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st: biprobit with endogenous regresor and marginal effects


From   Lina C <linacs81@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: biprobit with endogenous regresor and marginal effects
Date   Wed, 17 Aug 2011 08:50:25 +0100

Hello,

I'm estimating a bivariate probit model with an endogenous regressor
(that is instrumented). I have been following the threat (see below)
where it is suggested to calculate manually the marginal effects given
that -mfx neither -margins would work to estimate the marginal
effects.

Y1 = Y2 X
Y2 = Z X

I have two questions:
1. I have calculated the marginal effects as proposed below. However,
they have a different sign to the original coefficient of the
biprobit. I was wondering if this could happen or if there has been
some improvement to calculate the marginal effects in those cases in
Stata.

2. Is it common for the standard errors using the iprobit to be large
in comparison to running a 2SLS with 2 binary outcomes?

Thank you.

Lina.



-----Original Message-----
From: [hidden email]
[mailto:[hidden email]] On Behalf Of Austin Nichols
Sent: segunda-feira, 1 de Fevereiro de 2010 18:03
To: [hidden email]
Subject: Re: st: marginal effects in biprobit and average treatment effect
in switching probit

Paula Albuquerque <[hidden email]>:
-mfx- is not really appropriate (and -margins- will refuse to participate).
You need to fully specify what margin you are thinking about to get a
sensible marginal effect. Try calculating the marginal effect of X using
predictions after your -biprobit- and after the user-written command.
E.g.you might want to calculate the conditional prob of Y=1 given X=1
less the cond prob of Y=1 given X=0, letting X=1 and X=0 in turn for
each observation, and then averaging over observations.

sysuse nlsw88, clear
g x=race==1
g y=married
biprobit (y=x grade south smsa) (x=industry occupation union)
mfx
* margins, dydx(*)
g wasx=x
replace x=1
predict p1a, p11
predict p1b, p10
predict p1c, p01
predict p1d, p00
g p1=p1a/(p1a+p1c)
replace x=0
predict p0a, p11
predict p0b, p10
predict p0c, p01
predict p0d, p00
g p0=p0b/(p0b+p0d)
replace x=wasx
drop wasx
g dp=p1-p0
su dp
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