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Repeated Games Without Public Randomization: A Constructive Approach

Ani Dasgupta () and Sambuddha Ghosh
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Ani Dasgupta: International Maritime Business Department, Massachusetts Maritime Academy and Economics Department, Boston University.
Sambuddha Ghosh: Economics Group, Shanghai University of Finance and Economics

No WP2017-011, Boston University - Department of Economics - Working Papers Series from Boston University - Department of Economics

Abstract: We study discounted infinitely repeated games with perfect monitoring and without public randomization. Both symmetric and asymmetric discounting cases are considered; a new geometric construct called ‘self-accessibility’ is proposed and used to unify the analyses of these two cases. For symmetric discounting, our approach leads to easy computability of a discount factor bound needed to support a specific payoff vector in equilibrium. When discounting is allowed to be asymmetric, we show that any payoff vector that is in the interior of the smallest rectangular region containing the pureaction payoffs is realizable in the repeated game. Next, an easily-verifiable condition, ‘strict diagonalizability’, is offered as a sufficient and almost necessary condition for a payoff vector to be an equilibrium payoff for some discount factor vector. ‘Turnpike strategies’ that support a target payoff are explicitly constructed. Our results thus encompass and generalize Fudenberg and Maskin (1986, 1991).

Keywords: ambiguity; Repeated Games; Public Randomization; Asymmetric Discounting (search for similar items in EconPapers)
Pages: 56 pages
Date: 2017-09, Revised 2019-02
New Economics Papers: this item is included in nep-gth and nep-mic
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