DATASET

Germany nowcasting

Collection: EANow : Euro Area Macro-economic nowcasting 

Description

Monthly data set of conventional and uncoventional variables for economic nowcasting in Germany. The variables are aggregated monthly by averaging the latest available value at the time of the data update. The data set gathers country-specific traditional macro-economic series from statistical agencies, as well as big data alternative variables that can provide timely signals of economic developments. Examples of big data variables are text-based sentiment measures, indicators of media attention on economic topics or air quality indicators. For details on the application of the data set for economic nowcasting, check out the work by Barbaglia et al., “Testing Big Data in a Big Crisis: Nowcasting under COVID-19” (March 25, 2022), Available at SSRN: https://ssrn.com/abstract=4066479.

Contact

Email
luca.onorante (at) ec.europa.eu

Contributors

How to cite

Marco Ratto; Luca Tiozzo Pezzoli; Luca Onorante; Lorenzo Frattarolo; Luca Barbaglia (2022): Germany nowcasting. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/08d7791f-ab85-4f5e-8b55-e768e7c0514a

Keywords

big data nowcasting economic forecasting germany

Data access

Macro-economic nowcasting data Germany
URL 

Publications

Publication
Testing Big Data in a Big Crisis: Nowcasting under COVID-19
Barbaglia, Luca and Frattarolo, Lorenzo and Onorante, Luca and Tiozzo Pezzoli, Luca and Pericoli, Filippo M. and Ratto, Marco, Testing Big Data in a Big Crisis: Nowcasting under COVID-19 (March 25, 2022). Available at SSRN: https://ssrn.com/abstract=4066479 or http://dx.doi.org/10.2139/ssrn.4066479

Geographic areas

Germany

Temporal coverage

From date To date
1995-01-01 2022-09-01

Additional information

Published by
European Commission, Joint Research Centre
Created date
2022-07-27
Modified date
2022-09-13
Issued date
2022-07-27
Data theme(s)
Economy and finance
Update frequency
weekly
Identifier
http://data.europa.eu/89h/08d7791f-ab85-4f5e-8b55-e768e7c0514a
Popularity