Nowcasting the Output Gap

37 Pages Posted: 29 Apr 2020 Last revised: 31 Aug 2020

See all articles by Tino Berger

Tino Berger

University of Goettingen (Göttingen) - Department of Economics

James Morley

University of Sydney - School of Economics

Benjamin Wong

Monash University - Department of Econometrics & Business Statistics

Multiple version iconThere are 2 versions of this paper

Date Written: August 20, 2020

Abstract

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.

Keywords: Nowcasting, output gap, COVID-19

JEL Classification: C32, C55, E32

Suggested Citation

Berger, Tino and Morley, James and Wong, Benjamin, Nowcasting the Output Gap (August 20, 2020). Available at SSRN: https://ssrn.com/abstract=3586374 or http://dx.doi.org/10.2139/ssrn.3586374

Tino Berger

University of Goettingen (Göttingen) - Department of Economics ( email )

Platz der Goettinger Sieben 3
Goettingen, 37073
Germany

James Morley (Contact Author)

University of Sydney - School of Economics ( email )

Rm 607 Social Sciences Building
The University of Sydney
Sydney, NSW 2006 2008
Australia

HOME PAGE: http://https://sites.google.com/site/jamescmorley/

Benjamin Wong

Monash University - Department of Econometrics & Business Statistics ( email )

Wellington Road
Clayton, Victoria 3168
Australia

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