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Re: st: Bivariate probit model with partial observability and survey data

From   Stas Kolenikov <[email protected]>
To   [email protected]
Subject   Re: st: Bivariate probit model with partial observability and survey data
Date   Fri, 19 Aug 2011 09:20:18 -0500

-svy- likes to take over the formatting of output, and, in particular,
it suppresses the iteration log. If you type -svy, noisily: biprobit
(whatever)-, you'd probably see more. With weights and such, the
computation may take even longer than with i.i.d. settings, although
it should be in the order of single to low double digit %, rather than
a factor of 2 or 3.

BTW, you need to provide full references to whatever you are citing.
And the issue that you have is not with the bivariate probit, but with
-svy-, so non-econometricians would have just skipped your email.

2011/8/18 Eduardo Andrés Alfonso Sierra <[email protected]>:
> Hello everyone
> I am estimating a bivariate probit with partial observability
> following Poirier (1980), hoping to disentangle the determinants of
> the decision to participate in a health related program and the
> decision made by the program to accept or reject a person (which, for
> some variables might be in opposite directions). Hence, I have two
> decision functions that looks something like this:
> Y1 = X1*b + X2*c + Ui
> Y2 = X1*d +         + Vi
> The first one, models the decision made by the person whether or not
> to apply to the program.
> The second one, models the decision made by the people who run the
> program whether to accept or reject the person (and the exclusion
> restriction comes from the fact that the people running the program
> cannot observe several characteristics of the person applying, which
> might actually influence his decision to apply - X2).
> Partial observability arises from the fact that I can only observe if
> the person participates in the program (Y=Y1*Y2), but not the
> decisions Y1 and Y2 independently.
> So I am doing something like this in Stata:
> biprobit (apply = age male educ healthstatus riskfactors riskaversion)
> (accept = age male educ healthstatus), partial
> Where apply and accept are both equals to the participation status
> (Y=Y1*Y2), as explained in
> After trying several variables, a reasonable model converged (although
> it takes quite a lot of time).
> Now my problem is that I also have to take into account the survey
> design (quite complex I think - two stages, stratified, ...).
> According to the survey design, for estimating proportions and other
> parameters, I successfully configured the survey data in Stata as
> follows:
> svyset mysvypsu [pweight=expfact], fpc(mysvyfpc) strata(mysvystrata)
> singleunit(certainty) || segment
> So, after that I tried running the biprobit with the survey prefix
> (svy:biprobit) and it seems it does nothing. It just freezes showing
> the message: (running biprobit on estimation sample).
> I know that the the biprobit works quite fine with survey data (svy
> prefix), because I have used it before, but without the issue of
> partial observability (and also with significant fewer independent
> variables), but in this case, it is just not working at all!
> Any suggestion? Any help or idea would be greatly appreciated!
> Thanks in advance,
> Eduardo
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Stas Kolenikov, also found at
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