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st: When to use Poisson or Negative Binomial

From   "Querze, Alana Renee" <>
To   "" <>
Subject   st: When to use Poisson or Negative Binomial
Date   Thu, 26 May 2011 16:14:26 +0000

I am trying to figure out how to justify the use of either

xtpqml dvar ivar, fe


xtnbreg dvar ivar, fe

where my data is overdispersed. 

Cameron and Trivedi write that:

"the negative binomial has the attraction that, unlike Poisson, the estimator is designed to explicitly handle overdispersion... this may lead to improved efficiency in estimation and a default estimate of the VCE that should be much closer to the cluster-robust estimate of the VCE... at the same time, the Poisson panel estimators rely on weaker distributional assumptions˗˗essentially, correct specification of the mean˗˗and it may be more robust to use the Poisson panel estimators with cluster-robust standard errors" (Cameron and Trivedi, 2010, p.641).

But I don't know whether it is better to sacrifice robustness or efficiency.

Anyone know how to justify the use of one over the other? (BTW I have just under 400 districts and 52 months in my panel data).


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