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Agent-based macroeconomics: A baseline model

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  • Lengnick, Matthias

Abstract

This paper develops a baseline agent-based macroeconomic model and contrasts it with the common dynamic stochastic general equilibrium approach. Although simple, the model can reproduce a lot of the stylized facts of business cycles. The author argues that agent-based modeling is an adequate response to the recently expressed criticism of macroeconomic methodology because it allows for aggregate behavior that is more than simply a replication of microeconomic optimization decisions in equilibrium. At the same time it allows for absolutely consistent microfoundations, including the structure and properties of markets. Most importantly, it does not depend on equilibrium assumptions or fictitious auctioneers and does therefore not rule out coordination failures, instability and crisis by definition. A situation that is very close to a general equilibrium can instead be shown to result endogenously from non-rational micro interaction.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Economic Behavior & Organization.

Volume (Year): 86 (2013)
Issue (Month): C ()
Pages: 102-120

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Handle: RePEc:eee:jeborg:v:86:y:2013:i:c:p:102-120

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Web page: http://www.elsevier.com/locate/jebo

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Keywords: Agent-based macroeconomics; Complex adaptive systems; Microfoundations; Emergence; Complexity;

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Citations

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Cited by:
  1. 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, vol. 7(42), pages 1-44.
  2. Giovanni Dosi & Giorgio Fagiolo & Mauro Napoletano & Andrea Roventini, 2014. "Fiscal and Monetary Policies in Complex Evolving Economies," INET Research Notes 40, Institute for New Economic Thinking (INET).
  3. Muliere, Pietro & Suverato, Davide, 2014. "Income and Wealth Distributions in a Population of Heterogeneous Agents," Discussion Papers in Economics 20928, University of Munich, Department of Economics.
  4. Giorgio Fagiolo & Andrea Roventini, 2012. "Macroeconomic Policy in DSGE and Agent-Based Models," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 67-116.
  5. Salle, Isabelle & Yıldızoğlu, Murat & Sénégas, Marc-Alexandre, 2013. "Inflation targeting in a learning economy: An ABM perspective," Economic Modelling, Elsevier, vol. 34(C), pages 114-128.
  6. Isabelle SALLE & Marc-Alexandre SENEGAS & Murat YILDIZOGLU, 2013. "How Transparent About Its Inflation Target Should a Central Bank be? An Agent-Based Model Assessment," Cahiers du GREThA 2013-24, Groupe de Recherche en Economie Théorique et Appliquée.
  7. Patrascu Diana – Ramona, 2013. "The Representative Economic Agent – An Epistemological Approach," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 2, pages 42-46, April.
  8. repec:spo:wpecon:info:hdl:2441/f6h8764enu2lskk9p6go0e900 is not listed on IDEAS
  9. Mellár, Tamás & Hau, Orsolya & Sebestyén, Tamás, 2013. "Láthatóvá tehető-e a láthatatlan kéz? Egy ágensalapú piaci modell tapasztalatai
    [Can the invisible hand be rendered visible? Experiences of an agent-based market model]
    ," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(9), pages 992-1024.
  10. Doshchyn, Artur & Giommetti, Nicola, 2013. "Learning, Expectations, and Endogenous Business Cycles," MPRA Paper 49617, University Library of Munich, Germany.

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