Re: st: AW: Why is the adj. R-squared lower with time FE than with time & firm FE?

[itchiftc@rumms.uni-mannheim.de]

Hello Martin,

I also thought of the "penalizing effect" of including more variables  
(firm dummies) on the R-squared. However, in Eq.1, the adj. R-squared  
and the within R-squared (which corresponds to the unadjusted  
R-squared, that Stata reports with xtreg) are not much different from  
each other. For example the adjusted R-squared equals 0.627 and the  
within R-squared equals 0.615 in Eq.1 (the between R-squared however  
is higher: 0.723). In Eq. 2, the adj. R-squared rises to 0.916... How  
is this possible and what is the role of the between R-squared in this  
case?

Thanks in advance!
Ida


Zitat von Martin Weiss <martin.weiss1@gmx.de>:

> <>
>
> " Thus, intuitively, as there are more variables in the Eq.1, I thought that
>
> the adjusted R-squared should be higher than in Eq.2."
>
> It all depends on whether you are talking about the adjusted R2 or not. Note
> in the example that R2 does indeed increase, even when a meaningless
> covariate is added, and that the adjusted R2 penalizes you for an additional
> covariate, with the penalty exceeding the increase in the unadjusted R2...
>
> ***
> clear*
>  set obs 10000
>  set seed 123456
>  gen x=rnormal()
>  gen eps=rnormal()
>  gen noise = rnormal(0,10)
>
>  gen y =1+5*x+eps
>
>  qui reg y x
>  di in red e(r2) " " e(r2_a)
>  qui reg y x noise
>  di in red e(r2) " " e(r2_a)
> ***
>
>
> HTH
> Martin
>
>
> -----Ursprüngliche Nachricht-----
> Von: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von
> itchiftc@rumms.uni-mannheim.de
> Gesendet: Dienstag, 29. September 2009 14:28
> An: statalist@hsphsun2.harvard.edu
> Betreff: st: Why is the adj. R-squared lower with time FE than with time &
> firm FE?
>
> Dear Statlist,
>
> i know that this is rather an econometrical question, but may be still
> someone could help me...
> I'm estimating panel regressions (in Stata 10) and have two equations
> which are exactly the same, except for the included fixed effects:
> Equation #1 includes both company and time fixed effects:
> -xtreg y x1 x2 x3 timedummy2-timedummy9, fe cluster(firmid)
> whereas
> Equation #2 has only time fixed effects:
> -reg y x1 x2 x3 timedummy2-timedummy9, cluster(firmid).
>
> Looking at the adjusted R-Squared I was surprised to see that it is
> lower in Eq.1 than in Eq.2. As explained in econometric books (e.g.
> Stock and Watson 2007) icorporating fixed effects is simmilar to
> including dummies for each individual (in my case 80 firms). Thus,
> intuitively, as there are more variables in the Eq.1, I thought that
> the adjusted R-squared should be higher than in Eq.2.
>
> I found a thread with very comprehensive explanation on panel data
> R-squared:
> http://www.stata.com/statalist/archive/2006-03/msg00180.html
>
> stating in the end that
> "In the -xtreg, fe- calculation, we are washing out the explanatory
> effects of the intercepts."
>
> Is this the explanation for the lower adj. R-squared in Eq.1? I'm not
> quite sure and would appreciate any comment!
>
> Thanks,
> Ida
>
>
>
>
>
>
>
>
>
>
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