From Meso Decisions to Macro Results: An Agent-Based Approach of Policy Diffusion

From Meso Decisions to Macro Results: An Agent-Based Approach of Policy Diffusion

Stéphane Luyet (Lausanne University Hospital, Switzerland)
DOI: 10.4018/978-1-4666-5954-4.ch009
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Abstract

Policy diffusion needs to be studied as a complex phenomenon, since it involves interdependent relationships between autonomous and heterogeneous countries. This chapter aims at developing a simple computational model based on a theoretical model of policy diffusion (Braun & Gilardi, 2006) that helps to explain the emergence of diffusion in a complex system. Based on three simple conditions (ready, choose, change) and a few internal and external characteristics that define countries and their interactions, the model presented in this chapter shows that policies do diffuse and lead to local convergence and global divergence. Moreover, it takes time for a country to introduce the best-suited policy and for this policy to become very effective. To conclude, diffusion is a complex phenomenon and its outcomes, as ensued from the author's model, are in line with the theoretical expectations and the empirical evidence.
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2. Computational Agent-Based Models And Diffusion

Computational agent-based models (CABMs) have several uses. The first that comes to mind is prediction3. For our purpose, to demonstrate the emergence of complex behavior arising from simple rules is a more interesting use. For instance, Schelling’s segregation model (Schelling 1978) shows that segregated neighborhoods can appear due to simple “thoughts” (“I want 30% of my neighborhood to be composed of neighbors who are like me”).

After defining what we mean by computational agent-based modeling (Section 2.1), we will explain some of the significant examples of CABMs developed in social and political science (Section 2.2).

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