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Monitoring daily unemployment at risk

Helena Chuliá (), Ignacio Garrón () and Jorge Uribe ()
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Ignacio Garrón: Department of Econometrics and Statistics, University of Barcelona.

No 202211, IREA Working Papers from University of Barcelona, Research Institute of Applied Economics

Abstract: Using a high-frequency framework, we show that the Auroba-Diebold-Scotti (ADS) daily business conditions index significantly increases the accuracy of U.S. unemployment nowcasts in real-time. This is of particular relevance in times of recession, such as the Global Financial Crisis and the Covid-19 pandemic, when the unemployment rate is prone to rise steeply. Based on our results, the ADS index presents itself as a better predictor than the financial indicators widely used by the literature and central banks, including both interest and credit spreads and the VXO.

Keywords: Quantile regressions; Mixed-data sampling; Nowcast; Unemployment rate. JEL classification: C54; E23; E24; E27; E32. (search for similar items in EconPapers)
Pages: 20 pages
Date: 2022-07, Revised 2022-07
New Economics Papers: this item is included in nep-ban
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