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Approaches to Modeling the Adoption and Diffusion of Policies with Multiple Components

Published online by Cambridge University Press:  25 January 2021

Frederick J. Boehmke
Frederick J. Boehmke*
Affiliation:
University of Iowa
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Abstract

Scholars have begun to move beyond the dichotomous dependent variable—indicating whether a state adopts a policy or not in a given year—usually employed in event history analysis. In particular, they have devoted increasing attention to the components of policies that states adopt. I discuss a variety of estimators that have been employed to analyze the adoption and modification of policies with multiple components, including various forms of event history analysis, OLS, and event count models. With various modifications, the researcher can estimate models that treat each component as distinct, pool these models to leverage commonalities across components, or treat the components as identical parts of the same process. Each of these has its strengths and may be appropriate in certain circumstances. Nonetheless, in the majority of cases, some version of event history analysis for multiple or repeat failures is likely to be preferred. The different approaches are illustrated by studying state adoption of various obesity-related policies.

Type
The Practical Researcher
Information
State Politics & Policy Quarterly , Volume 9 , Issue 2 , Summer 2009 , pp. 229 - 252
Copyright
Copyright © 2009 by the Board of Trustees of the University of Illinois

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