Advances in nowcasting economic activity: The role of heterogeneous dynamics and fat tails

Juan Antolín-Díaz, Thomas Drechsel and Ivan Petrella

Journal of Econometrics, 2024, vol. 238, issue 2

Abstract: A key question for households, firms, and policy makers is: how is the economy doing now? This paper develops a Bayesian dynamic factor model that allows for nonlinearities, heterogeneous lead–lag patterns and fat tails in macroeconomic data. Explicitly modeling these features changes the way that different indicators contribute to the real-time assessment of the state of the economy, and substantially improves the out-of-sample performance of this class of models. In a formal evaluation, our nowcasting framework beats benchmark econometric models and professional forecasters at predicting US GDP growth in real time.

Keywords: Nowcasting; Dynamic factor models; Real-time data; Bayesian methods; Fat tails (search for similar items in EconPapers)
JEL-codes: C32 E01 E23 E32 O47 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:238:y:2024:i:2:s0304407623003500

DOI: 10.1016/j.jeconom.2023.105634

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