Get access

Information Exchange in Policy Networks

Authors


  • The authors wish to thank Martin F. Hellwig, Christoph Engel, Andreas Glöckner, Ben Domingue, Beaugitte Laurent, and four anonymous reviewers for helpful comments and the Max Planck International Research Network on Aging (MaxNetAging) for financial support. The replication dataset can be downloaded from http://hdl.handle.net/1902.1/17004. The R source code is available in the supporting information online.

Philip Leifeld is a Research Fellow at the Max Planck Institute for Research on Collective Goods, Kurt-Schumacher-Str. 10, 53113 Bonn, Germany (philip@philipleifeld.de). Volker Schneider is a Professor of Empirical Theory of the State, Department of Politics & Public Administration, Box D 81, University of Konstanz, 78457 Konstanz, Germany (Volker.Schneider@uni-konstanz.de).

Abstract

Information exchange in policy networks is usually attributed to preference similarity, influence reputation, social trust, and institutional actor roles. We suggest that political opportunity structures and transaction costs play another crucial role and estimate a rich statistical network model on tie formation in the German toxic chemicals policy domain. The results indicate that the effect of preference similarity is absorbed by institutional, relational, and social opportunity structures. Political actors choose contacts who minimize transaction costs while maximizing outreach and information. We also find that different types of information exchange operate in complementary, but not necessarily congruent, ways.

Get access to the full text of this article

Ancillary