Dear Austin, many thanks for your comments. I somehow felt my manual two-tep
was incorrect, but couldn't tell the source of invalidness. Can I follow-up on
my query and ask you for help on a related matter. The following command for
displaying the marginal effects for the MLE ivprobit:
mfx compute, predict(p)
does not allow for standard error calculation, the option nose is imposed. Any
ideas on how to get them?
Many thanks
Alejandro
In message <[email protected]>
[email protected] writes:
> Alejandro Delafuente --
> I cannot speak to your data, but your manual two-step is invalid (see
> Wooldridge http://www.stata.com/bookstore/cspd.html for more detail),
> as you cannot include the fitted Xb as a regressor and get an IV
> estimate. You can include the residual from the first step as an
> additional regressor in many nonlinear models to get an IV estimate,
> and the test that the coefficient on the residual is zero is a test of
> endogeneity. See below code for a comparison of methods. How are you
> calculating marginal effects? Carefully, I hope.
>
> sysuse auto, clear
> ivprobit for mpg (pr=wei), nolog
> est sto ivprobit
> ivprobit for mpg (pr=wei), twostep
> est sto ivp2step
> reg pr mpg wei
> predict vhat, resid
> predict xb
> probit for mpg pr vhat, nolog
> est sto man2step
> ren pr waspr
> ren xb price
> probit for mpg pr, nolog
> est stor wrong2step
> est table *, eq(1)
>
> On 12/6/06, Alejandro Delafuente
> <[email protected]> wrote:
> > Hello statalisters, am trying to estimate an ivprobit through maximum
> > likelihood: ivprobit dependent_var a b c (endogenous_var= d e d*b e*c)
> > I have a group of instruments two of which stand alone and another two have
> > been interacted with some variables from my group of exogenous regressors.
> > Some of my marginal effects have an implausible magnitude, in particular the
> > instrumented variable (ie, 4.8). Could someone explain to me the reason for
> > this inflated effects?
> >
> > I also tried to reestimate the above model in a two-step fashion:
> > ivprobit dependent_var a b c (endogenous_var= d e d*b e*c), twostep
> > Then again I obtained high magnitudes in the marginal effects of my
> > instrumented regressor.
> > I did the two-step estimation manually, first, regressing my endogenous var
on
> > my set of instruments and the other exogenous regressors, then I predict the
> > values and fit them into the probit. This time the coefficient of my
regressors
> > gave more plausible marginal effects. For instance, the marginal effect on
my
> > instrumented variable is 0.44). Obviously the manual procedure and Stata are
> > not doing the same thing, but not sure why. I can only think on the lack of
> > adjusment of the variance-covariance matrix in the manual procedure, but
that
> > should only affect the standard errors, isn't it?
> >
> > P.S.: A last bit of information is that my endogenous variable was generated
> > through a regression with some of the coefficients that are also included in
> > the probit model. Could this explain part of the inflated marginal effects
in
> > both of my ivprobit estimations.
> > Many thanks,
> > Alejandro
> >
> >
> > --
> > Alejandro de la Fuente
> > Department of International Development/QEH
> > University of Oxford, Mansfield Road, Oxford OX1 3TB
> > Tel: 01865 281836
> >
> > *
> > * 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/
> >
> *
> * 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/
>
--
Alejandro de la Fuente
Department of International Development/QEH
University of Oxford, Mansfield Road, Oxford OX1 3TB
Tel: 01865 281836
*
* 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/
