A dynamic separable network model with actor heterogeneity: An application to global weapons transfers

Lebacher, Michael; Thurner, Paul W. und Kauermann, Göran (2020): A dynamic separable network model with actor heterogeneity: An application to global weapons transfers. In: Journal of the Royal Statistical Society: Series A, Bd. 184, Nr. 1: S. 201-226

Abstract

In this paper, we analyse the network of international major conventional weapons (MCW) transfers from 1950 to 2016, based on data from the Stockholm International Peace Research Institute (SIPRI). The dataset consists of yearly bilateral arms transfers between pairs of countries, which allows us to conceive of the individual relationships as part of an overall trade network. For the analysis, we extend the separable temporal exponential random graph model (STERGM) to account for time‐varying effects on both the network level (trade network) and the actor level (country effects). Our investigation enables the identification of potentially differing driving forces that influence the formation of new trade relationships versus the persistence of existing ones. In accordance with political economy models, we expect security‐ and network‐related covariates to be most important for the formation of transfers, whereas repeated transfers should prevalently be determined by the importers’ market size and military spending. Our proposed modelling approach corroborates the hypothesis and quantifies the corresponding effects. Additionally, we subject the time‐varying heterogeneity effects to a functional principal component analysis. This analysis serves as an exploratory tool and allows us to identify countries with exceptional increases or decreases in their tendency to import and export weapons.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Sozialwissenschaften > Geschwister-Scholl-Institut für Politikwissenschaft ; Mathematik, Informatik und Statistik > Statistik > Lehrstühle/Arbeitsgruppen > Lehrstuhl für Statistik und ihre Anwendungen in Wirtschafts- und Sozialwissenschaften
• Themengebiete: 300 Sozialwissenschaften > 320 Politik
• Sprache: Englisch