TY - JOUR
T1 - Measuring uncertainty
AU - Jurado, Kyle
AU - Ludvigson, Sydney C.
AU - Ng, Serena
PY - 2015/3/1
Y1 - 2015/3/1
N2 - This paper exploits a data rich environment to provide direct econometric estimates of time-varying macroeconomic uncertainty. Our estimates display significant independent variations from popular uncertainty proxies, suggesting that much of the variation in the proxies 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 are larger, more persistent, and are more correlated with real activity. Our estimates provide a benchmark to evaluate theories for which uncertainty shocks play a role in business cycles.
AB - This paper exploits a data rich environment to provide direct econometric estimates of time-varying macroeconomic uncertainty. Our estimates display significant independent variations from popular uncertainty proxies, suggesting that much of the variation in the proxies 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 are larger, more persistent, and are more correlated 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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U2 - 10.1257/aer.20131193
DO - 10.1257/aer.20131193
M3 - Article
AN - SCOPUS:84924020820
SN - 0002-8282
VL - 105
SP - 1177
EP - 1216
JO - American Economic Review
JF - American Economic Review
IS - 3
ER -