Jan Tinbergen's legacy for economic networks: from the gravity model to quantum statistics

TL;DR

This paper traces Jan Tinbergen's influence from the gravity model of trade to modern quantum statistical models of economic networks, revealing how heterogeneity shapes network topology.

Contribution

It introduces a quantum statistical framework for economic networks, extending Tinbergen's gravity model to incorporate realistic network structures and heterogeneity.

Findings

Trade networks follow Fermi-Dirac statistics in binary form

Full trade networks exhibit mixed Bose-Fermi statistical behavior

Heterogeneity of countries constrains network topology

Abstract

Jan Tinbergen, the first recipient of the Nobel Memorial Prize in Economics in 1969, obtained his PhD in physics at the University of Leiden under the supervision of Paul Ehrenfest in 1929. Among many achievements as an economist after his training as a physicist, Tinbergen proposed the so-called Gravity Model of international trade. The model predicts that the intensity of trade between two countries is described by a formula similar to Newton's law of gravitation, where mass is replaced by Gross Domestic Product. Since Tinbergen's proposal, the Gravity Model has become the standard model of non-zero trade flows in macroeconomics. However, its intrinsic limitation is the prediction of a completely connected network, which fails to explain the observed intricate topology of international trade. Recent network models overcome this limitation by describing the real network as a member of a maximum-entropy statistical ensemble. The resulting expressions are formally analogous to quantum statistics: the international trade network is found to closely follow the Fermi-Dirac statistics in its purely binary topology, and the recently proposed mixed Bose-Fermi statistics in its full (binary plus weighted) structure. This seemingly esoteric result is actually a simple effect of the heterogeneity of world countries, that imposes strong structural constraints on the network. Our discussion highlights similarities and differences between macroeconomics and statistical-physics approaches to economic networks.