An economy exhibits structural heterogeneity when the forecasts of different agents have different effects on the determination of aggregate variables. Various forms of structural heterogeneity can arise and we study the important case of economies in which agents' behavior depends on forecasts...

We study the impact of adaptive learning for the design of a robust monetary policy using a small open-economy New Keynesian model. We find that slightly departing from rational expectations substantially changes the way the central bank deals with model misspecification. Learning induces an...

In this paper we consider regression models with forecast feedback. Agents' expectations are formed via the recursive estimation of the parameters in an auxiliary model. The learning scheme employed by the agents belongs to the class of stochastic approximation algorithms whose gain sequence is...

We examine the nonlinear model Xt = Et F(xt+1) . Markov SSEs exist near an indeterminate steady state, X = F(X), provided F´(X)> 1. We show that there exist Markov SSEs that are E-stable, and therefore locally stable under adaptive learning, if F´(X)< -1.

We consider the stability under adaptive learning of the complete set of solutions to the model when . In addition to the fundamentals solution, the literature describes both finite-state Markov sunspot solutions, satisfying a resonant frequency condition, and autoregressive solutions depending...

We develop a monetary model with flexible supply of labor, cash in advance constraints and government spending financed by seignorage. This model has two regimes. One regime is conventional with two steady states. The other regime has a unique steady state which can be determinate or...

Adaptive learning under constant-gain allows persistent deviations of beliefs from equilibrium so as to more realistically reflect agents' attempt of tracking the continuous evolution of the economy. A characterization of these beliefs is therefore paramount to a proper understanding of the role...

This paper proposes a new approach for modeling investor fear after rare disasters. The key element is to take into account that investors' information about fundamentals driving rare downward jumps in the dividend process is not perfect. Bayesian learning implies that beliefs about the...

This paper develops a theory of endogenously (non-)Ricardian beliefs. That is, whether Ricardian Equivalence holds in an equilibrium depends on endogenous private sector beliefs. The novelty here is a restricted perceptions viewpoint: in complex forecasting environments, agents forecast...