This chapter provides a survey of the recent work on learning in the context of macroeconomics. Learning has several roles. First, it provides a boundedly rational model of how rational expectations can be achieved. Secondly, learning acts as a selection device in models with multiple REE...

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...

This paper investigates the learnability of an equilibrium where agents formulate their forecasts under adaptive learning with heterogeneously misspecified econometric models; the equilibrium is called a Heterogeneous Misspecification Equilibrium (HME). The paper finds that the learnability...

If private sector agents update their beliefs with a learning algorithm other than recursive least squares, expectational stability or learnability of rational expectations equilibria (REE) is not guaranteed. Monetary policy under commitment, with a determinate and E-stable REE, may not imply...

We consider a linear stochastic univariate rational expectations model, with a predetermined variable, and provide alternative representations of SSEs (stationary sunspot equilibria). For a strict subset of the parameter space there exist SSEs that are locally stable under least squares learning...