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st: RE: RE: RE: predicting (ui) after( xtivreg2) ?!


From   "Schaffer, Mark E" <[email protected]>
To   <[email protected]>
Subject   st: RE: RE: RE: predicting (ui) after( xtivreg2) ?!
Date   Fri, 13 Apr 2007 13:46:35 +0100

Ahmed,

> -----Original Message-----
> From: [email protected] 
> [mailto:[email protected]] On Behalf Of 
> Al-Darwish, Ahmed
> Sent: Friday, April 13, 2007 1:26 PM
> To: [email protected]
> Subject: st: RE: RE: predicting (ui) after( xtivreg2) ?!
> 
> Dear Mark,
>   I did what you have suggested to predict (ui)..but I 
> couldn't get a fixed value over time  like what xtivreg does?!
> Would there be any other way to make it obtaining an 
> individual effect that is constant over time period.?!

Can you show us the code and perhaps we can figure out why it didn't
generate what you wanted?

--Mark

> Any comments will be appreciated?!
> Cheers;
> Ahmed
> ________________________________
> 
> From: [email protected] on behalf of 
> Schaffer, Mark E
> Sent: Wed 3/28/2007 4:59 PM
> To: [email protected]
> Subject: st: RE: predicting (ui) after( xtivreg2) ?!
> 
> 
> 
> Ahmed,
> 
> > -----Original Message-----
> > From: [email protected]
> > [mailto:[email protected]] On Behalf Of 
> Al-Darwish, 
> > Ahmed
> > Sent: Wednesday, March 28, 2007 1:05 PM
> > To: [email protected]
> > Subject: st: predicting (ui) after( xtivreg2) ?!
> >
> > Dear StataListers;
> > Is there a way to predict the values of (ai)s or(ui)s after running 
> > (xtivreg2) in a fixed effect -panel model?
> 
> Official -xtivreg- uses the terminology u_i and v_it, and the 
> -xtivreg2- help file refers to v_it.  -xtivreg2- will predict 
> a v_it but not a u_i.
> I assume that your ai and ui mean the same thing as u_i.
> 
> The problem is that -xtivreg2- doesn't estimate a coefficient 
> for the constant.
> 
> Maybe this is easy?
> 
> Put all your variables (including the IVs) into 
> mean-deviation form using Ben Jann's -center- command.  Make 
> sure you center using a consistent sample.  Estimating on 
> mean-deviation data should give you the same coefficients as 
> estimating on the raw data (a useful check to make sure 
> you've got the centering done correctly).
> 
> Use -predict- to get the v_it.
> 
> Use -matrix score- to get the fitted values yhat_it of your 
> demeaned dependent variable.
> 
> The u_i will be y_it - yhat_it - v_it.
> 
> Or am I missing something here?
> 
> --Mark
> 
> > Many Thanks;
> > Ahmed
> > 
> > 
> >
> > 
> >
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