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Re: st: bootstraping two stages together


From   "Danny Cohen-Zada" <danny.cohen.zada@gmail.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   Re: st: bootstraping two stages together
Date   Wed, 18 Jun 2008 23:08:35 +0200

Thank you very much for you very kind support. Actually, an ordinal probit model may also be appropriate since my outcome variable is level of health (My research is on the effect of religiosity (10 levels) on health (very healthy, somewhat healthy, not healthy). Does anybody provides consistent estimates for an iv oridnal probit model?

If not, i think i will run ivprobit models as you suggested. I guess people will not believe in an estimate that is not consistent. Do you agree?

Thanks again for your useful ideas

Danny


----- Original Message ----- From: "Austin Nichols" <austinnichols@gmail.com>
To: <statalist@hsphsun2.harvard.edu>
Sent: Wednesday, June 18, 2008 10:55 PM
Subject: Re: st: bootstraping two stages together



Danny Cohen-Zada <danny.cohen.zada@gmail.com>:
I think that's better than the first approach, but still not a
consistent estimator.  I don't know that anyone has derived one for
the multinomial logit case.  But if you are bound and determined to
proceed without showing consistency, then yes, use the control
function approach like so:

prog inconsist
syntax varlist, y2(varlist) z(varlist)
gettoken y x: varlist
reg `y2' `x' `z'
tempvar e
predict double e, resid
mlogit `y' `y2' `x' `e'
end
bs, reps(100): inconsist outcome xvars, y2(endogvar) z(instr)

But I think you could just run some -ivprobit- regressions instead...
g y0=(outcome==0) if !mi(outcome)
g y1=(outcome==1) if !mi(outcome)
g y2=(outcome==2) if !mi(outcome)

On Wed, Jun 18, 2008 at 4:42 PM, Danny Cohen-Zada
<danny.cohen.zada@gmail.com> wrote:
Dear Professor Austin,

Did i understand you well that i should do the following: Run the first
stage

y2 = b0+b1*x1+b2*x2+b3*z1 (z1 is an excluded instrument for y2)

then take the residuals of this equation - v2(hat)

Finally, I should estimate

y1 = a0+a1*y2+a2*x1+a3*x2+a4*v2(hat) (where y1 obtain the values
0,1,2)


If i am right, should i then also bootstrapt the standard errors.


Best,

Danny


----- Original Message ----- From: "Austin Nichols"
<austinnichols@gmail.com>
To: <statalist@hsphsun2.harvard.edu>
Sent: Wednesday, June 18, 2008 6:06 PM
Subject: Re: st: bootstraping two stages together



Danny Cohen-Zada <danoran@bgu.ac.il>:
You have more to worry about than correcting SEs--that does not sound
like a consistent estimator; see e.g. pp 12-13 of
http://www.nber.org/family/WNE/lect_6_controlfuncs.pdf
viz.
"Plugging in fitted values for y2 only works in the case where the
model is linear in y2"

On Wed, Jun 18, 2008 at 12:47 PM, Danny Cohen-Zada <danoran@bgu.ac.il>
wrote:

Dear stata members

I have a multinomial logit regression in which one of the covariates is
endogenous.

More specifically, the model is:


1) y1 = a0+a1*y2+a2*x1+a3*x2 (where y1 obtain the values
0,1,2)

2) y2 = b0+b1*x1+b2*x2+b3*z1 (z1 is an excluded instrument for y2)


To run this model, i first estimate equation 2 and obtain expected y2 and
then plug it in equation 1 (which is a multinomial logit regression). In
this case, i know that the standard error of the estimated a1 coefficient
is
not correct. I also know that i must bootstrap the two stages together
but I
do not know how to do it.

I will be thankful to anybody that can guide me in this issue.

Danny
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