Heterogeneous beliefs and learning in forward looking economic models

We study a class of forward looking economic models with heterogeneous agen ts in a bounded rationality setting. The agents employ the same recursive l earning rule to update beliefs but are characterized by different memory pa rameters. The peculiarity of the learning mechanism is that the learning ra te is not vanishing in the limit. Differently from what is obtained in the case of a vanishing learning step, i.e., the stability conditions in the he terogeneous agents case are those of the representative agent model, we sho w that heterogeneity matters for the expectational stability of a stationar y perfect foresight equilibrium and that the stability parameter restrictio ns with heterogeneous agents are stronger than in the case of homogeneous a gents. C62, D83, D84, E40.