Does Noise Hurt Economic Forecasts?

58 Pages Posted: 20 Dec 2023 Last revised: 19 Nov 2024

See all articles by Yuan Liao

Yuan Liao

Rutgers, The State University of New Jersey - Department of Economics

Xinjie Ma

Business School, National University of Singapore

Andreas Neuhierl

Washington University in St. Louis - John M. Olin Business School

Zhentao Shi

Department of Economics, the Chinese University of Hong Kong

Date Written: December 9, 2023

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. 

Keywords: machine learning, factor model, double descent, dense signals

JEL Classification: C1,G17,E47

Suggested Citation

Liao, Yuan and Ma, Xinjie and Neuhierl, Andreas and Shi, Zhentao, Does Noise Hurt Economic Forecasts? (December 9, 2023). Available at SSRN: https://ssrn.com/abstract=4659309 or http://dx.doi.org/10.2139/ssrn.4659309

Yuan Liao (Contact Author)

Rutgers, The State University of New Jersey - Department of Economics ( email )

Xinjie Ma

Business School, National University of Singapore ( email )

Andreas Neuhierl

Washington University in St. Louis - John M. Olin Business School ( email )

St. Louis, MO
United States

Zhentao Shi

Department of Economics, the Chinese University of Hong Kong ( email )

Shatin, N.T.
Hong Kong

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