We study the forecasting performance of three alternative large scale approaches using a dataset for Germany that consists of 123 variables in quarterly frequency. These three approaches handle the dimensionality problem evoked by such a large dataset by aggregating information, yet on different...

We study the forecasting performance of three alternative large scale approaches for German key macroeconomic variables using a dataset that consists of 123 variables in quarterly frequency. These three approaches handle the dimensionality problem evoked by such a large dataset by aggregating...

Up until now, the concept of compression in single- or multivariate regressions has been limited to the common-frequency case. Having an application of macroeconomic forecasting in mind, one inevitably has to deal with variables sampled at various frequencies. Consequently, this work attempts to...

In this paper we investigate whether differences exist among forecasts using real-time or latest-available data to predict gross domestic product (GDP). We employ mixed-frequency models and real-time data to reassess the role of survey data relative to industrial production and orders in...

The major focus of this paper is to determine whether the accuracy of German macroeconomic forecasts has improved over time. We examine 1-year-ahead forecasts of real GDP and inflation for 1967 to 2001 made by three major German forecasting groups and the OECD. We examine the accuracy of the...