Journal of Quantitative Criminology

, Volume 24, Issue 3, pp 269–284

Overdispersion and Poisson Regression

Original Paper

DOI: 10.1007/s10940-008-9048-4

Cite this article as:
Berk, R. & MacDonald, J.M. J Quant Criminol (2008) 24: 269. doi:10.1007/s10940-008-9048-4


This article discusses the use of regression models for count data. A claim is often made in criminology applications that the negative binomial distribution is the conditional distribution of choice when for a count response variable there is evidence of overdispersion. Some go on to assert that the overdisperson problem can be “solved” when the negative binomial distribution is used instead of the more conventional Poisson distribution. In this paper, we review the assumptions required for both distributions and show that only under very special circumstances are these claims true.


Poisson regression Negative binomial distribution Count data Overdispersion 

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  1. 1.Department of CriminologyUniversity of PennsylvaniaPhiladelphiaUSA

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