Clive,
It's all in the manual. The xtreg entry has about a page on how the R-sqs
reported are not like OLS R-sqs, whereas the areg entry has a sentence
saying that the areg R-sq is just the R-sq reported if you run an OLS
regression with dummies.
Cheers,
Mark
Quoting Clive Nicholas <[email protected]>:
> Kit Baum wrote:
>
> > Apples and oranges make a good fruit salad, but...
> >
> > The areg shows 11 region categories. The xtreg shows 304 groups
> of
> > 'pano'. If you use the same variable (e.g. region) in both
> commands,
> > you will get the same coefficients/std errors, or your computer
> is
> > broken.
>
> As a gangster from the East End of London might say, I've sorted it.
> I
> used my PANO (constituency) variable as the fixed effect in both
> models,
> after Scott Merryman's corrective suggestion. This got me the
> identical
> results I should have had for both LSDV and FE. I could have used
> REGION
> as my fixed effect, but the codes in this variable represent much
> larger
> areas of the UK. I prefer the former, since one cannot get much
> more
> precise regional FEs than parliamentary constituencies (unless you
> use
> local government wards, but that would be masochistic)!
>
> However, I noticed something in my two 'identical' models:
>
> . areg edconch edround2 edround3 edtime edtimesq edyear edpollch
> lagconch
> laglabch lagldmch clmargin ldmargin conplace edenp class if
> edmarker==1,
> absorb(pano)
>
> Number of obs = 1632
> F( 14, 1314) = 69.42
> Prob > F = 0.0000
> R-squared = 0.7324
> Adj R-squared = 0.6678
> Root MSE = 6.1165
>
> [...]
>
> . tsset pano edyear
>
> . xtreg edconch edround2 edround3 edtime edtimesq edyear edpollch
> lagconch
> laglabch lagldmch clmargin ldmargin conplace edenp class if
> edmarker==1,
> fe
>
> Fixed-effects (within) regression Number of obs =
> 1632
> Group variable (i): pano Number of groups =
> 304
>
> R-sq: within = 0.4252 Obs per group: min =
> 1
> between = 0.4157 avg =
> 5.4
> overall = 0.3644 max =
> 10
>
> F(14,1314) =
> 69.42
> corr(u_i, Xb) = -0.5123 Prob > F =
> 0.0000
>
> [...]
>
> Now, I have fit the same models here (with the same FE in both)
> whilst
> 'switching off' any weighting and cluster options in both of them.
> How is
> it that the R^2 is not the same in both models? Doubtless I'm
> overlooking
> something. Ta.
>
> CLIVE NICHOLAS |t: 0(044)191 222 5969
> Politics |e: [email protected]
> Newcastle University |http://www.ncl.ac.uk/geps
> *
> * For searches and help try:
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> * http://www.stata.com/support/statalist/faq
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>
Prof. Mark Schaffer
Director, CERT
Department of Economics
School of Management & Languages
Heriot-Watt University, Edinburgh EH14 4AS
tel +44-131-451-3494 / fax +44-131-451-3008
email: [email protected]
web: http://www.sml.hw.ac.uk/ecomes
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