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

From   Martin Weiss <[email protected]>
To   [email protected]
Subject   Re: st: difference between -heckman- and -treatreg-
Date   Sun, 31 Aug 2008 20:50:48 +0200

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.


Quoting Shehzad Ali <[email protected]>:


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,

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