAR <jayesh@i...>
:> To: statalist@h...
:> Subject: help with R-square of xtreg,fe and areg
:>
:> Dear Users,
:>
:> I have a basic question regarding the difference in xtreg,fe and
:areg.
:> Which R-square should I report in my results? R-sq: within, between
:or
:> overall obtained from xtreg,fe or shall I report R-squared or
:Adjusted
:> R-squared obtained from the areg.
:>
:> I am inclosing the output from the two commands. As you can clearly
:see
:> that both results are same in terms of coeff, p-value, F-stats,
:etc. The
:> only difference is with different R-squares. I am bit puzzled here,
:which
:> R-sq should I report in my final tables. I am using Stata 7.
:>
:> Any suggestion would be of help. Is there any reference, in which I
:can
:> find the differences in R-squares, in terms of interpretation,
:rather than
:> derivation?
:>
:> TIA,
:>
:> -Jayesh Kumar
:>
:**********************************************************************
:**
:> JAYESH KUMAR,
:> Research Scholar,
:> Indira Gandhi Institute Of Development Research (IGIDR),
:> Gen. Arun Kumar Vaidya Marg,
:> Santosh Nagar, Goregaon (East), Mumbai-400065, INDIA.
:> Tel # + 91 (22) 2840 0919/0920/0921  Extn. 591(Office) 263
:(Residence)
:> Fax # + 91 (22) 2840 2752/2026
:> visit: www.igidr.ac.in/~jayesh
:> SSRN Papers on the web at:
:> http://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=333715
:>
:**********************************************************************
:**
:> When I don't know what I'm doing I'm doing Research!
:>
:>
:>
:>
:> OUT PUT:
:>
:======================================================================
:==========
:>
:>
:> . xtreg inc age pq_a,fe
:>
:> Fixed-effects (within) regression               Number of obs
:=      5132
:> Group variable (i) : ind                        Number of groups
:=      2524
:>
:> R-sq:  within  = 0.0485                         Obs per group: min
:=         1
:>        between = 0.0045                                        avg
:=       2.0
:>        overall = 0.0054                                        max
:=         7
:>
:>                                                 F(2,2606)
:=     66.35
:> corr(u_i, Xb)  = -0.8909                        Prob > F
:=    0.0000
:>
:> --------------------------------------------------------------------
:----------
:>          inc |      Coef.   Std. Err.      t    P>|t|     [95%
:Conf. Interval]
:> -------------+------------------------------------------------------
:----------
:>          age |  -.0107904   .0009367   -11.52   0.000    -
:.0126272   -.0089536
:>         pq_a |   9.67e-06   .0000694     0.14   0.889    -
:.0001265    .0001458
:>        _cons |   .3441254   .0208627    16.49
:0.000     .3032161    .3850346
:> -------------+------------------------------------------------------
:----------
:>      sigma_u |  .26712239
:>      sigma_e |  .07998241
:>          rho |  .91772273   (fraction of variance due to u_i)
:> --------------------------------------------------------------------
:----------
:> F test that all u_i=0:     F(2523, 2606) =     4.40          Prob >
:F = 0.0000
:>
:>
:>
:>
:> . areg inc age pq_a,absorb(ind)
:>
:>                                                        Number of
:obs =    5132
:>                                                        F(  2,
:2606) =   66.35
:>                                                        Prob >
:F      =  0.0000
:>                                                        R-
:squared     =  0.8109
:>                                                        Adj R-
:squared =  0.6277
:>                                                        Root
:MSE      =  .07998
:>
:> --------------------------------------------------------------------
:----------
:>          inc |      Coef.   Std. Err.      t    P>|t|     [95%
:Conf. Interval]
:> -------------+------------------------------------------------------
:----------
:>          age |  -.0107904   .0009367   -11.52   0.000    -
:.0126272   -.0089536
:>         pq_a |   9.67e-06   .0000694     0.14   0.889    -
:.0001265    .0001458
:>        _cons |   .3441254   .0208627    16.49
:0.000     .3032161    .3850346
:> -------------+------------------------------------------------------
:----------
:>         ind  |     F(2523, 2606) =      4.399   0.000        (2524
:categories)
:>
:>
:>
:>
:>
:> *
:> *   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/
:
:
:
:*
:*   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/
:


*
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