DP15926 Advances in Nowcasting Economic Activity: Secular Trends, Large Shocks and New Data
|Author(s):||Juan Antolin-Diaz, Thomas Drechsel, Ivan Petrella|
|Publication Date:||March 2021|
|Keyword(s):||Bayesian methods, Covid-19 Recession, Daily economic index, Dynamic factor models, Fat Tails, Nowcasting, real-time data|
|JEL(s):||C32, E01, E23, E32, O47|
|Programme Areas:||Monetary Economics and Fluctuations|
|Link to this Page:||cepr.org/active/publications/discussion_papers/dp.php?dpno=15926|
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.