If you are trying to do selection bias correction as in Lee (1983) then you
may want to look at the SELMLOG command. Here's the description:
selmlog estimates linear regression models on a selected subset of
observations, where selectivity is modelled as a multinomial logit (as
opposed to univariate probit as in the Heckman model). It applies the
two-step method proposed by Bourguignon, Fournier and Gurgand (CREST, 2001,
www.crest.fr).
See http://www.crest.fr/pageperso/lmi/gurgand/selmlog.htm
Regards,
--Alex Cavallo
Lexecon
(312) 322-0208 voice
(312) 322-0218 fax
---------------------------------------------------------------------------------------------------------------------------------------------------------------
Fatma Bircan
Middle East Technical University
Department of Economics
210-2056
Hello,
I have been trying to do two-step estimation using mlogit. After
mlogit estimation, I calculate the lambda values for each choice as
follows;
pj= exp(v'b) where v is the set of explanatory variables in the
selection equationand b is the set of coefficients. j=0,1,...
Hj=invnorm(pj)
lambdaj=normd(Hj)/normprob(Hj)
and then including the lambda values, I estimate the equation of
primary interest which is a wage eqution in my case.
However, these estimation results do not give the efficient standard
errors. My question is that is there a stata rutin to obtain efficient
standard errors? How can I do the Heckman-correction to obtain
efficient standard errors.
Tahnk you in advance
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