Uncertainty Shocks and the Role of the Black Swan

A recent literature explores many ways in which uncertainty shocks can have important economic effects. But how large are uncertainty shocks and where do they come from? Researchers typically estimate a model with stochastic volatility, using all available data, then condition on the estimated model to infer volatility. This volatility is the uncertainty of an agent who knows the true probability of outcomes and whose only uncertainty is about what the draw from that distribution will be. We model a Bayesian forecaster who uses new data released each quarter to re-estimate the parameters that govern the shape of the probability distribution of GDP growth. Although the forecaster's parameter revisions are small, the probability of black swans (extreme events) is very sensitive to these revisions. Our real-time measure of GDP forecast uncertainty reveals that changes in the risk of a black swan explain most of the shocks to uncertainty.