Summary 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 to determine the factors by principal component analysis. The factors enter a linear dynamic model for German GDP. To evaluate its empirical...

In this paper the forecasting performance of popular leading indicators for the German business cycle is investigated. Survey based indicators (ifo business climate, ZEW index of economic sentiment) and composite leading indicators (Handelsblatt, Frankfurter Allgemeine Zeitung, Commerzbank) are...

Summary This paper provides a review of the recent literature concerned with large factor models as forecast devices.We focus on factor models that account for mixed-frequency data and missing observations at the end of the sample. These are data irregularities applied forecasters have to cope...

Mixed-data sampling (MIDAS) regressions allow to estimate dynamic equations that explain a low-frequency variable by high-frequency variables and their lags. When the difference in sampling frequencies between the regressand and the regressors is large, distributed lag functions are typically...

This paper compares the mixed-data sampling (MIDAS) and mixed-frequency VAR (MF-VAR) approaches to model specification in the presence of mixed-frequency data, e.g. monthly and quarterly series. MIDAS leads to parsimonious models which are based on exponential lag polynomials for the...