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Towards a credit network based early warning indicator for crises

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  • Catullo, Ermanno
  • Gallegati, Mauro
  • Palestrini, Antonio

Abstract

This paper presents an agent based model which underlines the importance of credit network and leverage dynamics in determining the resilience of the system, defining an early warning indicator for crises. The model reproduces macroeconomic dynamics emerging from the interactions of heterogeneous banks and firms in an endogenous credit network. Banks and firms are linked through multiple credit relations, which derive from individual target leverage choices: agents choose the more convenient leverage level, according to a basic reinforcement learning algorithm. Simulations are calibrated on balance sheet data of banks and firms quoted in the Japanese stock-exchange markets from 1980 to 2012.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:dyncon:v:50:y:2015:i:c:p:78-97
    DOI: 10.1016/j.jedc.2014.08.011
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    3. Giovanni Dosi & Andrea Roventini, 2017. "Agent-Based Macroeconomics and Classical Political Economy: Some Italian Roots," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 3(3), pages 261-283, November.
    4. Matkovskyy, Roman & Bouraoui, Taoufik & Hammami, Helmi, 2016. "Analysing the financial strength of Tunisia: An approach to estimate an index of financial safety," Research in International Business and Finance, Elsevier, vol. 38(C), pages 485-493.
    5. Hosseiny, Ali & Gallegati, Mauro, 2017. "Role of intensive and extensive variables in a soup of firms in economy to address long run prices and aggregate data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 51-59.
    6. Yuri Biondi & Feng Zhou, 2019. "Interbank credit and the money manufacturing process: a systemic perspective on financial stability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 437-468, September.
    7. Ermanno Catullo & Antonio Palestrini & Ruggero Grilli & Mauro Gallegati, 2018. "Early warning indicators and macro-prudential policies: a credit network agent based model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 81-115, April.
    8. Berardi, Simone & Tedeschi, Gabriele, 2017. "From banks' strategies to financial (in)stability," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 255-272.
    9. Sui, Xin & Li, Liang, 2018. "Guarantee network model and risk contagion," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 323-329.
    10. Di Guilmi, C. & Gallegati, M. & Landini, S. & Stiglitz, J.E., 2020. "An analytical solution for network models with heterogeneous and interacting agents," Journal of Economic Behavior & Organization, Elsevier, vol. 171(C), pages 189-220.

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    More about this item

    Keywords

    Economic crisis; Credit network; Leverage; Heterogeneity; Agent based model;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • G01 - Financial Economics - - General - - - Financial Crises

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