Learning From Disagreement in the U.S. Treasury Bond Market

Abstract

We study risk premiums in the US Treasury bond market from the perspective of a Bayesian econometrician RA who learns in real-time from disagreement among investors about future bond yields. Notably, disagreement has substantial predictive power for yields, and RA's risk premiums are less volatile than those in the analogous model without learning. RA's forecasts are substantially more accurate than the consensus forecasts of market professionals, particularly following U.S. recessions. The predictive power of disagreement is distinct from the (much weaker) forecasting power of inflation and output growth. Rather, it appears to reflect uncertainty about future fiscal policy.

Keywords: term structure of bond yields, learning, dispersion of beliefs, risk premiums

JEL Classification: E43, E44, G12, D83