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Title: Advances in Nowcasting Economic Activity: Secular Trends, Large Shocks and New Data

Author(s): Juan Antolin-Diaz, Thomas Drechsel and Ivan Petrella

Publication Date: March 2021

Keyword(s): Bayesian methods, Covid-19 Recession, Daily economic index, Dynamic factor models, Fat Tails, Nowcasting and real-time data

Programme Area(s): Monetary Economics and Fluctuations

Abstract: A key question for households, firms, and policy makers is: how is the economy doing now? We develop a Bayesian dynamic factor model and compute daily estimates of US GDP growth. Our framework gives prominence to features of modern business cycles absent in linear Gaussian models, including secular movements in growth, time-varying uncertainty, and fat tails. We also incorporate newly available high-frequency data on consumer behavior. The model beats benchmark econometric models and survey expectations at predicting GDP growth over two decades, and advances our understanding of macroeconomic data during the COVID-19 pandemic.

For full details and related downloads, please visit: https://cepr.org/active/publications/discussion_papers/dp.php?dpno=15926

Bibliographic Reference

Antolin-Diaz, J, Drechsel, T and Petrella, I. 2021. 'Advances in Nowcasting Economic Activity: Secular Trends, Large Shocks and New Data'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=15926