> -----Original Message-----
> From: [email protected] [mailto:owner-
> [email protected]] On Behalf Of Tinna
> Sent: Tuesday, September 13, 2005 3:37 PM
> To: [email protected]
> Subject: Re: st: RE: Marginal effects after ivprobit
>
> Thanks for the answer Scott. Yes I am pretty sure.
>
> If you try the same estimations again without regressing quietly then
> you will probably see that the coefficients you get after mfx are the
> same as from the original estimation.
<snip>
But they are not.
. webuse laborsup, clear
. ivprobit fem_work fem_educ kids (other_inc = male_educ) , nolog
Probit model with endogenous regressors Number of obs = 500
Wald chi2(3) = 163.88
Log likelihood = -2368.2062 Prob > chi2 = 0.0000
----------------------------------------------------------------------------
Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+--------------------------------------------------------------
fem_work |
other_inc | -.0542756 .0060854 -8.92 0.000 -.0662027 -.04234
fem_educ | .211111 .0268648 7.86 0.000 .1584569 .26376
kids | -.1820929 .0478267 -3.81 0.000 -.2758316 -.08835
_cons | .3672083 .4480724 0.82 0.412 -.5109975 1.2454
-------------+--------------------------------------------------------------
/lnsigma | 2.813383 .0316228 88.97 0.000 2.751404 2.8753
/athrho | .3907858 .1509443 2.59 0.010 .0949403 .68663
-------------+--------------------------------------------------------------
sigma | 16.66621 .5270318 15.66461 17.731
rho | .3720374 .1300519 .0946561 .59581
----------------------------------------------------------------------------
Instrumented: other_inc
Instruments: fem_educ kids male_educ
----------------------------------------------------------------------------
Wald test of exogeneity (/athrho = 0): chi2(1) = 6.70 Prob > chi2 =
0.0096
. estimates store iv
. mfx, predict(p)
warning: predict() expression p unsuitable for standard-error calculation;
option nose imposed
Marginal effects after ivprobit
y = Probability of positive outcome (predict, p)
= .44363395
----------------------------------------------------------------------------
variable | dy/dx X
---------------------------------+------------------------------------------
other_inc | -.0214364 49.6023
fem_educ | .0833791 12.046
kids | -.0719183 1.976
male_educ | 0 11.966
----------------------------------------------------------------------------
. estimates store mfx
Or, all together for easy comparison:
. estout iv mfx, style(fixed) margin meqs(fem_work) label varwidth(24)
varlabels(_cons Constant) keep(fem_work:) collabels(,none)
iv mfx
Does female work?
Other income -.0542756 -.0214364
Female education level .211111 .0833791
Number of children -.1820929 -.0719183
Constant
Scott
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
