• Medientyp: E-Book
  • Titel: Measuring Output Gap Nowcast Uncertainty
  • Beteiligte: Vahey, Shaun P. [Verfasser:in]; Mitchell, James [Verfasser:in]; Garratt, Anthony [Verfasser:in]
  • Erschienen: [S.l.]: SSRN, 2011
  • Erschienen in: CAMA Working Paper ; No. 16/2011
  • Umfang: 1 Online-Ressource (24 p)
  • Sprache: Englisch
  • DOI: 10.2139/ssrn.1868687
  • Identifikator:
  • Entstehung:
  • Anmerkungen: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments June 1, 2011 erstellt
  • Beschreibung: We propose a methodology to gauge the uncertainty in output gap nowcasts across a large number of commonly deployed vector autoregressions in US inflation and various measures of the output gap. Our approach constructs ensemble nowcast densities using a linear opinion pool. This yields well-calibrated nowcasts for US inflation in real time from 1991q2 to 2010q1, in contrast to those from a univariate autoregressive benchmark. The ensemble nowcast densities for the output gap are considerably more complex than for a single VAR specification. They cannot be described adequately by the first two moments of the forecast densities. To illustrate the usefulness of our approach, we calculate the probability of a negative output gap at around 45 percent between 2004 and 2007. Despite the Greenspan policy regime, and some large point estimates of the output gap, there remained a substantial risk that output was below potential in real time. Our ensemble approach also facilitates probabilistic assessments of “alternative scenarios”. A “dove” scenario (based on distinct output gap measurements) typically raises substantially the probability of a negative output gap (including 2004 through 2007) but has little impact in slumps, in our illustrative example
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