The nested structural organization of the worldwide trade multi-layer network View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Luiz G. A. Alves, Giuseppe Mangioni, Isabella Cingolani, Francisco Aparecido Rodrigues, Pietro Panzarasa, Yamir Moreno

ABSTRACT

Nestedness has traditionally been used to detect assembly patterns in meta-communities and networks of interacting species. Attempts have also been made to uncover nested structures in international trade, typically represented as bipartite networks in which connections can be established between countries (exporters or importers) and industries. A bipartite representation of trade, however, inevitably neglects transactions between industries. To fully capture the organization of the global value chain, we draw on the World Input-Output Database and construct a multi-layer network in which the nodes are the countries, the layers are the industries, and links can be established from sellers to buyers within and across industries. We define the buyers' and sellers' participation matrices in which the rows are the countries and the columns are all possible pairs of industries, and then compute nestedness based on buyers' and sellers' involvement in transactions between and within industries. Drawing on appropriate null models that preserve the countries' or layers' degree distributions in the original multi-layer network, we uncover variations of country- and transaction-based nestedness over time, and identify the countries and industries that most contributed to nestedness. We discuss the implications of our findings for the study of the international production network and other real-world systems. More... »

PAGES

2866

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-019-39340-w

DOI

http://dx.doi.org/10.1038/s41598-019-39340-w

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112390658

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30814565


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