Re: st: estimating treatment effect of a binary endogenous regressor on binary outcome

[Austin Nichols <austinnichols@gmail.com>]

Erkan Duman <erduman@sabanciuniv.edu>:

See also
http://www.stata-journal.com/article.html?article=st0144
http://www.stata.com/meeting/new-orleans13/abstracts/materials/nola13-barker.pdf

But what kind of endogeneity are you thinking you will correct?
With what instruments?
The story you tell for the LATE you are estimating and why it is
identified is at least as important as any statistic your program
spits out.
Tell the story as a thought experiment... e.g.
you imagine dropping a migrant Mexican parent on a randomly selected
US resident child, or randomly assigning a Mexican family to move to
the US instead of remaining in Mexico. (Replace Mexico with Turkey and
the US with Germany, or what have you.)


On Wed, Nov 13, 2013 at 4:22 AM, Erkan Duman <erduman@sabanciuniv.edu> wrote:
> Hello.
> I am working on the impacts of having a migrant at home on the school
> attendance of children. My regressor is an endogenous binary variable
> and the outcome is also binary. I have searched a lot to find an
> estimator which will consistently estimate the treatment effect.
> Chiburis et al. (2012) paper recommends bivariate probit or IV2SLS.
> However, bivariate probit requires strong assumptions (bivariate
> normal errors) and my specification does not satisfy this assumption
> which results in severly biased estimates. IV2SLS gives a treatment
> effect over 1 (actually around 10). In my study, the treatment
> receivers only constitute around 2 percent of the sample. I believe
> this low treatment probability causes problems in estimating the
> treatment effects because when I reduce the size of the control group
> and come up with a treatment group of 16% of the sample, the treatment
> estimate fits in (0,1) range ; still it is too high around 0.80. I
> have encountered a similar thing to my problem as "rare events" in the
> literature, but doesn't seem to solve my problem or maybe I am wrong.
> Also in http://www.stata.com/meeting/chicago11/materials/chi11_nichols.pdf
> some semi-parametric estimators are suggested by  Austin Nichols which
> do not require bivariate normal errors but weaker assumptions.
> However, I am not familiar with semi-parametric or nonparametric
> estimators. Can anyone help me with an appropriate semiparametric
> estimator and its stata command?
> I believe there is a solution to this estimation problem and I hope
> someone will help me.
> Thanks.
> Best regards.
>
> --
> Erkan Duman
> Graduate student - PhD
> Faculty of Art and Social Sciences
> Sabancı University
>
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