This paper exploits a data rich environment to provide direct econometric estimates of time-varying macro uncertainty, defined as the common variation in the unforecastable component of a large number of economic indicators. Our estimates display significant independent variations from popular uncertainty proxies, suggesting that much of their variation is not driven by uncertainty. Quantitatively important uncertainty episodes appear far more infrequently than indicated by popular uncertainty proxies, but when they do occur, they have larger and more persistent correlations with real activity. Our estimates provide a benchmark to evaluate theories for which uncertainty shocks play a role in business cycles.
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