Nowcasting Consumer Price Inflation in Germany with Retailer and Household Scanner Data


Guenter W. Beck
University of Siegen and Miggroprices

Kai Carstensen
Kiel University

Jan-Oliver Menz
Deutsche Bundesbank

Richard Schnorrenberger
Kiel University

In our research project, we aim to explore the extend to which both retail and household scanner data can provide a value-added to measuring and forecasting consumer price inflation. Notably, we seek to evaluate the potential of these data sets to construct reliable high-frequency real-time measures (nowcasts) of official consumer price inflation.

Working papers:
Beck, G.W., Carsten, K., Menz, J.-O., Schnorrenberger R. and E. Wieland (2022). Using high-frequency scanner data to evaluate German food prices in real time. Download paper.
A VoxEu article based on the paper is available here: