Mark,
Thank you for the tips.
At first I'd thought about running an IV, but then I
started thinking about the consequences on fitting a
binary variable using linear model i.e. the predicted
value from the 1st stage from a binary variable won't
be bounded between 0 and 1.
I'll look at the treatment effect approach.
Regards.
Sjamsu
--- Mark Schaffer <[email protected]> wrote:
> There are at least two approaches you can follow.
>
> First, you can estimate the system using -treatreg-.
> That means you also
> specificy a probit-type treatment equation for your
> endogenous dummy. -
> treatreg- estimates the treatment equation and the
> outcome equation for y
> as a system.
>
> Second, if want to estimate only the outcome
> equation y, you can simply
> use -ivreg- or -ivreg2-. Consistency of IV does not
> require the endogenous
> variable(s) to be continuous; endogenous dummies are
> fine. The results
> won't be as efficient as with the sytem estimation
> using -treatreg-, but
> they will have the advantage (as usual with
> single-equation methods) of
> being consistent under a broader range of
> assumptions than the system
> estimation results.
>
> Hope this helps.
>
> --Mark
>
> Quoting "S.Rahardja" <[email protected]>:
>
> > Dear Colleagues,
> >
> > I wonder if you could give me tips on how should I
> > deal with an endogenous dummy variable.
> > What I'm thinking is to run using OLS, say:
> > y = a + bX + dD + e
> >
> > where D= 0|1 is the endogenous dummy variable.
> >
> > Or, does this sound more like a selection problem
> > (where I can split the sample into two) ?
> >
> > Thank's in advance.
> >
> >
> >
> >
> > __________________________________
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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]
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>
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