IDEAS home Printed from https://ideas.repec.org/p/has/discpr/1702.html
   My bibliography  Save this paper

Saver types: An evolutionary-adaptive approach

Author

Listed:
  • Gergely Varga

    (Corvinus University of Budapest)

  • Janos Vincze

    (Institute of Economics, Centre for Economic and Regional Studies, Hungarian Academy of Sciences and Corvinus University of Budapest)

Abstract

We set up an agent-based macromodel focusing on consumption-saving without the assumption of utility maximization, but preserving certain "rational" aspects of human choice based on the idea of ecological rationality Todd et al. (2012). In this framework we address the classical problem of the efficiency of long-run capital accumulation. Three qualitatively different saving strategies are defined: 1. buffer stock saving (prudent and forward looking), 2. permanent income saving (forward looking without prudence), and 3. myopic saving (caring only about immediate consumption, and saving accidentally). In the model these types (that have subtypes depending on continuous parameters) may coexist, and we explore their respective survival chances by conducting simulations. It is found that prudent saving behavior becomes prevalent when the selection pressure is very high, but an economy comprising only prudent households tends to accumulate capital in excess of what is implied by the Golden Rule. As selecion pressure is reduced, myopic consumers appear, and under very low selection pressure the distribution of the main saver types becomes almost random. A seemingly puzzling fact emerges: the economy gets close to the Golden Rule of capital accumulation via endogenous selection of subtypes in a way that can be interpreted as "perverse exploitation", i.e. the exploitation of the rich by the poor. In other words, lowering the intensity of evolutionary forces, that results in more diversity in saver types, may be socially beneficial. Crickets may be useful for society as a whole, including prudent and cautious ants.

Suggested Citation

  • Gergely Varga & Janos Vincze, 2017. "Saver types: An evolutionary-adaptive approach," CERS-IE WORKING PAPERS 1702, Institute of Economics, Centre for Economic and Regional Studies.
  • Handle: RePEc:has:discpr:1702
    as

    Download full text from publisher

    File URL: http://econ.core.hu/file/download/mtdp/MTDP1702.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andrew B. Abel & N. Gregory Mankiw & Lawrence H. Summers & Richard J. Zeckhauser, 1989. "Assessing Dynamic Efficiency: Theory and Evidence," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 56(1), pages 1-19.
    2. S. Rao Aiyagari, 1994. "Uninsured Idiosyncratic Risk and Aggregate Saving," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 109(3), pages 659-684.
    3. Christopher D. Carroll, 1991. "Buffer stock saving and the permanent income hypothesis," Working Paper Series / Economic Activity Section 114, Board of Governors of the Federal Reserve System (U.S.).
    4. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    5. Tesfatsion, Leigh, 2006. "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 16, pages 831-880, Elsevier.
    6. Brenner, Thomas, 2006. "Agent Learning Representation: Advice on Modelling Economic Learning," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 18, pages 895-947, Elsevier.
    7. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    8. Olivier Jean Blanchard & Stanley Fischer, 1989. "Lectures on Macroeconomics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262022834, April.
    9. George A. Akerlof & Robert J. Shiller, 2010. "Animal Spirits: How Human Psychology Drives the Economy, and Why It Matters for Global Capitalism," Economics Books, Princeton University Press, edition 1, number 9163.
    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. Vincze, János & Varga, Gergely, 2016. "Megtakarítási típusok - egy adaptív-evolúciós megközelítés [Types of saving - an adaptive-evolutionary approach]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(2), pages 162-187.
    2. Lovric, M. & Kaymak, U. & Spronk, J., 2008. "A Conceptual Model of Investor Behavior," ERIM Report Series Research in Management ERS-2008-030-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. repec:zbw:iamodp:109915 is not listed on IDEAS
    4. Coronese, Matteo & Occelli, Martina & Lamperti, Francesco & Roventini, Andrea, 2023. "AgriLOVE: Agriculture, land-use and technical change in an evolutionary, agent-based model," Ecological Economics, Elsevier, vol. 208(C).
    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. Graubner, Marten, 2011. "The Spatial Agent-based Competition Model (SpAbCoM)," IAMO Discussion Papers 109915, Institute of Agricultural Development in Transition Economies (IAMO).
    7. Graupner, Marten, 2011. "The Spatial Agent-based Competition Model (SpAbCoM) [Das räumliche agenten-basierte Wettbewerbsmodell SpAbCoM]," IAMO Discussion Papers 135, Leibniz Institute of Agricultural Development in Transition Economies (IAMO).
    8. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
    9. Schuster, Stephan, 2012. "Applications in Agent-Based Computational Economics," MPRA Paper 47201, University Library of Munich, Germany.
    10. Delli Gatti,Domenico & Fagiolo,Giorgio & Gallegati,Mauro & Richiardi,Matteo & Russo,Alberto (ed.), 2018. "Agent-Based Models in Economics," Cambridge Books, Cambridge University Press, number 9781108400046, October.
    11. Waltman, L. & van Eck, N.J.P., 2009. "A Mathematical Analysis of the Long-run Behavior of Genetic Algorithms for Social Modeling," ERIM Report Series Research in Management ERS-2009-011-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    12. Robert Somogyi & Janos Vincze, 2011. "Price Rigidity and Strategic Uncertainty An Agent-based Approach," CERS-IE WORKING PAPERS 1135, Institute of Economics, Centre for Economic and Regional Studies.
    13. Rubén Fuentes-Fernández & Samer Hassan & Juan Pavón & José M. Galán & Adolfo López-Paredes, 2012. "Metamodels for role-driven agent-based modelling," Computational and Mathematical Organization Theory, Springer, vol. 18(1), pages 91-112, March.
    14. Paul De Grauwe, 2012. "Lectures on Behavioral Macroeconomics," Economics Books, Princeton University Press, edition 1, volume 1, number 9891.
    15. Klaus Jaffe, 2015. "Agent based simulations visualize Adam Smith's invisible hand by solving Friedrich Hayek's Economic Calculus," Papers 1509.04264, arXiv.org, revised Nov 2015.
    16. Francesco Lamperti & Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Alessandro Sapio, 2018. "And then he wasn't a she : Climate change and green transitions in an agent-based integrated assessment model," Working Papers hal-03443464, HAL.
    17. Zhang, Hui & Cao, Libin & Zhang, Bing, 2017. "Emissions trading and technology adoption: An adaptive agent-based analysis of thermal power plants in China," Resources, Conservation & Recycling, Elsevier, vol. 121(C), pages 23-32.
    18. 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.
    19. Richard Holt & J. Barkley Rosser & David Colander, 2011. "The Complexity Era in Economics," Review of Political Economy, Taylor & Francis Journals, vol. 23(3), pages 357-369.
    20. Fenintsoa Andriamasinoro & Raphael Danino-Perraud, 2021. "Use of artificial intelligence to assess mineral substance criticality in the French market: the example of cobalt," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 34(1), pages 19-37, April.
    21. Sensfuß, Frank & Ragwitz, Mario & Genoese, Massimo & Möst, Dominik, 2007. "Agent-based simulation of electricity markets: a literature review," Working Papers "Sustainability and Innovation" S5/2007, Fraunhofer Institute for Systems and Innovation Research (ISI).

    More about this item

    Keywords

    agent-based macromodel; bounded rationality; evolutionary learning; savings types;
    All these keywords.

    JEL classification:

    • C69 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Other
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:has:discpr:1702. 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: Nora Horvath (email available below). General contact details of provider: https://edirc.repec.org/data/iehashu.html .

    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.