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Re: st: logit with sample selection

From   Nishant Dass <[email protected]>
To   [email protected]
Subject   Re: st: logit with sample selection
Date   Mon, 25 Sep 2006 08:44:35 -0700 (PDT)

Hi Ian, Jean, Anders, and Maarten,

Thank you everyone for responding to my query.  

I am quite sure that the formula suggested by Ian wouldn't
work because, as indicated by Maarten, it would have to be
something that reflects the bivariate logistic
distribution.  I am aware of the bivariate normal formula
mentioned below but it wouldn't apply for a logit model.  

I was only wondering whether there is something similar for
a logit model because I had found this link in the
archives, which shows the IMR calculation for -mlogit- (but
not for -logit- explicitly.)  Check this:

As for Jean's suggestion about -heckprob-: I didn't want to
use that because 1) I have already tried it and it's taking
forever to converge, and 2) -logit- fits my data better
than -probit- and so, I wanted to use something like
"heckman + logit".  

Finally, Anders' suggestion: it is not immediately clear to
me how -gllamm- is applicable in my case but I will check

In any case, thanks a lot for the discussion.

If anyone can check the above link and add something for
-logit-, that'd be great.



--- Ian Watson <[email protected]> wrote:

> Nishant
> The approach you outline will work. The steps in Stata
> are straightforward.
> For example, if participation has two outcomes (working
> or not working),
> and you want an inverse mills ratio for the working
> outcome:
> logit work  age edu children region
> capture drop phat
> capture drop imr
> predict phat if e(sample), xb
> gen imr = normden(phat)/norm(phat)
> (Note that the capture drop lines are only needed if you
> insert this
> code into a do file which runs multiple times).

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