Changes in major global trade centers: Based on a visual assessment method.

Abstract

This paper uses a network model to analyze the impact of the COVID-19 pandemic on global trade centers. Using import-export trade data from 12 major economies, we visually assess the shifts in global trade network positions before and after the pandemic. By constructing a balanced trade network for the years 2018, 2019, and 2020, we examine how the pandemic has affected the trade connections of key countries. Our study finds that China maintained positive growth and strengthened its trade ties with the United States, while other major economies experienced declines in their network positions. Subsequently, we apply Liang-Kleeman Information Flow to conduct a causal analysis of the past 30 years of gross domestic product and trade data between China and the United States, demonstrating how economic growth patterns influence changes in the global trade network. This combination of network analysis and causal inference provides robust support for our conclusions on the evolving structure of global trade centers.