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  1. Estimating the Euro Area output gap using multivariate information and addressing the COVID-19 pandemic
    Erschienen: [2022]
    Verlag:  European Central Bank, Frankfurt am Main, Germany

    We estimate the euro area output gap by applying the Beveridge-Nelson decomposition based on a large Bayesian vector autoregression. Our approach incorporates multivariate information through the inclusion of a wide range of variables in the analysis... mehr

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    Verlag (kostenfrei)
    Resolving-System (kostenfrei)
    Resolving-System (kostenfrei)
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    DS 534
    keine Fernleihe

     

    We estimate the euro area output gap by applying the Beveridge-Nelson decomposition based on a large Bayesian vector autoregression. Our approach incorporates multivariate information through the inclusion of a wide range of variables in the analysis and addresses data issues associated with the COVID-19 pandemic. The estimated output gap lines up well with the CEPR chronology of the business cycle for the euro area and we find that hours worked, more than the unemployment rate, provides the key source of information about labor utilization in the economy, especially in pinning down the depth of the output gap during the COVID-19 recession when the unemployment rate rose only moderately. Our findings suggest that labor market adjustments to the business cycle in the euro area occur more through the intensive, rather than extensive, margin.

     

    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Ebook
    Format: Online
    ISBN: 9789289953030
    Weitere Identifier:
    hdl: 10419/269123
    Schriftenreihe: Working paper series / European Central Bank ; no 2716 (August 2022)
    Schlagworte: Beveridge-Nelson decomposition; output gap; Bayesian estimation; multivariate information
    Umfang: 1 Online-Ressource (circa 35 Seiten), Illustrationen