scholarly journals Crisis contagion in the world trade network

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Célestin Coquidé ◽  
José Lages ◽  
Dima L. Shepelyansky

Abstract We present a model of worldwide crisis contagion based on the Google matrix analysis of the world trade network obtained from the UN Comtrade database. The fraction of bankrupted countries exhibits an on-off phase transition governed by a bankruptcy threshold κ related to the trade balance of the countries. For κ>κc, the contagion is circumscribed to less than 10% of the countries, whereas, for κ<κc, the crisis is global with about 90% of the countries going to bankruptcy. We measure the total cost of the crisis during the contagion process. In addition to providing contagion scenarios, our model allows to probe the structural trading dependencies between countries. For different networks extracted from the world trade exchanges of the last two decades, the global crisis comes from the Western world. In particular, the source of the global crisis is systematically the Old Continent and The Americas (mainly US and Mexico). Besides the economy of Australia, those of Asian countries, such as China, India, Indonesia, Malaysia and Thailand, are the last to fall during the contagion. Also, the four BRIC are among the most robust countries to the world trade crisis.

2021 ◽  
pp. 39-47
Author(s):  
Justin Loye ◽  
Katia Jaffrès-Runser ◽  
Dima L. Shepelyansky

We develop the Google matrix analysis of the multiproduct world trade network obtained from the UN COMTRADE database in recent years. The comparison is done between this new approach and the usual Import-Export description of this world trade network. The Google matrix analysis takes into account the multiplicity of trade transactions thus highlighting in a better way the world influence of specific countries and products. It shows that after Brexit, the European Union of 27 countries has the leading position in the world trade network ranking, being ahead of USA and China. Our approach determines also a sensitivity of trade country balance to specific products showing the dominant role of machinery and mineral fuels in multiproduct exchanges. It also underlines the growing influence of Asian countries.


2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Justin Loye ◽  
Leonardo Ermann ◽  
Dima L. Shepelyansky

AbstractWe 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.


2011 ◽  
Vol 120 (6A) ◽  
pp. A-158-A-171 ◽  
Author(s):  
L. Ermann ◽  
D.L. Shepelyansky

PLoS ONE ◽  
2014 ◽  
Vol 9 (7) ◽  
pp. e100338 ◽  
Author(s):  
Tsuyoshi Deguchi ◽  
Katsuhide Takahashi ◽  
Hideki Takayasu ◽  
Misako Takayasu

2005 ◽  
Vol 355 (1) ◽  
pp. 138-144 ◽  
Author(s):  
Diego Garlaschelli ◽  
Maria I. Loffredo
Keyword(s):  

Author(s):  
José Lages ◽  
Justin Loye ◽  
Célestin Coquidé ◽  
Guillaume Rollin

The worldwide football transfer market is analyzed as a directed complex network: the football clubs are the network nodes and the directed edges are weighted by the total amount of money transferred from a club to another. The Google matrix description allows to treat every club independently of their richness and allows to measure for a given club the efficiency of player sales and player acquisitions. The PageRank algorithm, developed initially for the World Wide Web, naturally characterizes the ability of a club to import players. The CheiRank algorithm, also developed to analyze large scale directed complex networks, characterizes the ability of a club to export players. The analysis in the two-dimensional PageRank-CheiRank plan permits to determine the transfer balance of the clubs in a more subtle manner than the traditional import-export scheme. We investigate the 2017-2018 mercato concerning 2296 clubs, 6698 player transfers, and 147 player nationalities. The transfer balance is determined globally for different types of player trades (defender, midfielder, forward, …) and for different national football leagues. Although, on average, the network transfer flows from and to clubs are balanced, the discrimination by player type draws a specific portrait of each football club.


Author(s):  
Paolo Bartesaghi ◽  
Gian Paolo Clemente ◽  
Rosanna Grassi

AbstractIn this paper, we investigate the mesoscale structure of the World Trade Network. In this framework, a specific role is assumed by short- and long-range interactions, and hence by any suitably defined network-based distance between countries. Therefore, we identify clusters through a new procedure that exploits Estrada communicability distance and the vibrational communicability distance, which turn out to be particularly suitable for catching the inner structure of the economic network. The proposed methodology aims at finding the distance threshold that maximizes a specific quality function defined for general metric spaces. Main advantages regard the computational efficiency of the procedure as well as the possibility to inspect intercluster and intracluster properties of the resulting communities. The numerical analysis highlights peculiar relationships between countries and provides a rich set of information that can hardly be achieved within alternative clustering approaches.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Javier García-Algarra ◽  
Mary Luz Mouronte-López ◽  
Javier Galeano

AbstractThe World Trade Network (WTN) is a network of exchange flows among countries whose topological and statistical properties are a valuable source of information. Degree and strength (weighted degree) are key magnitudes to understand its structure and generative mechanisms. In this work, we describe a stochastic model that yields synthetic networks that closely mimic the properties of annual empirical data. The model combines two popular mechanisms of network generation: preferential attachment and multiplicative process. Agreement between empirical and synthetic networks is checked using the available series from 1962 to 2017.


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