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The Relative Performance of Poisson and Negative Binomial Regression Estimators
Author(s) -
Blackburn Mckinley L.
Publication year - 2015
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/obes.12074
Subject(s) - overdispersion , negative binomial distribution , estimator , count data , statistics , poisson distribution , mathematics , poisson regression , econometrics , negative multinomial distribution , quasi likelihood , regression analysis , binomial (polynomial) , beta binomial distribution , population , demography , sociology
Negative binomial estimators are commonly used in estimating models with count‐data dependent variables. In this paper, sampling experiments are used to evaluate the performance of these estimators relative to the simpler Poisson estimator in finite‐sample situations. The results do not suggest a clear preference for negative binomial estimators in situations in which the underlying dependent variables are overdispersed, unless the researcher is comfortable in assumptions about the precise form of the overdispersion.