By Cosmin Ilut and Martin Schneider
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.
Interesting paper that makes the important distinction between risk and uncertainty and thus say something in a structured way about how confidence has an impact on business cycles. As a bonus, this discussion does not require rational expectations,