st: Fixed effects logit model

["Marc Michelsen" <marcmichelsen@t-online.de>]

Dear Statalist-users,

I am estimating a logit model for a panel style data set. In order to
guarantee unbiased estimation, I have used company, industry and/or offer
year clusters (per Petersen, 2009). For my linear regressions I have made
positive experience with fixed-effects models. Their application for binary
outcome models is not as straightforward because the models rely solely on
within-variance. 

Running a fixed-effect logit model (-xtlogit, fe) shows highly significant
coefficients of my key variables, which would be very beneficial for my
study. However, more than 50% of my observations get lost in the regression
because of zero within variance. 
Is it consistent to show also a fixed effects logit model beside standard
logit models clustered by the above mentioned characteristics. What do I
have to keep in mind when interpreting the results (especially relative to
the other ML models)? Is it possible to calculate marginal effects for such
a fixed effects model (similar to Cameron/Trivedi, 2009, p. 516?

Thank you for considering this posting.

Regards
Marc  

Cameron, A. C., and P. K. Trivedi. Microeconometrics using stata: Stata
Press (2009).
Petersen, M. A. "Estimating standard errors in finance panel data sets:
Comparing approaches." Review of Financial Studies 22 (2009), 435.



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