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Measuring Uncertainty
Abstract
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. (JEL C53, D81, E32, G12, G35, L25)
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Citations
Cited by
Measuring Economic Policy Uncertainty*
Baker, S. R., Bloom, N., & Davis, S. J. (2016) · The Quarterly Journal of Economics · doi:10.1093/qje/qjw024 · Cited by 12,458
Fiscal Volatility Shocks and Economic Activity
Fernández-Villaverde, J., Guerrón-Quintana, P., Kuester, K., & Rubio-Ramírez, J. (2015) · American Economic Review · doi:10.1257/aer.20121236 · Cited by 938
Hsu, P.-H., Li, K., & Tsou, C.-Y. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3578215 · Cited by 665
Surprise and uncertainty indexes: Real-time aggregation of real-activity macro-surprises
Scotti, C. (2016) · Journal of Monetary Economics · doi:10.1016/j.jmoneco.2016.06.002 · Cited by 339
Christou, C., Cunado, J., Gupta, R., & Hassapis, C. (2017) · Journal of Multinational Financial Management · doi:10.1016/j.mulfin.2017.03.001 · Cited by 267
Metadata
- Authors
- Jurado, K., Ludvigson, S. C., & Ng, S.
- Venue
- American Economic Review
- Publisher
- American Economic Association
- Published
- 2015-03-01
- Volume
- 105
- Issue
- 3
- Pages
- 1177-1216
- ISSN
- 0002-8282 (ISSN-L)
- OpenAlex
- W4236290419
- Cited by
- 2,860
- References
- 0
- FWCI
- 478.31
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
