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Re: st: Modeling proportion with endogenous treatment indicator

From   Austin Nichols <>
Subject   Re: st: Modeling proportion with endogenous treatment indicator
Date   Fri, 10 Sep 2010 17:33:45 -0400

Guy Grossman <>:
I would start with -ivreg2- (on SSC) and use robust SEs (or
cluster-robust); the
coefficients will certainly be easy to interpret as dp/dX.  But see
for panel models with fractional outcomes and instruments.

On Fri, Sep 10, 2010 at 5:25 PM, Guy Grossman <> wrote:
> Dear Stata list -
> I am using Stata 10.1 on Mac and am seeking advice about the best way
> to fit the following model:
> Yij = bo + b1 * Tj  + b2 * Ci + b3 * Cj + eij + ej
> Tj = v0 + v1 * Zj + epsilon j, where...
> Yij = the dependent variable is a proportion (0<Yij <1), for person i
> from group j.
> Zj = encouragement to take up one of two types of treatment - applied
> at the group level j . Zj is binary: groups are either encouraged to
> take up Zj=0 or Zj=1.
> Tj = treatment take up - takes place at the group level j. Tj is
> binary (Tj=0 or Tj =1). Take up rates are about 80% for both
> treatments.
> Ci = control variables at the individual level i
> Cj = control variables at the group level j
> The idea is to apply an encouragement research design, using Zj as an
> instrumental variable for Tj.
> Given the nature of the dependent variable (proportion), my question
> is how is it best to fit the model in Stata. In the past I have used
> the glm command with link(logic) and family (bin) to fit a model with
> a dependent variable that was a proportion, but the independent
> variables were all exogenous. Is there a way to fit a glm with an
> endogenous independent variable? Is it possible to use treatreg with
> DV which is a proportion?
> I look forward for your astute recommendations.
> Thanks!
> Guy

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