So, the ‘most closely contested election in US history™’ is over and, predictably, it turned out to be a bit of a damp squib, at least for those looking for a contest.
Similar to previous election cycles, the inquest into how and why the polls were wrong has begun again.
But how wrong were the polls? Were they really predicting such a close race, or was much of that just press hype?
Quick Summary
- Polls Missed Again: Trump defied expectations, winning the popular vote and sweeping all key swing states.
- Surprising Demographic Shifts: Gains among Latino and Black voters reshaped the political landscape.
- Polling Errors Exposed: Sampling biases, shy voters, and outdated models led to miscalculations.
- Economic Concerns Ruled: Voters prioritized jobs and inflation, favoring Trump’s policies.
- Lessons for 2028: Pollsters must rethink methods to adapt to evolving voter behavior.
Polls and Final Results
Throughout the campaign, all the national polls and the polls in the seven key swing states indicated there was barely any daylight between Trump and Harris. Polling averages suggested that Harris would maintain a slight edge nationally, and gave her narrow leads in at least three swing states.
However, as the results came in, it became clear that Trump had won the popular vote and secured victories in all the crucial swing states, not just the four he probably needed to win the White House.
Once again, there was a significant underestimation of Trump’s support, which has been a recurring theme in recent elections. Trump’s ability to rally support among key demographics seems to have shifted the landscape significantly and caught pollsters and commentators unaware.
Swing State Analysis
In battleground states like Arizona and Wisconsin, polling had indicated competitive races. While Trump’s final margins were often within a few points of polling predictions, he outperformed expectations in all areas. For instance, in Pennsylvania, where polls showed a slight lead for Harris, Trump managed to flip the state with a 2 point victory. In fact, his results in all the swing states were between 1 and 4 points higher than polls predicted.
National Polling Discrepancies
At the national level, the pollsters expected Harris to maintain a slight edge. However, Trump’s ability to rally support among key demographics shifted the landscape significantly. The media’s portrayal of a close race may have contributed to an underestimation of Trump’s appeal among certain voter groups.
While the final national polls gave Harris a slim lead in the popular vote, in the end, Trump won it by about 1.5% or 2.5 million votes.
Margin of Error
All polls come with a margin of error of around 3% to 4%. Most pollsters were quite candid in admitting that both a Harris win and a Trump win were within the margin of error. So, were the final results within that margin of error or outside of it?
Harris held a 1.2% lead in the final round of national polls, and Trump finally won by 1.5%, which is a swing of 2.7%, which would be just within the margin of error of most polls.
In the swing states, the most marked difference between the polls and results was in Nevada, where Trump’s polling lead of less than 1% translated into a 4% victory. This is on the very edge of the margin of error.
The average difference between the final polls and actual results in most swing states was relatively small, within the margin of error, which just shows that even minor inaccuracies in polling forecasts can lead to substantial differences in the final outcome in tight races.
Interestingly, the discrepancies between the polls and final results were much larger in less hotly contested states. For example, in Florida, the polls predicted a narrow lead of about five points for Trump, but he ultimately won by 13 points. In New Jersey, Harris was expected to win by nearly 20 points but secured only a 10-point margin.
These numbers highlight how polling can miss critical shifts in voter sentiment, particularly if they happen late in a campaign. It may also suggest that the voter turnout and demographic models that pollsters use to interpret the raw data they collect may, in some cases, be based on assumptions that turn out to be false.
Demographic Shifts
The pattern in all three recent elections of underestimating Trump’s support has raised questions about polling methodologies and assumptions about voter behavior. Where pollsters relied on historical voting patterns, did they do so without accounting for significant demographic shifts which appear to have occured between elections?
Latino Voter Movement Toward Trump
One of the most notable demographic shifts was among Latino voters. Trump’s campaign successfully appealed to this group by focusing on economic issues and cultural values that resonated with many Latino communities. His messaging around job creation and economic growth attracted more support than anticipated.
Changes in Black Voter Support
While Harris maintained strong support among Black voters (approximately 83%), there was a slight decline from Biden’s performance in 2020. Trump’s outreach efforts and messaging aimed at addressing economic concerns appeared to resonate with some segments of Black voters, particularly younger and urban demographics.
Youth Vote
The youth vote proved to be less favorable for Harris than expected. While she secured a majority among young voters (ages 18-29), her support dropped compared to Biden’s performance in 2020. This decline reflects potential disengagement or disillusionment among younger voters regarding her campaign.
Gender Gap
The gender gap also played a crucial role in the election outcome. While Harris performed well among women overall, she struggled with older women who leaned more towards Trump. This shift highlights the complexities within gender demographics that can influence election results.
Polling Methodology Issues
Most demographic voting shifts appear to have happened right under our noses without being fully picked up by the polls. Where could the issues be?
Response Rate Challenges
One significant challenge faced by pollsters was declining response rates. Obtaining representative samples has become more difficult as people become increasingly adept at screening calls from unknown numbers. This decline disproportionately affected responses from specific demographics, particularly those more likely to support Trump.
Online vs Traditional Polling
The shift toward online polling methods has had mixed results. While online surveys can reach younger and more tech-savvy populations, they often lack representativeness due to self-selection bias—those who choose to participate may not reflect broader voting patterns.
Sampling Biases
Sampling biases have also contributed to inaccuracies in polling results. Many polls failed to adequately represent working-class voters and rural populations who tend to support Trump more strongly than urban voters.
Social Desirability Bias
The “shy” Trump voter effect—where supporters may be reluctant to disclose their preferences—has been cited as another reason for polling inaccuracies. This social desirability bias can lead to underreporting support for candidates viewed unfavorably by certain segments of society.
Other Contributing Factors
Elections are not just decided on the candidates’ strengths, personalities, or campaigns. The issues and trends of the day ultimately sway voters.
Incumbency Issues
2024 has not been a good year to go to the polls if you’re an incumbent government. Incredibly, every governing party that has faced its electorate this year has lost vote share by between 5% and 20%. In this context, Harris’s performance was at the more respectable end of the scale.
The diagram below shows the increase or decrease in vote share of incumbent governments (compared to the previous election) for all elections in developed countries since 1950. As you can clearly see, 2024 is the only year in which every incumbent government lost vote share.
Voters the world over are angry about jobs, the cost of living, and economic opportunity. Governments that were in power during the pandemic, on which many of those ills are still blamed, are paying the price.
Voter Concerns by Preferred Candidate
Economic issues, as always, played a significant role in shaping voter sentiment during this election cycle. Concerns about inflation and its impact on daily life resonated with many voters who felt their economic security was at risk.
The economy was the main issue for all voters and by far the number one priority of Trump voters. Health care and Supreme Court appointments were the top two concerns for Harris supporters, followed by the economy.
Many credited former President Donald Trump’s policies with enhancing job opportunities and stimulating economic growth, influencing undecided voters to support his campaign. Exit polls indicated that a significant portion of the electorate believed Trump would better manage the economy than Harris. Given voters’ importance on this single issue, it is likely the most important factor in deciding the election.
Lessons for Future Elections
As always, in the aftermath of an election, pollsters and commentators rush out their judgments on how accurate or otherwise the polls were and how things can be improved for next time.
Better Models and Samples
To improve accuracy in future elections, pollsters will be reassessing their methodologies and adapting to changing voter dynamics. Relying on historical data without accounting for demographic shifts can lead to significant inaccuracies.
Incorporating diverse sampling methods that reach underrepresented groups is crucial for obtaining accurate insights into voter sentiment. Pollsters will be doing more to actively seek out participants from various backgrounds to ensure broader representation. This might also mean more micro-targeting voters geographically to build a representative sample that includes all counties and regions of a state.
Additional Polling Methods
Exploring alternative polling methods—such as mixed-mode approaches that combine online surveys with traditional phone interviews—can enhance accuracy and reliability.
Recommendations for Improvement
- Mixed-Mode Polling Approaches:
- Utilizing online and traditional methods can help capture a broader range of voter opinions while mitigating biases inherent in any single method.
- Better Demographic Weighting:
- Adjusting samples based on demographic data such as age, race, and education can improve representativeness and accuracy in polling results.
- Enhanced Turnout Modeling:
- Developing more sophisticated models that account for changing turnout patterns will help predict electoral outcomes more accurately.
- Response Rate Solutions:
- Implementing strategies to increase response rates—such as offering incentives or using varied outreach methods—can help ensure more comprehensive data collection.
Looking Ahead to 2028
As we look forward to future elections, it is clear that many pollsters will be making significant changes to their polling methodologies. Embracing new technologies and methodologies will be essential to accurately capture public sentiment in what’s suddenly become a reshaped and increasingly complex political landscape.
Transparency in polling practices will also be vital for rebuilding trust with the electorate as we move toward the next presidential election cycle.
