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 (rational expectations equilibria). Third, the learning dynamics …

" parameter which converges in the limit to zero. These systems have recently been used to study the dynamics of adaptive learning …

We consider the impact of anticipated policy changes when agents form expectations using adaptive learning rather than … learning rule. We analyze these issues using two well-known set-ups, an endowment economy and the Ramsey model. In our set …-up there are important deviations from both rational expectations and purely adaptive learning. Our approach could be applied …

(X), provided F´(X)> 1. We show that there exist Markov SSEs that are E-stable, and therefore locally stable under adaptive learning …

We consider the stability under adaptive learning of the complete set of solutions to the model when . In addition to … representation used by agents in the learning process. Only the finite-state Markov sunspot solutions can be stable under learning. …

stable under adaptive learning, taking the form of noisy finite state Markov processes at resonant frequencies. For a range …

learning. We reconsider this issue and analyze the full set of solutions for the linearized model. Our main focus is on … learning if agents can utilize contemporaneous data. In an economy with a mixture of agents, some of whom only have access to …

models of expectations formation that rely on econometric learning. Some apparently natural policy rules turn out to imply … expectational instability of private agents' learning. We use the standard New Keynesian model to illustrate this problem and survey … learning. We then consider some practical concerns such as measurement errors in private expectations, observability of …

(constant gain) least-squares learning, for a range of gain parameters. We find that for operational forms of policy rules, ie … Honkapohja (2003, 2006) deliver robust learning stability. In contrast, many proposed alternatives become unstable under learning …