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Random Digraphs with Given Expected Degree Sequences: A Model for Economic Networks

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  • Mauro Gallegati

    (UNIVPM - Polytechnic University of Marche [Ancona, Italy] / Università Politecnica delle Marche [Ancona, Italia])

Abstract

Building upon the growing interest for complex network theory, the main ambition of this paper is to contribute to a more effective application of network theory to economic phenomena, and particularly to financial networks. We depart from recent contributions on credit networks in two respects. In the first place, we constrain diversification with the out- and in-degree distribution of nodes, by adopting a suitable extension of the expected degree model for random weighted digraphs. In the second place, we focus on real networks by using this extension as null model for statistical analysis. With the help of statistical inference, we provide a rigorous answer to the following question: do real networks obey our null model? Further, we show that this answer is tightly connected to the existence of clusters or modules, as defined by Newman and Girvan (2004), within networks.

Suggested Citation

  • Mauro Gallegati, 2011. "Random Digraphs with Given Expected Degree Sequences: A Model for Economic Networks," Post-Print hal-00989518, HAL.
  • Handle: RePEc:hal:journl:hal-00989518
    DOI: 10.1016/j.jebo.2011.01.022
    Note: View the original document on HAL open archive server: https://hal.science/hal-00989518
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    References listed on IDEAS

    as
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    Cited by:

    1. Orlando Gomes, 2017. "Heterogeneous wage setting and endogenous macro volatility," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(1), pages 27-57, April.
    2. Bargigli, Leonardo & Gallegati, Mauro, 2013. "Finding communities in credit networks," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 7, pages 1-39.
    3. Leonardo Bargigli, 2013. "Statistical Equilibrium Models for Sparse Economic Networks," Working Papers - Economics wp2013_25.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    4. Catullo, Ermanno & Gallegati, Mauro & Palestrini, Antonio, 2015. "Towards a credit network based early warning indicator for crises," Journal of Economic Dynamics and Control, Elsevier, vol. 50(C), pages 78-97.
    5. Leonardo Bargigli & Giovanni di Iasio & Luigi Infante & Fabrizio Lillo & Federico Pierobon, 2015. "Interbank markets and multiplex networks: centrality measures and statistical null models," Papers 1501.05751, arXiv.org.
    6. L. Bargigli & G. di Iasio & L. Infante & F. Lillo & F. Pierobon, 2015. "The multiplex structure of interbank networks," Quantitative Finance, Taylor & Francis Journals, vol. 15(4), pages 673-691, April.
    7. Leonardo Bargigli & Luca Riccetti & Alberto Russo & Mauro Gallegati, 2020. "Network calibration and metamodeling of a financial accelerator agent based model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(2), pages 413-440, April.
    8. Giorgio Fagiolo & Tiziano Squartini & Diego Garlaschelli, 2013. "Null models of economic networks: the case of the world trade web," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 75-107, April.
    9. Isaiah Hull & Or Sattath & Eleni Diamanti & Göran Wendin, 2024. "Quantum Technology for Economists," Contributions to Economics, Springer, number 978-3-031-50780-9.
    10. Bargigli, Leonardo & Gallegati, Mauro & Riccetti, Luca & Russo, Alberto, 2014. "Network analysis and calibration of the “leveraged network-based financial accelerator”," Journal of Economic Behavior & Organization, Elsevier, vol. 99(C), pages 109-125.
    11. Deborah Noguera & Gabriel Montes-Rojas, 2022. "Credit-constrained fluctuations and uncertainty in a network economy," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, vol. 1(80), pages 5-52, November.

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