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.
Barigozzi, M., Luciani, M. (2023). Measuring the Output Gap using Large Datasets. THE REVIEW OF ECONOMICS AND STATISTICS, 105(6), 1500-1514 [10.1162/rest_a_01119].
Measuring the Output Gap using Large Datasets
Barigozzi, Matteo;
2023
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.File | Dimensione | Formato | |
---|---|---|---|
RESTAT_Final_Main_doi.pdf
accesso aperto
Tipo:
Postprint
Licenza:
Licenza per accesso libero gratuito
Dimensione
1.79 MB
Formato
Adobe PDF
|
1.79 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.