Does economic uncertainty predict real activity in real time?

Bart Keijsers*, Dick van Dijk

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

We assess the predictive ability of 15 economic uncertainty measures in a real-time out-of-sample forecasting exercise for The Conference Board's coincident economic index and its components (industrial production, employment, personal income, and manufacturing and trade sales). The results show that the measures hold (real-time) predictive power for quantiles in the left tail. Because uncertainty measures are all proxies of an unobserved entity, we combine their information using principal component analysis. A large fraction of the variance of the uncertainty measures can be explained by two factors: a general economic uncertainty factor with a slight tilt toward financial conditions, and a consumer/media confidence index which remains elevated after recessions. Using a predictive regression model with the factors from the set of uncertainty measures yields more consistent gains compared to a model with an individual uncertainty measure. Further, although accurate forecasts are obtained using the National Financial Conditions Index (NFCI), the uncertainty factor models are better when forecasting employment, and in general, the uncertainty factors have predictive content that is complementary to the NFCI.

Original languageEnglish
Pages (from-to)748-762
JournalInternational Journal of Forecasting
Volume41
Issue number2
DOIs
Publication statusPublished - Apr 2025

Bibliographical note

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© 2024 The Author(s)

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