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Event history analysis demonstrates changes in outcomes for 83 policies, suggesting optimal approaches for modeling policy diffusion.
Event history analysis (EHA) revolutionized the study of policy diffusion. However, many diffusion studies are snapshots of a policy’s spread. This begs the question of what we are learning from studies of (often) incomplete diffusion. The simple question that we ask – when should a diffusion study be conducted? – is complex to answer. We offer insight into this question using literature on EHA and empirical observation. We use data from the State Innovation and Policy Diffusion database on 83 policies that were adopted by at least 42 states to demonstrate how key results change as the observation window changes. We conclude with advice on how to approach modeling and interpreting incomplete policy diffusion in the future.
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Mallinson et al. (2025) studied this question.
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