This paper provides a model framework to characterize the process of stochastic learning during the period of divergence from a de jure currency regime. The model outcome shows that divergence from a de jure regime is a process of slow learning in small steps, which indicates that the learning...

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...