Thesis (Ph. D.)--University of Texas at Austin, 2002. / Vita. Includes bibliographical references. Available also from UMI Company.

Thesis (Ph. D.)--University of Texas at Austin, 2002. / Vita. Includes bibliographical references. Available also from UMI Company.

Thesis (Ph. D.)--University of Notre Dame, 2004. / Thesis directed by Phillip R. Sloan and Michael J. Loux for the Program in History and Philosophy of Science. "January 2004." Includes bibliographical references (leaves 278-285).

My dissertation studies the optimal design of institutions and information structures for different objectives of a designer or a social planner. The questions addressed are interesting both from a theoretical point of view, and in terms of their real-life applications. The first chapter of the dissertation focuses on supermodular mechanism design in environments with arbitrary finite type spaces and interdependent valuations. In these environments, the designer may have to use Bayesian equilibrium as a solution concept, because ex post implementation may not be possible. We propose direct Bayesian mechanisms that are robust to certain forms of bounded rationality while controlling for equilibrium multiplicity. In quasi-linear environments with informational and allocative externalities, we show that any Bayesian mechanism that implements a social choice function can be converted into a supermodular mechanism that also implements the original decision rule. The proposed supermodular mechanism can be chosen in a way that minimizes the size of the equilibrium set, and we provide two sets of sufficient conditions to this effect: for general decision rules and for decision rules that satisfy a certain requirement. This is followed by conditions for supermodular implementation in unique equilibrium. The second chapter looks at the incentives of a revenue-maximizing seller (designer) who discloses information to a number of interacting bidders (agents). In particular, the designer chooses the level of precision with which agents can infer the quality of a common-value object from their privately observed signals. We restrict attention to the second-price sealed-bid auction format. If the seller has perfect commitment power and can choose the precision level before observing the quality of the object, in the presence of any small cost to precision it is ex ante optimal for her to choose completely uninformative signals. For the case when the seller chooses the precision level after observing the quality of the object, we characterize pooling, partial pooling, and separating equilibria. We show that in this setting the cost associated with precision can be viewed as a form of commitment device: if costs are too low, the best pooling equilibrium ceases to exist as the high type seller is too tempted to separate. Thus, the seller ends up with a lower ex ante expected payoff than in the case when cost parameters are above a certain threshold. The third chapter of this dissertation studies the optimal choice of information structure from the perspective of a designer maximizing a certain objective function. Generally speaking, there are two ways of creating incentives for interacting agents to behave in a desired way. One is by providing appropriate payoff incentives, which is the subject of mechanism design. The other is by choosing the information that agents observe, which we refer to as information design. We consider a model of symmetric information where a designer chooses and announces the information structure about a payoff relevant state. The interacting agents observe the signal realizations, update their beliefs, and take actions which affect the welfare of both the designer and the agents. We characterize the general finite approach to deriving the optimal information structure --- the one that maximizes the designer's ex ante expected utility subject to agents playing a Bayes Nash equilibrium. We then apply the general approach to a symmetric two state, two agent, and two actions environment in a parameterized underlying game and fully characterize the optimal information structure. It is never strictly optimal for the designer to use conditionally independent private signals. The optimal information structure may be a public signal, or may consist of correlated private signals. Finally, we examine how changes in the underlying game affect the designer's maximum payoff. This exercise provides a joint mechanism/information design perspective. / text

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published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

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