Enhanced Gravity Model of trade: reconciling macroeconomic and network models
Assaf Almog, Rhys Bird, Diego Garlaschelli

TL;DR
This paper introduces an Enhanced Gravity Model that combines macroeconomic factors and network topology to accurately reproduce the structure and trade volumes of the International Trade Network, improving upon traditional models.
Contribution
It presents a novel integrated model that unifies the gravity and network approaches within a maximum-entropy framework, allowing separate control of trade probabilities and volumes.
Findings
Successfully reproduces global topology and local link weights of ITN
Trade probabilities follow a geometric or exponential distribution with a zero volume point mass
Reconciles macroeconomic and network models into a single parsimonious framework
Abstract
The structure of the International Trade Network (ITN), whose nodes and links represent world countries and their trade relations respectively, affects key economic processes worldwide, including globalization, economic integration, industrial production, and the propagation of shocks and instabilities. Characterizing the ITN via a simple yet accurate model is an open problem. The traditional Gravity Model (GM) successfully reproduces the volume of trade between connected countries, using macroeconomic properties such as GDP, geographic distance, and possibly other factors. However, it predicts a network with complete or homogeneous topology, thus failing to reproduce the highly heterogeneous structure of the ITN. On the other hand, recent maximum-entropy network models successfully reproduce the complex topology of the ITN, but provide no information about trade volumes. Here we…
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