Analysis of risk propagation using the world trade network

TL;DR

This paper compares direct trade networks with personalized PageRank-based networks to better understand indirect influences in economic systems, demonstrating that PPR networks better explain GDP correlations and crisis propagation.

Contribution

It introduces a PPR-based trade network model to capture indirect economic influences, showing improved explanatory power over traditional direct trade analysis.

Findings

PPR network correlates more strongly with GDP than direct trade.

PPR explains the propagation of economic crises more effectively.

Indirect influences are significant in economic risk propagation.

Abstract

An economic system is an exemplar of a complex system in which all agents interact simultaneously. Interactions between countries have generally been studied using the flow of resources across diverse trade networks, in which the degree of dependence between two countries is typically measured based on the trade volume. However, indirect influences may not be immediately apparent. Herein, we compared a direct trade network to a trade network constructed using the personalized PageRank (PPR) encompassing indirect influences. By analyzing the correlation of the gross domestic product (GDP) between countries, we discovered that the PPR trade network has greater explanatory power on the propagation of economic events than direct trade by analyzing the GDP correlation between countries. To further validate our observations, an agent-based model of the spreading economic crisis was implemented for the Russia-Ukraine war of 2022. The model also demonstrates that the PPR explains the actual impact more effectively than the direct trade network. Our research highlights the significance of indirect and long-range relationships, which have often been overlooked