title: Network structure impacts global commodity trade growth and resilience.
abstract: Global commodity trade networks are critical to our collective sustainable development. Their increasing interconnectedness pose two practical questions: (i) Do the current network configurations support their further growth? (ii) How resilient are these networks to economic shocks? We analyze the data of global commodity trade flows from 1996 to 2012 to evaluate the relationship between structural properties of the global commodity trade networks and (a) their dynamic growth, as well as (b) the resilience of their growth with respect to the 2009 global economic shock. Specifically, we explore the role of network efficiency and redundancy using the information theory-based network flow analysis. We find that, while network efficiency is positively correlated with growth, highly efficient systems appear to be less resilient, losing more and gaining less growth following an economic shock. While all examined networks are rather redundant, we find that network redundancy does not hinder their growth. Moreover, systems exhibiting higher levels of redundancy lose less and gain more growth following an economic shock. We suggest that a strategy to support making global trade networks more efficient via, e.g., preferential trade agreements and higher specialization, can promote their further growth; while a strategy to increase the global trade networks' redundancy via e.g., more abundant free-trade agreements, can improve their resilience to global economic shocks.
authors.affiliation: Advanced Systems Analysis Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria.|Graduate School of Public Policy, University of Tokyo, Tokyo, Japan.
authors.forename: Ali
authors.identifier: http://orcid.org/0000-0002-5881-2568
authors.initials: A
authors.lastname: Kharrazi
authors.affiliation: Advanced Systems Analysis Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria.|Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University (MSU), Moscow, Russia.
authors.forename: Elena
authors.initials: E
authors.lastname: Rovenskaya
authors.affiliation: Advanced Systems Analysis Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria.|Biology Department, Towson University, Towson, Maryland, United States of America.
authors.forename: Brian D
authors.initials: BD
authors.lastname: Fath
mesh_terms: D003132:Commerce / Q000191:economics*; D006801:Humans; D007391:International Cooperation; D018803:Models, Economic