Although the U.S. case has been studied extensively, the importance of job finding and separation rates to unemployment variability remains unsettled. The aim of this paper is to contribute to this debate by adopting a novel lens, wavelet analysis. We resort to wavelet analysis to unveil time- and frequency-varying features regarding the contribution of the job finding and job separation rates for the U.S. unemployment rate dynamics. Drawing on this approach, we are able to reconcile some apparently contradictory findings reported in previous literature. We find that the job finding rate is more influential for the overall unemployment behaviour but the job separation rate also plays a critical role, especially during recessions. In particular, the job separation rate accounts for, on average, 53 percent of the unemployment variability at short-run fluctuations during recessions, in sharp contrast with an overall contribution of 21 percent over time and across frequencies.
Authors: Pedro Portugal, António Rua
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The covid19 pandemic has brought back the discussion on Unconditional Basic Income, as a possible solution to tackle some of our current and future challenges. The experiments and initiatives in the US (e.g. Mayors for Guaranteed Income) and the surge in pilots in Europe (e.g. most recently in Berlin) have triggered the debate, and raised new questions about the prospects of implementing such a policy. Watch this discussion jointly organized by CEPS - University of Minho and Nova SBE Economics of Policy.Learn more
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