Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/230388
Authors: 
Aaronson, Daniel
Brave, Scott A.
Butters, R. Andrew
Sacks, Daniel
Seo, Boyoung
Year of Publication: 
2020
Series/Report no.: 
Working Paper No. 2020-10
Abstract: 
We leverage an event-study research design focused on the seven costliest hurricanes to hit the US mainland since 2004 to identify the elasticity of unemployment insurance filings with respect to search intensity. Applying our elasticity estimate to the state-level Google Trends indexes for the topic "unemployment", we show that out-of-sample forecasts made ahead of the official data releases for March 21 and 28 predicted to a large degree the extent of the Covid-19 related surge in the demand for unemployment insurance. In addition, we provide a robust assessment of the uncertainty surrounding these estimates and demonstrate their use within a broader forecasting framework for US economic activity.
Subjects: 
unemployment insurance
Google Trends
hurricanes
search
unemployment
Covid-19
JEL: 
H12
J65
C53
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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