Structure of international trade hypergraphs

TL;DR

This paper investigates the structure of international trade hypergraphs, revealing unique hyperdegree behaviors and correlations that differ from pairwise networks, providing insights into trade strategies and demonstrating the utility of hypergraph analysis.

Contribution

It introduces a hypergraph framework for analyzing international trade data, decomposes hyperdegree correlations, and uncovers biases in trade relationships not visible in pairwise networks.

Findings

Hyperdegree behaviors differ from pairwise networks.

Identified bias of exporters towards certain importers and products.

Provided a theoretical framework for hypergraph analysis of trade data.

Abstract

We study the structure of the international trade hypergraph consisting of triangular hyperedges representing the exporter-importer-product relationship. Measuring the mean hyperdegree of the adjacent vertices, we first find its behaviors different from those in the pairwise networks and explain the origin by tracing the relation between the hyperdegree and the pairwise degree. To interpret the observed hyperdegree correlation properties in the context of trade strategies, we decompose the correlation into two components by identifying one with the background correlation remnant even in the exponential random hypergraphs preserving the given empirical hyperdegree sequence. The other component characterizes the net correlation and reveals the bias of the exporters of low hyperdegree towards the importers of high hyperdegree and the products of low hyperdegree, which information is not readily accessible in the pairwise networks. Our study demonstrates the power of the hypergraph approach in the study of real-world complex systems and offers a theoretical framework.