ABFR Webinar with Andreas Neuhierl and Michael McCracken

Описание: Title: Does Noise Hurt Economic Forecast?
Presenter: Andreas Neuhierl (Purdue University)
Discussant: Michael McCracken (Fed - St. Louis)
Host: Svetlana Bryzgalova (London Business School)
Date: Feb 26, 2026 12-1pm Eastern Time

00:00:00​​​ Welcome remarks
00:01:30 Presentation
00:32:00 Discussion
00:50:10 Q&A

Abstract:
This paper explores whether variable selection enhances economic forecasting. While economists often remove noise from predictors, we show that economic forecast models are not sparse if the outcome is driven by latent factors. We also prove a compelling result that including noise in predictions yields greater benefits than excluding it. Empirically, we apply this method to four common forecasting applications including forecasting the U.S. inflation rate and obtain results that surpass many commonly used models that rely on dimension reduction or variable selection.

ABFR:
ABFR is an interdisciplinary community of scholars with an interest in the methodology, applications, and socioeconomic implications of AI and big data for a wide range of areas in economics and finance. The forum organizes monthly presentations and discussions of papers by the leading world experts in the area, followed by an informal general post-seminar discussion. The virtual talks take place on the last Thursday
of each month from 12-1pm ET. For more information about the seminar series, including registration, please visit our website:
https://www.abfr-forum.org​​

ABFR is organized by Maryam Farboodi, Serhiy Kozak, Andy Neuhierl, Markus Pelger, and Lea Stern. It is also supported by Svetlana Bryzgalova, Lin William Cong, and The Advisory Committee, which includes Kay Giesecke, Gerald Hoberg, Wei Jiang, Bryan Kelly, Stefan Nagel, Andrew Patton, and Laura Veldkamp. ABFR hosting institutions are the Cornell FinTech Initiative and the Stanford AFTLab.