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 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...

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 introduce Behavioral Learning Equilibria (BLE) into a multivariate linear framework and apply it to New Keynesian DSGE models. In a BLE, boundedly rational agents use simple, but optimal AR(1) forecasting rules whose parameters are consistent with the observed sample mean and autocorrelation...

The recent nonexperimental literature on social learning focuses on showing that observational learning exists, that is, individuals do indeed draw inferences by observing the actions of others. We take this literature a step further by analyzing whether individuals are Bayesian social learners....

This paper is the first attempt to investigate the performance of different learning rules in fitting survey data of household and expert inflation expectations in five core European economies (France, Germany, Italy, Netherlands and Spain). Overall it is found that constant gain learning...