The role of term structure in an estimated DSGE model with learning

Agents can learn from financial markets to predict macroeconomic outcomes and learning dynamics can feed back into both the macroeconomy and financial markets. This paper builds on the adaptive learning (AL) model of Slobodyan andWouters (2012b) by introducing the term structure of interest rates. This feature results in more stable learning coefficients over the whole sample period. Our estimation results show that the inclusion of the term spread in the AL model results in an increase of the parameters characterizing endogenous persistence whereas the persistence of the exogenous shocks driving price and wage dynamics decreases. Moreover, the estimated model shows that the term spread innovations are an important source of persistent fluctuations under AL. This finding stands in sharp contrast to the lack of transmission of term premium shocks to the macroeconomy under rational expectations. Furthermore, our empirical results show that our extended model with term structure does an overall better job when reproducing U.S. business cycle features.