This paper examines the predictive content of the shadow rates for U.S. real activity and inflation in a data-rich environment. We find that the shadow rates contain substantial out-of-sample predictive power for inflation both in the non zero lower bound and zero lower bound periods. In contrast, the shadow rates are uninformative about future real activity.

This paper analyzes the predictive content of the level, slope and curvature of the yield curve for U.S. real activity in a data-rich environment. We find that the slope contains predictive power, but the level and curvature are not successful leading indicators. The predictive power of each of the yield curve factors fluctuates over time. The results show that economic conditions matter for the predictive ability of the slope. In particular, inflation persistence emerges as a key variable that affects the predictive content of the slope. The slope tends to forecast output growth better when inflation is highly persistent.

This paper re-examines the out-of-sample predictive power of interest rate spreads when the short-term nominal rates have been stuck at the zero lower bound and the Fed has used unconventional monetary policy. Our results suggest that the predictive power of some interest rate spreads have changed since the beginning of this period. In particular, the term spread has been a useful leading indicator since December 2008, but not before that. Credit spreads generally perform poorly in the zero lower bound and unconventional monetary policy period. However, the mortgage spread has been a robust predictor of economic activity over the 2003-2014 period.