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This paper uses a model of boundedly rational learning to account for the observations of recurrent hyperin°ations in the last decade. We study a standard monetary model where the fully rational expectations assumption is replaced by a formal de¯nition of quasi-rational learning. The model under learning is able to match remarkably well some crucial stylized facts observed during the recurrent hyperin°a-tions experienced by several countries in the 80's. We argue that, despite being a small departure from rational expectations, quasirational learning does not preclude falsi¯ability of the model, it does not violate reasonable rationality requirements and it can be used for policy evaluation.

We obtain a recursive formulation for a general class of optimization problems with forward-looking constraints which often arise in economic dynamic models, for example, in contracting problems with incentive constraints or in models of optimal policy. In this case, the solution does not satisfy the Bellman equation. Our approach consists of studying a recursive Lagrangian. Under standard general conditions, there is a recursive saddle-point functional equation (analogous to a Bellman equation) that characterizes a recursive solution to the planner's problem. The recursive formulation is obtained after adding a co-state variable μ t summarizing previous commitments reflected in past Lagrange multipliers. The continuation problem is obtained with μ t playing the role of weights in the objective function. Our approach is applicable to characterizing and computing solutions to a large class of dynamic contracting problems.