Why did they vote Trump?
The 2016 election of Donald Trump caught the media landscape and political analysts by surprise. Election models from the Huffington Post (Jackson and Hooper 2016) and New York Times (Katz 2016) gave Clinton a 98% and 85% chance of winning the election, respectively. Plagued by scandals, offensive comments about immigrants, Muslims, and women alike, and a general underperformance in pre-election polls, it is not surprising that Trump was thought to be an unlikely victor. So, when he won in defiance of the odds and media certainty, many pundits, analysts, journalists, and academics debated this unforeseen outcome. Two explanations that garnered much attention were the cultural backlash and economic anxiety arguments. The cultural backlash argument suggests that as society becomes more progressive, egalitarian, diverse, and less hegemonic, the previously dominant group lashes out in a reactionary manner, fearing that they are being displaced and losing their once hegemonic position in the social hierarchy (Norris & Inglehart 2019). Authoritarian populists, like Trump, can ride this wave of reactionary upswell to positions of power. Proponents of the economic anxiety argument posit that Trump voters are the losers of globalization and decades of neoliberal economics, leaving them behind (Mudde 2019). So, when a populist candidate, like Trump, promising to revive American manufacturing and bring back outsourced jobs runs against Clinton — perceived by many as unconcerned with the plight of the “left behind” — these economically anxious voters either throw their support behind the populist or disengage from the political process (McQuarrie 2017). There is compelling evidence on either side, but these positions are not dichotomous. For Trump voters, cultural backlash is far more dominant as the political driver for their electoral decisions. However, geographically localized economic anxiety depressed support for Clinton and boosted Trump’s odds in some crucial swing states. Thus, both factors played a complementary role in Donald Trump’s 2016 victory.
Economic Anxiety vs Economic Hardship
Trump has often been framed as a man of the working class. He certainly would like to present himself as such in many of his speeches. “That’s why the steelworkers are with me, that’s why the miners are with me, that’s why the working people, electricians, the plumbers, the sheet‐rockers, the concrete guys and gals, they’re all — they’re with us,” he announced during a rally on the 12th of August 2016 in Erie, Pennsylvania (Lamont et al. 2017). Despite this populist rhetoric, exit polls show that those hit hardest economically were not with Trump.
Exit polls of the 2016 Presidential election from the New York Times show that voters with household incomes under $30,000 and $50,000 leaned towards Clinton (Huang et al. 2016). Exit polls from the 2016 Democratic and Republican Presidential primaries show that Trump voters had higher median incomes than Clinton and Sanders supporters (Silver 2016). Trump is not an anomaly in this regard. Low-income voters are underrepresented in the Republican party relative to the Democratic party (Silver 2016). The relative lack of low-income voters shows that economic hardship does not necessarily correlate with support for Trump.
The level of unemployment in a county, another important metric of economic hardship, also shows no correlation with the level of Trump support in that county (Kolko 2016). However, economic hardship is not the same as economic anxiety. Economic hardship refers to “a person’s present-day economic struggles: poverty, joblessness, falling wages, foreclosure, bankruptcy. Anxiety is all about what lies ahead — concerns about saving for retirement or college, worry of a potential layoff, fears that your children’s prospects aren’t as bright as your own were” (Casselman 2017). While hardship is not predictive of support for Trump, there is some merit to the argument for economic anxiety when looking at metrics about the future state of the economy in counties across the country.
In counties with more subprime loans, more residents receiving disability payments, lower earnings among full-time workers, and slower job growth — Trump increased his margin against Clinton compared to Romney against Obama (Casselman 2017). Counties with a larger share of “routine jobs” — jobs in manufacturing, sales, clerical work, and other occupations that are vulnerable to automation or outsourcing — were also more likely to vote for Trump (Kolko 2016). What this suggests is that Trump voters may not be the hardest hit financially, on average, but they are often concentrated in parts of the country with poor economic prospects for the future. The economic anxiety borne out of these poor prospects for their local economies could influence some voters to support Trump. Correlation does not, however, indicate causation. A lot of these economic trends can be attributed, at least in part, to the demographics of these counties. Counties with older populations or fewer college-educated adults — two groups that leaned heavily towards Trump — tend to have slower job growth and a higher share of routine jobs (Kolko 2016). To entangle the complicated intertwining of demographics, economic patterns, and the various motivations driving voter behavior, we need to look at the sociological literature on this topic.
Researching voter attitudes
Researchers at the University of Massachusetts Amherst set out to measure the impact of racism & sexism and economic dissatisfaction on voters’ support for Trump (Schaffner et al. 2018). The researchers analyzed survey data that provided respondents with a set of statements and asked respondents to rate their agreement with them. They measured how prejudiced the respondents were against women & the degree to which they acknowledged or denied the presence of racism in America. The respondents were also asked to rate their satisfaction with their personal economic situation and answer if their household income had fallen, risen, or stayed stagnant.
The researchers found that while both economic dissatisfaction and race/gender attitudes affected a likely voter’s probability of voting for Trump, the impact of economic dissatisfaction was dwarfed by the impact of hostile sexism or denial of racism (Schaffner et al. 2018). The researchers observed that the least economically satisfied voters were about 13% more likely to vote for Trump than the most economically satisfied voters. However, the most sexist voters were 30% more likely to support Trump than the least sexist ones. Similarly, the voters who were least likely to acknowledge or care about racism in America were 30% more likely to support Trump than those who acknowledged or cared about racism the most. These observations held true while controlling for the effect of demographics, ideology, and other influencing factors.
The takeaway from this study should be that while we should not disregard the role of economic concerns, reactionary and prejudicial attitudes about race and gender — core components of the cultural backlash phenomenon — increased support for Trump far more than one’s economic concerns. This study’s findings are not an outlier in the extensive scholarship on this topic. Similar studies exploring the effects of economic concerns and cultural attitudes find that the role of economic anxiety, while not insignificant, is far outweighed by beliefs indicative of a cultural backlash.
Explaining the education gap
While both college-educated and non-college-educated White voters favored Trump over Clinton, the gap between their voting preferences in 2016 was the highest since the 80s (Tyson & Maniam 2016). These voters are also frequently discussed in arguments about economic anxiety & populism driving support for Trump among the white working class (Tankersley 2016).
Schaffner and his colleagues found that the reason non-college-educated Whites voted for Trump in higher margins than college-educated ones were more so due to their attitudes about race and gender than economic concerns (Schaffner et al. 2018). Other studies suggest similar findings.
A study published by the nonpartisan Public Religion Research Institute in collaboration with The Atlantic studied why White working-class voters, White voters without a four-year college degree, were drawn towards Trump. The authors of the study found that “besides partisanship, fears about immigrants and cultural displacement were more powerful factors than economic concerns in predicting support for Trump among white working-class voters” (Cox et al. 2017).
Perhaps unsurprisingly, being a Republican was the most significant factor driving White working-class voters to vote for Trump. Fearing cultural displacement — defined as feeling like a stranger in one’s own land and believing the U.S. needs protection against foreign influence — was the second most significant factor. Wanting to deport undocumented immigrants was the third most influential factor. Fears of being culturally displaced in an increasingly diversifying country and a strong desire to keep immigrants out reflect cultural backlash from these voters. Economic fatalism — defined by the authors as believing that college education is a gamble — was the fourth most significant predictor of a White working-class voter supporting Trump. Their economic fatalism displays a degree of economic anxiety since it shows that these voters are not optimistic about future economic prospects, given their doubts about the financial value of a college degree.
Interestingly, economic hardship — defined as being in fair or poor financial shape — predicted support for Clinton, not Trump. This is in line with similar findings that show Trump voters were somewhat motivated by economic anxiety, but voters facing economic hardship were more likely to support Clinton (Casselman 2017). Ultimately, cultural backlash is still the dominant factor in comparison to economic anxiety, and this study provides additional support for that argument.
Anti-Immigration Sentiment: Ethnocentrism or Economic Anxiety?
In his presidential announcement speech, Donald Trump infamously said, in reference to Mexican immigrants, “they’re bringing drugs. They’re bringing crime. They’re rapists. And some, I assume, are good people” (Trump 2015). Trump’s rhetoric towards immigrants, and especially undocumented immigrants, often conveyed such explicit xenophobia and fearmongering about crime and drugs. When talking about Muslim immigrants and refugees, he often invoked fears of terrorism (Lamont et al. 2017). He also positioned immigrants as competition for American workers. “Now [Hillary Clinton] is proposing to print instant work permits for millions of illegal immigrants, taking jobs directly from low‐income Americans. I will secure our border, protect our workers, and improve jobs and wages in your community” (Lamont et al. 2017), he declared during a rally in Wisconsin. Donald Trump’s rhetoric on immigration tapped into xenophobia and nativism, but also economic anxiety. His voters cared about these issues; immigration, terrorism, and the economy were some of the top priorities for Trump voters in 2016 (Pew Research 2016). Thus, it provides a valuable case study for understanding the impact of cultural backlash and economic anxiety.
Steven Miller, a political science professor at Clemson University, studied the attitudes of White Americans towards immigration in the United States from 1992 to 2017 to evaluate if these negative attitudes are better explained by ethnocentrism or economic anxiety. The working definition of ethnocentrism used in Miller’s study describes it as the tendency to view our in-group in competition with various out-groups. This mindset manifests behaviorally through attitudes like prejudice & nativism (Miller 2020). Since cultural backlash also manifests through similar prejudicial attitudes and an increased sense of competition with out-groups perceived by the dominant group as threats to their hegemonic status (Norris & Inglehart 2019), ethnocentrism serves as a good proxy for understanding cultural backlash in this study. Miller conclusively finds that “ethnocentrism has the largest and most precise effect on antiimmigration attitudes” (Miller 2020). Many metrics of economic anxiety do not have reliable effects on attitudes towards immigration. Of the ones that do, their influence is dwarfed by the much more significant impact of ethnocentrism. Miller’s findings provided further evidence for the cultural backlash argument, suggesting that Trump’s xenophobia, Islamophobia, and nativism resonated much more significantly with his voters than his economic arguments for restricting immigration.
Obama to Trump voters
In response to these arguments for cultural backlash, critics will often point to the electoral impact of former Obama voters who switched to Trump in 2016. “Clinton suffered her biggest losses in the places where Obama was strongest among white voters. It’s not a simple racism story,” Nate Cohn of the New York Times tweeted on election night (Cohn 2016a). Cohn is correct in saying that it is not a simple racism story, as much of the literature explored thus far has shown that economic concerns did play a part in Trump’s 2016 victory. However, even among voters who switched from once supporting Obama to supporting Trump, attitudes about race, religion, and immigration played a profound role.
About 9% of 2012 Obama voters flipped to supporting Trump in 2016, and 84% of these vote switchers were White (Bump 2018). Based on his analysis of voter survey data, John Sides, Washington Post journalist and political science professor at Vanderbilt University, demonstrates that standard economic issues such as entitlement programs or trade did not become more influential to White voter preference in 2016 compared to 2012. The state of the economy also did not impact voter preference any more than the previous election — those who believed the economy was getting worse voted against the party in power. Rather, attitudes about immigration, Black people, and Muslims became much more salient in 2016 (Sides 2017). Trump was able to draw increased attention to these issues of race, immigration, and religion. In doing so, he captured a segment of White Obama voters who had become increasingly less favorable to ethnic and religious minorities, Sides concludes (Sides 2017). His findings show that although economic issues did impact election results, cultural backlash — in the form of increasing racial animosity, xenophobia & Islamophobia — became more impactful than previous years while the importance of economics, welfare, and trade stayed about the same. However, it should be noted that many of these former Obama voters had begun shifting their attitudes even prior to 2012. To capture the full of how Obama’s coalition fractured requires a broader analysis.
Why did the Obama coalition crumble?
One of the critical reasons Clinton fell short of the 270 electoral votes needed to win the presidency, despite winning the popular vote by almost 2.9 million votes (Krieg 2016), was her inability to bring together the Obama coalition that propelled him to victory twice — a coalition of Black and Northern White voters key to winning swing states in the Midwest (Cohn 2016b).
In 2016, Democrats saw a historic shift in their voter composition. Low-income White voters left the party in decisive numbers. “For the first time in the history of the two parties, the Republican candidate did better among low-income whites than among affluent whites,” a New York Times analysis of exit poll and survey data found (Cohn 2016b). Donald Trump even won significant segments of former Obama voters who approved of Obama. “19 percent of white voters without a degree who approved of Mr. Obama’s performance” and “10 percent of white working-class voters who wanted to continue Mr. Obama’s policies” (Cohn 2016b) supported Trump over Clinton. Clinton’s weakness among the White working-class proved particularly detrimental in the swing states of the Upper Midwest, where “young white working-class voters represent a larger share of the vote there than anywhere else in the country” (Cohn 2016b).
Many Black voters also expressed their rejection of Clinton, although in a different way than White voters. Black voters did not flip to Trump in large numbers, but turnout dropped significantly. Key swing states like Michigan, Wisconsin, Pennsylvania, and Ohio all saw a decline in Black voter turnout. While Black and minority voter turnout saw an overall decline, White voter turnout increased according to census data (Frey 2017). This declining Black turnout “was heavily concentrated in Rust Belt territories like West Philadelphia, Milwaukee and Detroit” (McQuarrie 2017). Much like the departure of the White working-class, the decline in Black turnout in midwestern swing states heavily disadvantaged Clinton. “If black turnout had matched 2012 levels, Mrs. Clinton would have almost certainly scratched out wins in Wisconsin, Michigan, and Pennsylvania”, Nate Cohn of the New York Times finds (Cohn 2016b).
Sociologist Michael McQuarrie has characterized the shifting votes of the White working class and lower turnout of Black voters in the post-industrial Midwest as a “revolt of the Rust Belt” (McQuarrie 2017). Much of the research discussed so far shows how cultural backlash drove support for Trump through analysis of survey data. However, focusing exclusively on the attitudes of this broader set of voters can risk missing distinct geographical nuances that led to the revolt of the Rust Belt. The upper Midwest was once the center stage of American capitalism and industrial manufacturing. Wealth and population were concentrated in this region. “Between 1973 and 2007 the Rust Belt experienced a systematic withdrawal of institutional, state and financial investment” (McQuarrie 2017). The North American Free Trade Agreement (NAFTA) signed into law by Bill Clinton further solidified the deindustrialization of the Rust Belt and served as an object of ire for voters in the region. Just as Obama successfully appealed to industrial workers through his bailout of the auto industry, Trump campaigned on renegotiating NAFTA and characterized Clinton as an out-of-touch elite due to her support of the trade deal (Cohn 2016b).
Additionally, with declining unionization rates across the country and especially the Midwest, the Democratic party lost a crucial apparatus of their political machine. “The ability of unions to anchor white workers in the Democratic coalition” was gone (McQuarrie 2017). The consequences of decades of deindustrialization and de-unionization left economic and social consequences that Donald Trump successfully capitalized on in the Midwest states core to his electoral college victory.
Even in the rust belt’s rejection of Clinton, a racialized dynamic played out. Both White and Black Midwesterners alike felt marginalized by systemic economic decline, but White voters were in a unique position to express disregard for issues of race and bigotry. Thus, many of them turned to Trump, while Black voters expressed their dissatisfaction by withholding their vote. The economic disenfranchisement of the Rust Belt helped lay the groundwork for Clinton’s loss, but cultural backlash played a role in how voters expressed their rejection of the party.
In his 2016 bid for the presidency, Donald Trump tapped into a climate of cultural backlash, where issues of race, religion, and immigration became increasingly more relevant (Sides 2017). Voters who expressed significant hostile sexism (Schaffner et al. 2018), ethnocentrism (Miller 2020), fears of cultural displacement (Cox et al. 2017), or other prejudicial attitudes flocked to him in decisive numbers.
Economic anxiety also plagued counties across the country. In many of the counties where Trump won or overperformed, automation was a potent threat (Kolko 2016), earnings were low (Casselman 2017), job growth was slow (Casselman 2017), and decades of deindustrialization and de-unionization had left centers of American industry as shells of their former selves (McQuarrie 2017).
On an individual level, cultural backlash served as the most significant independent predictor for voters to support Trump, while economic anxiety played a secondary role. Geographically, however, economic anxiety helped depress turnout for Clinton and even boosted Trump’s numbers in many swing states Obama had dominated only four or eight years prior.
Faced with an opponent who was the first female presidential nominee of a major US party and viewed as an out-of-touch elite in many circles, Trump capitalized on both the prevailing climate of cultural backlash & and the undercurrent of economic anxiety in many electorally crucial areas to secure his victory. Understanding these dynamics is crucial to understanding the resurgent right-wing populism in recent years.
Bump, Philip. “4.4 Million 2012 Obama Voters Stayed Home in 2016 — More than a Third of Them Black.” The Washington Post. The Washington Post, March 12, 2018. https://www.washingtonpost.com/news/politics/wp/2018/03/12/4-4-million-2012-obama-voters-stayed-home-in-2016-more-than-a-third-of-them-black/.
Casselman, Ben. “Stop Saying Trump’s Win Had Nothing To Do With Economics.” FiveThirtyEight. FiveThirtyEight, January 9, 2017. https://fivethirtyeight.com/features/stop-saying-trumps-win-had-nothing-to-do-with-economics/.
Cohn, Nate. “How the Obama Coalition Crumbled, Leaving an Opening for Trump.” The New York Times. The New York Times, December 23, 2016. https://www.nytimes.com/2016/12/23/upshot/how-the-obama-coalition-crumbled-leaving-an-opening-for-trump.html.
Cohn, Nate. “Clinton Suffered Her Biggest Losses in the Places Where Obama Was Strongest among White Voters.” Twitter, November 9, 2016. https://twitter.com/Nate_Cohn/status/796243185739632640.
Cox, Daniel, Rachel Lienesch, and Robert Jones. “Beyond Economics: Fears of Cultural Displacement Pushed the White Working Class to Trump: PRRI/The Atlantic Report.” PRRI. Public Religion Research Institute, May 9, 2017. https://www.prri.org/research/white-working-class-attitudes-economy-trade-immigration-election-donald-trump/.
Frey, William H. “Census Shows Pervasive Decline in 2016 Minority Voter Turnout.” Brookings Institute. Brookings Institute, May 18, 2017. https://www.brookings.edu/blog/the-avenue/2017/05/18/census-shows-pervasive-decline-in-2016-minority-voter-turnout/.
Huang, Jon, Samuel Jacoby, Michael Strickland, and KK Rebecca Lai. “Election 2016: Exit Polls.” The New York Times. The New York Times, November 8, 2016. https://www.nytimes.com/interactive/2016/11/08/us/politics/election-exit-polls.html.
Jackson, Natalie, and Adam Hooper. “2016 President Forecast.” The Huffington Post. The Huffington Post, October 3, 2016. https://elections.huffingtonpost.com/2016/forecast/president.
Katz, Josh. “2016 Election Forecast: Who Will Be President?” The New York Times. The New York Times, November 8, 2016. https://www.nytimes.com/interactive/2016/upshot/presidential-polls-forecast.html.
Kolko, Jed. “Trump Was Stronger Where The Economy Is Weaker.” FiveThirtyEight. FiveThirtyEight, November 10, 2016. https://fivethirtyeight.com/features/trump-was-stronger-where-the-economy-is-weaker/.
Krieg, Gregory. “It’s Official: Clinton Swamps Trump in Popular Vote — CNN Politics.” CNN. CNN, December 22, 2016. https://www.cnn.com/2016/12/21/politics/donald-trump-hillary-clinton-popular-vote-final-count.
Lamont, Michèle, Bo Yun Park, and Elena Ayala-Hurtado. “Trump’s Electoral Speeches and His Appeal to the American White Working Class.” The British Journal of Sociology 68, no. S1 (November 8, 2017): 153–80. https://doi.org/10.1111/1468-4446.12315.
McQuarrie, Michael. “The Revolt of the Rust Belt: Place and Politics in the Age of Anger.” The British Journal of Sociology 68, no. S1 (November 8, 2017): 120–52. https://doi.org/https://doi.org/10.1111/1468-4446.12328.
Miller, Steven V. “Economic Anxiety or Ethnocentrism? An Evaluation of Attitudes toward Immigration in the U.S. from 1992 to 2017.” The Social Science Journal, July 16, 2020, 1–20. https://doi.org/10.1080/03623319.2020.1782638.
Mudde, Cas. “Causes .” Chapter. In The Far Right Today. Cambridge, UK: Polity Press, 2019. https://www.google.com/books/edition/The_Far_Right_Today/aD25DwAAQBAJ?hl=en&gbpv=0
Norris, Pippa, and Ronald Inglehart. “The Cultural Backlash Theory.” Essay. In Cultural Backlash: Trump, Brexit, and Authoritarian Populism, 32–64. Cambridge: Cambridge University Press, 2019. https://doi.org/10.1017/9781108595841.003.
Schaffner, Brian F., Matthew Macwilliams, and Tatishe Nteta. “Understanding White Polarization in the 2016 Vote for President: The Sobering Role of Racism and Sexism.” Political Science Quarterly 133, no. 1 (March 25, 2018): 9–34. https://doi.org/10.1002/polq.12737.
Sides, John. “Race, Religion, and Immigration in 2016.” Democracy Fund Voter Study Group. Democracy Fund Voter Study Group, June 2017. https://www.voterstudygroup.org/publication/race-religion-immigration-2016.
Silver, Nate. “The Mythology Of Trump’s ‘Working Class’ Support.” FiveThirtyEight. FiveThirtyEight, May 3, 2016. https://fivethirtyeight.com/features/the-mythology-of-trumps-working-class-support/.
Tankersley, Jim. “How Trump Won: The Revenge of Working-Class Whites.” The Washington Post. The Washington Post, November 9, 2019. https://www.washingtonpost.com/news/wonk/wp/2016/11/09/how-trump-won-the-revenge-of-working-class-whites/.
“Top Voting Issues in 2016 Election.” Pew Research Center — U.S. Politics & Policy. Pew Research Center, July 7, 2016. https://www.pewresearch.org/politics/2016/07/07/4-top-voting-issues-in-2016-election/.
Trump, Donald. “Donald Trump’s Presidential Announcement Speech.” Time. Time, June 16, 2015. https://time.com/3923128/donald-trump-announcement-speech/.
Tyson, Alec, and Shiva Maniam. “Behind Trump’s Victory: Divisions by Race, Gender and Education.” Pew Research Center. Pew Research Center, November 9, 2016. https://www.pewresearch.org/fact-tank/2016/11/09/behind-trumps-victory-divisions-by-race-gender-education/.