Randomizing world trade. II. A weighted network analysis

TL;DR

This paper analyzes the weighted and binary representations of the International Trade Network, revealing that weighted models do not derive from local properties and that traditional macroeconomic approaches fail to capture key network features.

Contribution

It demonstrates that weighted network representations of the ITN cannot be fully explained by local country-specific properties, challenging existing macroeconomic models.

Findings

Weighted representations are not traceable to local properties.

Traditional models fail to capture higher-order network features.

Knowledge of strength sequences alone is insufficient for understanding the ITN.

Abstract

Based on the misleading expectation that weighted network properties always offer a more complete description than purely topological ones, current economic models of the International Trade Network (ITN) generally aim at explaining local weighted properties, not local binary ones. Here we complement our analysis of the binary projections of the ITN by considering its weighted representations. We show that, unlike the binary case, all possible weighted representations of the ITN (directed/undirected, aggregated/disaggregated) cannot be traced back to local country-specific properties, which are therefore of limited informativeness. Our two papers show that traditional macroeconomic approaches systematically fail to capture the key properties of the ITN. In the binary case, they do not focus on the degree sequence and hence cannot characterize or replicate higher-order properties. In the weighted case, they generally focus on the strength sequence, but the knowledge of the latter is not enough in order to understand or reproduce indirect effects.