IDEAS home Printed from https://ideas.repec.org/p/tri/wpaper/1309.html
   My bibliography  Save this paper

Real and financial crises: A multi-agent approach

Author

Listed:
  • Mark Setterfield

    (Department of Economics, Trinity College)

  • Bill Gibson

    (Department of Economics,)

Abstract

Previous analyses of macroeconomic imbalances have employed models that either focus exclusively on real-side effects or financial-side disturbances. Real-side models usually make the unrealistic assumption that firms that save more than they invest effortlessly and costlessly transfer those surpluses to deficit firms, firms that require additional savings to sustain their plans for capital accumulation. On the other hand, there exists a well-developed, rigorous and elegant literature that uses the multi-agent systems (MAS) approach to analyze the recent financial crisis. These stand-alone models of the financial sector focus on the network structure of financial interplay but typically ignore real side interactions. In this paper, we develop a MAS model that integrates real and financial elements. The focus remains on the network structure and it is seen that randomly connected networks are more crash prone than are preferentially attached networks of financial agents. when real-financial interactions are taken into account. The results cast doubt on the connection between systemic risk and financial entities that are “too big or too linked to fail.”

Suggested Citation

  • Mark Setterfield & Bill Gibson, 2013. "Real and financial crises: A multi-agent approach," Working Papers 1309, Trinity College, Department of Economics, revised Jul 2014.
  • Handle: RePEc:tri:wpaper:1309
    as

    Download full text from publisher

    File URL: http://www3.trincoll.edu/repec/WorkingPapers2013/WP13-09.pdf
    File Function: First version, 2013
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stefan Thurner & J. Doyne Farmer & John Geanakoplos, 2012. "Leverage causes fat tails and clustered volatility," Quantitative Finance, Taylor & Francis Journals, vol. 12(5), pages 695-707, February.
    2. Raghuram G. Rajan & Rodney Ramcharan, 2011. "Land and Credit: A Study of the Political Economy of Banking in the United States in the Early 20th Century," Journal of Finance, American Finance Association, vol. 66(6), pages 1895-1931, December.
    3. Tedeschi, Gabriele & Iori, Giulia & Gallegati, Mauro, 2012. "Herding effects in order driven markets: The rise and fall of gurus," Journal of Economic Behavior & Organization, Elsevier, vol. 81(1), pages 82-96.
    4. Kregel, J A, 1985. "Hamlet without the Prince: Cambridge Macroeconomics without Money," American Economic Review, American Economic Association, vol. 75(2), pages 133-139, May.
    5. Carmen M. Reinhart & Kenneth S. Rogoff, 2009. "Varieties of Crises and Their Dates," Introductory Chapters, in: This Time Is Different: Eight Centuries of Financial Folly, Princeton University Press.
    6. Mark Setterfield (ed.), 2010. "Handbook of Alternative Theories of Economic Growth," Books, Edward Elgar Publishing, number 12814, March.
    7. Kosowski, Robert & Neftci, Salih N., 2014. "Principles of Financial Engineering," Elsevier Monographs, Elsevier, edition 3, number 9780123869685.
    8. Chamley,Christophe P., 2004. "Rational Herds," Cambridge Books, Cambridge University Press, number 9780521530927, June.
    9. repec:rnp:ecopol:09111 is not listed on IDEAS
    10. Chamley,Christophe P., 2004. "Rational Herds," Cambridge Books, Cambridge University Press, number 9780521824019, June.
    11. LeBaron, Blake, 2012. "Heterogeneous gain learning and the dynamics of asset prices," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 424-445.
    12. Robert Axtell, 1999. "The Emergence of Firms in a Population of Agents," Working Papers 99-03-019, Santa Fe Institute.
    13. Victoria Chick, 1983. "Macroeconomics after Keynes: A Reconsideration of the General Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262530457, December.
    14. Daron Acemoglu & Vasco M. Carvalho & Asuman Ozdaglar & Alireza Tahbaz‐Salehi, 2012. "The Network Origins of Aggregate Fluctuations," Econometrica, Econometric Society, vol. 80(5), pages 1977-2016, September.
    15. Harras, Georges & Sornette, Didier, 2011. "How to grow a bubble: A model of myopic adapting agents," Journal of Economic Behavior & Organization, Elsevier, vol. 80(1), pages 137-152.
    16. Anders Johansen & Olivier Ledoit & Didier Sornette, 2000. "Crashes As Critical Points," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(02), pages 219-255.
    17. Mark Setterfield & Andrew Budd, 2011. "A Keynes-Kalecki Model of Cyclical Growth with Agent-Based Features," Palgrave Macmillan Books, in: Philip Arestis (ed.), Microeconomics, Macroeconomics and Economic Policy, chapter 13, pages 228-250, Palgrave Macmillan.
    18. Iori, Giulia & De Masi, Giulia & Precup, Ovidiu Vasile & Gabbi, Giampaolo & Caldarelli, Guido, 2008. "A network analysis of the Italian overnight money market," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 259-278, January.
    19. Philip Arestis (ed.), 2011. "Microeconomics, Macroeconomics and Economic Policy," Palgrave Macmillan Books, Palgrave Macmillan, number 978-0-230-31375-0, May.
    20. Sushil Bikhchandani & David Hirshleifer & Ivo Welch, 1998. "Learning from the Behavior of Others: Conformity, Fads, and Informational Cascades," Journal of Economic Perspectives, American Economic Association, vol. 12(3), pages 151-170, Summer.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jean-Philippe Bouchaud, 2012. "Crises and collective socio-economic phenomena: simple models and challenges," Papers 1209.0453, arXiv.org, revised Dec 2012.
    2. Jonathan E. Alevy & Michael S. Haigh & John List, 2006. "Information Cascades: Evidence from An Experiment with Financial Market Professionals," NBER Working Papers 12767, National Bureau of Economic Research, Inc.
    3. Schlegel, Friederike & Hakenes, Hendrik, 2014. "Tapping the Financial Wisdom of the Crowd - Crowdfunding as a Tool to Aggregate Vague Information," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100563, Verein für Socialpolitik / German Economic Association.
    4. Drehmann, Mathias & Oechssler, Jorg & Roider, Andreas, 2007. "Herding with and without payoff externalities -- an internet experiment," International Journal of Industrial Organization, Elsevier, vol. 25(2), pages 391-415, April.
    5. Baumann, Michael Heinrich & Janischewski, Anja, 2025. "What are asset price bubbles? A survey on definitions of financial bubbles," MPRA Paper 123676, University Library of Munich, Germany.
    6. Hirshleifer, David & Teoh, Siew Hong, 2008. "Thought and Behavior Contagion in Capital Markets," MPRA Paper 9142, University Library of Munich, Germany.
    7. Schanne, Norbert, 2012. "The formation of experts' expectations on labour markets : do they run with the pack?," IAB-Discussion Paper 201225, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    8. Nathan M. Jensen Washington University, Rene Lindstadt, Trinity College Dublin, 2009. "Leaning Right and Learning from the Left: Diffusion of Corporate Tax Policy in the OECD," The Institute for International Integration Studies Discussion Paper Series iiisdp290, IIIS.
    9. Cao, H. Henry & Han, Bing & Hirshleifer, David, 2011. "Taking the road less traveled by: Does conversation eradicate pernicious cascades?," Journal of Economic Theory, Elsevier, vol. 146(4), pages 1418-1436, July.
    10. Chong Huang, 2018. "Coordination and social learning," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 65(1), pages 155-177, January.
    11. Szymon Chudziak, 2025. "Studying economic complexity with agent-based models: advances, challenges and future perspectives," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 20(2), pages 413-449, April.
    12. Hongbin Cai & Yuyu Chen & Hanming Fang, 2009. "Observational Learning: Evidence from a Randomized Natural Field Experiment," American Economic Review, American Economic Association, vol. 99(3), pages 864-882, June.
    13. Chong Huang, 2011. "Coordination and Social Learning," PIER Working Paper Archive 11-021, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    14. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 2005. "Information Cascades and Observational Learning," Working Paper Series 2005-22, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    15. Boğaçhan Çelen & Kyle Hyndman, 2012. "An experiment of social learning with endogenous timing," Review of Economic Design, Springer;Society for Economic Design, vol. 16(2), pages 251-268, September.
    16. Driver, Ciaran & Trapani, Lorenzo & Urga, Giovanni, 2013. "On the use of cross-sectional measures of forecast uncertainty," International Journal of Forecasting, Elsevier, vol. 29(3), pages 367-377.
    17. repec:ebl:ecbull:v:7:y:2006:i:7:p:1-12 is not listed on IDEAS
    18. Sofia Priazhkina & Samuel Palmer & Pablo Martín-Ramiro & Román Orús & Samuel Mugel & Vladimir Skavysh, 2024. "Digital Payments in Firm Networks: Theory of Adoption and Quantum Algorithm," Staff Working Papers 24-17, Bank of Canada.
    19. Gill, David & Sgroi, Daniel, 2008. "The Optimal Choice of Pre-launch Reviewer : How Best to Transmit Information using Tests and Conditional Pricing," The Warwick Economics Research Paper Series (TWERPS) 877, University of Warwick, Department of Economics.
    20. Andreas Blume & April Mitchell Franco & Paul Heidhues, 2021. "Dynamic coordination via organizational routines," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 72(4), pages 1001-1047, November.
    21. Marco Cipriani & Antonio Guarino, 2009. "Herd Behavior in Financial Markets: An Experiment with Financial Market Professionals," Journal of the European Economic Association, MIT Press, vol. 7(1), pages 206-233, March.

    More about this item

    Keywords

    Systemic risk; Crash; Herding; Bayesian learning; Endogenous money; preferential attachment; Agent-based models.;
    All these keywords.

    JEL classification:

    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • G01 - Financial Economics - - General - - - Financial Crises
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • B16 - Schools of Economic Thought and Methodology - - History of Economic Thought through 1925 - - - Quantitative and Mathematical
    • C00 - Mathematical and Quantitative Methods - - General - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tri:wpaper:1309. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Miguel Ramirez (email available below). General contact details of provider: https://edirc.repec.org/data/edtrius.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.