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Economic Networks: What do we know and what do we need to know?

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  • Frank Schweitzer

    ()

  • Giorgio Fagiolo
  • Didier Sornette
  • Fernando Vega-Redondo
  • Douglas R. White

Abstract

We examine the emergent field of economic networks and explore its ability to shed light on the global and volatile economy where credit, ownership, innovation, investment, and virtually every other economic activity is carried at a scale and scope that respects no geographical, organizational, or political boundaries. In this context, the study of economic networks and their dynamics must reflect the vast complexity of the interaction patterns and integrate it with a realistic account of the incentives and information that govern agents' behavior. The interplay of both has been shown to produce metastabilities, system crashes, and emergent structures in ways that are yet only poorly understood. Meeting this exciting scientific challenge requires a combination of time series analysis, complexity theory, and simulation with the analytical tools that have been developed by game theory, as well as graph and matrix theories. We argue that this will help achieving a better integration of theory and data models and provide a better understanding of the potentials and risks of modern economic systems.

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Bibliographic Info

Paper provided by ETH Zurich, Chair of Systems Design in its series Working Papers with number CCSS-09-010.

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Publication status: Published
Handle: RePEc:stz:wpaper:ccss-09-010

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Keywords: economic networks;

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References

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Citations

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Cited by:
  1. Andreas Koulouris & Ioannis Katerelos & Theodore Tsekeris, 2013. "Multi-Equilibria Regulation Agent-Based Model of Opinion Dynamics in Social Networks," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 11(1), pages 51-70.
  2. Brendan Markey-Towler & John Foster, 2013. "Understanding the causes of income inequality in complex economic systems," Discussion Papers Series 478, School of Economics, University of Queensland, Australia.
  3. Pawe{\l} Sieczka & Didier Sornette & Janusz A. Ho{\l}yst, 2010. "The Lehman Brothers Effect and Bankruptcy Cascades," Papers 1002.1070, arXiv.org, revised Sep 2011.
  4. Benjamin M. Tabak & Marcelo Yoshio Takami & J. M. C. Rocha & Daniel O. Cajueiro, 2011. "Directed Clustering Coefficient as a Measure of Systemic Risk in Complex Banking Networks," Working Papers Series 249, Central Bank of Brazil, Research Department.
  5. Andrey Sokolov & Rachel Webster & Andrew Melatos & Tien Kieu, 2012. "Loan and nonloan flows in the Australian interbank network," Papers 1202.3182, arXiv.org.
  6. Sokolov, Andrey & Webster, Rachel & Melatos, Andrew & Kieu, Tien, 2012. "Loan and nonloan flows in the Australian interbank network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(9), pages 2867-2882.
  7. H. Fan, 2012. "Distribution Of Producer Size In Globalized Market," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(07), pages 1250076-1-1.
  8. Rivera-Castro, Miguel A. & Miranda, José G.V. & Cajueiro, Daniel O. & Andrade, Roberto F.S., 2012. "Detecting switching points using asymmetric detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 170-179.

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