Robert,
Thanks for the clarification.
I have 4 variables in the selection equation that are
unique and 5 other variables that overlap with those from
the outcome equation. So I understand my model should be
ok.
Thanks,
Nishant
--- Robert Duval <rduval@gmail.com> wrote:
> Actually in this simple model X can equal W.
> This is because the Inverse Mills' Ratio is a nonlinear
> function of W
> so this can avoid perfect collinearity if W has a long
> enough support.
>
> In practice though, it is better to have at least one
> variable
> excluded from X in order to achieve better
> identification.
>
> robert
>
> On 10/16/06, Nishant Dass <nishant_dass@yahoo.com> wrote:
> > Philip,
> > Thank you for your succinct answer as well as the
> refernce;
> > I will check the book.
> > Regards,
> > Nishant
> >
> > --- Philip Fridborn
> <Philip.Fridborn.4605@student.uu.se>
> > wrote:
> >
> > > Hi,
> > > According to Wooldridge (2002) Econometric analysis
> of
> > > x-section and panel data
> > > you must have at least one variable in the selection
> > > model that is not included
> > > in the y-equation. This variable(-s) is supposed to
> > > affect z but not y.
> > > So, X and W do not have to be completely distinct.
> > >
> > > Philip Fridborn
> > >
> > > Citerar Nishant Dass <nishant_dass@yahoo.com>:
> > >
> > > > Dear list-members,
> > > >
> > > > If I have the following Heckman selection model:
> > > >
> > > > y = a + b.X + e (2nd stage)
> > > > z = c + d.W + u (selection equation)
> > > >
> > > > Would you know whether X and W have to be
> completely
> > > > distinct?
> > > >
> > > > I thought they ought to be distinct but I have seen
> > > some
> > > > papers that use variables that are common to both X
> and
> > > W.
> > > >
> > > >
> > > > Does anyone have a good answer or know of a
> definitive
> > > > source on this?
> > > >
> > > > Thanks for your suggestions.
> > > >
> > > > Nishant
> > > >
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