Learning with bounded memory in stochastic frameworks is incomplete in the sense that the learning dynamics cannot converge to an rational expectations equilibrium (REE). The properties of the dynamics arising from such rules are studied for models with steady states. If in standard linear...

Analytical expectational stability results are obtained for both Euler-equation and infinitehorizon adaptive learning in a simple stochastic growth model. The rational expectations equilibrium is stable under both types of learning, though there are differences in the learning dynamics.

Nominal GDP targeting has been advocated by a number of authors since it produces relative stability of inflation and output. However, all of the papers assume rational expectations on the part of private agents. In this paper I provide an analysis of this assumption. I use stability under...

We study macroeconomic systems with forward-looking private sector agents and a monetary authority that is trying to control the economy through the use of a linear policy feedback rule. A typical finding in the burgeoning literature in this area is that policymakers should be relatively...

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 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 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...

We introduce the E-correspondence principle for stochastic dynamic expectations models as a tool for comparative dynamics analysis. The principle is applicable to equilibria that are stable under least squares and closely related learning rules. With this technique it is possible to study,...

We introduce the E-correspondence principle for stochastic dynamic expectations models as a tool for comparative dynamics analysis. The principle is applicable to equilibria that are stable under least squares and closely related learning rules. With this technique it is possible to study,...