Literature DB >> 33322140

Interdependence of Sectors of Economic Activities for World Countries from the Reduced Google Matrix Analysis of WTO Data.

Célestin Coquidé1, José Lages1, Dima L Shepelyansky2.   

Abstract

We apply the recently developed reduced Google matrix algorithm for the analysis of the OECD-WTO World Network of Economic Activities. This approach allows to determine interdependencies and interactions of economy sectors of several countries, including China, Russia and the USA, properly taking into account the influence of all the other world countries and their economic activities. Within this analysis, we also obtain the sensitivity of EU countries' economies to the petroleum activity sector. We show that this approach takes into account the multiplicity of economical interactions between countries and activity sectors, thus providing a richer analysis compared to the usual export-import analysis.

Entities:  

Keywords:  Google matrix; Markovian process; PageRank; World Trade Organization; networks

Year:  2020        PMID: 33322140      PMCID: PMC7763222          DOI: 10.3390/e22121407

Source DB:  PubMed          Journal:  Entropy (Basel)        ISSN: 1099-4300            Impact factor:   2.524


  7 in total

1.  Cytoscape: a software environment for integrated models of biomolecular interaction networks.

Authors:  Paul Shannon; Andrew Markiel; Owen Ozier; Nitin S Baliga; Jonathan T Wang; Daniel Ramage; Nada Amin; Benno Schwikowski; Trey Ideker
Journal:  Genome Res       Date:  2003-11       Impact factor: 9.043

2.  Multinetwork of international trade: a commodity-specific analysis.

Authors:  Matteo Barigozzi; Giorgio Fagiolo; Diego Garlaschelli
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2010-04-09

3.  World-trade web: topological properties, dynamics, and evolution.

Authors:  Giorgio Fagiolo; Javier Reyes; Stefano Schiavo
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2009-03-27

4.  Structure and response in the world trade network.

Authors:  Jiankui He; Michael W Deem
Journal:  Phys Rev Lett       Date:  2010-11-05       Impact factor: 9.161

5.  A random matrix approach to credit risk.

Authors:  Michael C Münnix; Rudi Schäfer; Thomas Guhr
Journal:  PLoS One       Date:  2014-05-22       Impact factor: 3.240

6.  Inferring hidden causal relations between pathway members using reduced Google matrix of directed biological networks.

Authors:  José Lages; Dima L Shepelyansky; Andrei Zinovyev
Journal:  PLoS One       Date:  2018-01-25       Impact factor: 3.240

7.  Hubs and authorities in the world trade network using a weighted HITS algorithm.

Authors:  Tsuyoshi Deguchi; Katsuhide Takahashi; Hideki Takayasu; Misako Takayasu
Journal:  PLoS One       Date:  2014-07-22       Impact factor: 3.240

  7 in total
  2 in total

1.  Fibrosis Protein-Protein Interactions from Google Matrix Analysis of MetaCore Network.

Authors:  Ekaterina Kotelnikova; Klaus M Frahm; Dima L Shepelyansky; Oksana Kunduzova
Journal:  Int J Mol Sci       Date:  2021-12-22       Impact factor: 5.923

2.  COVID-19's Impact on International Trade.

Authors:  Célestin Coquidé; José Lages; Leonardo Ermann; Dima L Shepelyansky
Journal:  Entropy (Basel)       Date:  2022-02-24       Impact factor: 2.524

  2 in total

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