Dear Stata experts,

I have been struggling with some count panel data and I would like to estimate it with fixed effects. My data shows a little bit of overdispersion (when fitted with quasi-poisson the overdispersion parameter is 5.01 and the overdispersion test in AER in R is significant).

So to account for over dispersion, after some googling and reading the books, I gathered that there are two options: 1) to use NB regressions and 2) to use cluster-robust SE when fitting the data with Poisson, such as the xtpoisson command in Stata with FE and VCE(Robust) options.

I know there is also the quasi-poisson option but I am not ready to go there yet.

My problem is that I have not found any guidance on choosing between these two options. I am new to the list so forgive me if this has been answered before. Any help will be greatly appreciated here.

Best,

Alice

I have been struggling with some count panel data and I would like to estimate it with fixed effects. My data shows a little bit of overdispersion (when fitted with quasi-poisson the overdispersion parameter is 5.01 and the overdispersion test in AER in R is significant).

So to account for over dispersion, after some googling and reading the books, I gathered that there are two options: 1) to use NB regressions and 2) to use cluster-robust SE when fitting the data with Poisson, such as the xtpoisson command in Stata with FE and VCE(Robust) options.

I know there is also the quasi-poisson option but I am not ready to go there yet.

My problem is that I have not found any guidance on choosing between these two options. I am new to the list so forgive me if this has been answered before. Any help will be greatly appreciated here.

Best,

Alice

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