Intergovernmental Organizations: Forecasting Dyadic Membership

• In Event: Political Forecasting at the Cutting Edge

Abstract

An emerging theory of international relations posits that networks of interactions can help us better understand economic and political behaviors between stats at the systematic level. Understanding networks of state behavior requires data measuring bilateral flows. Dyadic data has previously been limited as a viable tool due to large data and processing constraints. However, with advances in computation technology and efforts at gather vast quantities of information, the learning curve for analyzing dyadic data has been reduced. This paper applies a dyadic framework to better understand a key element in the field of international relations one of the three “legs” of the Kantian tripod that theoretically underpins conflict onset and likelihood: mutual membership in intergovernmental organizations (IGOs). We utilize original data measuring state membership pin 409 IGOs that span 1916-2014 to study this phenomenon. These data have been transformed to produce a novel variable of shared IGO membership between state dyads, as well as another that weights membership scores by the relative prominence of the institution. We utilize a series of dyadic analyses to examine the drivers of states mutually entering into IGO membership, which helps contribute a nested framework for forecasting future IGO trends. This forecast has important implications on understanding the future of IGOs and the network effects produced by expected dyadic state membership over time.

Authors

• Austin S Matthews, University of Denver

• Jonathan Moyer, University of Denver

• David Kenneth Bohl, Frederick S Pardee Center for International Futures

• Collin J. Meisel, University of Denver