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Tipping points in macroeconomic agent-based models

Listed author(s):
  • Gualdi, Stanislao
  • Tarzia, Marco
  • Zamponi, Francesco
  • Bouchaud, Jean-Philippe
Registered author(s):

    The aim of this work is to explore the possible types of phenomena that simple macroeconomic Agent-Based models (ABMs) can reproduce. We propose a methodology, inspired by statistical physics, that characterizes a model through its “phase diagram” in the space of parameters. Our first motivation is to understand the large macro-economic fluctuations observed in the “Mark I” ABM devised by Delli Gatti and collaborators. In this regard, our major finding is the generic existence of a phase transition between a “good economy” where unemployment is low, and a “bad economy” where unemployment is high. We then introduce a simpler framework that allows us to show that this transition is robust against many modifications of the model, and is generically induced by an asymmetry between the rate of hiring and the rate of firing of the firms. The unemployment level remains small until a tipping point, beyond which the economy suddenly collapses. If the parameters are such that the system is close to this transition, any small fluctuation is amplified as the system jumps between the two equilibria. We have explored several natural extensions of the model. One is to introduce a bankruptcy threshold, limiting the firms maximum level of debt-to-sales ratio. This leads to a rich phase diagram with, in particular, a region where acute endogenous crises occur, during which the unemployment rate shoots up before the economy can recover. We also introduce simple wage policies. This leads to inflation (in the “good” phase) or deflation (in the “bad” phase), but leaves the overall phase diagram of the model essentially unchanged. We have also explored the effect of simple monetary policies that attempt to contain rising unemployment and defang crises. We end the paper with general comments on the usefulness of ABMs to model macroeconomic phenomena, in particular in view of the time needed to reach a steady state that raises the issue of ergodicity in these models.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0165188914001924
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    Article provided by Elsevier in its journal Journal of Economic Dynamics and Control.

    Volume (Year): 50 (2015)
    Issue (Month): C ()
    Pages: 29-61

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    Handle: RePEc:eee:dyncon:v:50:y:2015:i:c:p:29-61
    DOI: 10.1016/j.jedc.2014.08.003
    Contact details of provider: Web page: http://www.elsevier.com/locate/jedc

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    1. Edoardo Gaffeo & Domenico Delli Gatti & Saul Desiderio & Mauro Gallegati, 2008. "Adaptive Microfoundations for Emergent Macroeconomics," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 34(4), pages 441-463.
    2. Assenza, Tiziana & Delli Gatti, Domenico, 2013. "E Pluribus Unum: Macroeconomic modelling for multi-agent economies," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1659-1682.
    3. Alan Kirman, 2010. "The Economic Crisis is a Crisis for Economic Theory ," CESifo Economic Studies, CESifo, vol. 56(4), pages 498-535, December.
    4. J. Lorenz & S. Battiston & F. Schweitzer, 2009. "Systemic risk in a unifying framework for cascading processes on networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(4), pages 441-460, October.
    5. John Geanakoplos & Robert Axtell & J. Doyne Farmer & Peter Howitt & Benjamin Conlee & Jonathan Goldstein & Matthew Hendrey & Nathan M. Palmer & Chun-Yi Yang, 2012. "Getting at Systemic Risk via an Agent-Based Model of the Housing Market," American Economic Review, American Economic Association, vol. 102(3), pages 53-58, May.
    6. Giorgio Fagiolo & Andrea Roventini, 2012. "Macroeconomic Policy in DSGE and Agent-Based Models," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 67-116.
    7. repec:spo:wpecon:info:hdl:2441/f4rshpf3v1umfa09l8sci08kj is not listed on IDEAS
    8. Mauro Napoletano & Giovanni Dosi & Giorgio Fagiolo & Andrea Roventini, 2012. "Wage Formation, Investment Behavior and Growth Regimes: An Agent-Based Analysis," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 235-261.
    9. William A. Brock & Steven N. Durlauf, 2001. "Discrete Choice with Social Interactions," Review of Economic Studies, Oxford University Press, vol. 68(2), pages 235-260.
    10. Dosi, Giovanni & Fagiolo, Giorgio & Napoletano, Mauro & Roventini, Andrea, 2013. "Income distribution, credit and fiscal policies in an agent-based Keynesian model," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1598-1625.
    11. Imre Kondor & István Csabai & Gábor Papp & Enys Mones & Gábor Czimbalmos & Máté Sándor, 2014. "Strong random correlations in networks of heterogeneous agents," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 9(2), pages 203-232, October.
    12. Aoki,Masanao & Yoshikawa,Hiroshi, 2011. "Reconstructing Macroeconomics," Cambridge Books, Cambridge University Press, number 9781107634206, September.
    13. Hommes,Cars, 2015. "Behavioral Rationality and Heterogeneous Expectations in Complex Economic Systems," Cambridge Books, Cambridge University Press, number 9781107564978, September.
    14. Di Guilmi, C. & Gallegati, M. & Landini, S., 2008. "Economic dynamics with financial fragility and mean-field interaction: A model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3852-3861.
    15. Raberto, Marco & Teglio, Andrea & Cincotti, Silvano, 2012. "Debt, deleveraging and business cycles: An agent-based perspective," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 6, pages 1-49.
    16. Fabio Caccioli & Matteo Marsili & Pierpaolo Vivo, 2009. "Eroding market stability by proliferation of financial instruments," Papers 0910.0064, arXiv.org.
    17. Gauti B. Eggertsson & Paul Krugman, 2012. "Debt, Deleveraging, and the Liquidity Trap: A Fisher-Minsky-Koo Approach," The Quarterly Journal of Economics, Oxford University Press, vol. 127(3), pages 1469-1513.
    18. Ashraf, Quamrul & Gershman, Boris & Howitt, Peter, 2017. "Banks, market organization, and macroeconomic performance: An agent-based computational analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 135(C), pages 143-180.
    19. Buiter, Willem, 2009. "The unfortunate uselessness of most ’state of the art’ academic monetary economics," MPRA Paper 58407, University Library of Munich, Germany, revised 06 Mar 2009.
    20. Cornelia Metzig & Mirta Gordon, 2012. "Heterogeneous Enterprises in a Macroeconomic Agent-Based Model," Papers 1211.5575, arXiv.org.
    21. Bruce C. Greenwald & Joseph E. Stiglitz, 1993. "Financial Market Imperfections and Business Cycles," The Quarterly Journal of Economics, Oxford University Press, vol. 108(1), pages 77-114.
    22. Sander Van Der Hoog & Christophe Deissenberg & Herbert Dawid, 2008. "Production and Finance in EURACE," Working Papers halshs-00339758, HAL.
    23. A. Pyka & G. Fagiolo, 2007. "Agent-based Modelling: A Methodology for Neo-Schumpetarian Economics," Chapters,in: Elgar Companion to Neo-Schumpeterian Economics, chapter 29 Edward Elgar Publishing.
    24. Alan P. Kirman, 1992. "Whom or What Does the Representative Individual Represent?," Journal of Economic Perspectives, American Economic Association, vol. 6(2), pages 117-136, Spring.
    25. Thesmar , David & Landier , Augustin, 2014. "Instabilities in Large Economies: Aggregate Volatility Without Idiosyncratic Shocks," Les Cahiers de Recherche 1052, HEC Paris.
    26. M. Cristelli & L. Pietronero & A. Zaccaria, 2011. "Critical Overview of Agent-Based Models for Economics," Papers 1101.1847, arXiv.org.
    27. Leijonhufvud, Axel, 2006. "Agent-Based Macro," Handbook of Computational Economics,in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 36, pages 1625-1637 Elsevier.
    28. Ribin Lye & James Peng Lung Tan & Siew Ann Cheong, 2012. "Understanding agent-based models of financial markets: a bottom-up approach based on order parameters and phase diagrams," Papers 1202.0606, arXiv.org.
    29. Tesfatsion, Leigh S., 2002. "Agent-Based Computational Economics: Growing Economies from the Bottom Up," Staff General Research Papers Archive 5075, Iowa State University, Department of Economics.
    30. Herbert Dawid & Michael Neugart, 2011. "Agent-based Models for Economic Policy Design," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 37(1), pages 44-50.
    31. Lye, Ribin & Tan, James Peng Lung & Cheong, Siew Ann, 2012. "Understanding agent-based models of financial markets: A bottom–up approach based on order parameters and phase diagrams," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5521-5531.
    32. F. Caccioli & M. Marsili & P. Vivo, 2009. "Eroding market stability by proliferation of financial instruments," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(4), pages 467-479, October.
    33. Blake LeBaron & Leigh Tesfatsion, 2008. "Modeling Macroeconomies as Open-Ended Dynamic Systems of Interacting Agents," American Economic Review, American Economic Association, vol. 98(2), pages 246-250, May.
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