IDEAS home Printed from https://ideas.repec.org/p/isu/genres/2049.html
   My bibliography  Save this paper

A Computational Laboratory for Evolutionary Trade Networks

Author

Listed:
  • McFadzean, David
  • Stewart, Deron
  • Tesfatsion, Leigh S.

Abstract

This report presents, motivates, and illustrates the use of a computational laboratory for the investigation of evolutionary trade network formation among strategically interacting buyers, sellers, and dealers. The computational laboratory, referred to as the Trade Network Game Laboratory (TNG Lab), is targeted for the Microsoft Windows desktop. The TNG Lab is both modular and extensible and has a clear, easily operated graphical user interface. It permits visualization of the formation and evolution of trade networks by means of run-time animations. Data tables and charts reporting descriptive performance statistics are also provided in real time. The capabilities of the TNG Lab are demonstrated by means of labor market experiments. An automatic installation program for the TNG Lab is available online, as well as TNG Lab tutorials. TNG downloads, tutorials, and research articles can be accessed at: http://www2.econ.iastate.edu/tesfatsi/TNGHome.htm

Suggested Citation

  • McFadzean, David & Stewart, Deron & Tesfatsion, Leigh S., 2001. "A Computational Laboratory for Evolutionary Trade Networks," Staff General Research Papers Archive 2049, Iowa State University, Department of Economics.
  • Handle: RePEc:isu:genres:2049
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Tesfatsion, Leigh, 1995. "A Trade Network Game with Endogenous Partner Selection," ISU General Staff Papers 199505010700001034, Iowa State University, Department of Economics.
    2. McFadzean, David & Tesfatsion, Leigh, 1999. "A C++ Platform for the Evolution of Trade Networks," Computational Economics, Springer;Society for Computational Economics, vol. 14(1-2), pages 109-134, October.
    3. John M. Abowd & Francis Kramarz & David N. Margolis, 1999. "High Wage Workers and High Wage Firms," Econometrica, Econometric Society, vol. 67(2), pages 251-334, March.
    4. Tesfatsion, Leigh, 2001. "Structure, behavior, and market power in an evolutionary labor market with adaptive search," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 419-457, March.
    5. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    2. Mark Pingle & Leigh Tesfatsion, 2004. "Evolution Of Worker-Employer Networks And Behaviors Under Alternative Non-Employment Benefits: An Agent-Based Computational Study," World Scientific Book Chapters, in: Roberto Leombruni & Matteo Richiardi (ed.), Industry And Labor Dynamics The Agent-Based Computational Economics Approach, chapter 8, pages 129-163, World Scientific Publishing Co. Pte. Ltd..
    3. Pingle, Mark & Tesfatsion, Leigh, 2001. "Non-Employment Benefits and the Evolution of Worker-Employer Cooperation: Experiments with Real and Computational Agents," ISU General Staff Papers 200106010700001053, Iowa State University, Department of Economics.
    4. Pingle, Mark & Tesfatsion, Leigh, 2003. "Evolution of Worker-Employer Networks and Behaviors Under Alternative Non-Employment Benefits: An Agent-Based Computational Approach," Staff General Research Papers Archive 10376, Iowa State University, Department of Economics.
    5. 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.
    6. Mark Pingle and Leigh Tesfatsion, 2001. "Unemployment Insurance and the Evolution of Worker-Employer\n Cooperation: Experiments with Real and Artificial Agents," Computing in Economics and Finance 2001 279, Society for Computational Economics.
    7. Alan G. Isaac, 2008. "Simulating Evolutionary Games: A Python-Based Introduction," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(3), pages 1-8.
    8. Babanov, A. & Ketter, W. & Gini, M., 2008. "An Evolutionary Framework for Determining Heterogeneous Strategies in Multi-Agent Marketplaces," ERIM Report Series Research in Management ERS-2008-002-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.
    9. Halkos, George & Tsilika, Kyriaki, 2016. "Assessing classical input output structures with trade networks: A graph theory approach," MPRA Paper 72511, University Library of Munich, Germany.
    10. George E. Halkos & Kyriaki D. Tsilika, 2016. "Trading Structures for Regional Economies in CAS Software," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 523-533, October.
    11. George E. Halkos & Kyriaki D. Tsilika, 2018. "A New Vision of Classical Multi-regional Input–Output Models," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 571-594, March.

    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. Tesfatsion, Leigh, 1999. "Hysteresis In An Evolutionary Labor Market With Adaptive Search," Economic Reports 18189, Iowa State University, Department of Economics.
    2. Tesfatsion, Leigh, 1998. "Teaching Agent-Based Computational Economics to Graduate Students," ISU General Staff Papers 199807010700001043, Iowa State University, Department of Economics.
    3. Tesfatsion, Leigh, 1995. "How Economists Can Get Alife," Economic Reports 18196, Iowa State University, Department of Economics.
    4. Tesfatsion, Leigh, 1998. "Gale-Shapley Matching in an Evolutionary Trade Network Game," ISU General Staff Papers 199804010800001041, Iowa State University, Department of Economics.
    5. Tomas Klos, 1999. "Governance and Matching," Computing in Economics and Finance 1999 341, Society for Computational Economics.
    6. Pingle, Mark & Tesfatsion, Leigh, 2001. "Non-Employment Benefits and the Evolution of Worker-Employer Cooperation: Experiments with Real and Computational Agents," ISU General Staff Papers 200106010700001053, Iowa State University, Department of Economics.
    7. Klos, Tomas B. & Nooteboom, Bart, 2001. "Agent-based computational transaction cost economics," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 503-526, March.
    8. Tomas B. Klos, 1999. "Decentralized Interaction and Co-Adaptation in the Repeated Prisoner&2018;s Dilemma," Computational and Mathematical Organization Theory, Springer, vol. 5(2), pages 147-165, July.
    9. Mark Pingle and Leigh Tesfatsion, 2001. "Unemployment Insurance and the Evolution of Worker-Employer\n Cooperation: Experiments with Real and Artificial Agents," Computing in Economics and Finance 2001 279, Society for Computational Economics.
    10. Leigh Tesfatsion, 1999. "Market Power Effects on Worker-Employer Network Formation in Evolutionary Labor Markets with Adaptive Search," Computing in Economics and Finance 1999 543, Society for Computational Economics.
    11. Tesfatsion, Leigh, 2001. "Structure, behavior, and market power in an evolutionary labor market with adaptive search," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 419-457, March.
    12. Cincotti, Silvano & Raberto, Marco & Teglio, Andrea, 2010. "Credit money and macroeconomic instability in the agent-based model and simulator Eurace," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 4, pages 1-32.
    13. Leigh S. Tesfatsion, "undated". "An Evolutionary Trade Network Game with Preferential Partner Selection," Computing in Economics and Finance 1996 _057, Society for Computational Economics.
    14. Joshua M. Epstein, 2007. "Agent-Based Computational Models and Generative Social Science," Introductory Chapters, in: Generative Social Science Studies in Agent-Based Computational Modeling, Princeton University Press.
    15. Tesfatsion, Leigh, 1998. "Ex Ante Capacity Effects in Evolutionary Labor Markets with Adaptive Search," ISU General Staff Papers 199810010700001046, Iowa State University, Department of Economics.
    16. Tesfatsion, Leigh, 1995. "A Trade Network Game with Endogenous Partner Selection," ISU General Staff Papers 199505010700001034, Iowa State University, Department of Economics.
    17. Giorgio Fagiolo & Giovanni Dosi & Roberto Gabriele, 2005. "Towards an evolutionary interpretation of aggregate labor market regularities," Springer Books, in: Uwe Cantner & Elias Dinopoulos & Robert F. Lanzillotti (ed.), Entrepreneurships, the New Economy and Public Policy, pages 223-252, Springer.
    18. Tomas Klos, "undated". "Decentralized Interaction and Co-adaptation in the Repeated Prisoner's Dilemma," Computing in Economics and Finance 1997 88, Society for Computational Economics.
    19. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    20. Yang, J.-H. Steffi, 2009. "Social network influence and market instability," Journal of Mathematical Economics, Elsevier, vol. 45(3-4), pages 257-276, March.

    More about this item

    Keywords

    Trade networks; evolutionary game; partner choice; Agent-based test bed; Trade Network Game laboratory;
    All these keywords.

    JEL classification:

    • B4 - Schools of Economic Thought and Methodology - - Economic Methodology
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • D2 - Microeconomics - - Production and Organizations
    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior

    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:isu:genres:2049. 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: Curtis Balmer (email available below). General contact details of provider: https://edirc.repec.org/data/deiasus.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.