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Heterogeneous Interacting Agent Models for Understanding Monetary Economies

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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.

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  • 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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    Citations

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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. Alan G. Isaac, 2019. "Exploring the Social-Architecture Model," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 45(4), pages 565-589, October.
    5. Otto, Christian & Willner, Sven Norman & Wenz, Leonie & Frieler, Katja & Levermann, Anders, 2017. "Modeling loss-propagation in the global supply network: The dynamic agent-based model acclimate," OSF Preprints 7yyhd, Center for Open Science.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Otto, C. & Willner, S.N. & Wenz, L. & Frieler, K. & Levermann, A., 2017. "Modeling loss-propagation in the global supply network: The dynamic agent-based model acclimate," Journal of Economic Dynamics and Control, Elsevier, vol. 83(C), pages 232-269.
    11. Rengs, Bernhard & Scholz-Waeckerle, Manuel, 2017. "Consumption & Class in Evolutionary Macroeconomics," MPRA Paper 80021, University Library of Munich, Germany.
    12. 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.
    13. Caleb Stroup, 2015. "International Deal Experience and Cross-Border Acquisitions," Working Papers 15-03, Davidson College, Department of Economics.
    14. 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.
    15. Bernhard Rengs & Manuel Scholz-Wäckerle, 2019. "Consumption & class in evolutionary macroeconomics," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 229-263, March.
    16. Yoshiyuki Arata, 2017. "Endogenous business cycles caused by nonconvex costs and interactions," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 367-391, July.
    17. Rengs, Bernhard & Scholz-Wäckerle, Manuel & van den Bergh, Jeroen, 2020. "Evolutionary macroeconomic assessment of employment and innovation impacts of climate policy packages," Journal of Economic Behavior & Organization, Elsevier, vol. 169(C), pages 332-368.
    18. 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.
    19. Rodríguez-Vives, Marta & Giron, Celestino, 2017. "Leverage interactions: a national accounts approach," Statistics Paper Series 19, European Central Bank.
    20. 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, University of Hamburg, Department of Socioeconomics.
    21. 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.
    22. Aydilek, Harun & Aydilek, Asiye, 2020. "Do we really need heterogeneous agent models?," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 147-153.
    23. 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.
    24. Bernhard Rengs & Manuel Scholz-Wäckerle & Ardjan Gazheli & Miklós Antal & Jeroen C.J.M. van den Bergh, 2015. "Testing Innovation, Employment and Distributional Impacts of Climate Policy Packages in a Macro-evolutionary Systems Setting. WWWforEurope Working Paper No. 83," WIFO Studies, WIFO, number 57891.
    25. Shyam Gouri Suresh, 2015. "Rational versus Adaptive Expectations in an Agent-Based Model of a Barter Economy," Working Papers 15-02, Davidson College, Department of Economics.

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