The fragmentation of production across countries has become an important feature of the glob- alization in recent decades and is often conceptualized by the term, global value chains (GVCs). When empirically investigating the GVCs, previous studies are mainly interested in knowing how global the GVCs are rather than how the GVCs look like. From a complex networks perspective, we use the World Input-Output Database (WIOD) to study the global production system. We find that the industry-level GVCs are indeed not chain-like but are better characterized by the tree topology. Hence, we compute the global value trees (GVTs) for all the industries available in the WIOD. Moreover, we compute an industry importance measure based on the GVTs and compare it with other network centrality measures. Finally, we discuss some future applications of the GVTs.  Based on the GVNs, the GVTs can be obtained by a modified breadth-first search algo- rithm. First, we choose an industry as the root of the GVT and the tree grows as we add the most relevant industries to the root industry in terms of the value-added contribution. Second, since the GVNs are almost completely connected (This is a general feature of the input-output networks due to the aggregated industry classification), we search the GVTs based on a threshold of the edge weight, which we denote by α, in order to separate the most relevant industries from the less relevant ones. Third, we limit the breadth-first search to a fixed number of rounds, which we denote by γ. Again, this is to ensure that only the most relevant industries with respect to the root industry are included in the GVTs. 





Theory of complex networks proved successful in the description of a variety of static networks ranging from biology to computer and social sciences and to economics and finance. Here we use network models to describe the evolution of a particular economic system, namely the Interna- tional Trade Network (ITN). Previous studies often assume that globalization and regionalization in international trade are contradictory to each other. We re-examine the relationship between globalization and regionalization by viewing the international trade system as an interdependent complex network. We use the modularity optimization method to detect communities and commu- nity cores in the ITN during the years 1995-2011. We find rich dynamics over time both inter- and intra-communities. Most importantly, we have a multilevel description of the evolution where the global dynamics (i.e., communities disappear or reemerge) tend to be correlated with the regional dynamics (i.e., community core changes between community members). In particular, the Asia- Oceania community disappeared and reemerged over time along with a switch in leadership from Japan to China. Moreover, simulation results show that the global dynamics can be generated by a preferential attachment mechanism both inter- and intra- communities.










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