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

Aysegul Sahin, Murat Tasci, Jin Yan

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 the 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 decline to 5.4 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

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Year of publication:	February 2021
Authors:	Şahin, Ayşegül ; Tasci, Murat ; Yan, Jin
Institutions:	National Bureau of Economic Research (issuing body)
Publisher:	2021: Cambridge, Mass : National Bureau of Economic Research
Subject:	Arbeitsmarktprognose \| Employment forecast \| Prognoseverfahren \| Forecasting model \| Coronavirus \| USA \| United States

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