World impact of kernel European Union 9 countries from Google matrix analysis of the world trade network

被引：0
|
作者：
Justin Loye
Leonardo Ermann
Dima L. Shepelyansky
机构：
[1] Université de Toulouse,Laboratoire de Physique Théorique
[2] CNRS,Institut de Recherche en Informatique de Toulouse
[3] UPS,Departamento de Física Teórica
[4] Université de Toulouse,undefined
[5] UPS,undefined
[6] GIyA,undefined
[7] Comisión Nacional de Energía Atómica,undefined
来源：
Applied Network Science | / 6卷
关键词：
Complex networks; World trade; Google matrix; PageRank;
D O I：
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学科分类号：
摘要：
We use the United Nations COMTRADE database for analysis of the multiproduct world trade network. With this data, considered for years 2012–2018, we determined the world trade impact of the Kernel of EU 9 countries (KEU9), being Austria, Belgium, France, Germany, Italy, Luxembourg, Netherlands, Portugal, Spain, considered as one united country. We apply the advanced Google matrix analysis for investigation of the influence of KEU9 and show that KEU9 takes the top trade network rank positions thus becoming the main player of the world trade being ahead of USA and China. Our network analysis provides additional mathematical grounds in favor of the recent proposal (Saint-Etienne in: Osons l’Europe des Nations. Editions de l’Observatoire/Humensis, Paris, 2018) of KEU9 super-union which is based only on historical, political and economy basis.
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