Scale free is not rare in international trade networks

Linqing Liu,Chang Tan,Mengyun Shen

doi:10.1038/s41598-021-92764-1

Linqing Liu, Chang Tan + Show 1 more

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https://doi.org/10.1038/s41598-021-92764-1

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Journal: Scientific Reports	Publication Date: Jun 25, 2021
Citations: 8	License type: open-access

Affiliation: Wuhan University, Southwest University

Abstract

Failing to consider the strong correlations between weights and topological properties in capacity-weighted networks renders test results on the scale-free property unreliable. According to the preferential attachment mechanism, existing high-degree nodes normally attract new nodes. However, in capacity-weighted networks, the weights of existing edges increase as the network grows. We propose an optimized simplification method and apply it to international trade networks. Our study covers more than 1200 product categories annually from 1995 to 2018. We find that, on average, 38%, 38% and 69% of product networks in export, import and total trade are scale-free. Furthermore, the scale-free characteristics differ depending on the technology. Counter to expectations, the exports of high-technology products are distributed worldwide rather than concentrated in a few developed countries. Our research extends the scale-free exploration of capacity-weighted networks and demonstrates that choosing appropriate filtering methods can clarify the properties of complex networks.

Highlights

Failing to consider the strong correlations between weights and topological properties in capacityweighted networks renders test results on the scale-free property unreliable
To avoid the complications derived from trade flow imbalances[13] and to take into consideration the heterogeneity of imports and exports, we build an undirected import network (IMN), an undirected export network (EXN) and an undirected total trade network (TTN) based on each product trade dataset
We noticed that their simplification methods are inappropriate for capacity-weighted networks due to two drawbacks

Summary

Introduction

Failing to consider the strong correlations between weights and topological properties in capacityweighted networks renders test results on the scale-free property unreliable. Our research extends the scale-free exploration of capacity-weighted networks and demonstrates that choosing appropriate filtering methods can clarify the properties of complex networks. Scale-free networks were first introduced in 1999 by Barabási and Albert[1] after testing of many real networks in different fields by verifying that their degree distributions follow power law. Despite the dispute provoked by B&C’s article, investigations of the existence of scale-free networks[7,8,9,10] and explorations of methods to test power-law[11] distribution continue. Ignoring weights or applying inappropriate methods to weighted networks can lead to biased results when exploring the scale-free property. According to our replication of LWE applied to international trade data, we argue that LWE limits the exploration of the scale-free property (more details in Supplementary Note 1): 1. As high flow is mostly associated with hubs, high-degree nodes are more likely to form cliques with nodes of equal or higher degree according to the so-called rich-club phenomenon[16]

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Conclusion