Replication data for: Measuring Uncertainty

Principal Investigator(s):  View help for Principal Investigator(s) Kyle Jurado; Sydney C. Ludvigson; Serena Ng

Version:  View help for Version V1

Name File Type Size Last Modified
README.txt text/plain 2.3 KB 10/11/2019 09:17:PM
aggu.mat application/octet-stream 14.5 MB 10/11/2019 09:17:PM
calibratef.m text/plain 435 bytes 10/11/2019 09:17:PM
ceevardata.xlsx application/vnd.openxmlformats-officedocument.spreadsheetml.sheet 180.5 KB 10/11/2019 09:17:PM
compute_uf.m text/plain 1.2 KB 10/11/2019 09:17:PM
compute_uy.m text/plain 1.9 KB 10/11/2019 09:17:PM
factors.m text/plain 3.3 KB 10/11/2019 09:17:PM
generate_aggu.m text/plain 1.1 KB 10/11/2019 09:17:PM
generate_arferrors.m text/plain 1 KB 10/11/2019 09:17:PM
generate_arsvdraws.r text/plain 1.1 KB 10/11/2019 09:17:PM

Project Description

Summary:  View help for Summary 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)

Scope of Project

JEL Classification:  View help for JEL Classification
      C53 Forecasting Models; Simulation Methods
      D81 Criteria for Decision-Making under Risk and Uncertainty
      E32 Business Fluctuations; Cycles
      G12 Asset Pricing; Trading Volume; Bond Interest Rates
      G35 Payout Policy
      L25 Firm Performance: Size, Diversification, and Scope


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Published Versions

V1 [2019-10-12]

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