Information, incentives, and goals in election forecasts

Andrew Gelman*, Jessica Hullman, Christopher Wlezien, George Elliott Morris

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Presidential elections can be forecast using information from political and economic conditions, polls, and a statistical model of changes in public opinion over time. However, these “knowns” about how to make a good presidential election forecast come with many unknowns due to the challenges of evaluating forecast calibration and communication. We highlight how incentives may shape forecasts, and particularly forecast uncertainty, in light of calibration challenges. We illustrate these challenges in creating, communicating, and evaluating election predictions, using the Economist and Fivethirtyeight forecasts of the 2020 election as examples, and offer recommendations for forecasters and scholars.

Original languageEnglish (US)
Pages (from-to)863-880
Number of pages18
JournalJudgment and Decision Making
Issue number5
StatePublished - Sep 1 2020


  • Elections
  • Forecasting
  • Polls
  • Probability

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Applied Psychology
  • Economics and Econometrics


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