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> The main reason for the difference is that AREG counts the machine 
> equivalent of the case dummies when it computes the R2; EXTREG, FE 
> does not.  It follows that a lion's share of the variance you've 
> explained is due to the case specific attributes you've included in 
> your models.
> 
> Two incidental matters:  First, if you end up using XTREG, FE the 
> proper R2 to report is the "within".  Second, R2 square values aren't 
> the best measure of anything that matters although referees sometimes 
> think they matter .  The point is I wouldn't spend much space in your 
> write up on these values.
> 
> Dave Jacobs
> 
> At 12:22 PM 2/4/2008, you wrote:
> >Dear all,
> >
> >hi I write to ask you one question regarding the difference between 
> >areg and xtreg, fe. In particular I would like to understand the 
> >difference concerning the r squared. Indeed I use a fixed effects 
> >model to estimate the returns to education on a panel of 
> >individuals. I performed fixed effects estimates for two categories 
> >of workers, blue collars (which are many) and white collars.
> >I found out interesting results. However, for blue collars the 
> >estimates of the r-squared with xtreg,fe are the following:
> >r^2 within 0.07
> >r^2 between 0.002
> >r^2 overall 0.004
> >when I do the same estimation with areg, I obtain an r^2 of 0.80. a 
> >huge difference.
> >
> >I would like to understand why is there a so big difference, and 
> >which one I should report...
> >
> >Another related question concern the estimates for white collars. 
> >The xtreg, fe have an overall r^2 of 0.27 (much better than the 
> >previous one). However when I try the areg command it says that the 
> >matrix is not positive definite (I use also some lagged values of my 
> >variable of interests in the estimation).
> >
> >Could anyone help me?
> >many thanks
> >jenny
> >
> >
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