International Trade Flows and Geo-Political Episodes—Network Perspective

Ahaan Shah, Keyaan Shah and Homa Hosseinmardi
Additional contact information
Ahaan Shah: Jayshree Periwal International School
Keyaan Shah: Dhirubhai Ambani International School
Homa Hosseinmardi: Computational Social Science Lab, University of Pennsylvania

Chapter Chapter 2 in Applied Economic Research and Trends, 2024, pp 17-36 from Springer

Abstract: Abstract Today, globalization and international trade have created a network of countries that are deeply interconnected with each other socially, politically and economically. At the same time, however, this network has experienced significant disruptions over the 5-year period of 2016–2020 in the form of the US-China trade war, Brexit and COVID-19. This chapter presents an analysis of the changes observed in bilateral international trade relations from a social networks perspective over this period and draws connections between the network analysis and these phenomena. The analysis has been done based on the IMF database of over 78,000 trading pairs for the 5 years with USD 88.31 trillion volume; after applying materiality filters resulting in 9119 trading pairs accounting for over 90% volume. The analysis reveals a high degree of concentration: The top 20 pairs account for over 25% of world trade. There is a tight cohesion observed by way of cluster formation amongst countries located within a particular geographical region. It is worth noting that modularity of the clusters has reduced over the period which could be because established trading pairs going beyond their regular partners to other countries in order to fulfil their trade requirements. The centrality measures have remained largely consistent at the network level and for individual countries, clusters or regions. China emerged as the most central trading partner over the years. Further, China’s centrality improved during the period; while the United States lost some ground. The United Kingdom’s centrality also fell consistently, which could be attributed to Brexit. The findings from this report may be subjected to further granular analysis of different product components of the relevant trade flows or may be used to analyze subsequent events, such as the Russia-Ukraine conflict and other such geo-political disruptive episodes.

Keywords: International trade; Social network analysis; Bilateral trade flows; Centrality; Community detection; Clusters (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-031-49105-4_2

Ordering information: This item can be ordered from
http://www.springer.com/9783031491054

DOI: 10.1007/978-3-031-49105-4_2

Access Statistics for this chapter

More chapters in Springer Proceedings in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().