EconPapers    
Economics at your fingertips  
 

Nowcasting in Real Time Using Popularity Priors

George Monokroussos

MPRA Paper from University Library of Munich, Germany

Abstract: This paper proposes a Bayesian nowcasting approach that utilizes information coming both from large real-time data sets and from priors constructed using internet search popularity measures. Exploiting rich information sets has been shown to deliver significant gains in nowcasting contexts, whereas popularity priors can lead to better nowcasts in the face of model and data uncertainty in real time, challenges which can be particularly relevant during turning points. It is shown, for a period centered on the latest recession in the United States, that this approach has the potential to deliver particularly good real-time nowcasts of GDP growth.

Keywords: Nowcasting; Gibbs Sampling; Factor Models; Kalman Filter; Real-Time Data; Google Trends; Monetary Policy; Great Recession. (search for similar items in EconPapers)
JEL-codes: C11 C22 C53 E37 E52 (search for similar items in EconPapers)
Date: 2015-11-01
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/68594/1/MPRA_paper_68594.pdf original version (application/pdf)

Related works:
Journal Article: Nowcasting in real time using popularity priors (2020) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:68594

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().

 
Page updated 2025-03-19
Handle: RePEc:pra:mprapa:68594