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We consider a decision maker who ranks actions according to the smooth ambiguity criterion of Klibanoff, Marinacci, and Mukerji (2005). An action is justifiable if it is a best reply to some belief over probabilistic models. We show that higher ambiguity aversion expands the set of justifiable actions. A similar result holds for risk aversion. Our results follow from a generalization of the duality lemma of Wald (1949) and Pearce (1984).

This paper provides a general framework for analyzing self-confirming policies. We study self-confirming equilibria in recurrent decision problems with incomplete information about the true stochastic model. We characterize stationary monetary policies in a linear-quadratic setting.

The mathematical framework of psychological game theory is useful for describing many forms of motivation where preferences depend directly on one’s own or others’ beliefs. It allows for incorporating, for example, emotions, reciprocity, image concerns, and self-esteem in economic analysis. We explain how and why, discussing basic theory, experiments, applied work, and methodology.

In this paper we model contract incompleteness \"from the ground up,\" as arising endogenously from the costs of describing the environment and the parties' behavior. Optimal contracts may exhibit two forms of incompleteness: discretion, meaning that the contract does not specify the parties' behavior with sufficient detail; and rigidity, meaning that the parties' obligations are not sufficiently contingent on the external state. The model sheds light on the determinants of rigidity and discretion in contracts, and yields rich predictions regarding the impact of changes in the exogenous parameters on the degree and form of contract incompleteness.

A repeated game with incomplete information is considered in which a patient long run player, whose type is unknown, faces a sequence of short run opponents. Watson's (1993) study is qualified and the line of inquiry of Watson and Battigalli (1994) concerning settings in which reputations are effective is extended. Two main conditions on the beliefs of the players, along with weak rationalizability, imply the reputation result. It is shown that it is necessary to assume that the conditional beliefs of the short run players satisfy a stochastic independence property.

The authors argue that the rationalizability approach is particularly appropriate to analyze games with genuine incomplete information.

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.(This abstract was borrowed from another version of this item.)