Null Models of Economic Networks: The Case of the World Trade Web

TL;DR

This paper analyzes the World Trade Web using null network models that preserve local properties, revealing that binary trade networks are explained by degree sequences, while weighted networks require additional information.

Contribution

It introduces a null model approach that analytically predicts network properties in economic networks, addressing limitations of previous models.

Findings

Binary WTW properties explained by node-degree sequences.

Weighted WTW patterns not fully predicted by total imports/exports.

Null models provide insights into trade network structure.

Abstract

In all empirical-network studies, the observed properties of economic networks are informative only if compared with a well-defined null model that can quantitatively predict the behavior of such properties in constrained graphs. However, predictions of the available null-model methods can be derived analytically only under assumptions (e.g., sparseness of the network) that are unrealistic for most economic networks like the World Trade Web (WTW). In this paper we study the evolution of the WTW using a recently-proposed family of null network models. The method allows to analytically obtain the expected value of any network statistic across the ensemble of networks that preserve on average some local properties, and are otherwise fully random. We compare expected and observed properties of the WTW in the period 1950-2000, when either the expected number of trade partners or total country trade is kept fixed and equal to observed quantities. We show that, in the binary WTW, node-degree sequences are sufficient to explain higher-order network properties such as disassortativity and clustering-degree correlation, especially in the last part of the sample. Conversely, in the weighted WTW, the observed sequence of total country imports and exports are not sufficient to predict higher-order patterns of the WTW. We discuss some important implications of these findings for international-trade models.