Digest

The 2024 presidential election forecast has launched, showing Biden and Trump with tied likelihoods of winning, with Biden having a 52% chance and Trump having a 48% chance. The forecast is based on a combination of polls and fundamentals, with the model putting less weight on the polls than people might expect due to the early stage of the election. The forecast considers historical data, including polling volatility and economic indicators, but also acknowledges the uncertainty of unknown unknowns. The model suggests that the election will be close, with a 62% chance of being decided by a smaller margin than the vote share for third-party candidates. The forecast also highlights the importance of tipping point states, with Pennsylvania currently being the likeliest, followed by North Carolina. The model also suggests a 12% chance that Biden wins the popular vote but loses the electoral college, while Trump has a 1% chance of the same outcome. The forecast does not make any pronouncements about polling bias, but it does take into account the higher than average amount of error observed in the past two election cycles. The forecast is a tool to help people understand the uncertainty of elections and to make informed decisions about the potential outcomes.

Outlines

00:00:00

Introduction and Forecast Launch

This Chapter introduces the 2024 presidential election forecast, which has been launched and shows Biden and Trump with tied likelihoods of winning. The forecast shows Biden with a 52% chance of winning and Trump with a 48% chance. The podcast is recorded on June 10th, and the forecast may have changed since then. The forecast can be accessed at 538.com.

00:01:46

Understanding the Forecast: Polls vs. Fundamentals

This Chapter delves into the methodology behind the forecast, explaining the balance between polls and fundamentals. The model gives less weight to polls than expected due to the early stage of the election and the possibility of polling error. The forecast considers historical data on polling volatility and economic indicators, but also acknowledges the uncertainty of unknown unknowns. The chapter discusses the importance of understanding the forecast as a tool for understanding election dynamics rather than a definitive prediction.

00:02:12

Tipping Point States and Electoral College

This Chapter focuses on the concept of tipping point states and the electoral college. The forecast suggests that Pennsylvania is the likeliest tipping point state, followed by North Carolina. The chapter explains how the model calculates tipping point states and the role of national and state-specific movement in the polls. The chapter also discusses the possibility of a split between the popular vote and the electoral college, with a 12% chance that Biden wins the popular vote but loses the electoral college.

00:26:37

Polling Bias and Uncertainty

This Chapter addresses the issue of polling bias and its impact on the forecast. The model does not make any predictions about polling bias, but it does take into account the higher than average amount of error observed in the past two election cycles. The chapter discusses the importance of understanding the forecast as a tool for understanding uncertainty rather than a definitive prediction. The chapter also explores the potential for future revisions to the model based on new data and insights.

00:30:41

The Purpose of the Forecast and Success Metrics

This Chapter discusses the purpose of the forecast and the metrics used to evaluate its success. The forecast is designed to help people understand the uncertainty of elections and to make informed decisions about the potential outcomes. The chapter emphasizes the importance of understanding the forecast as a tool for understanding uncertainty rather than a definitive prediction. The chapter also discusses the importance of considering the histogram of potential outcomes rather than just the point prediction.

00:34:03

Future Forecasts and Down Ballot Races

This Chapter discusses the future plans for the forecast, including the development of forecasts for down ballot races. The chapter also explores the potential for future revisions to the model based on new data and insights. The chapter concludes with a discussion of the importance of understanding the forecast as a tool for understanding uncertainty rather than a definitive prediction.

Keywords

Q&A

• What are the key factors driving the 2024 presidential election forecast?

  The forecast is driven by a combination of polls and fundamentals. The model puts less weight on the polls than people might expect due to the early stage of the election and the possibility of polling error. The forecast also considers historical data on polling volatility and economic indicators, but acknowledges the uncertainty of unknown unknowns.

• What are the likeliest tipping point states in the 2024 election?

  The forecast suggests that Pennsylvania is the likeliest tipping point state, followed by North Carolina. The model calculates tipping point states based on simulations of the election, taking into account both national and state-specific movement in the polls.

• How does the forecast account for polling bias?

  The forecast does not make any pronouncements about polling bias, but it does take into account the higher than average amount of error observed in the past two election cycles. The model simulates polling error based on historical data, acknowledging the possibility of significant errors in polls.

• What is the purpose of the 2024 presidential election forecast?

  The forecast is designed to help people understand the uncertainty of elections and to make informed decisions about the potential outcomes. It is a tool for understanding election dynamics rather than a definitive prediction. The histogram of potential outcomes is a key feature of the forecast, highlighting the range of possible results.

• What are some of the key takeaways from the 2024 presidential election forecast?

  The forecast suggests that the election will be close, with a 62% chance of being decided by a smaller margin than the vote share for third-party candidates. The model also suggests a 12% chance that Biden wins the popular vote but loses the electoral college, while Trump has a 1% chance of the same outcome. The forecast emphasizes the importance of understanding the uncertainty of elections and the need to consider a range of possible outcomes.

Show Notes