st: Count data model with underdispersion

[F Tollnek <f.tollnek@student.uni-tuebingen.de>]

Dear Statalist Team!

I am working with a count data model, where my dependent variable is  
the number of children per family. The independent variables are  
dummies (birth decades, occupational groups) and the data set is a  
cross section.

Because there are uncertainties about the people who reported "zero"  
children, I have to truncate the data at the zero values. As often  
proposed, I used the Zero Truncated Poisson model for analyzing my  
data, but the problem is that there is significant underdispersion  
given.

Cameron and Trivedi (Microeconometrics Uisng STATA (2010), S. 575)  
suggest for ordinary Poisson and significant Overdispersion, to use  
the option "vce(robust" as to correct for this problem. Does this also  
work for ztp and underdispersion?

Another possibility would be a Generalized Poisson Model, which  
delivers smaller standard errors. But, if I compare the Akaike  
Criterion for both if these models, the ztp gets a better value. Could  
you give me a hint, which model I should use?
If I should use the Generalized Model, can you tell me, how I can get  
the R squared?

Furthermore, I would like to calculate marginal effects, which I did  
with "margins". Unfortunately margins is not supported by "outreg2".  
Can I still use the mfx command in Stata 11 to calcualte the marginal  
effect? (Because mfx is supported by outreg2).


These are a lot of questions, but I hope that someone can help me.

Thank you very much in advance!

Best regards

Franziska
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