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Complex Network Analysis in Socioeconomic Models

In: Complexity and Geographical Economics

Author

Listed:
  • Luis M. Varela

    (Universidad de Santiago de Compostela)

  • Giulia Rotundo

    (Territory and Finance, Sapienza University of Rome)

  • Marcel Ausloos

    (Rés. Beauvallon, rue de la Belle Jardiniére
    Royal Netherlands Academy of Arts and Sciences)

  • Jesús Carrete

    (Universidad de Santiago de Compostela
    LITEN, CEA-Grenoble)

Abstract

This chapter aims at reviewing complex network models and methods that were either developed for or applied to socioeconomic issues, and pertinent to the theme of New Economic Geography. After an introduction to the foundations of the field of complex networks, the present summary adds insights on the statistical mechanical approach, and on the most relevant computational aspects for the treatment of these systems. As the most frequently used model for interacting agent-based systems, a brief description of the statistical mechanics of the classical Ising model on regular lattices, together with recent extensions of the same model on small-world Watts–Strogatz and scale-free Albert-Barabási complex networks is included. Other sections of the chapter are devoted to applications of complex networks to economics, finance, spreading of innovations, and regional trade and developments. The chapter also reviews results involving applications of complex networks to other relevant socioeconomic issues, including results for opinion and citation networks. Finally, some avenues for future research are introduced before summarizing the main conclusions of the chapter.

Suggested Citation

  • Luis M. Varela & Giulia Rotundo & Marcel Ausloos & Jesús Carrete, 2015. "Complex Network Analysis in Socioeconomic Models," Dynamic Modeling and Econometrics in Economics and Finance, in: Pasquale Commendatore & Saime Kayam & Ingrid Kubin (ed.), Complexity and Geographical Economics, edition 127, pages 209-245, Springer.
    • Handle: RePEc:spr:dymchp:978-3-319-12805-4_9
    DOI: 10.1007/978-3-319-12805-4_9
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    Citations

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    Cited by:

    1. Gian Paolo Clemente & Rosanna Grassi & Chiara Pederzoli, 2020. "Networks and market-based measures of systemic risk: the European banking system in the aftermath of the financial crisis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 159-181, January.
    2. Bahrami, Mohammad & Chinichian, Narges & Hosseiny, Ali & Jafari, Gholamreza & Ausloos, Marcel, 2020. "Optimization of the post-crisis recovery plans in scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    3. Lucas Cuadra & Sancho Salcedo-Sanz & Javier Del Ser & Silvia Jiménez-Fernández & Zong Woo Geem, 2015. "A Critical Review of Robustness in Power Grids Using Complex Networks Concepts," Energies, MDPI, vol. 8(9), pages 1-55, August.
    4. Abreu, Mariana Piaia & Grassi, Rosanna & Del-Vecchio, Renata R., 2019. "Structure of control in financial networks: An application to the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 302-314.
    5. Gian Paolo Clemente & Alessandra Cornaro, 2020. "Bounding robustness in complex networks under topological changes through majorization techniques," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 93(6), pages 1-12, June.
    6. Rosanna Grassi & Paolo Bartesaghi & Stefano Benati & Gian Paolo Clemente, 2021. "Multi-Attribute Community Detection in International Trade Network," Networks and Spatial Economics, Springer, vol. 21(3), pages 707-733, September.
    7. Paolo Bartesaghi & Gian Paolo Clemente & Rosanna Grassi, 2022. "Community structure in the World Trade Network based on communicability distances," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(2), pages 405-441, April.

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