The Dynamic Co‐Evolution of International Politics and the Global Trade Network: Evidence From a Stochastic Actor‐Oriented Model

ABSTRACT As globalization faces headwinds from rising geopolitical tensions, the interaction between international politics and trade has become increasingly complex. Moving beyond static gravity models, this paper examines the dynamic co‐evolution of international political relations and the global trade network. Using a Stochastic Actor‐Oriented Model (SAOM) on a dataset of 139 economies from 1996 to 2023, we model the global trade network as an endogenous and evolving system rather than a set of independent dyads. The results show that diplomatic proximity significantly increases the likelihood of trade‐tie formation, and that this effect strengthens markedly after 2016, approaching the explanatory importance of geographic distance. The estimates also reveal strong reciprocity and triadic closure in the trade network, indicating that trade ties emerge within clustered and path‐dependent structures. Overall, the findings suggest that the contemporary trade system is increasingly shaped by the interaction between geopolitical affinity and network embeddedness.

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Publication Details

Journal
World Economy
Published
2026-06-30
DOI
https://doi.org/10.1111/twec.70125
Primary Topic
International Relations and Foreign Policy
Type
article
Field-Weighted Citation Impact
0.00
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article

The Dynamic Co‐Evolution of International Politics and the Global Trade Network: Evidence From a Stochastic Actor‐Oriented Model

Xiaoying Su, Shanshan Lan, Feng Tang, Shiping Yan
World Economy
International Relations and Foreign Policy
article

The Dynamic Co‐Evolution of International Politics and the Global Trade Network: Evidence From a Stochastic Actor‐Oriented Model

Xiaoying Su, Shanshan Lan, Feng Tang, Shiping Yan
article en

Abstract

ABSTRACT As globalization faces headwinds from rising geopolitical tensions, the interaction between international politics and trade has become increasingly complex. Moving beyond static gravity models, this paper examines the dynamic co‐evolution of international political relations and the global trade network. Using a Stochastic Actor‐Oriented Model (SAOM) on a dataset of 139 economies from 1996 to 2023, we model the global trade network as an endogenous and evolving system rather than a set of independent dyads. The results show that diplomatic proximity significantly increases the likelihood of trade‐tie formation, and that this effect strengthens markedly after 2016, approaching the explanatory importance of geographic distance. The estimates also reveal strong reciprocity and triadic closure in the trade network, indicating that trade ties emerge within clustered and path‐dependent structures. Overall, the findings suggest that the contemporary trade system is increasingly shaped by the interaction between geopolitical affinity and network embeddedness.

World Economy
University of International Business and Economics (CN), Guangxi University (CN), Khon Kaen University (TH), North China University of Water Resources and Electric Power (CN), Nanning Normal University (CN)
Openalex Percentile: Top 4%
International Relations and Foreign Policy
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