Reconstructing the world trade multiplex: the role of intensive and extensive biases
Rossana Mastrandrea, Tiziano Squartini, Giorgio Fagiolo, Diego, Garlaschelli

TL;DR
This paper introduces a null model for the World Trade Multiplex that reproduces node strengths and degrees, revealing layer-specific biases and providing insights into the structure of economic networks.
Contribution
It develops an enhanced null model incorporating both strengths and degrees, and introduces the concepts of extensive and intensive biases in multiplex networks.
Findings
Model accurately reproduces observed network properties
Reveals layer-specific local constraints shape multiplex structure
Highlights the importance of both strength and degree in network modeling
Abstract
In economic and financial networks, the strength of each node has always an important economic meaning, such as the size of supply and demand, import and export, or financial exposure. Constructing null models of networks matching the observed strengths of all nodes is crucial in order to either detect interesting deviations of an empirical network from economically meaningful benchmarks or reconstruct the most likely structure of an economic network when the latter is unknown. However, several studies have proved that real economic networks and multiplexes are topologically very different from configurations inferred only from node strengths. Here we provide a detailed analysis of the World Trade Multiplex by comparing it to an enhanced null model that simultaneously reproduces the strength and the degree of each node. We study several temporal snapshots and almost one hundred layers…
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Taxonomy
TopicsComplex Network Analysis Techniques · Complex Systems and Time Series Analysis
