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On the topologic structure of economic complex networks: Empirical evidence from large scale payment network of Estonia

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  • Rendón de la Torre, Stephanie
  • Kalda, Jaan
  • Kitt, Robert
  • Engelbrecht, Jüri

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.

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  • Rendón de la Torre, Stephanie & Kalda, Jaan & Kitt, Robert & Engelbrecht, Jüri, 2016. "On the topologic structure of economic complex networks: Empirical evidence from large scale payment network of Estonia," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 18-27.
  • Handle: RePEc:eee:chsofr:v:90:y:2016:i:c:p:18-27
    DOI: 10.1016/j.chaos.2016.01.018
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    2. Clemente, G.P. & Grassi, R., 2018. "Directed clustering in weighted networks: A new perspective," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 26-38.
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    4. Wang Yijie & Ke Yanyan & Ma Xianrui & Ren Yitian, 2020. "What is the Industrial Structure Changes of China?," Journal of Systems Science and Information, De Gruyter, vol. 8(6), pages 487-503, December.
    5. Hazan, Aurélien, 2019. "A maximum entropy network reconstruction of macroeconomic models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 1-17.
    6. Carolina E S Mattsson & Teodoro Criscione & Frank W Takes, 2022. "Circulation of a digital community currency," Papers 2207.08941, arXiv.org, revised Jun 2023.
    7. Cerqueti, Roy & Deffains-Crapsky, Catherine & Storani, Saverio, 2022. "Similarity-based heterogeneity and cohesiveness of networked companies issuing minibonds," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    8. Zhao Li & Ren Zhuoming & Zhao Ziyi & Weng Tongfeng, 2024. "Topological perturbations on resilience of the world trade competition network," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-9, December.

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