> I didn't but also didn't think it was necessary.
I don't know if that will fix your problem or not, but I would go
ahead and try it.
areg estimates a one-way fixed effects model so even if strictly
speaking you don't have a time dimension in your problem you can frame
it as a panel estimation problem.
e.g. if instead of having many individuals observed over time you have
many households with several individuals in it and you want to
estimate household fixed effects.... you can think of the household as
your categorical variable to be absorbed and your individuals as your
repeated observations within that category.
robert
On 2/27/06, Radu Ban <[email protected]> wrote:
> I didn't but also didn't think it was necessary. There is no time
> element to the data. I was just puzzled as to why -areg- didn't notice
> the colinearity.
>
> -radu
>
> 2006/2/27, Robert Duval <[email protected]>:
> > Did you tsset your data?
> > robert
> >
> > On 2/27/06, Radu Ban <[email protected]> wrote:
> > > Dear Listers,
> > >
> > > I've encountered this puzzling behavior of -areg-:
> > >
> > > egen total_hh_nr = sum(hh_nr), by(keyid)
> > > ...
> > >
> > > areg y x1 x2 total_hh_nr, absorb(keyid)
> > >
> > > [by mistake I included total_hh_nr in the regression]. The puzzle is
> > > that when I run the regression "total_hh_nr" doesn't drop out (as I
> > > would expect, due to invariance within "keyid"). The standard error on
> > > "total_hh_nr" comes out very large, of the order 10^8, so there is
> > > something weird going on, but I cannot figure out what. Furthermore,
> > > the coefficient on "total_hh_nr" changes at every run of the program.
> > > So, what is going on in here?
> > >
> > > Thanks so much,
> > > Radu Ban
> > >
> > > *
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> > >
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