Ambiguous Business Cycles
This paper considers business cycle models with agents who dislike both risk and ambiguity (Knightian uncertainty). Ambiguity aversion is described by recursive multiple priors preferences that capture agents' lack of confidence in probability assessments. While modeling changes in risk typically requires higher-order approximations, changes in ambiguity in our models work like changes in conditional means. Our models thus allow for uncertainty shocks but can still be solved and estimated using first-order approximations. In our estimated medium-scale DSGE model, a loss of confidence about productivity works like 'unrealized' bad news. Time-varying confidence emerges as a major source of business cycle fluctuations.
We would like to thank George-Marios Angeletos, Francesco Bianchi, Lars Hansen, Nir Jaimovich, Alejandro Justiniano, Christian Matthes, Fabrizio Perri, Giorgio Primiceri, Bryan Routledge, Juan Rubio-Ramirez and Rafael Wouters, as well as workshop and conference participants at Boston Fed, Carnegie Mellon, CREI, Duke, ESSIM (Gerzensee), Federal Reserve Board, NBER Summer Institute, New York Fed, NYU, Ohio State, Rochester, San Francisco Fed, SED (Ghent), Stanford, UC Santa Barbara and Yonsei for helpful discussions and comments. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.