AN ESTIMATED DSGE MODEL WITH LEARNING BASED ON TERM STRUCTURE INFORMATION

Abstract

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, S. and R. Wouters (2012a) American Economic Journal: Macroeconomics 4, 65–101.] by introducing the term structure of interest rates. This extension enables term structure information to fully characterize agents’ expectations in real time. This feature addresses an imperfect information issue neglected in the related AL literature. The term structure of interest rates results in a strong channel of persistence driven by multi-period forecasting. Including the term structure in the AL model results in a model fit similar to that obtained in the rational expectation (RE) version of the model, but it greatly reduces the importance of other endogenous sources of aggregate persistence such as price and wage stickiness and the elasticity of the cost of adjusting capital. The model estimated also shows that term premium innovations are a major source of persistent fluctuations in nominal variables under AL. This stands in sharp contrast to the lack of transmission of term premium shocks to the macroeconomy under REs.