Re: st: difference between -heckman- and -treatreg-

[Martin Weiss <martin.weiss@uni-tuebingen.de>]

Well, start from the examples in -h heckman- and -h treatreg-, and do  
not be fooled by the similarity with respect to computation: There is  
a reason why Stata supplies two estimators.

In - h heckman-, the wage that is supposed to be modelled is missing  
in 657 cases (-ta wage, m- to see that). Heckman allows one to take  
into account the mechanism that determines the censoring of 657 cases,  
i.e. the labor supply behavior of the women in the dataset. So the  
selection equation models this question with -possibly- different  
covariates from the outcome equation - the determination of the wage  
itself.

-h treatreg-, on the other hand, shows the effect of the -enodgenous-  
choice of attending college on earnings. There are no missing cases  
here (-ta ww, m- to see that) but the choice of a higher degree  
impacts earnings. As more able students tend to choose this career  
track, the decision is endogenous and must be explicitly modelled.


HTH
Martin

Quoting Shehzad Ali <sia500@york.ac.uk>:


> Hi,
>
> I was wondering if someone can explain the difference between how
> -heckman- and -treatreg are estimated. I understand that analysts
> usually prefer -heckman- for sample selection bias and -treatreg- for
> endogeneity bias. But I was not sure how the two models are different
> computationally because they both use hazard ratio (or inverse Mills).
> Is hazard ratio different from IMR? Can anyone direct me to an article
> that explains the computational and theoretical difference between the
> two models?
>
> Thank you,
>
> Shehzad
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