Intellectual merit: When an individual chooses an action under uncertainty, she cannot be sure of the ensuing outcome. Following Savage, it is standard practice to model this uncertainty by means of a set of states of the world. These describe the individual's ex-ante perception of the contingencies that may influence the outcome. The outcome of any action is uniquely determined by the state that is realized. It follows that each state necessarily provides a complete description of the environment. Thus this modeling approach assumes that the decision-maker has in mind a complete list of all relevant and finely detailed contingencies. The assumption of a forward-looking agent who conceives of future contingencies seems relatively uncontroversial. However, in realistic settings, the following description of the agent seems more plausible: she conceives of some relevant contingencies or states of the world but she is aware that these contingencies are coarse--they leave out some details that may affect outcomes. Though she may not be able to describe these finer details, she is aware that they exist and this may affect her behavior. This project is concerned with modeling such an agent.
The agent just described is not "boundedly rational" or unsophisticated--quite the contrary. Outside of artificial laboratory-style settings, it would seem impossible for any decision-maker, or for an outside observer, to identify all relevant and finely detailed contingencies. It is a sophisticated agent who is aware of her limited foresight and who takes it into account in decision-making. In contrast, an individual who uses a Savage-style state space and acts as though her conception of the future is complete seems naive.
Coarseness of perceptions is relevant only if it can be identified from economic data. The axiomatic method to be adopted takes only behavior (or preference) as observable and characterizes that behavior which can be thought of as if it were based on coarse perceptions.
Broader impact: There are potentially many broad-ranging applications of a model with coarse perceptions. State space modeling is pervasive in economics and finance. But if agents use coarse contingencies rather than Savage-style states, then their behavior will differ from predictions of standard models. The project will explore the behavioral implications of coarseness in a range of applied settings, including asset markets, consumption/savings contexts, and strategic settings. Think, for example, of a portfolio choice setting. An investor may identify some factors that are likely to influence returns to financial securities. However, few investors would believe that they have identified all possible relevant factors. Awareness that their conceptions are missing some details would presumably affect the choice of portfolios. Implications for asset pricing theory would follow.
