Fear and Loathing in the American Electorate: Part 2

Demographic predictors of 2020 vote

Steve Genco


Photo credit: 1931 still from the movie Frankenstein

This is Part 2 of an eight-part exploration of the 2020 American National Election Study, focusing on the motivations and sources of information driving the American electorate, especially the Republican/conservative voters who cast their votes for Donald Trump in 2020. Here are quick links to the other seven parts.

  • Part 1: The most important question facing American democracy today
  • Part 3: Media consumption — Where do voters get their information and what difference does it make?
  • Part 4: Seven “deplorable” beliefs that predict 2020 Presidential vote
  • Part 5: The role of conspiracies and misinformation in the 2020 election
  • Part 6: Partisan animosity
  • Part 7: Combining sources of behavior — Path models of the 2020 Presidential vote
  • Part 8: Republicans have crossed the Rubicon — Conclusions and implications

Let’s begin with a few facts about the election. Voter turnout was high in 2020. People who reported voting made up about 77% of the respondents in the ANES post-election survey. Since the official recorded turnout in the election was 67% of all citizens 18 and over,¹ there appears to be a fair amount of wishful thinking built into these numbers. But even at 67%, turnout was historically high in 2020.

Here is how people reported their votes for President.

The official tally for the Presidential race was 51.3% for Biden (81,268,924 votes) and 46.9% for Trump (74,216,154 votes). The approximate 2.4% over-reporting for Biden and 3.1% under-reporting for Trump can be attributed to a bandwagon effect that often follows elections, in which the reported vote for the winner often surpasses the actual vote. This apparent amount of “misremembering” in 2020 is not unusual compared to other elections.

This discrepancy between actual and reported Presidential vote highlights an important fact about surveys. Answers to survey questions should not be interpreted as accurate indicators of actual behavior. They are responses “in the moment” that reflect memory, which may be mistaken or distorted, and social desirability bias, which inclines people to present themselves in ways they hope will be perceived positively, even by an anonymous interviewer (most interviews for this survey were conducted over video Zoom sessions).

Survey responses should be thought of as accessible stated preferences, not facts. They represent how people want to be seen as much as what they “really” think.²

Demographics represent the conditions in which we find ourselves at a given point in our lives. Some, like gender, are constant throughout our lives. Others, like age, education, income, and residency vary in regular or irregular ways over our lifecycles. Here are some of the most important demographic factors that had an impact on the outcome of the 2020 Presidential election.


The candidacies of Donald Trump and Hillary Clinton in 2016 triggered a “gender gap” in presidential voting that only widened in 2020, as women reacted to the many failings and cruelties of the Trump Administration to a greater degree than men.

An interesting aspect of this gender gap is that it is not consistent across other demographic conditions. For example, a crosstab of vote by gender by age reveals that the gap is greatest in the most “Trump friendly” age group of 55 and above, in which older men give a majority vote to Trump, but older women gave a 7-point preference for Biden.

A similar pattern is revealed when vote differences by gender are compared within “local identity” groups. In the post-election survey, people were asked “Regardless of where you currently live, do you usually think of yourself as a city person, a suburb person, a small-town person, a country or rural person, or something else?” This “localid” variable proved a good predictor of Presidential vote, with further variations by gender.

Here we see an excellent illustration of partisan polarization in the American electorate. City ID people overwhelmingly supported Biden over Trump, with no significant differences between men and women. In contrast, Rural ID people overwhelmingly supported Trump, but here the gender gap reemerges: Rural ID women gave Biden 11% more votes than Rural ID men. In the suburbs and small towns, we see a similar mirror image, although less extreme. Suburban ID people prefer Biden to Trump, Small town ID people prefer Trump to Biden, both to a lesser degree than City ID people and Rural ID. In both conditions, men and women vote similarly.

Another interesting finding in this graphic is the voting behavior of suburban woman. Identified by many observers as a key ingredient to a Biden victory in 2020, suburban women were indeed a significant voting block for Biden, but only slightly more so than suburban men (62% Biden vote vs. 57% Biden vote for suburban men).


Race was a highly significant demographic factor in the 2020 Presidential election. As many commentators have noted, white America is where Trump held an advantage, while he was decisively rejected by non-white America. Here is how the vote breaks down by race and gender.

White Americans moderately preferred Trump to Biden, men slightly more than women. Non-white Americans overwhelmingly preferred Biden to Trump, with men and women voting similarly.


A second demographic gap that widened in 2020 was the difference in voting behavior between college-educated and non-college-educated Americans. This difference shows up dramatically in the following graphic.

Among Americans with less than a college degree, votes for Trump and Biden were close to evenly split, even for those with some post-high school educational experience. But the pattern shifts radically for college graduates and those with post-graduate experience, with votes for Trump plummeting among the more highly educated.³

A college education provides a potential antidote to whatever attraction Trump maintained after one term in office.


Income has been cited by more than a few observers as an important ingredient in the 2020 Presidential vote. The ANES data shows this not to be the case. Dividing Americans into income quintiles reveals few differences in voting patterns across income groups.

Although Biden won all five income groups, he did much better in the Low-Mid 20% and the Highest 20%, two groups with presumably quite different financial interests and perspectives. This implies that it was not financial interests per se that fueled Biden’s win.

Biden’s significant advantage in the highest income group should be a red flag for the GOP.

While Trump drew many new voters into the Republican Party, the ANES data suggests that he has significantly weakened the Party among its previously most loyal constituency — the rich. Adding gender to this graphic reveals some of the dynamics involved.

In both income groups where Trump performed most poorly, it was women more than men who contributed to Biden’s advantage.

Financial insecurity

Many pundits and analysts thought that Donald Trump squeaked out a victory in 2016 because he spoke to a lower-income audience suffering from economic anxiety and stagnant wages, especially in the traditionally blue rust-belt states. But later analyses proved this was not the case.⁴ Nor was it true in the 2020 vote for Trump.

To examine the effects of financial insecurity on Presidential vote, I created an insecure scale based on three questions.

  • “How concerned are you about losing your health insurance in the next year?”
  • “How concerned are you about being able to pay health care expenses for you and your family in the next year?”
  • “So far as you and your family are concerned, how worried are you about your current financial situation?”

Answers to these questions formed a reliable and consistent scale of financial insecurity (Cronbach’s alpha = .77) that was rescaled to the range 0-to-1. Matching scores on this scale with Presidential votes, Biden voters expressed significantly greater financial insecurity than Trump voters.

Similarly, significantly greater anxiety was expressed on the liberal side of the ideological spectrum than on the conservative side.

Financial insecurity clearly motivated voters, but not in Trump’s favor.

Financially-insecure Americans in 2020 did not see a second Trump term as something that would benefit them.


Religion is closely tied to demographics, community, and upbringing. It became highly politicized in the 2020 election. In particular, people who identified as fundamentalist or evangelical were seen as a key constituency for Trump, and indeed proved to be the case in the final vote tally.

However, there are very different flavors of fundamentalism in the American public, with very different implications for political behavior. This is best captured by comparing the voting behavior of white and non-white fundamentalists.⁵

Here we see another mirror-image effect among members of the public who identify themselves as fundamentalist or evangelical. White fundamentalist/evangelicals voted overwhelming for Trump, while non-white fundamentalist/evangelicals voted overwhelmingly for Biden. Among those who did not self-identify as fundamentalist/evangelical, race is a more dominant factor, with non-white, non-fundamentalist Americans significantly more likely to vote for Biden and white, non-fundamentalist Americans slightly more likely to vote for Trump.

Another illustration of the centrality of religious motivations in 2020 voting behavior can be seen in voting patterns by education levels within fundamentalist and non-fundamentalist groups.

Among non-fundamentalists, voting patterns show the same college-graduate effect we saw for education-based voting across the full sample. But among fundamentalists, any effect of college education on vote is washed away by the overriding effect of fundamentalist beliefs on Presidential vote.

All of these examples, especially the last one, illustrate an important principle:

Demographics is not destiny.

Although a person’s position in life places both constraints and opportunities in front of them, it is their beliefs, motivations, and goals that determine what they do given those constraints and opportunities. Deliberative behavior like a Presidential vote is a product of three things: what information “comes to mind” at the moment of decision, what you believe to be right and true (that is, your evaluation of that information), and what goals you are trying to achieve. As we shall see, each of these elements played an important role in understanding the internal deliberations of Trump and Biden voters in 2020.

Continue to Part 3: Media consumption — Where do voters get their information and what difference does it make?


  1. William H. Frey. “Turnout in 2020 election spiked among both Democratic and Republican voting groups, new census data shows,” Brookings Institute, May 5, 2021, online here.
  2. For more on this topic from a marketing perspective, see my article “Why Consumer Preferences Don’t Predict Consumer Behavior,” available on Medium here.
  3. Weighted educational attainment reported in the 2020 ANES survey breaks down as follows: Less than high school graduate, 7.4%; high school graduate, 26.8%; some post-high school education, 29.2%; college graduate, 23.4%; post-graduate education, 13.3%
  4. See Chokshi, Niraj. “Trump Voters Driven by Fear of Losing Status, Not Economic Anxiety, Study Finds,” New York Times, April 24, 2018, online here.
  5. Respondents who identified as fundamentalist, evangelical, or both made up 21.8% of the sampled public. This compares to 65% of the public that self-identified as religious or spiritual but not fundamentalist or evangelical, and about 13% of the public that self-identified as non-religious.



Steve Genco

Steve is author of Intuitive Marketing (2019) & Neuromarketing for Dummies (2013). He holds a PhD in Political Science from Stanford University.