We propose new indices to measure macroeconomic uncertainty. The indices measure how unexpected a realization of a representative macroeconomic variable is relative to the unconditional forecast error distribution. We use forecast error distributions based on the nowcasts and forecasts of the Survey of Professional Forecasters. We further compare the new indices with those proposed in the literature and assess their macroeconomic impact.

We propose a decomposition to distinguish between Knightian uncertainty (ambiguity) and risk, where the …rst measures the uncertainty about the probability distribution generating the data, while the second measures uncertainty about the odds of the outcomes when the probability distribution is known. We use the Survey of Professional Forecasters (SPF) density forecasts to quantify overall uncertainty as well as the evolution of the di¤erent components of uncertainty over time and investigate their importance for macroeconomic ‡uctuations. We also study the behavior and evolution of the various components of our decomposition in a model that features ambiguity and risk.

We propose new methods for evaluating predictive densities that focus on the models'actual predictive ability in …nite samples. The tests o¤er a simple way of evaluating the correct speci…cation of predictive densities, either parametric or non-parametric. The results indicate that our tests are well sized and have good power in detecting mis-speci…cation in predictive densities. An empirical application to the Survey of Professional Forecasters and a baseline Dynamic Stochastic General Equilibrium model shows the usefulness of our methodology.

This paper proposes a framework to implement regression-based tests of predictive ability in unstable environments, including, in particular, forecast unbiasedness and efficiency tests, commonly referred to as tests of forecast rationality. Our framework is general: it can be applied to model-based forecasts obtained either with recursive or rolling window estimation schemes, as well as to forecasts that are model-free. The proposed tests provide more evidence against forecast rationality than previously found in the Federal Reserve's Greenbook forecasts as well as survey-based private forecasts. It confirms, however, that the Federal Reserve has additional information about current and future states of the economy relative to market participants.