--- Ian Watson wrote:
> 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)
I am not so sure. As I understand, the IMR is derived from the assumption
that the error terms in the selection equation and the wage equation
together form a bivariate normal distribution. In this logistic
framework they would form a bivariate logistic distribution and this animal
is a lot less pretty (or less extensively studied) than the bivariate normal.
I could be wrong though.
HTH,
Maarten
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting adress:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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