title: Detecting causality in policy diffusion processes.
abstract: A universal question in network science entails learning about the topology of interaction from collective dynamics. Here, we address this question by examining diffusion of laws across US states. We propose two complementary techniques to unravel determinants of this diffusion process: information-theoretic union transfer entropy and event synchronization. In order to systematically investigate their performance on law activity data, we establish a new stochastic model to generate synthetic law activity data based on plausible networks of interactions. Through extensive parametric studies, we demonstrate the ability of these methods to reconstruct networks, varying in size, link density, and degree heterogeneity. Our results suggest that union transfer entropy should be preferred for slowly varying processes, which may be associated with policies attending to specific local problems that occur only rarely or with policies facing high levels of opposition. In contrast, event synchronization is effective for faster enactment rates, which may be related to policies involving Federal mandates or incentives. This study puts forward a data-driven toolbox to explain the determinants of legal activity applicable to political science, across dynamical systems, information theory, and complex networks.
authors: Department of Mechanical and Aerospace Engineering, New York University, Tandon School of Engineering, Brooklyn, New York 11201, USA.
authors: Carsten
authors: C
authors: Grabow
authors: Department of Community Health Sciences and Department of Health Policy and Management, Fielding School of Public Health, University of California, 650 Charles Young Dr., Los Angeles, California 90095, USA.
authors: James
authors: J
authors: Macinko
authors: Department of Nutrition, Food Studies, and Public Health, 411 Lafayette Street, New York University, Steinhardt School of Culture, Education, and Human Development, New York, New York 10003, USA.
authors: Diana
authors: D
authors: Silver
authors: Department of Mechanical and Aerospace Engineering, New York University, Tandon School of Engineering, Brooklyn, New York 11201, USA.
authors: Maurizio
authors: M
authors: Porfiri
mesh_terms: D019540:Area Under Curve; D015984:Causality; D003198:Computer Simulation; D019277:Entropy; D017711:Nonlinear Dynamics; D057766:Policy; D012372:ROC Curve; D014481:United States