Real-Time Forecasting of GDP Based on a Large Factor Model with Monthly and Quarterly Data

Deutsche Bundesbank Discussion Paper Series 1: Economic Studies No. 33/06

60 Pages Posted: 28 Feb 2007

See all articles by Christian Schumacher

Christian Schumacher

Deutsche Bundesbank

Jörg Breitung

University of Bonn; Deutsche Bundesbank

Multiple version iconThere are 2 versions of this paper

Date Written: February 2007

Abstract

This paper discusses a factor model for estimating monthly GDP using a large number of monthly and quarterly time series in real-time. To take into account the different periodicities of the data and missing observations at the end of the sample, the factors are estimated by applying an EM algorithm combined with a principal components estimator. We discuss the in-sample properties of the estimator in real-time environments and methods for out-of-sample forecasting. As an empirical application, we estimate monthly German GDP in real-time, discuss the nowcast and forecast accuracy of the model and the role of revisions. Furthermore, we assess the contribution of timely monthly data to the forecast performance.

Keywords: Monthly GDP, EM algorithm, principal components, factor models

JEL Classification: E37, C53

Suggested Citation

Schumacher, Christian and Breitung, Jörg, Real-Time Forecasting of GDP Based on a Large Factor Model with Monthly and Quarterly Data (February 2007). Deutsche Bundesbank Discussion Paper Series 1: Economic Studies No. 33/06, Available at SSRN: https://ssrn.com/abstract=965685 or http://dx.doi.org/10.2139/ssrn.965685

Christian Schumacher (Contact Author)

Deutsche Bundesbank ( email )

Wilhelm-Epstein-Str. 14
Frankfurt/Main, 60431
Germany

Jörg Breitung

University of Bonn ( email )

Postfach 2220
Bonn, D-53012
Germany

Deutsche Bundesbank

Wilhelm-Epstein-Strasse 14
Frankfurt/Main D-60431
Germany

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