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Re: st: IV Probit

From   Austin Nichols <>
Subject   Re: st: IV Probit
Date   Thu, 15 Mar 2012 14:22:52 -0400

Robert Davidson <>:
I think you should still report the -ivreg2- estimates and diagnostics.
In particular, *you should not use -ivprobit- for this case*
--look at this from the -ivprobit- help file:
"Both estimators assume that the endogenous regressors are continuous
and are not appropriate for use with discrete endogenous regressors."
See also

On Thu, Mar 15, 2012 at 12:46 PM, Robert Davidson <> wrote:
> Thank you for your response.  My endogenous regressor is also binary,
> so even the first stage model is binary in nature.  Does this
> basically mean that I cannot produce much in the way of diagnostics
> other than to simply show that the instrument is highly correlated
> with the endogenous regressor and weakly correlated with the error
> term in the original model for which the instrument is to be used?
> On Thu, Mar 15, 2012 at 12:18 PM, Austin Nichols
> <> wrote:
>> Robert Davidson <>:
>> The theory of the diagnostics is not developed for -ivprobit- or any
>> other nonlinear model,
>> but you can certainly report the diagnostics for the linear probability model
>> that corresponds using -ivreg2-. Since weak instruments are a property
>> of the first stage, this is as much as any reviewer is likely to want.
>> Overidentification tests are also possible via -gmm-.
>> On Thu, Mar 15, 2012 at 11:19 AM, Robert Davidson <> wrote:
>>> Hello,
>>> I am trying to estimate an ivprobit model in Stata 11.2.
>>> I would like to estimate an F-statistic to assess weak instruments and
>>> perform other tests to assess the potential endogeneity of the
>>> instrument. None of the commands available with ivreg seem to work. I
>>> have looked at the help for ivprobit and the post estimation commands
>>> and cannot find these things. I imagine these calculations are basic,
>>> but I have not used ivprobit before and cannot find guidance online.
>>> I am estimating a standard ivprobit though the standard errors are
>>> clustered by groups.
>>> Thank you,
>>> Rob

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