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A Computational Laboratory for Evolutionary Trade Networks

Author

Listed:
  • David McFadzean

    (Javien Canada Inc)

  • Deron Stewart

    (Consultant Programmer)

  • Leigh Tesfatsion

    (Iowa State University)

Abstract

This study 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 targetted 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 real-time animations. Data tables and charts reporting descriptive performance are also provided in real time. The capabilities of the TNG Lab are demonstrated by means of labor market experiments.

Suggested Citation

  • David McFadzean & Deron Stewart & Leigh Tesfatsion, 2000. "A Computational Laboratory for Evolutionary Trade Networks," Computational Economics 0004004, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpco:0004004
    Note: Type of Document - Zip file containing pdf, html, and gif files; prepared on IBM PC - PC-TEX/; to print on HP/PostScript/; pages: 22 ; figures: included
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    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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, January.
    Full references (including those not matched with items on IDEAS)

    Citations

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    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: 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," Economic Reports 18190, 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. 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.
    9. 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.
    10. repec:kap:compec:v:51:y:2018:i:3:d:10.1007_s10614-016-9624-x is not listed on IDEAS

    More about this item

    Keywords

    Agent-based computational economics; Computational Laboratory; Buyer-seller trade networks; Evolution; Network animation; Endogenous interactions; Labor market experiments; C++ class framework;

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • J2 - Labor and Demographic Economics - - Demand and Supply of Labor
    • J6 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers

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