Of course, you're right. In this case, -heckprob- does not make much
sense. Thanks for that one.
Regarding the -first- option, I get the first stage results no matter if
I turn the -first- option on or off (stata 10.0).
Best regards,
melanie
Martin Weiss schrieb:
> If all you want from -heckprob- are the first stage results, would it not be
> easier to use the respective -probit- instead of -heckprob- to get those
> predictions?
>
> *************
> webuse school, clear
> heckprob private years logptax, sel(vote=years loginc logptax) nolog first
> *shortcut to your goal
> prob vote years loginc logptax
> *************
>
> BTW, the first stage results in the -heckprob- are only displayed if the log
> for the maximization is on AND you specify the -first- option. Weirdly, when
> I turn the log off with the -nolog- option, -first- seems to be ignored...
>
> HTH
> Martin
>
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of mbaier
> Sent: Tuesday, November 04, 2008 12:19 PM
> To: [email protected]
> Subject: st: need help with heckprob in conjunction with ivprobit
>
> Dear statalisters,
> I am new to Stata and I am not sure if the estimation procedure below
> makes sense or if there are any pitfalls I may have ignored. Any help
> would be greatly appreciated.
>
> My overall goal is to estimate the propensity to cooperate (yes/no)
> subject to a few independent variables.
>
> 1) As first part of my estimation, I want to correct for selection bias,
> since only the innovators had to answer if they cooperate or not. I
> tried two ways,
> one is the procedure suggested according to
> http://www.stata.com/statalist/archive/2006-09/msg00772.html and the
> second one is doing a heckprob, more precisely:
>
> xi: heckprob coop xi.independent varlist, select (inno=xi.independent
> varlist), first
>
> In fact, I am not interested in the heckprob equation, but only in the
> selection equation, since I want to determine the Inverse Mill' s Ratio.
> After heckprob, I calculate the linear predictors of the selection equation
> predict psel, xbsel
> generate IMR= normalden(psel)/normal(pesel)
>
> I use the calculated values of IMR as additional regressor for the
> substantial equation in 2).
>
> I have two questions: Is there a difference if I use the heckprob or the
> procedure described in the link above (which was for a logit)? I
> understand that one is following a probit and the other one a logit
> distribution, but apart from this? As far as I can see from the results
> of the second equation, there seems to be no difference.
> Does it cause any problems if I only have categorial variables as
> regressors?
>
> 2) The second part, the substantial equation, is supposed to account for
> the selection bias of being an innovator or not AND the endogeneity of
> the R&D intensity as an IV.
> I consider R&D intensity as an endogneous variable, because theory says
> that the propensity to cooperate and R&D intensity are interdependent.
> Since cooperation is a dichotomous variable, I use
>
> xi: ivprobit coop xi.independent varlist IMR (R&D_int=instruments)
>
> The results of ivprobit show a significant Rho(-0.9), indicating that
> R&D_int is in fact endogeneous (as far as I understand).
> Unfortunately, not only the coefficient of the IMR turnes out to be
> totally insignificant, but many regressors have become insignificant,
> too. What does it mean and how can I solve this problem? I suspect that
> the insignificance of the IMR coefficient may be caused by the fact that
> the LR test of indep.equ. in the preceding heckprobit equation was
> Prob>chi2=0.1461, but I am not sure if this tips the scales.
>
> I know these are a lot of questions, but maybe someone could show me the
> right path. Maybe there are further aspects which I forgot to consider.
> Thanks a lot,
> melanie
>
> -
> melanie baier
> c-lab
>
>
>
>
>
>
>
> *
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>
> *
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>
--
Dipl.-Volkswirtin
Melanie Baier
C-LAB
Business Development
Fuerstenallee 11
33102 Paderborn, Germany
Phone: +49 5251 60 61 35
Fax: +49 5251 60 60 66
URL: www.c-lab.de
*
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