Unemployment in the Time of COVID-19: A Flow-Based Approach to Real-time Unemployment Projections
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.
We thank seminar participants at Columbia University and at the Dallas Fed. The views expressed in this paper are the authors' own, and do not necessarily represent the views of the Federal Reserve Bank of Cleveland, the Board of Governors of the Federal Reserve System, or the National Bureau of Economic Research.