IDEAS home Printed from https://ideas.repec.org/p/rye/wpaper/wp012.html
   My bibliography  Save this paper

Evolution of the Week

Author

Listed:
  • Amy Peng

    (Department of Economics, Ryerson University, Toronto, Canada)

  • Francis McKenna

    (Ontario Ministry of Finance, Toronto, Canada)

Abstract

The purpose of this paper is to provide an intuitive explanation of the emergence and evolution of the week based on a historical precedent draw from ancient Egypt. In this paper, we view the week as a coordinating social institution that was created to resolve a fundamental problem of society - coordinating market exchange. Artificial adaptive agents are used to simulate the interactions among farmers going to market. The results show that the length of the week that emerges depends on the chosen cost and benefit specifications and random interactions.

Suggested Citation

  • Amy Peng & Francis McKenna, 2009. "Evolution of the Week," Working Papers 012, Ryerson University, Department of Economics.
    • Handle: RePEc:rye:wpaper:wp012
    as

    Download full text from publisher

    File URL: https://www.arts.ryerson.ca/economics/repec/pdfs/wp012.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Epstein, Joshua M, 2001. "Learning to Be Thoughtless: Social Norms and Individual Computation," Computational Economics, Springer;Society for Computational Economics, vol. 18(1), pages 9-24, August.
    2. Young, H Peyton, 1993. "The Evolution of Conventions," Econometrica, Econometric Society, vol. 61(1), pages 57-84, January.
    3. Arthur, W Brian, 1994. "Inductive Reasoning and Bounded Rationality," American Economic Review, American Economic Association, vol. 84(2), pages 406-411, May.
    4. Holland, John H & Miller, John H, 1991. "Artificial Adaptive Agents in Economic Theory," American Economic Review, American Economic Association, vol. 81(2), pages 365-371, May.
    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. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    2. John Conlisk, 1996. "Why Bounded Rationality?," Journal of Economic Literature, American Economic Association, vol. 34(2), pages 669-700, June.
    3. William Tracy, 2014. "Paradox Lost: The Evolution of Strategies in Selten’s Chain Store Game," Computational Economics, Springer;Society for Computational Economics, vol. 43(1), pages 83-103, January.
    4. Tesfatsion, Leigh, 1998. "Teaching Agent-Based Computational Economics to Graduate Students," ISU General Staff Papers 199807010700001043, Iowa State University, Department of Economics.
    5. Tesfatsion, Leigh, 1995. "How Economists Can Get Alife," Economic Reports 18196, Iowa State University, Department of Economics.
    6. Furtado, Bernardo Alves & Eberhardt, Isaque Daniel Rocha, 2015. "Modelo espacial simples da economia: uma proposta teórico-metodológica [A simple spatial economic model: a proposal]," MPRA Paper 67005, University Library of Munich, Germany.
    7. Fontana, Magda, 2010. "Can neoclassical economics handle complexity? The fallacy of the oil spot dynamic," Journal of Economic Behavior & Organization, Elsevier, vol. 76(3), pages 584-596, December.
    8. Marc Deissenroth & Martin Klein & Kristina Nienhaus & Matthias Reeg, 2017. "Assessing the Plurality of Actors and Policy Interactions: Agent-Based Modelling of Renewable Energy Market Integration," Complexity, Hindawi, vol. 2017, pages 1-24, December.
    9. Olivier Tercieux & Mark Voorneveld, 2010. "The cutting power of preparation," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 71(1), pages 85-101, February.
    10. Magda Fontana, 2010. "The Santa Fe Perspective on economics: emerging patterns in the science of complexity," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 167-196.
    11. Zakaria Babutsidze, 2012. "Consumer Learning through Interaction: Effects on Aggregate Outcomes," Chapters, in: Guido Buenstorf (ed.), Evolution, Organization and Economic Behavior, chapter 4, Edward Elgar Publishing.
    12. Dunia López-Pintado & Duncan J. Watts, 2008. "Social Influence, Binary Decisions and Collective Dynamics," Rationality and Society, , vol. 20(4), pages 399-443, November.
    13. Schunk, Daniel, 2003. "Modeling the Use of Nonrenewable Resources Using a Genetic Algorithm," Sonderforschungsbereich 504 Publications 03-23, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    14. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
    15. Yves Saillard, 2004. "L'analyse économique des normes : représentation et traitement des interactions dans les modèles de simulation," Post-Print halshs-00104866, HAL.
    16. 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.
    17. Mary Burke & Gary Fournier, 2005. "The Emergence of Local Norms in Networks," Computing in Economics and Finance 2005 299, Society for Computational Economics.
    18. Heath, Chip & Ho, Ben & Berger, Jonah, 2006. "Focal points in coordinated divergence," Journal of Economic Psychology, Elsevier, vol. 27(5), pages 635-647, October.
    19. David Chavalarias, 2006. "Metamimetic Games : Modeling Metadynamics in Social Cognition," Post-Print hal-00007743, HAL.
    20. Tercieux, O.R.C. & Voorneveld, M., 2005. "The Cutting Power of Preparation," Other publications TiSEM 75173341-627f-4eb2-91f1-0, Tilburg University, School of Economics and Management.

    More about this item

    Keywords

    social institution; coordination games; agent based models;
    All these keywords.

    JEL classification:

    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact
    • B52 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Historical; Institutional; Evolutionary; Modern Monetary Theory;
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

    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:rye:wpaper:wp012. 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: Doosoo Kim (email available below). General contact details of provider: https://edirc.repec.org/data/deryeca.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.