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Sequential Decision Making and Information Aggregation in Small Networks*

Published online by Cambridge University Press:  07 April 2014

John W. Patty  and
Elizabeth Maggie Penn
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Abstract

This article describes and investigates a model of strategic sequential decision making in networked policy-making environments with three agents. The primary interest is the effect of network structure on sequential policy making and information aggregation. The model and results illustrate how individual policy decisions of varying weight (in terms of a decision maker's unilateral effect on policy outcomes) can enable information aggregation in decentralized environments. In the studied environment, the incentive compatibility conditions for information aggregation are not invariant to network isomorphisms: individuals’ positions in the network matter. The study derives exact conditions for every acyclic network of three or fewer agents and illustrates the counterintuitive nature of comparative statics with respect to both network structure and individual agents’ policy preferences and discretionary authority.

Type
Original Articles
Information
Political Science Research and Methods , Volume 2 , Issue 2 , October 2014 , pp. 243 - 271
Copyright
Copyright © The European Political Science Association 2014 

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Footnotes

*John Patty is Associate Professor, Department of Political Science and Director, Center for New Institutional Social Sciences, Washington University in Saint Louis, Seigle Hall, St. Louis, MO 63130 ([email protected]). Elizabeth Maggie Penn is Associate Professor, Department of Political Science, Washington University in Saint Louis, Seigle Hall, St. Louis, MO 63130 ([email protected]). We thank Ethan Bueno de Mesquita, Randy Calvert, Justin Fox, Sean Gailmard, Daniel Magleby, Gary Miller, Keith Schnakenberg, Francesco Squintani, Stephane Wolton and Jon Woon for very helpful comments on this project, as well as two anonymous reviewers and audience members at the EITM miniconference at the 2013 MPSA annual meetings. As usual, all errors are our own.

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