Information Exchange in Policy Networks

By Philip Leifeld

Political outcomes are often the result of policy networks which span multiple types of actors. The question is how these policy networks operate, and how they are organized. We therefore look at tie formation, the decision of any two actors to cooperate, using an exponential random graph model (ERGM), a recent development in statistical network science.

Previous research on the same question had raised the hypothesis that preference similarity among political actors may be the primary driver of tie formation: if actor A and actor B have similar goals, they tend to exchange strategic information or, more generally, cooperate.

However, this explanation may be too simple in many cases. Other research has shown that there are differences between collaborative networks and adversarial networks. In the former, political actors try to overcome collective action situations to achieve a common goal, while in the latter, they compete for lobbying access and policy influence. Consequently, the effect of preference similarity may hold only in some cases but not in others.

In our research article, we therefore develop and test an alternative theory of tie formation in policy networks: transaction cost politics. Actors would benefit from as many information exchange ties with others as possible — but due to a lack of resources, they have to make choices. This leads them to connect to contacts who minimize transaction costs while maximizing outreach and information. They choose those ties that are relatively easy and cheap to establish or show above-average promise to be of high quality for their goal attainment.

Political actors therefore exploit three types of opportunity structures: institutional, relational, and social:

  • An institutional opportunity for contact-making is common participation with other actors in institutionalized policy committees; if actor A meets actor B frequently in joint committees, it is relatively cheap to exchange information with B.
  • Relational opportunities could be other, existing communication channels between A and B or information flows in the other direction.
  • And social opportunity structures increase the anticipated quality of a potential contact; for example, the presence of several third-party actors C who are connected both to A and B increases A’s confidence in the value of B as a cooperation partner and decreases further search costs. Additionally, B’s perceived quality is determined by his or her influence and involvement in the decision-making process.


Our ERGM shows that all of these factors play a role, lending broad support to our transaction cost theory of tie formation in policy networks. Interestingly, the effect of preference similarity, which is so prevalent in the literature, becomes insignificant when these factors are introduced into the model. We also show that different types of information exchange (political/strategic versus technical/scientific) follow different logics.

Two lessons can be learned from this research: first, at least in some cases, transaction costs and opportunity structures are more important than preference similarity. And second, tie formation is not a unified phenomenon — it really depends on the type of relation and institutional context of the policy network (lobbying versus collective action, decision-making versus implementation, technical versus strategic information exchange etc.).

About the Author: Philip Leifeld is a postdoctoral fellow in political science at the University of Konstanz in Germany and at EAWAG, the ETH water research institute in Zurich, Switzerland. The article “Information Exchange in Policy Networks” by Leifeld and Volker Schneider appeared in the July 2012 issue of the American Journal of Political Science.


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The American Journal of Political Science (AJPS) is the flagship journal of the Midwest Political Science Association and is published by Wiley.