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Re: st: difference between -heckman- and -treatreg-
Thanks, Martin and Mark. I appreciate that the two phenomena of sample
selection and endogeneity bias are different in terms of whether or not the
outcome variable is observed. But are formulae for hazard/inverse Mills
ratios the same for the two cases since they both use a probit model to
generate the ratio? Obviously, as you mentioned, the outcome variable and
covariates will be different in the probit models for the -heckman- and
-treatreg-.
Secondly, once we have the ratio, do both heckman and treatreg use the
ratio as an additional regressor in the same way? If this is true, then the
difference between the two is only in the probits, and once we have the
probit then IMR or Hazard would be calculated and used in the outcome
equation in the same way. Is that right?
Finally, why do we call the ratio 'hazard' in -treatreg- and 'imr' in
-heckman-?
Thank you,
Shehzad
On Aug 31 2008, Martin Weiss wrote:
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 <[email protected]>:
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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