| Summary: | 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.
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