• Graduate Programs
    • Tinbergen Institute Research Master in Economics
      • Why Tinbergen Institute?
      • Research Master
      • Admissions
      • Course Registration
      • PhD Vacancies
      • Selected PhD Placements
    • Facilities
    • Browse our Courses
    • Research Master Business Data Science
    • PhD Vacancies
  • Research
  • Browse our Courses
  • Events
    • Summer School
      • Applied Public Policy Evaluation
      • Deep Learning
      • Economics of Blockchain and Digital Currencies
      • Economics of Climate Change
      • Foundations of Machine Learning with Applications in Python
      • From Preference to Choice: The Economic Theory of Decision-Making
      • Gender in Society
      • Machine Learning for Business
      • Marketing Research with Purpose
      • Sustainable Finance
      • Tuition Fees and Payment
      • Business Data Science Summer School Program
    • Events Calendar
    • Events Archive
    • Tinbergen Institute Lectures
    • 16th Tinbergen Institute Annual Conference
    • Annual Tinbergen Institute Conference
  • News
  • Job Market Candidates
  • Alumni
    • PhD Theses
    • Master Theses
    • Selected PhD Placements
    • Key alumni publications
    • Alumni Community

Keijsers, B. and \van Dijk\, D. (2025). Does economic uncertainty predict real activity in real time? International Journal of Forecasting, 41(2):748--762.


  • Affiliated authors
    Dick van Dijk, Bart Keijsers
  • Publication year
    2025
  • Journal
    International Journal of Forecasting

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.