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...

Im Rahmen moderner geldpolitischer Strategien spielt das Konzept des Produktionspotenzials eine wichtige Rolle. Es repräsentiert die nachhaltigen Produktionsmöglichkeiten einer Volkswirtschaft, die ohne Gefahren für die Preisstabilität realisiert werden können. Für eine empirische...

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 estimates and forecasts trend output and output gaps for the Euro area. In the monetary strategy of the European Central Bank (ECB), trend output is used to forecast a reference value for money. For this purpose, trend output must be forecasted as well. In this paper, a...

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...

This paper addresses the relative importance of monetary indicators for forecasting inflation in the euro area in a Bayesian framework. Bayesian Model Averaging (BMA)based on predictive likelihoods provides a framework that allows for the estimation of inclusion probabilities of a particular...

This paper discusses pooling versus model selection for now- and forecasting in the presence of model uncertainty with large, unbalanced datasets. Empirically, unbalanced data is pervasive in economics and typically due to different sampling frequencies and publication delays. Two model classes...