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# Re: st: Calculating margins after biprobit

 From Tirthankar Chakravarty To statalist@hsphsun2.harvard.edu Subject Re: st: Calculating margins after biprobit Date Tue, 6 Dec 2011 03:10:12 -0800

```Two comments:

1) The way that you have estimated the binary outcome with binary
endogenous variables model using -biprobit- is not correct. Here is a
replication of an example in Wooldridge, "Econometric Analysis of
Cross-Section and Panel Data", 2nd ed., 2010, MIT Press, to be found
in table 15.2, pg. 598:

*********************************************************************************
use http://fmwww.bc.edu/ec-p/data/wooldridge2k/LABSUP, clear
biprobit (worked=nonmomi educ c.age##c.age black hispan morekids) ///
(morekids=nonmomi educ c.age##c.age black hispan samesex)
*********************************************************************************

Here "morekids" is the binary endogenous variable and "worked" is the
binary outcome. Note how the model is entered in Stata. The
coefficient on the binary endogenous variable is -0.703, as reported
in the text.

2) It is important to be sure what you mean by marginal/partial
effects in this context. One such quantity of interest, which can be
called partial effect of a change in the binary endogenous variable,
for an individual would be:

P[Y1i=1|Y2i=1, Zi] - P[Y1i=1|Y2i=0, Zi]

where Y1 is the binary outcome and Y2 is the binary endogenous
variable; Z are all the exogenous variables in the system. This can be
constructed in Stata as the nonlinear prediction:

***********************************
predictnl probch = predict(pcond1) - ///
predict(p10)/(1-predict(pmarg2))
***********************************

after the estimation above. The sample average of this quantity (use
-summ-) is the average partial effect, where partial effect is defined
as above. Other "partial effects" of interest can be defined.

Please see section 15.7.3 in Prof. Woodridge's book for an excellent
discussion of these issues.

T

On Mon, Dec 5, 2011 at 12:37 PM, urbain thierry YOGO <yogout@gmail.com> wrote:
> Try the following command
> margins, dydx(_all) post
> this is equivalent to  mfx compute, predict(p11) with
> (p11)=(depvar1=1, depvar2=1)
> however a simple and general way is the following
>
> The marginal effects for, Pr(depvar1=1, depvar2=1), are
> mfx compute, predict(p11)
> The marginal effects for Pr(depvar1=1, depvar2=0) are
> mfx compute, predict(p10)
> The marginal effects for Pr(depvar1=0, depvar2=1) are
> mfx compute, predict(p01)
> The marginal effects for Pr(depvar1=0, depvar2=0) are
> mfx compute, predict(p00)
>
>
>
> 2011/12/5, Wakeman, Simon <Simon.Wakeman@esmt.org>:
>> I am investigating the effect of a binary variable X on a binary variable Y,
>> where X is potentially endogenous. I estimated a biprobit:
>>  biprobit (Y = X ) (X = Z).
>>
>> However, when I use the following margins command
>>  margins, dydx(X) over(X)
>> I get the error message:
>> "default prediction is a function of possibly stochastic quantities other
>> than e(b)"
>>
>> I also tried mfx but it does not seem to produce a marginal effect for X.
>>
>> I would much appreciate if anyone can tell me how to obtain the marginal
>> effect of X on Y.
>>
>>
>> Simon
>>
>>
>> *
>> *   For searches and help try:
>> *   http://www.stata.com/help.cgi?search
>> *   http://www.stata.com/support/statalist/faq
>> *   http://www.ats.ucla.edu/stat/stata/
>>
>
>
> --
> *Urbain Thierry YOGO
> P.h.D candidate in Economics*
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/

--
Tirthankar Chakravarty
tchakravarty@ucsd.edu
tirthankar.chakravarty@gmail.com

*
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```