Measuring US Aggregate Output and Output Gap Using Large Datasets

45 Pages Posted: 8 Aug 2018

See all articles by Matteo Barigozzi

Matteo Barigozzi

London School of Economics and Political Science

Matteo Luciani

Federal Reserve Board

Date Written: July 21, 2018

Abstract

We propose new measures of US aggregate output and output gap computed by means of a Non-Stationary Dynamic Factor model estimated on a large dataset of macroeconomic indicators, combined with a non-parametric Trend-Cycle decomposition of the factors. We find that: (i) since 2010 output growth was on average 0.4% higher than measured by GDP, the difference being been concentrated in the first quarter of the year; (ii) while for several consecutive years before the financial crisis the economy operated above its potential, as of 2017:Q4 there is still slack in the economy. Both our measures are robust to data revisions.

Keywords: Gross Domestic Output, Output Gap, Non-stationary Approximate Dynamic Factor Model, Trend-Cycle Decomposition

JEL Classification: C32, C38, C55, E0

Suggested Citation

Barigozzi, Matteo and Luciani, Matteo, Measuring US Aggregate Output and Output Gap Using Large Datasets (July 21, 2018). Available at SSRN: https://ssrn.com/abstract=3217816 or http://dx.doi.org/10.2139/ssrn.3217816

Matteo Barigozzi (Contact Author)

London School of Economics and Political Science ( email )

Houghton Street
London, England WC2A 2AE
United Kingdom

Matteo Luciani

Federal Reserve Board ( email )

20th and C Streets, NW
Washington, DC 20551
United States

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