In this paper, the author considers how boundedly rational agents learn rational expectations when all equilibrium price functions or forecasts of future equilibrium prices are required to be computable. The paper examines two learning environments. In the first, agents have perfect information about the state of nature. In this case, the theory of machine inference can be applied to show that there is a broad class of computable economies whose rational expectations equilibria can be learned by inductive inference. In the second environment, agents do not have perfect information about the state of nature. In this case, a version of Godel's incompleteness theorem implies that rational expectations equilibria cannot be learned.

In this paper, I show the existence of stationary rational expectations equilibria in a simple two-island, overlapping generations model of the type first considered by Lucas, in which all uncertainty is endogenous. The result is obtained by first constructing "sunspot" equilibria on each island separately and then using the equilibrium pricing equations to eliminate the sunspot variable. In the resulting equilibrium, each island's prices serve as the sunspot for the other island. The constructed equilibrium is nontrivially stochastic.

In this paper, we analyze optimal contracts in an infinitely repeated agency model in which both the principal and agent discount the future. We show that there is a stationary representation of the optimal contract when the agent's conditional discounted expected utility is used as a state variable. This representation reduces the multi-period problem to a static variational problem which can be analyzed using standard variational techniques. This reduction is used to obtain several properties of the contract.