In this paper we use Complex Network Theory to quantitatively characterize and synthetically describe the complexity of trade between nations. In particular, we focus our attention on export fluxes. Starting from the bipartite countries-products network defined by export fluxes, we define two complementary graphs projecting the original network on countries and products respectively. We define, in both cases, a distance matrix amongst countries and products. Specifically, two countries are similar if they export similar products. This relationship can be quantified by building the Minimum Spanning Tree and the Minimum Spanning Forest from the distance matrices for products and countries. Through this simple and scalable method we are also able to carry out a community analysis. It is not gone unnoticed that in this way we can produce an effective categorization for products providing several advantages with respect to traditional classifications of COMTRADE [1]. Finally, the forests of countries allows for the detection of competitors' community and for the analysis of the evolution of these communities.
Cristelli, M., Tacchella, A., Gabrielli, A., Pietronero, L., Scala, A., Caldarelli, G. (2012). Competitors' communities and taxonomy of products according to export fluxes. THE EUROPEAN PHYSICAL JOURNAL. SPECIAL TOPICS, 212(1), 115-120 [10.1140/epjst/e2012-01657-4].
Competitors' communities and taxonomy of products according to export fluxes
Gabrielli A.;
2012-01-01
Abstract
In this paper we use Complex Network Theory to quantitatively characterize and synthetically describe the complexity of trade between nations. In particular, we focus our attention on export fluxes. Starting from the bipartite countries-products network defined by export fluxes, we define two complementary graphs projecting the original network on countries and products respectively. We define, in both cases, a distance matrix amongst countries and products. Specifically, two countries are similar if they export similar products. This relationship can be quantified by building the Minimum Spanning Tree and the Minimum Spanning Forest from the distance matrices for products and countries. Through this simple and scalable method we are also able to carry out a community analysis. It is not gone unnoticed that in this way we can produce an effective categorization for products providing several advantages with respect to traditional classifications of COMTRADE [1]. Finally, the forests of countries allows for the detection of competitors' community and for the analysis of the evolution of these communities.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.