We document an unpleasant feature of Epstein-Zin preferences in a stylized model economy of the long-run risk type now widespread in Asset Pricing: Agents with preference parameters commonly described as indicating a "preference for early resolution of uncertainty" achieve higher utility levels...

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...

Strong consistency of least squares estimators of the slope parameter in simple linear regression models is established for predetermined stochastic regressors. The main result covers a class of models which falls outside the applicability of what is presently available in the literature. An...

We propose behavioral learning equilibria as a plausible explanation of coordination of individual expectations and aggregate phenomena such as excess volatility in stock prices and high persistence in inflation. Boundedly rational agents use a simple univariate linear forecasting rule and...

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...

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 note evaluates how adaptive learning agents weigh different pieces of information when forming expectations with a recursive least squares algorithm. The analysis is based on a new and more general non-recursive representaion of the learning algorithm, namely, a penalized weighted least...

This paper evaluates how the way agents weight information when forming expectations can affect the econometric estimation of models with adaptive learning. One key new finding is that misspecification of the uncertainty about initial beliefs under constantgain least squares learning can...

This paper analyzes how the formation of expectations constrains monetary and fiscal policy design. Economic agents have imperfect knowledge about the economic environment and the policy regime in place. Households and firms learn about the policy regime using historical data. Regime uncertainty...

This paper demonstrates that the adaptive learning approach to modelling private sector expectations can be used as an equilibriumselection mechanism in a natural-rate monetary model with unemployment persistence.In particular, it is shown that only one of the two rational expectations...