Learning in intertemporal equilibrium models and the sunspot case
This chapter describes the concept of sunspot equilibrium in non-stochastic models, and shows the results of convergence to this equilibrium under reasonable learning rules. It discusses the existence of learning equilibria. The hypothesis of perfect prevision is made for finding some equilibria which eventually agents will attain. The proof for a non-linear case is based in a construction of a bifurcation of the field defined by the equilibrium equations in the steady state. The bounded rationality of economic agents requires that they use learning rules in order to formulate expectations about future states and the learning procedures lead the economy to one or another equilibrium. Multiplicity of equilibria in economic models is one of the main concerns of theoretical macroeconomists. When there exists multiplicity of equilibria in intertemporal equilibrium models, the Arrow–Debreu model is insufficient to explain theoretically which of them will prevail.