A New Database for Inferring Public Policy Innovativeness and Diffusion Networks

41 Pages Posted: 11 Jul 2018

See all articles by Frederick J. Boehmke

Frederick J. Boehmke

University of Iowa - Department of Political Science

Mark Brockway

University of Notre Dame, College of Arts & Letters, Department of Political Science, Students

Bruce A. Desmarais

Pennsylvania State University

Jeffrey J. Harden

University of Colorado at Boulder - Department of Political Science

Scott LaCombe

University of Iowa

Fridolin Linder

New York University (NYU) - Social Media and Political Participation (SMaPP) Lab

Hanna Wallach

Microsoft Research New York City

Date Written: June 19, 2018

Abstract

Despite its rich tradition, there are key limitations to researchers' ability to make generalizable inferences about state policy diffusion. This paper introduces new data and methods to move from empirical analyses of single policies to the analysis of comprehensive populations of policies and rigorously inferred diffusion networks. We have gathered policy adoption data appropriate for estimating policy innovativeness and tracing diffusion ties in a targeted manner (e.g., by policy domain, time period, or policy type) and extended the development of methods necessary to accurately and efficiently infer those ties. Our State Policy Innovation and Diffusion (SPID) database includes 728 different policies coded by topic area. We provide an overview of this new dataset and illustrate two key uses: (1) static and dynamic innovativeness measures and (2) latent diffusion networks that capture common pathways of diffusion between states across policies. The scope of the data allow us to compare patterns in both across policy topic areas. We conclude that these new resources will enable researchers to empirically investigate classes of questions that were difficult or impossible to study previously, but whose roots go back to the origins of the political science policy innovation and diffusion literature.

Keywords: policy diffusion, policy innovation, latent networks

Suggested Citation

Boehmke, Frederick J. and Brockway, Mark and Desmarais, Bruce A. and Harden, Jeffrey J. and LaCombe, Scott and Linder, Fridolin and Wallach, Hanna, A New Database for Inferring Public Policy Innovativeness and Diffusion Networks (June 19, 2018). Available at SSRN: https://ssrn.com/abstract=3199383 or http://dx.doi.org/10.2139/ssrn.3199383

Frederick J. Boehmke

University of Iowa - Department of Political Science ( email )

Iowa City, IA 52242
United States

Mark Brockway

University of Notre Dame, College of Arts & Letters, Department of Political Science, Students ( email )

217 O'Shaughnessy Hall
Notre Dame, IN 46556
United States

Bruce A. Desmarais (Contact Author)

Pennsylvania State University ( email )

University Park, State College, PA 16801
United States

HOME PAGE: http://sites.psu.edu/desmaraisgroup

Jeffrey J. Harden

University of Colorado at Boulder - Department of Political Science ( email )

333 UCB
Boulder, CO 80309-0333
United States

HOME PAGE: http://spot.colorado.edu/~jeha9919/

Scott LaCombe

University of Iowa ( email )

341 Schaeffer Hall
Iowa City, IA 52242-1097
United States

Fridolin Linder

New York University (NYU) - Social Media and Political Participation (SMaPP) Lab ( email )

New York, NY
United States

Hanna Wallach

Microsoft Research New York City ( email )

641 Avenue of Americas
New York, NY 10011
United States

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