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Efficient Dynamic Coordination with Individual Learning

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  • Amil Dasgupta
  • Jakub Steiner
  • Colin Stewart

Abstract

We study how the presence of multiple participation opportunities coupled with individual learning about payoffs affects the ability of agents to coordinate efficiently in global coordination games. Two players face the option to invest irreversibly in a project in one of many rounds. The project succeeds if some underlying state variable è is positive and both players invest, possibly asynchronously. In each round they receive informative private signals about è, and asymptotically learn the true value of è. Players choose in each period whether to invest or to wait for more precise information about è. We show that with sufficiently many rounds, both players invest with arbitrarily high probability whenever investment is socially efficient, and delays in investment disappear when signals are precise. This result stands in sharp contrast to the usual static global game outcome in which players coordinate on the risk-dominant action. We provide a foundation for these results in terms of higher order beliefs.

Suggested Citation

  • Amil Dasgupta & Jakub Steiner & Colin Stewart, 2007. "Efficient Dynamic Coordination with Individual Learning," FMG Discussion Papers dp600, Financial Markets Group.
  • Handle: RePEc:fmg:fmgdps:dp600
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    References listed on IDEAS

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    Cited by:

    1. John Duffy, 2009. "Equilibrium Selection in Static and Dynamic Entry Games," Working Paper 376, Department of Economics, University of Pittsburgh, revised Dec 2011.
    2. Sylvain Chassang & Gerard Padró I Miquel, 2010. "Conflict and Deterrence Under Strategic Risk," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(4), pages 1821-1858.

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    More about this item

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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