An Agent-Based Model of the 2020 International Policy Diffusion in Response to the COVID-19 Pandemic with Particle Filter
Yannick Oswald,
Nick Malleson,
Keiran Suchak
Abstract:Global problems, such as pandemics and climate change, require rapid international coordination and diffusion of policy. These phenomena are rare however, with one notable example being the international policy response to the COVID-19 pandemic in early 2020. Here we build an agent-based model of this rapid policy diffusion, where countries constitute the agents and with the principal mechanism for diffusion being peer mimicry. Since it is challenging to predict accurately the policy diffusion curve, we utiliz… Show more
ObjectiveThis article examines the diffusion of paramilitary police units across the United States to consider the computational turn in social science.MethodsThe process of police diffusion is modeled by comparing traditional predictive models with agent‐based modeling (ABM) under constant and flexible binding conditions. The data are drawn from the Census of State and Local Law Enforcement Agencies 2000, 2004 and the United States Cities Database.ResultsABM was not superior to traditional predictive models when it came to predicting policy diffusion and that flexible binding provides superior predictive capabilities over constant binding.ConclusionsPublic policy scholars should exercise caution in adopting computational methods as they may not offer advantages over traditional predicative analysis. Policy diffusion of police militarization is not driven by geographical proximity but may reflect hierarchical influences in the form of federal policy or the influence of far‐flung organizations perceived to be similar. This may cause inappropriate policies and practices to be adopted.
ObjectiveThis article examines the diffusion of paramilitary police units across the United States to consider the computational turn in social science.MethodsThe process of police diffusion is modeled by comparing traditional predictive models with agent‐based modeling (ABM) under constant and flexible binding conditions. The data are drawn from the Census of State and Local Law Enforcement Agencies 2000, 2004 and the United States Cities Database.ResultsABM was not superior to traditional predictive models when it came to predicting policy diffusion and that flexible binding provides superior predictive capabilities over constant binding.ConclusionsPublic policy scholars should exercise caution in adopting computational methods as they may not offer advantages over traditional predicative analysis. Policy diffusion of police militarization is not driven by geographical proximity but may reflect hierarchical influences in the form of federal policy or the influence of far‐flung organizations perceived to be similar. This may cause inappropriate policies and practices to be adopted.
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