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st: Marginal effet and s.e. after logit2


From   Mélanie Lefèvre <Melanie.Lefevre@kuleuven.be>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: Marginal effet and s.e. after logit2
Date   Thu, 5 Dec 2013 09:53:07 +0000

Dear statalist users,

I am trying to use -margins- after the command logit2 (similar to cluster2, from here: http://www.kellogg.northwestern.edu/faculty/petersen/htm/papers/se/se_programming.htm). However, logit2 does not support the predict option p. 

. logit2 Y X1 X2, fcluster(state) tcluster(month)
(output hidden)
. estimates esample:
. margins, dydx(t_7) predict(p)
Warning: cannot perform check for estimable functions.
option p not allowed
r(198);

The xb option (default in logit2) works well:
. margins, dydx(X1)
Warning: cannot perform check for estimable functions.

Average marginal effects                          Number of obs   =    1342637

Expression   : Linear prediction, predict()
dy/dx w.r.t. : X1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       X1 |  -.0270068   .0088744    -3.04   0.002    -.0444003   -.0096132
------------------------------------------------------------------------------

I would like to obtain the marginal effect, as well as a confidence interval for it, expressed in probabilities rather than in linear prediction.

I tried to calculate the marginal effect and the s.e. by hand:
. predict xb, xb
. gen me=exp(xb)/(1+exp(xb))^2*_b[X1]
. matrix V=get(VCE)
. matrix J=r(Jacobian)
. matrix M= J*V*J'
. display sqrt(M[1,1])
The variable 'me' gives me the marginal effect but the s.e. are not displayed because logit2 does not return the Jacobian. I tries the same procedure after logit and it gives me exactly the same result as margins.

I also tried to modify the logit2 ado file to make it accept the p option but fail to do so.

Does someone has any idea of how I could obtain the correct standard errors for the marginal effect (expressed in probabilities) after the command loigit2?

Thanks a lot.

Mélanie.

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