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http://hdl.handle.net/2445/187583
Title: | Monitoring daily unemployment at risk |
Author: | Chuliá Soler, Helena Garrón, Ignacio Uribe Gil, Jorge Mario |
Keywords: | Anàlisi de regressió Mostreig (Estadística) Unemployment Regression analysis Sampling (Statistics) Atur |
Issue Date: | 2022 |
Publisher: | Universitat de Barcelona. Facultat d'Economia i Empresa |
Series/Report no: | [WP E-IR22/11] |
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. |
Note: | Reproducció del document publicat a: http://www.ub.edu/irea/working_papers/2022/202211.pdf |
It is part of: | IREA – Working Papers, 2022, IR22/11 |
URI: | http://hdl.handle.net/2445/187583 |
Appears in Collections: | Documents de treball (Institut de Recerca en Economia Aplicada Regional i Pública (IREA)) |
Files in This Item:
File | Description | Size | Format | |
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IR22_011_Chulia+Garron+Uribe.pdf | 2.1 MB | Adobe PDF | View/Open |
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