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Tipping points in macroeconomic agent-based models

Author

Listed:
  • Gualdi, Stanislao
  • Tarzia, Marco
  • Zamponi, Francesco
  • Bouchaud, Jean-Philippe

Abstract

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.

Suggested Citation

  • Gualdi, Stanislao & Tarzia, Marco & Zamponi, Francesco & Bouchaud, Jean-Philippe, 2015. "Tipping points in macroeconomic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 50(C), pages 29-61.
  • Handle: RePEc:eee:dyncon:v:50:y:2015:i:c:p:29-61
    DOI: 10.1016/j.jedc.2014.08.003
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    Cited by:

    1. Marko Petrovic & Bulent Ozel & Andrea Teglio & Marco Raberto & Silvano Cincotti, 2017. "Eurace Open: An agent-based multi-country model," Working Papers 2017/09, Economics Department, Universitat Jaume I, Castellón (Spain).
    2. Gualdi, Stanislao & Mandel, Antoine, 2016. "On the emergence of scale-free production networks," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 61-77.
    3. Matt V. Leduc & Sebastian Poledna & Stefan Thurner, 2016. "Systemic Risk Management in Financial Networks with Credit Default Swaps," Papers 1601.02156, arXiv.org, revised Oct 2017.
    4. Giorgio Fagiolo & Andrea Roventini, 2017. "Macroeconomic Policy in DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(1), pages 1-1.
    5. Wood, Aaron D. & Mason, Charles F. & Finnoff, David, 2016. "OPEC, the Seven Sisters, and oil market dominance: An evolutionary game theory and agent-based modeling approach," Journal of Economic Behavior & Organization, Elsevier, vol. 132(PB), pages 66-78.
    6. repec:ijm:journl:v10:y:2017:i:3:p:184-201 is not listed on IDEAS
    7. Mauro Napoletano, 2017. "A Short Walk on the Wild Side: Agent-Based Models and their Implications for Macroeconomic Analysis," GREDEG Working Papers 2017-40, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), University of Nice Sophia Antipolis.
    8. Poledna, Sebastian & Bochmann, Olaf & Thurner, Stefan, 2017. "Basel III capital surcharges for G-SIBs are far less effective in managing systemic risk in comparison to network-based, systemic risk-dependent financial transaction taxes," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 230-246.
    9. Aur'elien Hazan, 2017. "Stock-flow consistent macroeconomic model with nonuniform distributional constraint," Papers 1708.00645, arXiv.org.
    10. Hazan, Aurélien, 2017. "Volume of the steady-state space of financial flows in a monetary stock-flow-consistent model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 589-602.
    11. Jacopo Rocchi & Enoch Yan Lok Tsui & David Saad, 2016. "Emerging interdependence between stock values during financial crashes," Papers 1611.02549, arXiv.org.
    12. repec:eee:phsmap:v:490:y:2018:i:c:p:278-288 is not listed on IDEAS
    13. repec:eee:ecosta:v:5:y:2018:i:c:p:83-106 is not listed on IDEAS
    14. Marco Raberto & Bulent Ozel & Linda Ponta & Andrea Teglio & Silvano Cincotti, 2016. "From financial instability to green finance: the role of banking and monetary policies in the Eurace model," Working Papers 2016/07, Economics Department, Universitat Jaume I, Castellón (Spain).
    15. Aur'elien Hazan, 2016. "Volume of the steady-state space of financial flows in a monetary stock-flow-consistent model," Papers 1601.00822, arXiv.org, revised Jan 2017.
    16. Andrea Teglio & Andrea Mazzocchetti & Linda Ponta & Marco Raberto & Silvano Cincotti, 2015. "Budgetary rigour with stimulus in lean times: Policy advices from an agent-based model," Working Papers 2015/07, Economics Department, Universitat Jaume I, Castellón (Spain).
    17. repec:bla:rdevec:v:21:y:2017:i:3:p:713-730 is not listed on IDEAS
    18. repec:zbw:ifweej:201815 is not listed on IDEAS

    More about this item

    Keywords

    Agent-based computational economics; Aggregative models; Cycles;

    JEL classification:

    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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