Re: st: Sequential Probit

[Maarten buis <maartenbuis@yahoo.co.uk>]

--- On Thu, 3/3/11, Elin Vimefall wrote:
> I would like to use a sequential probit with three steps to
> analyze schooling of children:
> 
> Step 1: Do the child have  any formal education
> Step 2: Have the child finished primary education
> Step 3: Is the child currently in secondary education (or
> above)?
> 
> Does anyone know how to do this in stata?

Say you have an education variable, ed, where ed==1 when child 
has no formal education, ed==2 when child has finish primary
and stopped, and ed==3 when child is currenltly in secondary
education. Then you create two new variables:

gen byte ed12 = ed >= 2 if !missing(ed)
gen byte ed23 = ed == 3 if !missing(ed) & ed12 == 1

So ed12 is 1 when the child passed the first transition and 0
when it failed, and ed23 is 1 when the child passed the 
second transition, 0 when it failed and missing when it was
no longer "at risk", that is, the child failed the first 
transition.

Say you wanted to include the variables x1 and x2 as your
explanatory variable, then you would estimate a sequental
probit as follows:

probit ed12 x1 x2
probit ed23 x1 x2

[Warning: shameless self-promotion coming up]

Personally I prefer the sequential logit, as I find the
results easier to interpret, there is a nice decomposition
possible the relates the effects of x1 and x2 on the highest
achieved outcome to the effects of these variables during
each transition (I should think it is nice as I developed
it...), and I developed some tools to investigate the 
potential influence of unobserved variables in this model.

The decomposition is discussed here:
<http://www.maartenbuis.nl/dissertation/chap_6.pdf>

The tools for investigating the potential influence of 
unobserved heterogeneity are discussed here:
<http://www.maartenbuis.nl/publications/uh.html>

Both are implemented in the -seqlogit- package, which can 
be downloaded by typing in Stata -ssc install seqlogit-
 
> Is there any different between a sequential probit model
> and a multivariat probit with sample selection?

Yes, the latter model estimates more structure on the error 
terms. The problem with that is that there is obviously 
very little information in your data on that structure, so
model assumptions tend to be too important in such models 
for my taste, but tastes notoriously differ.

Hope this helps,
Maarten

--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany

http://www.maartenbuis.nl
--------------------------


      

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