The Spread of Policy Diffusion Studies: A Systematic Review and Meta-Analysis, 1990-2018

Abstract

Research on how policies diffuse throughout the American federal system is robust and vast, but there has yet to be a systematic accounting for its results. Using a systematic review and metaanalysis, this study presents the most comprehensive analysis to date of how policy innovation flows state-to-state and the average effects of commonly used variables in the study of policy diffusion (e.g., neighbor adoptions, ideological distance between states, legislative professionalism, and more). Additionally, heterogeneity in these effects is examined across regulatory, morality, and governance policy types. The study not only reveals what we know about policy diffusion after 30 years of quantitative analysis, it identifies several correctable gaps in the literature. The results not only support the efforts to expand diffusion research to large-n analyses, but they also reveal additional benefits of small-n event history studies for the progressive advancement of this important research program.

Information and Policy Innovation in U.S. States

“…. .” (Mallinson 2020, 26). Geographic continuity is thus a primary explanation for why states adopt new policies.…”

“…A significant body of research finds a positive effect of contiguity on policy adoption (W. D. Berry and Baybeck 2005;Walker 1969; see Gilardi 2016, andMaggetti andGilardi 2016 for detailed overviews of how geographic proximity has been used in diffusion research). In the most comprehensive meta-analysis review to date of diffusion studies, Mallinson (2020) finds that neighbors/ geographic contiguity remains one of the most common covariates in models of state policy diffusion (73% of the 507 studies analyzed), along with measures of slack resources, ideology, and legislative professionalism. Mallinson notes this is one of the few variables in his literature review that has a consistently positive effect on policy innovation across hundreds of publications, albeit with heterogeneous effects depending on the issue area.…”

Crossing the boundaries: reimagining innovation and diffusion

“…Although previous studies of policy innovation and diffusion have fruitful models, we can still develop a better understanding in Region 5, Region 6, Region 7, and Region 8 which emphasize the future predictions of scholars rather than the empirical studies based on past data. In Region 5, Mallinson (2020) Gilardi (2016) expands the existing concepts and their measurement and argues that we should discuss explicitly the practical implications of diffusion. In Region 7, Shippan and Volden (2012) provide seven lessons for scholars and practitioners who relate to policy diffusion.…”

Policy Diffusion Results: A New Database for Systematic Review and Meta-Analysis

“…is beyond the scope of this research note. Those results can be found in Mallinson (2020a). While external forces are of greatest interest to diffusion researchers who are working to identify the specific mechanisms that drive innovation adoption (learning, competition, coercion, emulation, social contagion), researchers from many different fields are interested in variables that are otherwise often used as controls in diffusion models.…”