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Measuring Output Gap Nowcast Uncertainty

  • Anthony Garratt

    ()

  • James Mitchell

    ()

  • Shaun P. Vahey

    ()

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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File URL: https://cama.crawford.anu.edu.au/pdf/working-papers/2011/162011.pdf
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Paper provided by Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University in its series CAMA Working Papers with number 2011-16.

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Length: 24 pages
Date of creation: Jun 2011
Date of revision:
Handle: RePEc:een:camaaa:2011-16
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