I have a couple of comments, but no ready to use solution:
o If I remember correctly the use of the inverse mills ratio is derived
from the assumption that both the error in the selection equation and
in the equation of interest are normal. In that case I wouldn't use
the IMR with -mlogit-.
o You don't give a proper citation for the ``paper by Glewwe'', so I
can't look it up and give you advise on that.
o Models that deal with similar problems have been discussed in the
special issue of the Stata Journal in 2006 on simulated maximum
likelihood, The Stata Journal volume 6 issue 2.
o multinomial probit relaxes the IIA assumption if you allow for
correlation between error terms, but these models are typically
harder
to estimate, so I would start with multinomial logit and only move to
multinomial probit if necesary.
o Are you sure you don't have a double selection process going on?
Selecetion equation 1: is there a fever? Selection equation 2: Do you
have acces to modern healthcare? (if not there isn't much of choice)
Finally the model of interest: do you go to public, private, or other
healthcare institutions?
Hope this helps,
Maarten
--- Thuilliez Josselin <[email protected]> wrote:
> Dear list-members,
>
> I would like to estimate a multinomial logit or multinomial probit
> model with
> sample selection. The selection equation is based on a simple Logit
> or Probit
> model. I have 3 questions.
>
> Firstly, since there is only Heckprob in Stata I was wondering
> whether
> it would be correct to do the following:
> a- estimate the selection equation using Logit or Probit
> b- calculate the inverse Mill's ratio
> c- use the IMR as a regressor in the second-stage multinomial logit
> or
> probit model
>
> Secondly, if this is incorrect: how can I do? Is there a stata
> program
> that allow to take into account selection bias in multinomial models?
> I have seen a paper of Glewwe (3-choice multinomial probit with
> selectivity corrections) but it does not provide any solution for
> programing this in Stata.
>
> Thirdly, if there is a way to solve this problem, is it better to use
> the multinomial Logit or the multinomial Probit. Is it possible for
> instance, to relaxe the IIA assumption using the multinomial probit
> and at the same time correcting for the selection bias?
>
> The object of the study is to determine the determinants of
> healthcare
> seeking behaviour for children with fever in developing countries.
> My data looks like:
> First choice: Dummy variable for fever: 0 (no fever) / 1(fever)
> Second choice:
> 0 No acces to modern healthcare (reference category)
> 1 Public health facility
> 2 Private health facility
> 3 Other medical facility
>
> I'd greatly appreciate any suggestions.Thank you in advance.
>
> Josselin
> *
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>
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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