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st: Count data model with underdispersion


From   F Tollnek <f.tollnek@student.uni-tuebingen.de>
To   statalist@hsphsun2.harvard.edu
Subject   st: Count data model with underdispersion
Date   Mon, 23 Jan 2012 11:43:43 +0100

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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