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The Generalization in the Generalized Event Count Model, with Comments on Achen, Amato, and Londregan

Published online by Cambridge University Press:  04 January 2017

Gary King  and
Curtis S. Signorino
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Abstract

We use an analogy with the normal distribution and linear regression to demonstrate the need for the Generalized Event Count (GEC) model. We then show how the GEC provides a unified framework within which to understand a diversity of distributions used to model event counts, and how to express the model in one simple equation. Finally, we address the points made by Christopher Achen, Timothy Amato, and John Londregan. Amato's and Londregan's arguments are consistent with ours and provide additional interesting information and explanations. Unfortunately, the foundation on which Achen built his paper turns out to be incorrect, rendering all his novel claims about the GEC false (or in some cases irrelevant).

Type
Symposium on the Generalized Event Count Estimator
Information
Political Analysis , Volume 6 , 1996 , pp. 225 - 252
Copyright
Copyright © Society for Political Methodology 

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