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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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  • Stephanie Rend'on de la Torre
  • Jaan Kalda
  • Robert Kitt
  • Juri Engelbrecht

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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  • Stephanie Rend'on de la Torre & Jaan Kalda & Robert Kitt & Juri Engelbrecht, 2016. "On the topologic structure of economic complex networks: Empirical evidence from large scale payment network of Estonia," Papers 1602.04352, arXiv.org.
  • Handle: RePEc:arx:papers:1602.04352
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    References listed on IDEAS

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    1. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 1999. "Mean-field theory for scale-free random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 272(1), pages 173-187.
    2. Frank Schweitzer & Giorgio Fagiolo & Didier Sornette & Fernando Vega-Redondo & Douglas R. White, 2009. "Economic Networks: What Do We Know And What Do We Need To Know?," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 12(04n05), pages 407-422.
    3. Kirsten Bonde Rørdam & Morten Linnemann Bech, 2008. "The Topology of Danish Interbank Money Flows," FRU Working Papers 2009/01, University of Copenhagen. Department of Economics. Finance Research Unit.
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    Cited by:

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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. 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).
    7. Carolina E S Mattsson & Teodoro Criscione & Frank W Takes, 2022. "Circulation of a digital community currency," Papers 2207.08941, arXiv.org, revised Jun 2023.
    8. Edgar J. Sánchez Carrera & Vanesa Avalos-Gaytán & Yajaira Cardona Valdés, 2019. "Synchronization of globalized economies," Working Papers 1909, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2019.

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