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Novel Modelling of the Operation of the Financial Intermediary System – Agent-based Macro Models

Author

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  • Bence Mérõ

    (Magyar Nemzeti Bank)

Abstract

The study describes three agent-based macro models – expanded with the banking sector – that may later, following adequate further development, serve as bases for regulatory decisions. By presenting and explaining these models, the author attempts to make the readers understand the nature, essence and framework of agent-based modelling, also highlighting the difficulties that arise during modelling.

Suggested Citation

  • Bence Mérõ, 2019. "Novel Modelling of the Operation of the Financial Intermediary System – Agent-based Macro Models," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 18(3), pages 83-113.
    • Handle: RePEc:mnb:finrev:v:18:y:2019:i:3:p:83-113
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    File URL: http://en-hitelintezetiszemle.mnb.hu/letoltes/fer-18-3-st4-mero.pdf
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    References listed on IDEAS

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    1. Popoyan, Lilit & Napoletano, Mauro & Roventini, Andrea, 2017. "Taming macroeconomic instability: Monetary and macro-prudential policy interactions in an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 117-140.
    2. Francesco Lamperti & Antoine Mandel & Mauro Napoletano & Alessandro Sapio & Andrea Roventini & Tomas Balint & Igor Khorenzhenko, 2017. "Taming macroeconomic instability," PSE-Ecole d'économie de Paris (Postprint) hal-03399574, HAL.
    3. A G Haldane & A E Turrell, 2018. "An interdisciplinary model for macroeconomics," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 34(1-2), pages 219-251.
    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. Holcombe, Mike & Coakley, Simon & Kiran, Mariam & Chin, Shawn & Greenough, Chris & Worth, David & Cincotti, Silvano & Raberto, M. & Teglio, Andrea & Deissenberg, Christophe & Hoog, Sander van der & Da, 2013. "Large-Scale Modeling of Economic Systems," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 62347, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    6. Cúrdia, Vasco & Woodford, Michael, 2016. "Credit Frictions and Optimal Monetary Policy," Journal of Monetary Economics, Elsevier, vol. 84(C), pages 30-65.
    7. Schüler, Yves Stephan & Hiebert, Paul P. & Peltonen, Tuomas A., 2015. "Characterising the financial cycle: A multivariate and time-varying approach," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112985, Verein für Socialpolitik / German Economic Association.
    8. Riccetti, Luca & Russo, Alberto & Gallegati, Mauro, 2016. "Stock market dynamics, leveraged network-based financial accelerator and monetary policy," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 509-524.
    9. Grazzini, Jakob & Richiardi, Matteo G. & Tsionas, Mike, 2017. "Bayesian estimation of agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 26-47.
    10. Stolzenburg, Ulrich, 2015. "The agent-based Solow growth model with endogenous business cycles," Economics Working Papers 2015-01, Christian-Albrechts-University of Kiel, Department of Economics.
    11. Erlingsson, Einar Jon & Teglio, Andrea & Cincotti, Silvano & Stefansson, Hlynur & Sturlusson, Jon Thor & Raberto, Marco, 2014. "Housing market bubbles and business cycles in an agent-based credit economy," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 8, pages 1-42.
    12. Mr. Jaromir Benes & Mr. Michael Kumhof & Mr. Douglas Laxton, 2014. "Financial Crises in DSGE Models: A Prototype Model," IMF Working Papers 2014/057, International Monetary Fund.
    13. Riccetti, Luca & Russo, Alberto & Gallegati, Mauro, 2013. "Leveraged network-based financial accelerator," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1626-1640.
    14. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    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 (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-49.
    16. J. Doyne Farmer & Duncan Foley, 2009. "The economy needs agent-based modelling," Nature, Nature, vol. 460(7256), pages 685-686, August.
    17. Christophe Deissenberg & Sander van Der Hoog & Herbert Dawid, 2008. "EURACE: A Massively Parallel Agent-Based Model of the European Economy," Working Papers halshs-00339756, HAL.
    18. Horst Hanusch & Andreas Pyka (ed.), 2007. "Elgar Companion to Neo-Schumpeterian Economics," Books, Edward Elgar Publishing, number 2973.
    19. Lawrence J. Christiano & Roberto Motto & Massimo Rostagno, 2014. "Risk Shocks," American Economic Review, American Economic Association, vol. 104(1), pages 27-65, January.
    20. Salle, Isabelle L., 2015. "Modeling expectations in agent-based models — An application to central bank's communication and monetary policy," Economic Modelling, Elsevier, vol. 46(C), pages 130-141.
    21. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    22. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
    23. Joseph E. Stiglitz, 2011. "Rethinking Macroeconomics: What Failed, And How To Repair It," Journal of the European Economic Association, European Economic Association, vol. 9(4), pages 591-645, August.
    24. Baptista, Rafa & Farmer, J. Doyne & Hinterschweiger, Marc & Low, Katie & Tang, Daniel & Uluc, Arzu, 2016. "Macroprudential policy in an agent-based model of the UK housing market," Bank of England working papers 619, Bank of England.
    25. Gertler, Mark & Karadi, Peter, 2011. "A model of unconventional monetary policy," Journal of Monetary Economics, Elsevier, vol. 58(1), pages 17-34, January.
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    More about this item

    Keywords

    agent-based modelling; banking sector; money creation;
    All these keywords.

    JEL classification:

    • B52 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Historical; Institutional; Evolutionary; Modern Monetary Theory;
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • Y2 - Miscellaneous Categories - - Introductions and Prefaces

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