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The nested structural organization of the worldwide trade multi-layer network.

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This study introduces a multi-layer network to analyze global value chains, revealing country and industry contributions to trade nestedness. It offers a novel perspective on international production networks.

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Area of Science:

  • Ecology
  • Economics
  • Network Science

Background:

  • Nestedness analysis traditionally uses bipartite networks for meta-communities and trade.
  • Bipartite trade networks overlook inter-industry transactions, limiting global value chain analysis.

Purpose of the Study:

  • To develop a multi-layer network model for global value chains.
  • To compute and analyze nestedness in international trade, considering both country and transaction perspectives.
  • To identify key countries and industries influencing trade network structure.

Main Methods:

  • Constructed a multi-layer network using World Input-Output Database data.
  • Defined buyers' and sellers' participation matrices for trade analysis.
  • Computed nestedness using null models preserving network degree distributions.

Main Results:

  • Uncovered temporal variations in country- and transaction-based nestedness.
  • Identified specific countries and industries significantly contributing to trade network nestedness.
  • Demonstrated the utility of multi-layer networks for understanding complex economic systems.

Conclusions:

  • The multi-layer network approach provides a more comprehensive view of global value chains than bipartite models.
  • Findings offer insights into the structure and dynamics of international production networks.
  • The methodology can be applied to analyze other complex real-world systems.