A new approach to analyzing coevolving longitudinal networks in international relations

Shahryar Minhas, Peter D Hoff and Michael D Ward
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Shahryar Minhas: Department of Political Science, Duke University
Peter D Hoff: Departments of Statistics & Biostatistics, University of Washington
Michael D Ward: Department of Political Science, Duke University

Journal of Peace Research, 2016, vol. 53, issue 3, 491-505

Abstract: Previous models of international conflict have suffered two shortfalls. They tend not to embody dynamic changes, focusing rather on static slices of behavior over time across a single relational dimension. These models have also been empirically evaluated in ways that assumed the independence of each country, when in reality they are searching for the interdependence among all countries. A number of approaches are available now for analyzing relational data such as international conflict in a network context and a number of these can even handle longitudinal relational data, but none are developed to the point of exploring how networks can coevolve over time. We illustrate a solution to the limitations of existing approaches and apply this novel, dynamic, network based approach to study the dependencies among the ebb and flow of daily international interactions using a newly developed, and openly available, database of events among nations.

Keywords: dynamic networks; event data; international crises; tensor products; time series (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:sae:joupea:v:53:y:2016:i:3:p:491-505

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