IDEAS home Printed from https://ideas.repec.org/p/ags/iamodp/109915.html
   My bibliography  Save this paper

The Spatial Agent-based Competition Model (SpAbCoM)

Author

Listed:
  • Graubner, Marten

Abstract

The paper presents a detailed documentation of the underlying concepts and methods of the Spatial Agent-based Competition Model (SpAbCoM). For instance, SpAbCoM is used to study firms’ choices of spatial pricing policy (GRAUBNER et al., 2011a) or pricing and location under a framework of multi-firm spatial competition and two-dimensional markets (GRAUBNER et al., 2011b). While the simulation model is briefly introduced by means of relevant examples within the corresponding papers, the present paper serves two objectives. First, it presents a detailed discussion of the computational concepts that are used, particularly with respect to genetic algorithms (GAs). Second, it documents SpAbCoM and provides an overview of the structure of the simulation model and its dynamics. Das vorliegende Papier dokumentiert die zugrundeliegenden Konzepte und Methoden des Räumlichen Agenten-basierten Wettbewerbsmodells (Spatial Agent-based Competition Model)SpAbCoM. Anwendungsbeispiele dieses Simulationsmodells untersuchen die Entscheidung bezüglich der räumlichen Preisstrategie von Unternehmen (GRAUBNER et al., 2011a) oder Preissetzung und Standortwahl im Rahmen eines räumlichen Wettbewerbsmodells, welches mehr als einen Wettbewerber und zweidimensionalen Marktgebiete berücksichtigt. Während das Simulationsmodell in den jeweiligen Arbeiten kurz anhand eines Beispiels eingeführt wird, dient das vorliegende Papier zwei Zielen. Zum Einen sollen die verwendeten computergestützten Konzepte, hier speziell Genetische Algorithmen (GA), detailliert vorgestellt werden. Zum Anderen besteht die Absicht dieser Dokumentation darin, einen Überblick über die Struktur von SpAbCoM und die während einer Simulation ablaufenden Prozesse zu gegeben.

Suggested Citation

  • Graubner, Marten, 2011. "The Spatial Agent-based Competition Model (SpAbCoM)," IAMO Discussion Papers 109915, Institute of Agricultural Development in Transition Economies (IAMO).
    • Handle: RePEc:ags:iamodp:109915
    DOI: 10.22004/ag.econ.109915
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/109915/files/DP135_Graubner-1a.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.109915?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
    ---><---

    References listed on IDEAS

    as
    1. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, April.
    2. Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
    3. Haruvy, Ernan & Roth, Alvin E. & Unver, M. Utku, 2006. "The dynamics of law clerk matching: An experimental and computational investigation of proposals for reform of the market," Journal of Economic Dynamics and Control, Elsevier, vol. 30(3), pages 457-486, March.
    4. Michael Kopel & Herbert Dawid, 1998. "On economic applications of the genetic algorithm: a model of the cobweb type," Journal of Evolutionary Economics, Springer, vol. 8(3), pages 297-315.
    5. 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.
    6. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    7. Riechmann, Thomas, 2001. "Genetic algorithm learning and evolutionary games," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 1019-1037, June.
    8. Vriend, Nicolaas J., 2000. "An illustration of the essential difference between individual and social learning, and its consequences for computational analyses," Journal of Economic Dynamics and Control, Elsevier, vol. 24(1), pages 1-19, January.
    9. Alemdar, Nedim M. & Sirakaya, Sibel, 2003. "On-line computation of Stackelberg equilibria with synchronous parallel genetic algorithms," Journal of Economic Dynamics and Control, Elsevier, vol. 27(8), pages 1503-1515, June.
    10. Jasmina Arifovic & John Ledyard, 2004. "Scaling Up Learning Models in Public Good Games," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 6(2), pages 203-238, May.
    11. Marten Graubner & Alfons Balmann & Richard J. Sexton, 2011. "Spatial Price Discrimination in Agricultural Product Procurement Markets: A Computational Economics Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(4), pages 949-967.
    12. 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.
    13. Tony Curson Price, 1997. "Using co-evolutionary programming to simulate strategic behaviour in markets," Levine's Working Paper Archive 588, David K. Levine.
    14. 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.
    15. Tony Curzon Price, 1997. "Using co-evolutionary programming to simulate strategic behaviour in markets," Journal of Evolutionary Economics, Springer, vol. 7(3), pages 219-254.
    16. Thomas Riechmann, 1999. "Learning and behavioral stability An economic interpretation of genetic algorithms," Journal of Evolutionary Economics, Springer, vol. 9(2), pages 225-242.
    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. repec:zbw:iamodp:109915 is not listed on IDEAS
    2. 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).
    3. Graubner, Marten & Sexton, Richard J., 2021. "Spatial competition in agricultural procurement markets," 2021 Annual Meeting, August 1-3, Austin, Texas 313962, Agricultural and Applied Economics Association.
    4. Ludo Waltman & Nees Eck & Rommert Dekker & Uzay Kaymak, 2011. "Economic modeling using evolutionary algorithms: the effect of a binary encoding of strategies," Journal of Evolutionary Economics, Springer, vol. 21(5), pages 737-756, December.
    5. Duffy, John, 2006. "Agent-Based Models and Human Subject Experiments," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 19, pages 949-1011, Elsevier.
    6. 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.
    7. 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.
    8. Mattheos Protopapas & Francesco Battaglia & Elias Kosmatopoulo, 2008. "Coevolutionary Genetic Algorithms for Establishing Nash Equilibrium in Symmetric Cournot Games," Working Papers 004, COMISEF.
    9. Graubner, Marten & Sexton, Richard J., 2023. "More competitive than you think? Pricing and location of processing firms in agricultural markets," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 105(3), pages 784-808.
    10. Vinícius Ferraz & Thomas Pitz, 2024. "Analyzing the Impact of Strategic Behavior in an Evolutionary Learning Model Using a Genetic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 437-475, February.
    11. Marten Graubner & Richard J. Sexton, 2023. "More competitive than you think? Pricing and location of processing firms in agricultural markets," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(3), pages 784-808, May.
    12. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.
    13. Shu-Heng Chen & Chung-Ching Tai, 2006. "Republication: On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(4), pages 313-331, November.
    14. Sylvie Geisendorf, 2011. "Internal selection and market selection in economic Genetic Algorithms," Journal of Evolutionary Economics, Springer, vol. 21(5), pages 817-841, December.
    15. Weidlich, Anke & Veit, Daniel, 2008. "A critical survey of agent-based wholesale electricity market models," Energy Economics, Elsevier, vol. 30(4), pages 1728-1759, July.
    16. 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.
    17. Hommes, Cars & Lux, Thomas, 2013. "Individual Expectations And Aggregate Behavior In Learning-To-Forecast Experiments," Macroeconomic Dynamics, Cambridge University Press, vol. 17(2), pages 373-401, March.
    18. 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).
    19. Mikhail Anufriev & Jasmina Arifovic & John Ledyard & Valentyn Panchenko, 2013. "Efficiency of continuous double auctions under individual evolutionary learning with full or limited information," Journal of Evolutionary Economics, Springer, vol. 23(3), pages 539-573, July.
    20. Renaud Bourlès & Juliette Rouchier, 2012. "Evolving Informal Risk-Sharing Cooperatives and Other-Regarding Preferences," Working Papers halshs-00793706, HAL.
    21. Victorien Barbet & Renaud Bourlès & Juliette Rouchier, 2020. "Informal risk-sharing cooperatives: the effect of learning and other-regarding preferences," Journal of Evolutionary Economics, Springer, vol. 30(2), pages 451-478, April.

    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:ags:iamodp:109915. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/iamoode.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.