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Studying Policy Diffusion with Stochastic Actor-Oriented Models

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Networked Governance

Abstract

This chapter demonstrates the potential of stochastic actor-oriented models (SAOMs) and co-evolution designs for policy-diffusion research. SAOMs are statistical models, introduced by Snijders (1995), for studying network data measured over time. In this chapter, I introduce these models in a non-technical way and present an exemplary application to the diffusion of national foreign trade policies (FTPs) via trade flows across countries.

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Notes

  1. 1.

    I thank Kai-Uwe Schnapp, Christian W. Martin, James Hollway, and Thomas Sommerer for helpful comments.

  2. 2.

    This chapter is a revised section of Mohrenberg (2014). The application to FTP diffusion via trade flows is from a research project that I am pursuing together with Christian W. Martin (Martin and Mohrenberg 2015).

  3. 3.

    This list describes various examples of policy diffusion that would be more accurately described as “polity diffusion,” such as institutional settings or the national legal organization of political authority. I nonetheless use the term “policy diffusion” when referring to all of these examples (cf. Gilardi 2012; Solingen 2012).

  4. 4.

    The terms actor, vertex, and node as well as tie and edge are synonyms with respect to network analysis. The vocabulary mainly differs between academic disciplines.

  5. 5.

    Jackson (2008) speaks of “diffusion within networks.” I prefer the shorter term “network diffusion” but make no claims as to conceptual differences.

  6. 6.

    For a more comprehensive treatment of these and additional alternative models, see, e.g., Jackson (2008).

  7. 7.

    For non-directed networks, Wasserman and Faust (1995, p. 109) provide the following definition of components: “The nodes in a disconnected graph may be partitioned into two or more subsets in which there are no paths between the nodes in different subsets. The connected subgraphs in a graph are called components.”

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Authors and Affiliations

  1. ETH Zurich, Zurich, Switzerland

    Steffen Mohrenberg

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  1. Steffen Mohrenberg
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Correspondence to Steffen Mohrenberg .

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Editors and Affiliations

  1. SOCIUM—Research Center on Inequality and Social Policy, University of Bremen, Bremen, Germany

    Betina Hollstein

  2. Faculty of Economics and Social Sciences IPA Institute for Employment Relations and Labour, Helmut-Schmidt-University—University of the Federal Armed Forces Hamburg, Hamburg, Germany

    Wenzel Matiaske

  3. Political Science Department, Universität Hamburg, Hamburg, Germany

    Kai-Uwe Schnapp

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Mohrenberg, S. (2017). Studying Policy Diffusion with Stochastic Actor-Oriented Models. In: Hollstein, B., Matiaske, W., Schnapp, KU. (eds) Networked Governance. Springer, Cham. https://doi.org/10.1007/978-3-319-50386-8_10

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