Hostname: page-component-8448b6f56d-sxzjt Total loading time: 0 Render date: 2024-04-17T07:37:35.396Z Has data issue: false hasContentIssue false
  • English
  • Français

Persistent Policy Pathways: Inferring Diffusion Networks in the American States

Published online by Cambridge University Press:  23 April 2015

BRUCE A. DESMARAIS ,
JEFFREY J. HARDEN  and
FREDERICK J. BOEHMKE
BRUCE A. DESMARAIS*
Affiliation:
University of Massachusetts Amherst
JEFFREY J. HARDEN*
Affiliation:
University of Colorado Boulder
FREDERICK J. BOEHMKE*
Affiliation:
University of Iowa
*
Bruce A. Desmarais is Assistant Professor, Department of Political Science, University of Massachusetts Amherst, 420 Thompson Hall, 200 Hicks Way, Amherst, MA 01003 (desmarais@polsci.umass.edu).
Jeffrey J. Harden is Assistant Professor, Department of Political Science, University of Colorado Boulder, 416 Fleming, UCB 333, Boulder, CO 80309 (jeffrey.harden@colorado.edu).
Frederick J. Boehmke is Professor, Department of Political Science, and Director of the Social Science Program in the Public Policy Center, University of Iowa, 341 Schaeffer Hall, Iowa City, IA 52242 (frederick-boehmke@uiowa.edu).
Get access Rights & Permissions [Opens in a new window]

Abstract

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.

Type
Research Article
Information
American Political Science Review , Volume 109 , Issue 2 , May 2015 , pp. 392 - 406
Copyright
Copyright © American Political Science Association 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Akers, Ronald L., Krohn, Marvin D., Lanza-Kaduce, Lonn, and Radosevich, Marcia. 1979. “Social Learning and Deviant Behavior: A Specific Test of a General Theory.” American Sociological Review 44 (4): 636–55.CrossRefGoogle ScholarPubMed
Baybeck, Brady, Berry, William D., and Siegel, David A.. 2011. “A Strategic Theory of Policy Diffusion Via Intergovernmental Competition.” Journal of Politics 73 (1): 232–47.CrossRefGoogle Scholar
Berkes, Fikret. 2009. “Evolution of Co-management: Role of Knowledge Generation, Bridging Organizations and Social Learning.” Journal of Environmental Management 90 (5): 1692–702.Google Scholar
Berry, William D., and Baybeck, Brady. 2005. “Using Geographic Information Systems to Study Interstate Competition.” American Political Science Review 99 (4): 505–19.CrossRefGoogle Scholar
Berry, Frances Stokes, and Berry, William D.. 1990. “State Lottery Adoptions as Policy Innovations: An Event History Analysis.” American Political Science Review 84 (2): 395–415.CrossRefGoogle Scholar
Berry, William D., Ringquist, Evan J., Fording, Richard C., and Hanson, Russell L.. 1998. “Measuring Citizen and Government Ideology in the American States, 1960–93.” American Journal of Political Science 42 (1): 327–48.Google Scholar
Boehmke, Frederick J. 2005. The Indirect Effect of Direct Legislation: How Institutions Shape Interest Group Systems. Columbus, OH: The Ohio State University Press.Google Scholar
Boehmke, Frederick J. 2009. “Policy Emulation or Policy Convergence? Potential Ambiguities in the Dyadic Event History Approach to State Policy Emulation.” Journal of Politics 71 (3): 1125–40.Google Scholar
Boehmke, Frederick J., and Skinner, Paul. 2012 a. “The Determinants of State Policy Innovativeness.” Presented at the Annual State Politics and Policy Conference, Houston, TX.CrossRefGoogle Scholar
Boehmke, Frederick J., and Skinner, Paul. 2012 b. “State Policy Innovativeness Revisited.” State Politics & Policy Quarterly 12 (3): 303–29.Google Scholar
Boehmke, Frederick J., and Witmer, Richard. 2004. “Disentangling Diffusion: The Effects of Social Learning and Economic Competition on State Policy Innovation and Expansion.” Political Research Quarterly 57 (1): 39–51.CrossRefGoogle Scholar
Boushey, Graeme. 2010. Policy Diffusion Dynamics in America. New York: Cambridge University Press.Google Scholar
Box-Steffensmeier, Janet M., Arnold, Laura W., and Zorn, Christopher J. W.. 1997. “The Strategic Timing of Position Taking in Congress: A Study of the North American Free Trade Agreement.” American Political Science Review 91 (2): 324–38.Google Scholar
Cranmer, Skyler J., and Desmarais, Bruce A.. 2011. “Inferential Network Analysis with Exponential Random Graph Models.” Political Analysis 19 (1): 66–86.Google Scholar
Denham, Bryan E. 2014. “Intermedia Attribute Agenda Setting in the New York Times: The Case of Animal Abuse in U.S. Horse Racing.” Journalism & Mass Communication Quarterly 91 (1): 17–37.Google Scholar
Denny, Matthew J. 2014. “Influence in the United States Senate.” Presented at the Annual Meeting of the Midwest Political Science Association, Chicago, IL.Google Scholar
Dorussen, Han, and Ward, Hugh. 2008. “Intergovernmental Organizations and the Kantian Peace: A Network Perspective.” Journal of Conflict Resolution 52 (2): 189–212.Google Scholar
Ellison, Glenn, and Fudenberg, Drew. 1995. “Word-of-Mouth Communication and Social Learning.” Quarterly Journal of Economics 110 (1): 93–125.CrossRefGoogle Scholar
Fowler, James H., Heaney, Michael T., Nickerson, David W., Padgett, John F., and Sinclair, Betsy. 2011. “Causality in Political Networks.” American Politics Research 39 (2): 437–80.Google Scholar
Garrett, Kristin N. and Joshua M. Jansa. 2015. “Interest Group Influence in Policy Diffusion Networks.” Forthcoming, State Politics & Policy Quarterly.Google Scholar
Ghanadan, Rebecca, and Koomey, Jonathan G.. 2005. “Using Energy Scenarios to Explore Alternative Energy Pathways in California.” Energy Policy 33 (9): 1117–42.Google Scholar
Gilardi, Fabrizio. 2010. “Who Learns from What in Policy Diffusion Processes?” American Journal of Political Science 54 (3): 650–66.Google Scholar
Golan, Guy. 2006. “Intermedia Agenda Setting and Global News Coverage: Assessing the Influence of the New York Times on Three Television Evening News Programs.” Journalism Studies 7 (2): 323–33.Google Scholar
Gomez-Rodriguez, Manuel, Leskovec, Jure, and Krause, Andreas. 2010. Inferring Networks of Diffusion and Influence. In The 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD).CrossRefGoogle Scholar
Graham, Erin R., Shipan, Charles R., and Volden, Craig. 2013. “The Diffusion of Policy Diffusion Research in Political Science.” British Journal of Political Science 43 (3): 673–701.Google Scholar
Gray, Virginia. 1973. “Innovation in the States: A Diffusion Study.” American Political Science Review 67 (4): 1174–85.Google Scholar
Grossback, Lawrence J., Nicholson-Crotty, Sean, and Peterson, David A. M.. 2004. “Ideology and Learning in Policy Diffusion.” American Politics Research 32 (5): 521–45.Google Scholar
Hafner-Burton, Emilie M., Kahler, Miles, and Montgomery, Alexander H.. 2009. “Network Analysis for International Relations.” International Organization 63 (3): 559–92.Google Scholar
Hero, Rodney E., and Tolbert, Caroline J.. 1996. “A Racial/Ethnic Diversity Interpretation of Politics and Policy in the States of the U.S.” American Journal of Political Science 40 (3): 851–71.CrossRefGoogle Scholar
Hummon, Norman P. 2000. “Utility and Dynamic Social Networks.” Social Networks 22 (3): 221–49.Google Scholar
Karch, Andrew. 2007. Democratic Laboratories: Policy Diffusion Among the American States. Ann Arbor, MI: University of Michigan Press.Google Scholar
Karch, Andrew, Nicholson-Crotty, Sean C., Woods, Neal D., and Bowman, Ann O’M.. 2013. “Policy Diffusion and the Pro-Innovation Bias.” Presented at the Annual State Politics and Policy Conference, Iowa City, IA.Google Scholar
King, James D. 2000. “Changes in Professionalism in U.S. State Legislatures.” Legislative Studies Quarterly 25 (2): 327–43.Google Scholar
Kingdon, John W. 1973. Congressmen’s Voting Decisions. New York: Harper & Row.Google Scholar
Kirke, Deirdre M. 2004. “Chain Reactions in Adolescents? Cigarette, Alcohol and Drug Use: Similarity Through Peer Influence or the Patterning of Ties in Peer Networks?” Social Networks 26 (1): 3–28.Google Scholar
Klarner, Carl. 2003. “The Measurement of the Partisan Balance of State Government.” State Politics & Policy Quarterly 3 (3): 309–19.Google Scholar
Krackardt, David. 1987. “QAP Partialling as a Test of Spuriousness.” Social Networks 9 (2): 171–86.Google Scholar
Lazer, David, and Friedman, Allan. 2007. “The Network Structure of Exploration and Exploitation.” Administrative Science Quarterly 52 (4): 667–94.Google Scholar
Mason, Winter, and Watts, Duncan J.. 2012. “Collaborative Learning in Networks.” Proceedings of the National Academy of Sciences 109 (3): 764–9.Google Scholar
Matthews, Donald R., and Stimson, James A.. 1975. Yeas and Nays: Normal Decision-Making in the U.S. House of Representatives. New York: Wiley.Google Scholar
May, Peter J. 1992. “Policy Learning and Failure.” Journal of Public Policy 12 (4): 331–54.Google Scholar
Mintrom, Michael, and Vergari, Sandra. 1998. “Policy Networks and Innovation Diffusion: The Case of State Education Reforms.” Journal of Politics 60 (1): 126–48.Google Scholar
Mooney, Christopher Z. 2001. “Modeling Regional Effects on State Policy Diffusion.” Political Research Quarterly 54 (1): 103–24.Google Scholar
Neuman, W. Russell, Guggenheim, Lauren, Jang, S. Mo, and Bae, Soo Young. 2014. “The Dynamics of Public Attention: Agenda-Setting Theory Meets Big Data.” Journal of Communication 64 (2): 193–214.Google Scholar
Nicholson-Crotty, Sean. 2009. “The Politics of Diffusion: Public Policy in the American States.” Journal of Politics 71 (1): 192–205.Google Scholar
Nussbaum, Alex. 2007. “Scientists: State Must Act on Warming Now.” The Washington Post. February 21.Google Scholar
Pacheco, Julianna. 2012. “The Social Contagion Model: Exploring The Role of Public Opinion on the Diffusion of Anti-Smoking Legislation across the American States.” Journal of Politics 74 (1): 187–202.Google Scholar
Rice, Ronald E., Grant, August E., Schmitz, Joseph, and Torobin, Jack. 1990. “Individual and Network Influences on the Adoption and Perceived Outcomes of Electronic Messaging.” Social Networks 12 (1): 27–55.Google Scholar
Ringe, Nils, Victor, Jennifer Nicoll, and Gross, Justin H.. 2013. “Keeping Your Friends Close and Your Enemies Closer? Information Networks in Legislative Politics.” British Journal of Political Science 43 (3): 601–28.Google Scholar
Shipan, Charles R., and Volden, Craig. 2006. “Bottom-Up Federalism: The Diffusion of Antismoking Policies from U.S. Cities to States.” American Journal of Political Science 50 (4): 825–43.CrossRefGoogle Scholar
Shipan, Charles R., and Volden, Craig. 2012. “Policy Diffusion: Seven Lessons for Scholars and Practitioners.” Public Administration Review 72 (6): 788–96.Google Scholar
Simon, Herbert Alexander. 1976. Administrative Behavior: A Study of Decision-Making Processes in Administrative Organization. New York: Free Press.Google Scholar
Tam Cho, Wendy K., and Fowler, James H.. 2010. “Legislative Success in a Small World: Social Network Analysis and the Dynamics of Congressional Legislation.” Journal of Politics 72 (1): 124–35.Google Scholar
Tan, Yue, and Weaver, David H.. 2009. “Local Media, Public Opinion, and State Legislative Policies: Agenda Setting at the State Level.” The International Journal of Press/Politics 14 (4): 454–76.Google Scholar
Volden, Craig. 2006. “States as Policy Laboratories: Emulating Success in the Children’s Health Insurance Program.” American Journal of Political Science 50 (2): 294–312.Google Scholar
Volden, Craig, Ting, Michael M., and Carpenter, Daniel P.. 2008. “A Formal Model of Learning and Policy Diffusion.” American Political Science Review 102 (3): 319–32.Google Scholar
Wagner, John. 2007. “Bills to Cut Pollution, Aid Bay, are Signed into Law.” The Washington Post. April 25.Google Scholar
Walker, Jack L. 1969. “The Diffusion of Innovations Among the American States.” American Political Science Review 63 (3): 880–99.Google Scholar
Supplementary material: PDF

Desmarais supplementary material

Appendix

Download Desmarais supplementary material(PDF)
PDF 419.4 KB