This paper discusses a large-scale factor model for the German economy. Following the recent literature, a data set of 121 time series is used via principal component analysis to determine the factors, which enter a dynamic model for German GDP. The model is compared with alternative univariate...

This paper considers factor forecasting with national versus factor forecasting with international data. We forecast German GDP based on a large set of about 500 time series, consisting of German data as well as data from Euro-area and G7 countries. For factor estimation, we consider standard...

This paper compares two single-equation approaches from the recent nowcast literature: Mixed-data sampling (MIDAS) regressions and bridge equations. Both approach are used to nowcast a low-frequency variable such as quarterly GDP growth by higher-frequency business cycle indicators. Three...

This paper discusses the forecasting performance of alternative factor models based on a large panel of quarterly time series for the german economy. One model extracts factors by static principals components analysis, the other is based on dynamic principal components obtained using frequency...