Abstract
The main purpose of this paper is to apply big-data and scale-free complex network techniques to the study of world trade, with a specific focus on the investigation of ECLAC and structuralist ideas. A secondary objective is to illustrate the potentialities of the use of the new science of complex networks in economics, in what has been recently referred to as an econophysics research agenda. We work with a trade network of 101 countries and 762 products (SITC-4) which generated 1,756,224 trade links in 2013. The empirical results based on network analysis and computational methods reported here point in the direction of what ECLAC economists used to argue; countries with higher income per capita concentrate in producing and exporting manufactured and complex goods at the center of the trade network; countries with lower income per capita specialize in producing and exporting non-complex commodities at the network’s periphery.
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