Exploring dependence structures in the international arms trade network: A network autocorrelation approach

Lebacher, Michael; Thurner, Paul W.; Kauermann, Göran (2020): Exploring dependence structures in the international arms trade network: A network autocorrelation approach. In: Statistical Modelling, Vol. 20, No. 2: pp. 195-218

Abstract

In this article, we analyse dependence structures among international trade flows of major conventional weapons from 1952 to 2016. We employ a Network Disturbance Model commonly used in inferential network analysis and spatial econometrics. The dependence structure is represented by pre-defined weight matrices that allow for correlating flows from the network of international arms exchange. Three dependence structures are proposed, representing sender-, receiver- and sender–receiver-related dependencies. The appropriateness of the presumed structures is comparatively assessed using the Akaike Information Criterion (AIC). It turns out that the dependence structure among the arms trade flows is complex and can be represented best by a specification that relates each arms trade flow to all exports and imports of the sending and the receiving state. Controlling for exogenous variables, we find that the trade volume increases with the GDP of the sending and the receiving state while the impact of geographical distance, regime dissimilarity and formal alliance membership is rather small.

• Item Type: Journal article
• Faculties: Social Sciences > Geschwister-Scholl-Institute for Political Science; Mathematics, Computer Science and Statistics > Statistics > Chairs/Working Groups > Chair of Statistics - Methodology and Applications in Economics, Social and Life Sciences
• Subjects: 300 Social sciences > 320 Political science
• Language: English