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Implicit Substantive Assumptions Underlying the Generalized Event Count Estimator

Published online by Cambridge University Press:  04 January 2017

Christopher H. Achen
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Abstract

The Generalized Event Count (GEC) estimator (King 1989a) is a statistical model for event counts. Its great attraction is that it provides a general likelihood function for count data, regardless of whether the data come from a Poisson, binomial, or negative binomial distribution. In consequence, it has been used in several recent statistical studies of event counts in the social sciences.

Underlying the GEC, however, are unorthodox substantive assumptions about how the event counts have been generated (Amato, this volume). This paper gives some simple examples in which the GEC logic is clearly visible, and it shows how failures of the implicit assumptions can lead to erroneous GEC coefficient estimates and standard errors.

Type
Symposium on the Generalized Event Count Estimator
Information
Political Analysis , Volume 6 , 1996 , pp. 155 - 173
Copyright
Copyright © Society for Political Methodology 

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