Hierarchical Structure of the Foreign Trade: The Case of the United State

TL;DR

This paper analyzes the hierarchical structure of US foreign trade from 1985 to 2011 using network methods, revealing key clusters and influential countries that impact trade and investment strategies.

Contribution

It applies hierarchical network techniques to US trade data, identifying key clusters and influential countries, and assesses the statistical reliability of the network links.

Findings

European Union and Asian countries are central in the trade network.

Key trading partners include Canada, China, Mexico, and Japan.

Clusters are formed based on geographical and economic similarities.

Abstract

This study uses hierarchical structure methods (minimal spanning tree, (MST) and hierarchical tree, (HT)) to examine the hierarchical structures of the United State (US) foreign trade by using the real prices of their commodity export and import move together over time. We obtain the topological properties among the countries based on US foreign trade over the periods of 1985-2011. We also perform the bootstrap techniques to investigate a value of the statistical reliability to the links of the MSTs. Finally, we use a clustering linkage procedure in order to observe the cluster structure much better. The results of the topologies structural of these trees are as follows: i) We identified different clusters of countries according to their geographical location and economic growth. ii) Our results show that the European Union and Asian countries are more important within the network, due to a tighter connection with other countries. The country's most important trading partners are the Canada, China, Mexico, Japan, Germany, United Kingdom, South Korea, France, Taiwan, India, Singapore and Netherlands iii) We have also found that these countries play a significance role for US foreign trade and have important implications for the design of portfolio and investment strategies.