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Using Network Reliability to Understand International Food Trade Dynamics.

Madhurima Nath1, Srinivasan Venkatramanan1, Bryan Kaperick1

  • 1Virginia Tech, Blacksburg, VA 24060, USA.

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Analyzing international food trade networks reveals that clusters of connected countries form in regions with liberal trade. Intensifying trade increases cluster size, reducing resilience to disruptions.

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Area of Science:

  • Agricultural Economics
  • Network Science
  • International Trade

Background:

  • Food security and social welfare depend on understanding food network structures and dynamics.
  • International trade networks are complex systems influenced by various factors.

Purpose of the Study:

  • To analyze the structural and dynamical properties of international trade networks for four solanaceous crops.
  • To develop a novel method for identifying dynamics-induced clusters in directed weighted networks.

Main Methods:

  • Utilized the Food and Agricultural Organization (FAO) trade database.
  • Applied Moore-Shannon network reliability analysis.
  • Developed a new approach to detect clusters of highly-connected nodes.

Main Results:

  • Trade network structures and dynamics vary significantly across different commodities.
  • Clusters predominantly form between adjacent countries with liberal bilateral trade relations.
  • Increased trade intensification leads to larger clusters, diminishing the number of countries resilient to disruptions.
  • An aggregate network analysis reveals clusters distinct from those in individual commodity networks.

Conclusions:

  • Liberal trade policies foster geographically concentrated trade clusters.
  • Growing trade intensifies these clusters, potentially increasing systemic risk.
  • Aggregate network analysis provides a different perspective on trade interdependencies.