IDEAS home Printed from
   My bibliography  Save this paper

Building a Macroeconomic Data Collection Simulator on the Internet using the Human Agent Based Simulation Method


  • Kyoung whan Choe



Since the internet have become popular to the public, a new simulation method, which involves a large number of people in the simulation process, has been enabled. In this paper, a macroeconomic data collection simulator on the internet, which can model a closed economic system by using such the simulation method, is proposed. The simulator provides a market system with its users; therefore, they can buy, produce and sell products. System administrators can coordinate the market by controlling four macroeconomic variables. With some extensions, the simulator can model an open economic system.

Suggested Citation

  • Kyoung whan Choe, 2001. "Building a Macroeconomic Data Collection Simulator on the Internet using the Human Agent Based Simulation Method," Computational Economics 0103001, EconWPA.
  • Handle: RePEc:wpa:wuwpco:0103001
    Note: Type of Document - Acrobat PDF; prepared on IBM PC ; pages: 12 ; figures: included

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Paul Klemperer, 2002. "What Really Matters in Auction Design," Journal of Economic Perspectives, American Economic Association, vol. 16(1), pages 169-189, Winter.
    2. 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.
    3. Bower, John & Bunn, Derek, 2001. "Experimental analysis of the efficiency of uniform-price versus discriminatory auctions in the England and Wales electricity market," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 561-592, March.
    4. Klemperer, Paul, 1999. " Auction Theory: A Guide to the Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 13(3), pages 227-286, July.
    5. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    6. von der Fehr, Nils-Henrik Morch & Harbord, David, 1993. "Spot Market Competition in the UK Electricity Industry," Economic Journal, Royal Economic Society, vol. 103(418), pages 531-546, May.
    7. 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.
    8. Rust, John & Miller, John H. & Palmer, Richard, 1994. "Characterizing effective trading strategies : Insights from a computerized double auction tournament," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 61-96, January.
    9. Gode, Dhananjay K & Sunder, Shyam, 1993. "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 119-137, February.
    10. Green, Richard J & Newbery, David M, 1992. "Competition in the British Electricity Spot Market," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 929-953, October.
    11. 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.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Macroeconomics; Internet; Human Agent based Simulation;

    JEL classification:

    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:wpa:wuwpco:0103001. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.