Band-Pass Filtering with High-Dimensional Time Series

34 Pages Posted: 16 Jun 2023

See all articles by Alessandro Giovannelli

Alessandro Giovannelli

University of Rome Tor Vergata

Marco Lippi

Einaudi Institute for Economics and Finance (EIEF)

Tommaso Proietti

University of Rome II - Department of Economics and Finance

Date Written: June 15, 2023

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

JEL Classification: C22, C52, C58

Suggested Citation

Giovannelli, Alessandro and Lippi, Marco and Proietti, Tommaso, Band-Pass Filtering with High-Dimensional Time Series (June 15, 2023). CEIS Working Paper No. 559, Available at SSRN: https://ssrn.com/abstract=4480271 or http://dx.doi.org/10.2139/ssrn.4480271

Alessandro Giovannelli

University of Rome Tor Vergata ( email )

Via di Tor Vergata
Rome, Lazio 00133
Italy

Marco Lippi

Einaudi Institute for Economics and Finance (EIEF) ( email )

Via Due Macelli, 73
Rome, 00187
Italy

Tommaso Proietti (Contact Author)

University of Rome II - Department of Economics and Finance ( email )

Via Columbia, 2
Rome, 00133
Italy

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
44
Abstract Views
236
PlumX Metrics