EconPapers    
Economics at your fingertips  
 

Band-Pass Filtering with High-Dimensional Time Series

Alessandro Giovannelli, Marco Lippi and Tommaso Proietti

No 559, CEIS Research Paper from Tor Vergata University, CEIS

Abstract: The paper deals with the construction of a synthetic indicator of economic growth, obtained by projecting a quarterly measure of aggregate economic activity, namely gross domestic product (GDP), into the space spanned by a finite number of smooth principal components, representative of the medium-to-long-run component of economic growth of a high-dimensional time series, available at the monthly frequency. The smooth principal components result from applying a cross-sectional filter distilling the low-pass component of growth in real time. The outcome of the projection is a monthly nowcast of the medium-to-long-run component of GDP growth. After discussing the theoretical properties of the indicator, we deal with the assessment of its reliability and predictive validity with reference to a panel of macroeconomic U.S. time series.

Keywords: Nowcasting; Principal Components Analysis; Macroeconomic Indicators (search for similar items in EconPapers)
JEL-codes: C22 C52 C58 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2023-06-15, Revised 2023-06-15
New Economics Papers: this item is included in nep-gro and nep-mfd
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ceistorvergata.it/RePEc/rpaper/RP559.pdf Main text (application/pdf)

Related works:
Working Paper: Band-Pass Filtering with High-Dimensional Time Series (2023) 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:rtv:ceisrp:559

Ordering information: This working paper can be ordered from
CEIS - Centre for Economic and International Studies - Faculty of Economics - University of Rome "Tor Vergata" - Via Columbia, 2 00133 Roma
https://ceistorvergata.it

Access Statistics for this paper

More papers in CEIS Research Paper from Tor Vergata University, CEIS CEIS - Centre for Economic and International Studies - Faculty of Economics - University of Rome "Tor Vergata" - Via Columbia, 2 00133 Roma. Contact information at EDIRC.
Bibliographic data for series maintained by Barbara Piazzi ().

 
Page updated 2024-06-08
Handle: RePEc:rtv:ceisrp:559