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Heterogeneous Interacting Agent Models for Understanding Monetary Economies

Author

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  • Joseph E Stiglitz

    (Finance & Economics Department, Graduate School of Business, Columbia University, 7W Uris Hall, New York, NY 10027, USA.)

  • Mauro Gallegati

    (Department of Economics, Università Politecnica delle Marche, Piazzale Martelli 8, Ancona 60121, Italy. E-mails: mauro.gallegati@gmail.com, mauro.gallegati@univpm.it)

Abstract

The representative agent (RA) approach of the mainstream economics allows a rich analysis of intertemporal maximization; but it rules out the possibility of the analysis of complex interactions. It is the latter that are at the root of this and other crises. We argue that the RA approach is simply not up to the task of enhancing our understanding of modern macroeconomies and that the standard cannot provide an adequate framework for understanding the economy even in more normal times.We advocate a bottom-up approach, where high-level (macroeconomic) systems may possess new and different properties than the low-level (microeconomic) systems on which they are based. The heterogeneous agent approach provides an alternative, one which has already proven its metal in helping us understand the interlinkages which helped give rise to the crisis.

Suggested Citation

  • Joseph E Stiglitz & Mauro Gallegati, 2011. "Heterogeneous Interacting Agent Models for Understanding Monetary Economies," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 37(1), pages 6-12.
  • Handle: RePEc:pal:easeco:v:37:y:2011:i:1:p:6-12
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    References listed on IDEAS

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    Cited by:

    1. ARATA Yoshiyuki, 2015. "Endogenous Business Cycles Caused by Nonconvex Costs and Interactions," Discussion papers 15085, Research Institute of Economy, Trade and Industry (RIETI).
    2. Kristoufek, Ladislav & Vošvrda, Miloslav S., 2016. "Herding, minority game, market clearing and efficient markets in a simple spin model framework," FinMaP-Working Papers 68, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    3. Li, Xi Hao, 2013. "Standardization for Agent-based Modeling in Economics," MPRA Paper 47396, University Library of Munich, Germany.
    4. Ricetti, Luca & Russo, Alberto & Gallegati, Mauro, 2013. "Unemployment benefits and financial leverage in an agent based macroeconomic model," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 7, pages 1-44.
    5. repec:eee:dyncon:v:83:y:2017:i:c:p:232-269 is not listed on IDEAS
    6. Rengs, Bernhard & Scholz-Waeckerle, Manuel, 2017. "Consumption & Class in Evolutionary Macroeconomics," MPRA Paper 80021, University Library of Munich, Germany.
    7. Safarzyńska, Karolina & van den Bergh, Jeroen C.J.M., 2017. "Integrated crisis-energy policy: Macro-evolutionary modelling of technology, finance and energy interactions," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 119-137.
    8. Caleb Stroup, 2015. "International Deal Experience and Cross-Border Acquisitions," Working Papers 15-03, Davidson College, Department of Economics.
    9. Juan Manuel Larrosa, 2016. "Agentes computacionales y análisis económico," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 18(34), pages 87-113, January-J.
    10. Rodríguez-Vives, Marta & Giron, Celestino, 2017. "Leverage interactions: a national accounts approach," Statistics Paper Series 19, European Central Bank.
    11. Ioana Maria BUCERZAN, 2015. "The Propagation Of Insolvency Among Business In Romania," EURINT, Centre for European Studies, Alexandru Ioan Cuza University, vol. 2, pages 64-79.
    12. Matteo G. Richiardi, 2015. "The future of agent-based modelling," LABORatorio R. Revelli Working Papers Series 141, LABORatorio R. Revelli, Centre for Employment Studies.
    13. Yuri Biondi & Simone Righi, 2016. "What does the financial market pricing do? A simulation analysis with a view to systemic volatility, exuberance and vagary," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 11(2), pages 175-203, October.
    14. Bernhard Rengs & Manuel Scholz-Wäckerle & Ardjan Gazheli & Miklós Antal & Jeroen van den Bergh, 2015. "Testing innovation, employment and distributional impacts of climate policy packages in a macro-evolutionary systems setting," WWWforEurope Working Papers series 83, WWWforEurope.
    15. Matteo G. Richiardi, 2017. "The Future of Agent-Based Modeling," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(2), pages 271-287, March.
    16. repec:spr:jeicoo:v:12:y:2017:i:2:d:10.1007_s11403-015-0169-1 is not listed on IDEAS
    17. Nadja König & Ingrid Größl, 2014. "Catching up with the Joneses and Borrowing Constraints: An Agent-based Analysis of Household Debt," Macroeconomics and Finance Series 201404, Hamburg University, Department Wirtschaft und Politik.
    18. Yuri Biondi & Feng Zhou, 2017. "Interbank Credit and the Money Manufacturing Process. A Systemic Perspective on Financial Stability," Papers 1702.08774, arXiv.org.
    19. Váry, Miklós, 2015. "Piaci alkalmazkodás ragadós árak mellett - Calvo-típusú ármerevség egy ágensalapú modellben
      [Market adjustment under sticky prices: the price rigidity of a Calvo type in an agent-based model]
      ," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(1), pages 48-77.
    20. repec:dav:wpaper:15-02 is not listed on IDEAS

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