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A Formal Model of Learning and Policy Diffusion

  • CRAIG VOLDEN (a1), MICHAEL M. TING (a2) and DANIEL P. CARPENTER (a3)
Abstract

We present a model of learning and policy choice across governments. Governments choose policies with known ideological positions but initially unknown valence benefits, possibly learning about those benefits between the model's two periods. There are two variants of the model; in one, governments only learn from their own experiences, whereas in the other they learn from one another's experiments. Based on similarities between these two versions, we illustrate that much accepted scholarly evidence of policy diffusion could simply have arisen through independent actions by governments that only learn from their own experiences. However, differences between the game-theoretic and decision-theoretic models point the way to future empirical tests that discern learning-based policy diffusion from independent policy adoptions.

Copyright
COPYRIGHT: © American Political Science Association 2008
Corresponding author
Craig Volden is Professor of Political Science, The Ohio State University, Columbus, OH 43210-1373; E-mail: volden.2@osu.edu.
Michael M. Ting is Associate Professor of Political Science and Public Affairs, Columbia University, New York, NY 10027; E-mail: mmt2033@columbia.edu.
Daniel P. Carpenter is Professor of Government, Harvard University, Cambridge, MA 02138. E-mail: dcarpenter@gov.harvard.edu.
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American Political Science Review
  • ISSN: 0003-0554
  • EISSN: 1537-5943
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