On the topologic structure of economic complex networks: Empirical evidence from large scale payment network of Estonia. (September 2016)

• Record Type: Journal Article
• Authors: Rendón de la Torre, Stephanie; Kalda, Jaan; Kitt, Robert; Engelbrecht, Jüri
• Is Part Of: Chaos, solitons and fractals. Volume 90(2016)
• Page Start: 18
• Page End: 27
• Publication Date: 2016-09
• Subjects: Complex systems -- Network topology -- Scale-free networks -- Economic networks; Chaotic behavior in systems -- Periodicals; Solitons -- Periodicals; Fractals -- Periodicals; Chaotic behavior in systems; Fractals; Solitons; Periodicals; 003.7
• DOI: 10.1016/j.chaos.2016.01.018
• Languages: English
• ISSNs: 0960-0779

Abstract

Highlights: First topological analysis of the economic structure of Estonia based on payments data. The network is heterogeneous and has a scale-free structure. Low clustering coefficient, low average shortest path length and disassortativity. A simulation to identify the percolation threshold at which the network is destroyed. Abstract: This paper presents the first topological analysis of the economic structure of an entire country based on payments data obtained from Swedbank. This data set is exclusive in its kind because around 80% of Estonia's bank transactions are done through Swedbank; hence, the economic structure of the country can be reconstructed. Scale-free networks are commonly observed in a wide array of different contexts such as nature and society. In this paper, the nodes are comprised by customers of the bank (legal entities) and the links are established by payments between these nodes. We study the scaling-free and structural properties of this network. We also describe its topology, components and behaviors. We show that this network shares typical structural characteristics known in other complex networks: degree distributions follow a power law, low clustering coefficient and low average shortest path length. We identify the key nodes of the network and perform simulations of resiliency against random and targeted attacks of the nodes with two different approaches. With this, we find that by identifying and studying the links between the nodes is possible to perform vulnerability analysis of the Estonian economy with respect to economic shocks.