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Limited Information Aggregation and Externalities - A Simple Model of Metastable Market

Author

Listed:
  • Gong, Zheng
  • Tian, Feng
  • Xu, Boyan

Abstract

We analyze a model in which agents’ decisions to enter or exit investments are influenced from their individual and external parties’ transaction histories. Actual investment outcomes are unknown to all participants until the end of decision periods, but outcomes do change depending on the number of participating players in the market and the market’s current state of condition. In this particular model, agents have access to external parties’ information from those who are within their specific social network. Our study of limited information aggregation mainly focuses on market responses to investors’ decisions of exiting the investment. With social structures complicating investment outcomes, we present a model that describes how markets can enter relatively stable statuses long enough for exiting participants to return, which brings the investment back to normal conditions. Our model also supports previous studies that limited information aggregation can cause the exogenous shock effect of global collapse.

Suggested Citation

  • Gong, Zheng & Tian, Feng & Xu, Boyan, 2013. "Limited Information Aggregation and Externalities - A Simple Model of Metastable Market," MPRA Paper 52143, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:52143
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    References listed on IDEAS

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    1. , & , & ,, 2014. "Dynamics of information exchange in endogenous social networks," Theoretical Economics, Econometric Society, vol. 9(1), January.
    2. Guarino, Antonio & Huck, Steffen & Jeitschko, Thomas D., 2006. "Averting economic collapse and the solipsism bias," Games and Economic Behavior, Elsevier, vol. 57(2), pages 264-285, November.
    3. Hikmet Gunay, 2008. "The role of externalities and information aggregation in market collapse," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 35(2), pages 367-379, May.
    4. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    5. Curtis R. Taylor & Thomas D. Jeitschko, 2001. "Local Discouragement and Global Collapse: A Theory of Coordination Avalanches," American Economic Review, American Economic Association, vol. 91(1), pages 208-224, March.
    6. Sushil Bikhchandani & David Hirshleifer & Ivo Welch, 1998. "Learning from the Behavior of Others: Conformity, Fads, and Informational Cascades," Journal of Economic Perspectives, American Economic Association, vol. 12(3), pages 151-170, Summer.
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    More about this item

    Keywords

    Information aggregation; Social structure; Internet Externality; Simulation;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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