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Re: st: IV estimation for probit models with binary endogenous variable...?


From   Antoine Terracol <Antoine.Terracol@univ-paris1.fr>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: IV estimation for probit models with binary endogenous variable...?
Date   Thu, 02 Apr 2009 12:50:47 +0200

If you are ready to assume joint normality, then -biprobit- should do the trick:

/*------------------------------*/
clear
set obs 10000
set seed 987654321
drawnorm e1 e2, cov(1,0.5\0.5,1)
drawnorm x1 x2 z1 z2
g endog=(1+z1+z2+e1>0)
g y=(1+endog+x1+x2+e2>0)
probit y endog x1 x2 /*biased*/
biprobit (y= endog x1 x2) (endog=z1 z2)
/*------------------------------*/

Antoine




F.S.A.Milway@warwick.ac.uk wrote:
Dear All,
I have a problem that you may be able to help with?

I have a model of the following form:

y = a + b1x1 + b2x2 + ... +xn + u

Where y = a binary dependent variable (a probit model)
X1 is a binary variable with potential reverse causality (endogenous)
x2 - xn are exogenous variables.

I wondered whether you may use IV for this? and how I would go about this?

Would I run for example:

probit X1 X2...Xn Z

save the predicted values and then put them back into my origional equation?

Any help with this matter would be greatly appreciated.

Kind Regards

Fiona M




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