Anmerkungen:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments April 22, 2014 erstellt
Beschreibung:
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 accuracy and in matching (future) survey forecasts