Stochastic Dominance of Signals and Reparametrization in Adverse Selection Model
نویسندگان
چکیده
This paper investigates how a pair of signals about the type of the agent can be compared in the classical principal agent model with adverse selection. Signal comparison in this model has two distinctive features that make it di cult to directly apply the results from decision theory: timing of the game and the number of incentive compatibility constraint. The signal in the model takes the form of probability distribution and two popular means of comparing a pair of probability distributions are considered: First Order Stochastic Dominance (FOSD) and Second Order Stochastic Dominance (SOSD). It is straightforwardly shown that FOSD relation implies more informativeness, which guarantees higher pro t to the principal. In contrast, SOSD relation is largely a ected by the parametrization of the agent's type and it might not guarantee more informativeness under some circumstances. Nevertheless, if the parameter of the agent is properly changed so that it re ects the principal's pro t rather than the agent's cost, SOSD relation may guarantee higher pro t to the principal. Under some appropriate conditions, this paper o ers a construction algorithm for the reparametrization that SOSD relation implies more informativeness. JEL Classi cation: C44, C60, D86
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