Nowcasting the output gap

Tino Berger, James Morley, Benjamin Wong

Research output: Contribution to journalArticleResearchpeer-review

15 Citations (Scopus)


We propose a way to directly nowcast the output gap using the Beveridge–Nelson decomposition based on a mixed-frequency Bayesian VAR. The mixed-frequency approach produces similar but more timely estimates of the U.S. output gap compared to those based on a quarterly model, the CBO measure of potential, or the HP filter. We find that within-quarter nowcasts for the output gap are more reliable than for output growth, with monthly indicators for a credit risk spread, consumer sentiment, and the unemployment rate providing particularly useful new information about the final estimate of the output gap. An out-of-sample analysis of the COVID-19 crisis anticipates the exceptionally large negative output gap of −8.3% in 2020Q2 before the release of real GDP data for the quarter, with both conditional and scenario nowcasts tracking a dramatic decline in the output gap given the April data.

Original languageEnglish
Pages (from-to)18-34
Number of pages17
JournalJournal of Econometrics
Issue number1
Publication statusPublished - Jan 2023


  • COVID-19
  • Nowcasting
  • Output gap

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