IDEAS home Printed from https://ideas.repec.org/a/spr/joevec/v29y2019i1d10.1007_s00191-018-0553-9.html
   My bibliography  Save this article

Demand, credit and macroeconomic dynamics. A micro simulation model

Author

Listed:
  • Huub Meijers

    (Maastricht University)

  • Önder Nomaler

    (Eindhoven University of Technology)

  • Bart Verspagen

    (UNU-MERIT and Maastricht University)

Abstract

We develop a micro simulation model for the macroeconomic business cycle. Our model is based on three main ideas. First, we want to specify how macroeconomic coordination is achieved without a dominating influence of price mechanisms. Second, we want to incorporate the stock-flow-consistent (SFC) approach that has become popular in post-Keynesian macroeconomics. Existing macroeconomic models often pay no attention to how short-run outcomes (in the form of surpluses or deficits on the account balances of individual agents, or groups of agents) accumulate into long-run debt. The SFC approach models such deficits and surpluses, and their accumulation, explicitly, and imposes a logic in which these long-run balances co-determine the macroeconomic coordination outcome. Third, we want to allow for bankruptcies as a major mechanism in the business cycle. In reality, bankruptcies are a way in which long-run balances get adjusted, but most often the SFC models do not allow bankruptcies as a way in which long-run balances adjust. In our model, bankruptcies arise because agents do not adapt their behavior quickly enough as debt, or assets, accumulate. This is parametrized, so that bankruptcies can disappear in the simulation runs, which enables us to compare the nature of business cycles with and without bankruptcies. Our results show a clear business cycle that is driven by accumulation of financial assets and the effects this has on the real economy. By changing some of the key parameters, we show how the nature of the business cycle changes as a result of changes in the assumed behavior of agents.

Suggested Citation

  • Huub Meijers & Önder Nomaler & Bart Verspagen, 2019. "Demand, credit and macroeconomic dynamics. A micro simulation model," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 337-364, March.
  • Handle: RePEc:spr:joevec:v:29:y:2019:i:1:d:10.1007_s00191-018-0553-9
    DOI: 10.1007/s00191-018-0553-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00191-018-0553-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00191-018-0553-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. George A. Akerlof, 2009. "How Human Psychology Drives the Economy and Why It Matters," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(5), pages 1175-1175.
    2. Pasinetti,Luigi L., 2007. "Keynes and the Cambridge Keynesians," Cambridge Books, Cambridge University Press, number 9780521872270, October.
    3. 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.
    4. Dosi, Giovanni & Fagiolo, Giorgio & Roventini, Andrea, 2010. "Schumpeter meeting Keynes: A policy-friendly model of endogenous growth and business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1748-1767, September.
    5. Silverberg, Gerald & Verspagen, Bart, 1994. "Collective Learning, Innovation and Growth in a Boundedly Rational, Evolutionary World," Journal of Evolutionary Economics, Springer, vol. 4(3), pages 207-226, September.
    6. 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.
    7. Rafael Di Tella & Huw Pill & Ingrid Vogel, 2005. "Institutions, Macroeconomics, and the Global Economy:(Casebook)," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 5830, February.
    8. Caiani, Alessandro & Godin, Antoine & Caverzasi, Eugenio & Gallegati, Mauro & Kinsella, Stephen & Stiglitz, Joseph E., 2016. "Agent based-stock flow consistent macroeconomics: Towards a benchmark model," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 375-408.
    9. 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.
    10. Robert R. Keller, 1983. "Keynesian and Institutional Economics: Compatibility and Complementarity?," Journal of Economic Issues, Taylor & Francis Journals, vol. 17(4), pages 1087-1095, December.
    11. 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.
    12. Claudio H. Dos Santos, 2005. "A stock-flow consistent general framework for formal Minskyan analyses of closed economies," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 27(4), pages 712-735.
    13. Pascal Seppecher & Isabelle Salle, 2015. "Deleveraging crises and deep recessions: a behavioural approach," Applied Economics, Taylor & Francis Journals, vol. 47(34-35), pages 3771-3790, July.
    14. Peter Howitt, 2006. "The Microfoundations of the Keynesian Multiplier Process," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 1(1), pages 33-44, May.
    15. Dawid, H. & Harting, P. & Neugart, M., 2014. "Economic convergence: Policy implications from a heterogeneous agent model," Journal of Economic Dynamics and Control, Elsevier, vol. 44(C), pages 54-80.
    16. C. W. M. Naastepad, 2006. "Technology, demand and distribution: a cumulative growth model with an application to the Dutch productivity growth slowdown," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 30(3), pages 403-434, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nomaler, Önder & Spinola, Danilo & Verspagen, Bart, 2021. "R&D-based economic growth in a supermultiplier model," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 1-19.
    2. Giovanni Dosi & Andrea Roventini, 2019. "More is different ... and complex! the case for agent-based macroeconomics," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 1-37, March.
    3. Alessia Cafferata & Marwil J. Dávila-Fernández & Serena Sordi, 2021. "(Ir)rational explorers in the financial jungle," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1157-1188, September.
    4. Nomaler, Önder & Spinola, Danilo & Verspagen, Bart, 2020. "Schumpeter and Keynes: Economic growth in a super-multiplier model," MERIT Working Papers 2020-049, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).

    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. 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.
    2. repec:hal:spmain:info:hdl:2441/dcditnq6282sbu1u151qe5p7f is not listed on IDEAS
    3. repec:spo:wpmain:info:hdl:2441/dcditnq6282sbu1u151qe5p7f is not listed on IDEAS
    4. 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.
    5. Emanuele Russo, 2021. "Harrodian instability in decentralized economies: an agent-based approach," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(2), pages 539-567, July.
    6. repec:spo:wpmain:info:hdl:2441/5hussro0tc951q0jqpu8quliqu is not listed on IDEAS
    7. repec:hal:spmain:info:hdl:2441/5hussro0tc951q0jqpu8quliqu is not listed on IDEAS
    8. repec:hal:spmain:info:hdl:2441/5bnglqth5987gaq6dhju3psjn3 is not listed on IDEAS
    9. Francesco Lamperti & Antoine Mandel & Mauro Napoletano & Alessandro Sapio & Andrea Roventini & Tomas Balint & Igor Khorenzhenko, 2017. "Taming macroeconomic instability," SciencePo Working papers Main hal-03399574, HAL.
    10. Andrew G. Haldane & Arthur E. Turrell, 2019. "Drawing on different disciplines: macroeconomic agent-based models," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 39-66, March.
    11. repec:spo:wpmain:info:hdl:2441/5bnglqth5987gaq6dhju3psjn3 is not listed on IDEAS
    12. Giovanni Dosi & Andrea Roventini, 2019. "More is different ... and complex! the case for agent-based macroeconomics," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 1-37, March.
    13. Roberto Veneziani & Luca Zamparelli & Corrado Di Guilmi, 2017. "The Agent-Based Approach To Post Keynesian Macro-Modeling," Journal of Economic Surveys, Wiley Blackwell, vol. 31(5), pages 1183-1203, December.
    14. Laura Carvalho & Corrado Di Guilmi, 2020. "Technological unemployment and income inequality: a stock-flow consistent agent-based approach," Journal of Evolutionary Economics, Springer, vol. 30(1), pages 39-73, January.
    15. Roberto Veneziani & Luca Zamparelli & Michalis Nikiforos & Gennaro Zezza, 2017. "Stock-Flow Consistent Macroeconomic Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 31(5), pages 1204-1239, December.
    16. Guerini, Mattia & Napoletano, Mauro & Roventini, Andrea, 2018. "No man is an Island: The impact of heterogeneity and local interactions on macroeconomic dynamics," Economic Modelling, Elsevier, vol. 68(C), pages 82-95.
    17. Alberto Russo, 2017. "An Agent Based Macroeconomic Model with Social Classes and Endogenous Crises," 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 285-306, November.
    18. Dosi, Giovanni & Fagiolo, Giorgio & Napoletano, Mauro & Roventini, Andrea & Treibich, Tania, 2015. "Fiscal and monetary policies in complex evolving economies," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 166-189.
    19. Mauro Napoletano, 2018. "A Short Walk on the Wild Side: Agent-Based Models and their Implications for Macroeconomic Analysis," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(3), pages 257-281.
    20. Luca Riccetti & Alberto Russo & Mauro Gallegati, 2022. "Firm–bank credit network, business cycle and macroprudential policy," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(2), pages 475-499, April.
    21. Ítalo Pedrosa & Dany Lang, 2018. "Heterogeneity, distribution and financial fragility of non-financial firms: an agent-based stock-flow consistent (AB-SFC) model," Working Papers hal-01937186, HAL.
    22. 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).
    23. Teglio, Andrea & Mazzocchetti, Andrea & Ponta, Linda & Raberto, Marco & Cincotti, Silvano, 2019. "Budgetary rigour with stimulus in lean times: Policy advices from an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 59-83.
    24. Marco Raberto & Bulent Ozel & Linda Ponta & Andrea Teglio & Silvano Cincotti, 2019. "From financial instability to green finance: the role of banking and credit market regulation in the Eurace model," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 429-465, March.
    25. Adrian Carro & Marc Hinterschweiger & Arzu Uluc & J Doyne Farmer, 2023. "Heterogeneous effects and spillovers of macroprudential policy in an agent-based model of the UK housing market," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 32(2), pages 386-432.
    26. Popoyan, Lilit & Napoletano, Mauro & Roventini, Andrea, 2020. "Winter is possibly not coming: Mitigating financial instability in an agent-based model with interbank market," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).

    More about this item

    Keywords

    stock-flow; consistent; macroeconomic models; agent-based macroeconomic models;
    All these keywords.

    JEL classification:

    • E00 - Macroeconomics and Monetary Economics - - General - - - General
    • E12 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Keynes; Keynesian; Post-Keynesian; Modern Monetary Theory
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • B52 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Historical; Institutional; Evolutionary; Modern Monetary Theory;

    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:spr:joevec:v:29:y:2019:i:1:d:10.1007_s00191-018-0553-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.