Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/187583
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dc.contributor.authorChuliá Soler, Helena-
dc.contributor.authorGarrón, Ignacio-
dc.contributor.authorUribe Gil, Jorge Mario-
dc.date.accessioned2022-07-12T09:56:05Z-
dc.date.available2022-07-12T09:56:05Z-
dc.date.issued2022-
dc.identifier.urihttp://hdl.handle.net/2445/187583-
dc.description.abstractUsing 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.ca
dc.format.extent20 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoengca
dc.publisherUniversitat de Barcelona. Facultat d'Economia i Empresaca
dc.relation.isformatofReproducció del document publicat a: http://www.ub.edu/irea/working_papers/2022/202211.pdf-
dc.relation.ispartofIREA – Working Papers, 2022, IR22/11-
dc.relation.ispartofseries[WP E-IR22/11]ca
dc.rightscc-by-nc-nd, (c) Chuliá Soler et al., 2022-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceDocuments de treball (Institut de Recerca en Economia Aplicada Regional i Pública (IREA))-
dc.subject.classificationAnàlisi de regressió-
dc.subject.classificationMostreig (Estadística)-
dc.subject.classificationUnemployment-
dc.subject.otherRegression analysis-
dc.subject.otherSampling (Statistics)-
dc.subject.otherAtur-
dc.titleMonitoring daily unemployment at riskca
dc.typeinfo:eu-repo/semantics/workingPaperca
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
Appears in Collections:Documents de treball (Institut de Recerca en Economia Aplicada Regional i Pública (IREA))

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