IDEAS home Printed from https://ideas.repec.org/a/pal/easeco/v48y2022i4d10.1057_s41302-022-00221-2.html
   My bibliography  Save this article

An Agent-Based Macroeconomic Model with Endogenous Intertemporal Decision Rules

Author

Listed:
  • Adalbert Mayer

    (Washington College)

Abstract

This paper uses an evolutionary algorithm to create endogenous intertemporal decision rules in an agent-based macroeconomic model. This approach addresses the Lucas critique in an agent-based model and links agent-based macroeconomic modeling to the standard DSGE framework. It can replicate the intertemporal decision rules given by the rational expectations solution to a representative agent growth model; at the same time, it is possible to model alternative information sets used to form the intertemporal decision rules. The dynamics in response to shocks depend in a non-trivial way on the interplay of expectations formation and the microstructure of the interaction between individual agents.

Suggested Citation

  • Adalbert Mayer, 2022. "An Agent-Based Macroeconomic Model with Endogenous Intertemporal Decision Rules," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 48(4), pages 548-579, October.
  • Handle: RePEc:pal:easeco:v:48:y:2022:i:4:d:10.1057_s41302-022-00221-2
    DOI: 10.1057/s41302-022-00221-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41302-022-00221-2
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41302-022-00221-2?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Edoardo Gaffeo & Domenico Delli Gatti & Saul Desiderio & Mauro Gallegati, 2008. "Adaptive Microfoundations for Emergent Macroeconomics," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 34(4), pages 441-463.
    2. Duffy, John & McNelis, Paul D., 2001. "Approximating and simulating the stochastic growth model: Parameterized expectations, neural networks, and the genetic algorithm," Journal of Economic Dynamics and Control, Elsevier, vol. 25(9), pages 1273-1303, September.
    3. Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Joseph E. Stiglitz & Tania Treibich, 2020. "Rational Heuristics? Expectations And Behaviors In Evolving Economies With Heterogeneous Interacting Agents," Economic Inquiry, Western Economic Association International, vol. 58(3), pages 1487-1516, July.
    4. Pascal Seppecher & Isabelle L Salle & Marc Lavoie, 2018. "What drives markups? Evolutionary pricing in an agent-based stock-flow consistent macroeconomic model," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 27(6), pages 1045-1067.
    5. Ashraf, Quamrul & Gershman, Boris & Howitt, Peter, 2016. "How Inflation Affects Macroeconomic Performance: An Agent-Based Computational Investigation," Macroeconomic Dynamics, Cambridge University Press, vol. 20(2), pages 558-581, March.
    6. Bullard, James & Duffy, John, 1999. "Using Genetic Algorithms to Model the Evolution of Heterogeneous Beliefs," Computational Economics, Springer;Society for Computational Economics, vol. 13(1), pages 41-60, February.
    7. Seppecher, Pascal, 2012. "Flexibility Of Wages And Macroeconomic Instability In An Agent-Based Computational Model With Endogenous Money," Macroeconomic Dynamics, Cambridge University Press, vol. 16(S2), pages 284-297, September.
    8. Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
    9. Pascal Seppecher & Isabelle Salle & Dany Lang, 2019. "Is the market really a good teacher?," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 299-335, March.
    10. 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.
    11. S. Sirakaya & Stephen Turnovsky & M. Alemdar, 2006. "Feedback Approximation of the Stochastic Growth Model by Genetic Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 185-206, May.
    12. Armen A. Alchian, 1950. "Uncertainty, Evolution, and Economic Theory," Journal of Political Economy, University of Chicago Press, vol. 58, pages 211-211.
    13. Alan Kirman, 2014. "Is it rational to have rational expectations?," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 13(1), pages 29-48, June.
    14. Kirman, Alan, 2016. "Ants And Nonoptimal Self-Organization: Lessons For Macroeconomics," Macroeconomic Dynamics, Cambridge University Press, vol. 20(2), pages 601-621, March.
    15. 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.
    16. Arifovic, Jasmina, 2000. "Evolutionary Algorithms In Macroeconomic Models," Macroeconomic Dynamics, Cambridge University Press, vol. 4(3), pages 373-414, September.
    17. Lengnick, Matthias, 2013. "Agent-based macroeconomics: A baseline model," Journal of Economic Behavior & Organization, Elsevier, vol. 86(C), pages 102-120.
    18. Bullard, James & Duffy, John, 1998. "A model of learning and emulation with artificial adaptive agents," Journal of Economic Dynamics and Control, Elsevier, vol. 22(2), pages 179-207, February.
    19. 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.
    20. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
    21. Alan Kirman, 2006. "Demand Theory and General Equilibrium: From Explanation to Introspection, a Journey down the Wrong Road," History of Political Economy, Duke University Press, vol. 38(5), pages 246-280, Supplemen.
    22. Svensson, Lars E O, 1985. "Money and Asset Prices in a Cash-in-Advance Economy," Journal of Political Economy, University of Chicago Press, vol. 93(5), pages 919-944, October.
    23. Cars Hommes, 2021. "Behavioral and Experimental Macroeconomics and Policy Analysis: A Complex Systems Approach," Journal of Economic Literature, American Economic Association, vol. 59(1), pages 149-219, March.
    24. Tesfatsion, Leigh, 2006. "Agent-Based Computational Modeling and Macroeconomics," ISU General Staff Papers 200601010800001585, Iowa State University, Department of Economics.
    25. Arifovic, Jasmina, 1995. "Genetic algorithms and inflationary economies," Journal of Monetary Economics, Elsevier, vol. 36(1), pages 219-243, August.
    26. Ljungqvist, Lars & Sargent, Thomas J., 2012. "Recursive Macroeconomic Theory, Third Edition," MIT Press Books, The MIT Press, edition 3, volume 1, number 0262018748, December.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. 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.
    3. Isabelle Salle & Marc-Alexandre Sénégas & Murat Yıldızoğlu, 2019. "How transparent about its inflation target should a central bank be?," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 391-427, March.
    4. Severin Reissl, 2021. "Heterogeneous expectations, forecasting behaviour and policy experiments in a hybrid Agent-based Stock-flow-consistent model," Journal of Evolutionary Economics, Springer, vol. 31(1), pages 251-299, January.
    5. 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.
    6. Váry, Miklós, 2021. "The long-run real effects of monetary shocks: Lessons from a hybrid post-Keynesian-DSGE-agent-based menu cost model," Economic Modelling, Elsevier, vol. 105(C).
    7. Elena Deryugina & Alexey Ponomarenko, 2021. "Explaining the lead–lag pattern in the money–inflation relationship: a microsimulation approach," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1113-1128, September.
    8. Pascal Seppecher & Isabelle Salle & Dany Lang, 2019. "Is the market really a good teacher?," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 299-335, March.
    9. Caleb Stroup, 2017. "International Deal Experience And Cross-Border Acquisitions," Economic Inquiry, Western Economic Association International, vol. 55(1), pages 73-97, January.
    10. 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 (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 7, pages 1-44.
    11. Silvano Cincotti & Marco Raberto & Andrea Teglio, 2022. "Why do we need agent-based macroeconomics?," Review of Evolutionary Political Economy, Springer, vol. 3(1), pages 5-29, April.
    12. Pascal Seppecher & Isabelle L Salle & Marc Lavoie, 2018. "What drives markups? Evolutionary pricing in an agent-based stock-flow consistent macroeconomic model," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 27(6), pages 1045-1067.
    13. Eugenio Caverzasi & Alberto Russo, 2018. "Toward a new microfounded macroeconomics in the wake of the crisis," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 27(6), pages 999-1014.
    14. Bernardo A. Furtado & Miguel A. Fuentes & Claudio J. Tessone, 2019. "Policy Modeling and Applications: State-of-the-Art and Perspectives," Complexity, Hindawi, vol. 2019, pages 1-11, February.
    15. Rengs, Bernhard & Scholz-Waeckerle, Manuel, 2017. "Consumption & Class in Evolutionary Macroeconomics," MPRA Paper 80021, University Library of Munich, Germany.
    16. Lamperti, F. & Dosi, G. & Napoletano, M. & Roventini, A. & Sapio, A., 2018. "Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-based Integrated Assessment Model," Ecological Economics, Elsevier, vol. 150(C), pages 315-339.
    17. 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.
    18. 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.
    19. Shu-Heng Chen & Chia-Hsuan Yeh, 1999. "Evolving Traders and the Faculty of the Business School: A New Architecture of the Artificial Stock Market," Computing in Economics and Finance 1999 613, Society for Computational Economics.
    20. Isabelle Salle & Pascal Seppecher, 2017. "Stabilizing an Unstable Complex Economy," CEPN Working Papers hal-01527740, HAL.

    More about this item

    Keywords

    Agent-based macroeconomics; Evolutionary algorithm; Expectations formation;
    All these keywords.

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

    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:pal:easeco:v:48:y:2022:i:4:d:10.1057_s41302-022-00221-2. 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.palgrave-journals.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.