This paper proposes a new method of forecasting euro area quarterly real GDP that uses area-wide indicators, which are derived by optimally pooling the information contained in national indicator series. Following the ideas of predictive modeling, we construct the area-wide indicators by...

In this report we document the ETLAnow project. ETLAnow is a model for forecasting with big data. At the moment, it predicts the unemployment rate in the EU-28 countries using Google search data. This document is subject to updates as the ETLAnow project advances.

Accurate real-time macroeconomic data are essential for policy-making and economic nowcasting. In this paper, I introduce a real-time database for German regional economic accounts (READ-GER). The database contains real-time information for nine macroeconomic aggregates and the 16 German states....

This paper proposes a new method of forecasting euro area quarterly real GDP that uses areawide indicators, which are derived by optimally pooling the information contained in national indicator series. Following the ideas of predictive modeling, we construct the area-wide indicators by...

"Big data" is becoming an increasingly important aspect of our daily lives as the digital sources of information and intelligence that it encompasses become more structured and more publicly available. These sources may enable the generation of new datasets providing high-frequency and timely...

In this paper, we propose a framework to evaluate the information content of subjective expert density forecasts using micro data from the ECB's Survey of Professional Forecasters (SPF). A key aspect of our analysis is the use of scoring functions which evaluate the entire predictive densities,...

Euro area labour market variables are published with a considerable lag, longer than in the case of real GDP. We develop a suite of models to provide a more timely estimate (nowcast) of euro area quarterly employment growth based on a broad range of monthly indicators. The suite includes a batch...

This paper compares within-sample and out-of-sample fit of a DSGE model with rational expectations to a model with adaptive learning. The Galí, Smets and Wouters model is the chosen laboratory using quarterly real-time euro area data vintages, covering 2001Q1-2019Q4. The adaptive learning model...

Empirical estimations of the drivers for loan extension mainly apply the outstanding stock of bank credit as the dependent variable. This paper picks up the critique of Behrendt (2016), namely that such estimations may lead to misleading results, as the change of the stock is not only driven by...

This paper – which takes into consideration overall experience with the Harmonised Index of Consumer Prices (HICP) as well as the improvements made to this measure of inflation since 2003 – finds that the HICP continues to fulfil the prerequisites for the index underlying the ECB’s...