  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 integrate these two
currently incompatible approaches via the introduction of an Enhanced Gravity
Model (EGM) of trade. The EGM is the simplest model combining the GM with the
network approach within a maximum-entropy framework. Via a unified and
principled mechanism that is transparent enough to be generalized to any
economic network, the EGM provides a new econometric framework wherein trade
probabilities and trade volumes can be separately controlled by any combination
of dyadic and country-specific macroeconomic variables. The model successfully
reproduces both the global topology and the local link weights of the ITN,
parsimoniously reconciling the conflicting approaches. It also indicates that
the probability that any two countries trade a certain volume should follow a
geometric or exponential distribution with an additional point mass at zero
volume.
