How 538's 2024 presidential election forecast works

Contributing sentiments towards policy:

56% : We also consult a set of economic and political indicators that political scientists and forecasters have collectively dubbed the "fundamentals."
55% : Then, we might find another simulation in which polls underestimate Trump by 4-5 points on the margin — a repeat of what we saw in the 2020 election.
52% : We include these economic and political fundamentals in a Bayesian regression to predict the two-party vote share in each state from 1952 to 2020.
51% : It is also used in a separate regression to make sure potential polling bias is correlated across states — a process detailed in Step 3.This approach can be thought of as predicting polling averages using regression models with various political and demographic variables.
50% : States where the Democratic or Republican vote share has tended to rise and fall in tandem — such as New York and Connecticut — receive higher similarity scores.
46% : We use 11 indicators that have historically correlated with election outcomes:One quick comment on this mix of indicators: Usually when political scientists talk about "fundamental" economic indicators they are referring only to objective metrics of the economy.
46% : Recently, it has also become clear that political polarization is decreasing the electorate's responsiveness to external shocks to the system.
46% : Another is that, as a matter of coincidence, the bias in our fundamentals predictions has tended to counteract bias in the polls; in years like 2020 when the polls underestimated Trump, the fundamentals overestimated his support, generating a combined prediction that was closer to the actual outcome of the election than either component prediction on its own.
41% : Presidential approval ratings are also now dragged down by political and ideological polarization, with a shrinking share of the opposing party that any candidate can win over.
36% : Our model treats districts as separate geographic units similar to states, but with larger confidence intervals.*****Additional research also suggests that voters blame the incumbent party more for a bad economy when the president is running for reelection than when the party runs a new candidate (such as when the incumbent is term-limited).

*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.