TY - JOUR
T1 - Persistent policy pathways
T2 - Inferring diffusion networks in the American States
AU - Desmarais, Bruce A.
AU - Harden, Jeffrey J.
AU - Boehmke, Frederick J.
N1 - Funding Information:
Previous versions of this article were presented at the Political Networks and Causality Conference (May 2013, University of Chicago), State Politics and Policy Conference (May 2013, University of Iowa), Political Networks Conference (June 2013, Indiana University), Political Methodology Conference (July 2013, University of Virginia), and New Frontiers in Policy Diffusion Conference (March 2014, University of Iowa). For helpful feedback, we thank Craig Volden, Chuck Shipan, Betsy Sinclair, Tom Carsey, Virginia Gray, Kristin Garrett, Josh Jansa, Brian Schaffner, Ray La Raja, Jesse Rhodes, Jan Box-Steffensmeier, Meg Shannon, Anand Sokhey, Scott Althaus, and the editors and anonymous reviewers at the APSR. Bruce A. Desmarais acknowledges support from the National Science Foundation (Grants No. SES-1357606 and No. CISE-1320219).
Publisher Copyright:
© 2015 American Political Science Association.
PY - 2015/4/23
Y1 - 2015/4/23
N2 - The transmission of ideas, information, and resources forms the core of many issues studied in political science, including collective action, cooperation, and development. While these processes imply dynamic connections among political actors, researchers often cannot observe such interdependence. One example is public policy diffusion, which has long been a focus of multiple subfields. In the American state politics context, diffusion is commonly conceptualized as a dyadic process whereby states adopt policies (in part) because other states have adopted them. This implies a policy diffusion network connecting the states. Using a dataset of 187 policies, we introduce and apply an algorithm that infers this network from persistent diffusion patterns. The results contribute to knowledge on state policy diffusion in several respects. Additionally, in introducing network inference to political science, we provide scholars across the discipline with a general framework for empirically recovering the latent and dynamic interdependence among political actors.
AB - The transmission of ideas, information, and resources forms the core of many issues studied in political science, including collective action, cooperation, and development. While these processes imply dynamic connections among political actors, researchers often cannot observe such interdependence. One example is public policy diffusion, which has long been a focus of multiple subfields. In the American state politics context, diffusion is commonly conceptualized as a dyadic process whereby states adopt policies (in part) because other states have adopted them. This implies a policy diffusion network connecting the states. Using a dataset of 187 policies, we introduce and apply an algorithm that infers this network from persistent diffusion patterns. The results contribute to knowledge on state policy diffusion in several respects. Additionally, in introducing network inference to political science, we provide scholars across the discipline with a general framework for empirically recovering the latent and dynamic interdependence among political actors.
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U2 - 10.1017/S0003055415000040
DO - 10.1017/S0003055415000040
M3 - Article
AN - SCOPUS:84928549274
SN - 0003-0554
VL - 109
SP - 392
EP - 406
JO - American Political Science Review
JF - American Political Science Review
IS - 2
ER -