st: fixed effects glm - fractional dependent variable

[joe j <joe.stata@gmail.com>]

Dear all,

I have a panel data with the dependent variable being a faction,
including some zeros (about 1%) and ones (about 10%). These 0s and 1s
are real outcomes indeed (that is, not the results of censoring).

So I am going in favor of a glm model as proposed in the literature
(e.g. Papke, Leslie E. and Jeffrey M. Wooldridge. 1996.  Econometric
Methods for Fractional Response Variables with an Application to
401(k) Plan Participation Rates. Journal of Applied Econometrics
11(6):619-632.):

"glm dependent_variable independent_variable, family(binomial)
link(logit) robust"

What I would like to do is run a fixed effect model. However, there
are too many dummy variables to create (over 16,000 in a sample of
over 40,000 observations); moreover, I am not sure dummy variable
approach is appropriate given the non-linear nature of the model.

My first thought was to use:

vce(cluster panel_variable)

Is that the closest I could get to a fixed effect model?

Thanks,
Joe.
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