We study the properties of generalized stochastic gradient (GSG) learning in forward-looking models. We examine how the conditions for stability of standard stochastic gradient (SG) learning both differ from and are related to E-stability, which governs stability under least squares learning. SG...

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...

Macroeconomic expectations of various economic agents are characterized by substantial cross-sectional heterogeneity. In this paper, we focus on expectations heterogeneity among professional forecasters. We first present stylized facts and discuss theoretical explanations for heterogeneous...

We experimentally investigate how price expectations are formed in a large asset market where subjects' only task is to forecast the future price of a risky asset. The realized prices depend on these expectations. We observe small (6 participants) and large markets (about 100 participants). In...

We compare forecasts from different adaptive learning algorithms and calibrations applied to US real-time data on inflation and growth. We find that the Least Squares with constant gains adjusted to match (past) survey forecasts provides the best overall performance both in terms of forecasting...

Using a long-panel dataset of Japanese firms that contains firm-level sales forecasts, we provide evidence on firm-level uncertainty and imperfect information over their life cycle. We find that firms make non-negligible and positively correlated forecast errors. However, they make more precise...

Out-of-sample forecasting tests of DSGE models against time-series benchmarks such as an unrestricted VAR are increasingly used to check a) the specification b) the forecasting capacity of these models. We carry out a Monte Carlo experiment on a widely-used DSGE model to investigate the power of...