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The Diffusion of Policy Diffusion Research in Political Science

Published online by Cambridge University Press:  24 September 2012

Erin R. Graham ,
Charles R. Shipan  and
Craig Volden
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Abstract

Over the past fifty years, top political science journals have published hundreds of articles about policy diffusion. This article reports on network analyses of how the ideas and approaches in these articles have spread both within and across the subfields of American politics, comparative politics and international relations. Then, based on a survey of the literature, the who, what, when, where, how and why of policy diffusion are addressed in order to identify and assess some of the main contributions and omissions in current scholarship. It is argued that studies of diffusion would benefit from paying more attention to developments in other subfields and from taking a more systematic approach to tackling the questions of when and how policy diffusion takes place.

Type
Articles
Information
British Journal of Political Science , Volume 43 , Issue 3 , July 2013 , pp. 673 - 701
Copyright
Copyright © Cambridge University Press 2012 

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Footnotes

*

Department of History and Politics, Drexel University (email: [email protected]); Department of Political Science, University of Michigan (email: [email protected]); and Frank Batten School of Leadership and Public Policy, University of Virginia (email: [email protected]), respectively. The authors thank Rachel Schneider and Mike Zilis for valuable research assistance, Derek Stafford for helpful assistance with network analyses, and participants at the Annual Meeting of the American Political Science Association, Boston, Mass., 2008, for useful suggestions. The article has gained immensely from generous comments made by Jenna Bednar, Bill Berry, Fred Boehmke, Sarah Brooks, Claire Dunlop, Lorraine Eden, Rob Franzese, Katharina Füglister, Fabrizio Gilardi, Virginia Gray, Don Haider-Markel, Andrew Karch, David Levi-Faur, Covadonga Meseguer, William Minozzi, Chris Mooney, Ben Noble, Aseem Prakash, Claudio Radaelli, Harvey Starr, Diane Stone, Hugh Ward, Kurt Weyland, Alan Wiseman and the anonymous reviewers.

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17 The third author also read the abstracts for approximately 20 per cent of the papers for which the first two authors agreed about the category. In every case, this confirmed the coding by the first two authors.

18 In order to derive the networks, we utilize the Fructerman–Reingold energizing algorithm, which is the most commonly used algorithm for networks with more than 500 nodes. An energizing algorithm provides information about the clusters of nodes, where each study in our dataset is a separate node, and about the distances between these nodes. Each node may be thought of as a steel ring that is magnetically charged and has a different charge from its neighbour. Thus, each node wants to repel every other node; so pushing the nodes closer together requires energy. The edges connecting the nodes are then thought of as also having springs. Stretching the spring requires energy as well, so now there are two forces acting on the rings at the same time: the springs connecting them that pull the nodes together, and the magnetic charges that push them apart. Energizing algorithms allow the springs and charges to find a balance, minimizing the energy necessary to hold the network together. The Fructerman–Reingold algorithm differs from others (e.g., Kamada–Kawaii) in the way it derives the relationship between the length of the spring and the tension on the endpoints.

19 For example, while most of the articles study the spread of policies, a large number study the spread of war/conflict in IR, the spread of democracy in CP, or the spread of norms.

20 While network analyses can be used for a variety of purposes, our purpose here is mainly to demonstrate the degree of connectedness across subfields and the nature of the discussions taking place in each area of scholarship. Colour versions of Figures 2, 3 and 4 allow the patterns to be seen more easily; these are posted online at http://sitemaker.umich.edu/cshipan/datasets.

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22 There has been considerable debate regarding the role of automated drawing algorithms in network analysis. Like many methods, these algorithms can be abused, such as by relying on rotations or projections that offer visually misleading conclusions. Among the many ways to address such concerns, researchers may wish to explore and display results for meaningful subsets of the data, as we do in Figures 2–4. Moreover, although we were careful about accurately illustrating the particular scholarly debates highlighted by subsets in the figures, it is important to note that not every article within the shown subset ‘Race to the Bottom’ was found with the ‘race to the bottom’ search terms, nor is every article outside of that subset about something other than a race to the bottom. The same is true for each of the other subsets shown. Rather, these subsets illustrate the main debates taking place in each part of the figure.

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84 These four may not be exhaustive. We have a lively ongoing debate among coauthors, for example, about whether ‘imitation’ (Shipan and Volden, ‘The Mechanisms of Policy Diffusion’) is simply a combination of socialization and learning or whether it contains processes orthogonal to those factors. Here we treat it as the former.

85 Our list of four mechanisms arises from a comprehensive reading of diffusion scholarship across the AP, CP and IR subfields. Perhaps unsurprisingly, it closely resembles the lists of Simmons, Dobbin and Garrett (‘Introduction: The International Diffusion of Liberalism’), studying the international diffusion of liberalism, and of Shipan and Volden (‘The Mechanisms of Policy Diffusion’), studying diffusion in American politics. One main noteworthy difference is our inclusion of ‘socialization’, instead of earlier authors’ ‘emulation’ or ‘imitation’.

86 Louis Dembitz Brandeis, ‘Dissenting Opinion’, New State Ice Co. v. Liebmann, 285 U.S. 262, 311 (1932).

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107 Collier and Messick, ‘Prerequisites versus Diffusion’.

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109 Haas, ‘Epistemic Communities and International Policy Coordination’; Adler, ‘The Emergence of Cooperation: National Epistemic Communities and the International Evolution of the Idea of Nuclear Arms Control’.

110 Acharya, ‘How Ideas Spread’.

111 See, for example, Dolowitz, ‘British Employment Policy in the 1980s’.

112 See, for instance, Martha Finnemore, ‘International Organizations as Teachers of Norms’; Füglister, ‘Where Does Learning Take Place?’.

113 Case, Anne C., Hines, James R. Jr. and Rosen, Harvey S., ‘Budget Spillovers and Fiscal Policy Interdependence: Evidence from the States’, Journal of Public Economics, 52 (1993), 285–307Google Scholar

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115 Volden, ‘States as Policy Laboratories’.

116 Simmons and Elkins, ‘The Globalization of Liberalization’.

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119 Boehmke and Witmer, ‘Disentangling Diffusion’.

120 Shipan, Charles R. and Volden, Craig, ‘The Mechanisms of Policy Diffusion’, American Journal of Political Science, 52 (2008), 840–57 CrossRefGoogle Scholar

121 Berry and Baybeck, ‘Using Geographic Information Systems to Study Interstate Competition’.

122 See, for example, Cao, ‘Networks as Channels of Policy Diffusion’.

123 Abrahamson, Eric and Rosenkopf, Lori, ‘Institutional and Competitive Bandwagons: Using Mathematical Modeling as a Tool to Explore Innovation Diffusion’, Academy of Management Review, 18 (1993), 487–517 CrossRefGoogle Scholar

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124 See, for instance, Weyland, Bounded Rationality and Policy Diffusion.

125 See, for example, Finnemore and Sikkink, ‘International Norm Dynamics and Political Change’.

126 See, for example, Weyland, Bounded Rationality and Policy Diffusion.

127 For example, the work of Shipan and Volden (‘Bottom-up Federalism’) has normative implications for public health advocates, who have long argued about whether to target smoking at the state or local levels. Their analysis demonstrates the conditions under which such advocates should pursue each strategy.

128 Such disparate conversations are by no means solely caused by subfield divides. For example, early works in the AP literature were in many ways talking past one another, with some focused on the spread of policies (see, for instance, Gray, ‘Innovation in the States’) and others interested in the innovativeness of states as judged by when they adopted such policies (see, for example, Walker, ‘The Diffusion of Innovations among the American States’).

129 Füglister, ‘Where Does Learning Take Place?’

130 Kelemen, R. Daniel and Sibbitt, Eric C., ‘The Globalization of American Law’, International Organization, 58 (2004), 103–36 CrossRefGoogle Scholar

131 Shipan and Volden, ‘Bottom-up Federalism’.

132 Milner, Helen V., ‘The Digital Divide: The Role of Political Institutions in Technology Diffusion’, Comparative Political Studies, 39 (2006), 176–99 CrossRefGoogle Scholar

133 Checkel, ‘Norms, Institutions, and National Identity in Contemporary Europe’.

134 Neumayer, Eric and Plümper, Thomas, ‘Conditional Spatial Policy Dependence: Theory and Model Specification’, Comparative Political Studies, 45 (2012), 819–49 CrossRefGoogle Scholar

135 Crain, Robert L., ‘Fluoridation: Diffusion of an Innovation among Cities’, Social Forces, 44 (1966), 467–76 CrossRefGoogle Scholar

136 See, for example, Balla, ‘Interstate Professional Associations and the Diffusion of Policy Innovations’; Mintrom, ‘Policy Entrepreneurs and the Diffusion of Innovation’; Skocpol, Abend-Wein, Howard and Lehmann, ‘Women's Associations and the Enactment of Mothers’ Pensions in the United States’.

137 Stone, ‘Learning Lessons and Transferring Policy across Time, Space and Disciplines’.

138 Bailey and Rom, ‘A Wider Race?’

139 Prakash and Potoski, ‘Racing to the Bottom?’ Zeng and Eastin, ‘International Economic Integration and Environmental Protection’.

140 Zeng and Eastin, ‘International Economic Integration and Environmental Protection’; Finnemore, ‘International Organizations as Teachers of Norms’.

141 Drezner, ‘Globalization, Harmonization, and Competition’. The nature of the diffusing policies themselves also may influence how policy diffusion comes about. Whether policies are observable, whether they easily can be tried and abandoned, and their degree of complexity may affect not only their speed of adoption but also the reliance of policy makers on particular diffusion mechanisms (see, for example, Rogers, The Diffusion of Innovations; Boushey, Policy Diffusion Dynamics in America; Makse and Volden, ‘The Role of Policy Attributes in the Diffusion of Innovations’). The level of controversy surrounding new policy ideas influences diffusion (see, for instance, Scott P. Hays, ‘Patterns of Reinvention: The Nature of Evolution during Policy Diffusion’, Policy Studies Journal, 24 (1996), 551–66), perhaps leading to higher standards for judging successes elsewhere or to a stronger resistance to coercion or socialization. Therefore, although scholars have shown policy diffusion to be relevant across numerous areas of policy adoption (see, for example, Christopher Z. Mooney and Mei-Hsien Lee, ‘Legislative Morality in the American States: The Case of Pre-Roe Abortion Regulation Reform’, American Journal of Political Science, 39 (1995), 599–627), the nature of that diffusion may depend fundamentally on the type of policy that is spreading.

142 Walker, ‘The Diffusion of Innovations among the American States’.

143 Bradley Canon and Lawrence Baum, ‘Patterns of Adoption of Tort Law Innovations: An Application of Diffusion Theory to Judicial Doctrines’, American Political Science Review, 75 (1981), 975–87.

144 See, for example, Gray, ‘Innovation in the States’.

145 However, see Boushey, Policy Diffusion Dynamics in America.

146 Welch and Thompson, ‘The Impact of Federal Incentives on State Policy Innovation’; Mooney, ‘Modeling Regional Effects on State Policy Diffusion’; Gilardi, Füglister and Luyet, ‘Learning from Others’.

147 Mintrom, Michael and Vergari, Sandra, ‘Policy Networks and Innovation Diffusion: The Case of State Education Reforms’, Journal of Politics, 60 (1998), 126–48 CrossRefGoogle Scholar

148 Braun, Dietmar and Gilardi, Fabrizio, ‘Taking “Galton's Problem” Seriously: Towards a Theory of Policy Diffusion’, Journal of Theoretical Politics, 18 (2006), 298–322 CrossRefGoogle Scholar

149 Volden, Ting and Carpenter, ‘A Formal Model of Learning and Policy Diffusion’.

150 We are also hopeful that the current trend of increasing coauthorships and collaborations will help scholars overcome interdisciplinary and subfield barriers, in ways already becoming apparent between sociology and political science (see, for instance, Simmons, Dobbin and Garrett, ‘Introduction: The International Diffusion of Liberalism’, Simmons, Dobbin and Garrett, eds, The Global Diffusion of Markets and Democracy; Givan, Soule and Roberts, eds, The Diffusion of Social Movements).