Unemployment in the Time of COVID-19: A Flow-Based Approach to Real-time Unemployment Projections

Ayşegül Şahin (), Murat Tasci and Jin Yan ()
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Jin Yan: https://liberalarts.utexas.edu/economics/phd/profile.php?id=jy9777

No 21-25, Working Papers from Federal Reserve Bank of Cleveland

Abstract: This paper presents a flow-based methodology for real-time unemployment rate projections and shows that this approach performed considerably better at the onset of the COVID-19 recession in spring 2020 in predicting the peak unemployment rate as well as its rapid decline over the year. It presents an alternative scenario analysis for 2021 based on this methodology and argues that the unemployment rate is likely to end slightly below 5 percent by the end of 2021. The predictive power of the methodology comes from its combined use of real-time data with the flow approach.

Keywords: D21; J6; R1 (search for similar items in EconPapers)
Pages: 29
Date: 2021-11-09
New Economics Papers: this item is included in nep-lab and nep-mac
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Citations: View citations in EconPapers (3)

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https://doi.org/10.26509/frbc-wp-202125 Full Text (text/html)

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Working Paper: Unemployment in the Time of COVID-19: A Flow-Based Approach to Real-time Unemployment Projections (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedcwq:93330

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DOI: 10.26509/frbc-wp-202125

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