Dear colleagues,
The Department of Economics cordially invites you to the WU
Research Seminar in Economics on Wednesday, January
7th, with Kai Carstensen (https://www.stat-econ.uni-kiel.de/en/team/prof-dr-kai-carstensen?set_language=en) presenting:
" Nowcasting consumer price inflation using high-frequency scanner data: evidence from Germany".
Abstract: We study how millions of granular and weekly household scanner data combined with machine learning can help to improve the real-time nowcast of German inflation. Our nowcasting exercise targets three hierarchy
levels of inflation: individual products, product groups, and headline inflation. At the individual product level, we construct a large set of weekly scanner-based price indices that closely match their official counterparts, such as butter and coffee beans.
Within a mixed-frequency setup, these indices significantly improve inflation nowcasts already after the first seven days of a month. For nowcasting product groups such as processed and unprocessed food, we apply shrinkage estimators to exploit the large set
of scanner-based price indices, resulting in substantial predictive gains over autoregressive time series models. Finally, by adding high-frequency information on energy and travel services, we construct competitive nowcasting models for headline inflation
that are on par with, or even outperform, survey-based inflation expectations.
With best regards,
Harald Oberhofer
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Univ.-Prof. Dr. Harald Oberhofer
Department of Economics
WU Vienna University of Economics and Business
Phone: +43/1/31336-4984
Email: harald.oberhofer@wu.ac.at
https://www.wu.ac.at/en/economics/people/oberhofer-h
Austrian Institute of Economic Research (WIFO)
Phone: +43/1/7982601-468
Email: harald.oberhofer@wifo.ac.at
http://www.wifo.ac.at/harald_oberhofer