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Rationalization and Incomplete Information

Listed author(s):
  • Battigalli Pierpaolo

    ()

    (Università Bocconi, IEP)

  • Siniscalchi Marciano

    ()

    (Northwestern University and Princeton University)

We analyze a family of extensive-form solution procedures for games with incomplete information that do not require the specification of an epistemic type space a la Harsanyi, but can accommodate a (commonly known) collection of explicit restrictions D on first-order beliefs. For any fixed D we obtain a solution called D-rationalizability.In static games, D-rationalizability characterizes the set of outcomes (combinations of payoff types and strategies) that may occur in any Bayesian equilibrium model consistent with D; these are precisely the outcomes consistent with common certainty of rationality and of the restrictions D. Hence, our approach to the analysis of incomplete-information games is consistent with Harsanyi's, and it may be viewed as capturing the robust implications of Bayesian equilibrium analysis.In dynamic games, D-rationalizability yields a forward-induction refinement of this set of Bayesian equilibrium outcomes. Focusing on the restriction that first-order beliefs be consistent with a given distribution on terminal nodes, we obtain a refinement of self-confirming equilibrium. In signalling games, this refinement coincides with the Iterated Intuitive Criterion.

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Article provided by De Gruyter in its journal The B.E. Journal of Theoretical Economics.

Volume (Year): 3 (2003)
Issue (Month): 1 (June)
Pages: 1-46

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Handle: RePEc:bpj:bejtec:v:advances.3:y:2003:i:1:n:3
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