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On The Computation Of Value Correpondences Of Dynamic Games

Author

Listed:
  • Sevin Yeltekin

    (Northwestern University)

  • Chris Sleet

    (University of Texas-Austin)

Abstract

Recursive Game Theory provides theoretical procedured for computing the equilibrium payoff sets of repeated games and the equilibrium payoff correspondences of dynamic games. These procedures can not be directly implemented on a computer since they involve the computations of objects with infinite cardinality. In the context of repeated games, Conklin, Judd and Yeltekin(1999) emphasize the value of inner and outer approximation schemes that permit both the computation of ( approximate) value sets and an estimate of the computational error. In this paper, we propose, and implement outer and inner approximation methods for value correspondences, that naturally occur in the analysis of dynamic games. The procedure utilizes set valued step functions. We provide applications to international borrowing and lending and intergenerational transfers.

Suggested Citation

  • Sevin Yeltekin & Chris Sleet, 2000. "On The Computation Of Value Correpondences Of Dynamic Games," Computing in Economics and Finance 2000 204, Society for Computational Economics.
    • Handle: RePEc:sce:scecf0:204
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    Cited by:

    1. Philipp Renner & Simon Scheidegger, 2017. "Machine learning for dynamic incentive problems," Working Papers 203620397, Lancaster University Management School, Economics Department.

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