Measuring the Output Gap Using Large Datasets

62 Pages Posted: 8 Aug 2018 Last revised: 3 Dec 2020

See all articles by Matteo Barigozzi

Matteo Barigozzi

University of Bologna

Matteo Luciani

Board of Governors of the Federal Reserve System

Date Written: December 2, 2020

Abstract

We propose a new measure of the output gap based on a dynamic factor model that is estimated on a large number of U.S. macroeconomic indicators and which incorporates relevant stylized facts about macroeconomic data (co-movements, non-stationarity, and the slow drift in long-run output growth over time). We find that, (1) from the mid-1990s to 2008, the U.S. economy operated above its potential; and, (2) in 2018:Q4, the labor market was tighter than the market for goods and services. Because it is mainly data driven, our measure is a natural complementary tool to the theoretical models used at policy institutions.

Keywords: 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 the Output Gap Using Large Datasets (December 2, 2020). Available at SSRN: https://ssrn.com/abstract=3217816 or http://dx.doi.org/10.2139/ssrn.3217816

Matteo Barigozzi (Contact Author)

University of Bologna ( email )

Piazza Scaravilli 2
Bologna, 40100
Italy

Matteo Luciani

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

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