Statistical mechanics of the international trade network

TL;DR

This paper demonstrates that the international trade network from 1950 to 2000 can be modeled as a sequence of equilibrium states where trade volumes are primarily determined by countries' GDPs, allowing for predictive linear response analysis.

Contribution

It introduces a statistical mechanics framework for the international trade network, showing that trade patterns are consistent with maximally random weighted networks driven by GDPs.

Findings

Trade network is a typical maximally random weighted network each year.

Bilateral trade fluctuations follow the fluctuation-response theorem.

Yearly trade changes align with predictions based on GDP variations.

Abstract

Analyzing real data on international trade covering the time interval 1950-2000, we show that in each year over the analyzed period the network is a typical representative of the ensemble of maximally random weighted networks, whose directed connections (bilateral trade volumes) are only characterized by the product of the trading countries' GDPs. It means that time evolution of this network may be considered as a continuous sequence of equilibrium states, i.e. quasi-static process. This, in turn, allows one to apply the linear response theory to make (and also verify) simple predictions about the network. In particular, we show that bilateral trade fulfills fluctuation-response theorem, which states that the average relative change in import (export) between two countries is a sum of relative changes in their GDPs. Yearly changes in trade volumes prove that the theorem is valid.