Bookmark and Share

Notice: On March 31, it was announced that Statalist is moving from an email list to a forum. The old list will shut down on April 23, and its replacement, statalist.org is already up and running.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

Re: st: RE: Drop in R-squared when adding variables in xtreg


From   "Gaetano Dadamo" <gaetano.dadamo@uv.es>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: Drop in R-squared when adding variables in xtreg
Date   Mon, 22 Apr 2013 20:06:21 +0200

The one that I was talking about is the overall R-squared. 

I noticed that the within R-squared increased while the between R-squared falls, and that was puzzling me (and definitely driving the result of the overall R-squared)


 

Il giorno Lunedi, 22 Aprile, 2013 19:15 CEST, "Jacobs, David" <jacobs.184@sociology.osu.edu> ha scritto: 
 
> The R Squared that matters in a fixed effects analysis is the within one.  Are you telling us about another?
> 
> Dave Jacobs
> 
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Gaetano Dadamo
> Sent: Monday, April 22, 2013 3:51 AM
> To: statalist@hsphsun2.harvard.edu
> Subject: st: Drop in R-squared when adding variables in xtreg
> 
> Dear statalisters,
> 
> I’ve been performing a FE regression with Stata and I have puzzling results: for example, I run the model
> 
> xtreg y y1 x year_dummies, fe cluster(country)
> 
> where y1 is the first lag of y, and get an overall R-squared of 0.71. Then, I want to see the effect of institutional variable z on the coefficient of y1 and z, so I run the regression
> 
> xtreg y y1 x z*y1 z*x year_dummies, fe cluster(country) 
> 
> but my overall R-squared falls to 0.21. I have the same number of observation in both samples. It is the between R-squared that falls a lot.
> 
> Why is that? Shouldn’t the explicative power of the regression not fall when adding variables anyways? 
> 
> I have that results with two different institutional variables: one is Union Density which is quite variable across and within units, so it definitely cannot be a problem of multicollinearity; the other one is a dummy for New Member States of EU which is constant within countries (but, since it is interacted, does not drop out of the system). Here R-squared falls from 0.71 to 0.06.
> 
> Is there a problem with the estimation? More generally: is the (overall) R-squared the best way for looking at the goodness of fit here?
> 
> Thank you so much.
> 
> Gaetano
> 
> 
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/faqs/resources/statalist-faq/
> *   http://www.ats.ucla.edu/stat/stata/
> 
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/faqs/resources/statalist-faq/
> *   http://www.ats.ucla.edu/stat/stata/
> 
 
 



*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/faqs/resources/statalist-faq/
*   http://www.ats.ucla.edu/stat/stata/


© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   Site index