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Coronavirus effects on the U.S. unemployment: evidence from Google trends

This paper investigates the relationship between Google search queries of "coronavirus" and "unemployment" using daily data from the United States. The investigation is achieved by employing a structural vector autoregression model, where queries of "interest rate" and "inflation" are also included. Historical decomposition analysis suggests that the spike in the search interest of "unemployment" is mostly explained by that of "coronavirus" in March 2020. The results also show that one unit of a positive shock in the search interest of "coronavirus" leads to 3 units of a significant cumulative increase in that of "unemployment" after one week which increases to 6 units after one month.

Lead investigator:

Hakan Yilmazkuday


Florida International University, Miami

Primary topic:

Attitudes, media & governance

Region of data collection:

North America

Country of data collection


Status of data collection


Type of data being collected:

Publicly available

Unit of real-time data collection


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