Adaptive Learning with Term Structure Information

This paper builds on the Euler-equation approach to adaptive learning (AL) by considering term structure information in addition to macroeconomic data. We consider a medium-scale DSGE model where the term structure expectations hypothesis is imposed. The model estimated under AL using term structure information has a better fit. Estimation results show that term structure provides useful real-time information in forecasting macroeconomic variables above and beyond that provided by revised macroeconomic data. In particular, term structure information greatly improves the matching of AL expectations to the corresponding forecasts reported in the Survey of Professional Forecasters, which further contributes to the empirical validity of AL.