Recently I wrote my Senior paper on who the Trump voter was. Here it is.

Just two months ago, our country underwent the most divisive election in recent memory. The election was marked with talks of private servers, Russia, Clinton corruption, media bias, rigging, and “pu**y gate”. After eighteen months of campaigning, Donald Trump went into Election Day with a thirty percent chance of winning but came out the President-elect, in defiance of all serious predictions. Regardless of one’s opinions of Donald Trump and his supporters, it is important to examine who they were, what they believe, and what drove them.

The 2016 election was extremely close. Donald Trump won by two-tenths of a point in Michigan, seven-tenths in Wisconsin and eight-tenths in Pennsylvania for the eleventh smallest electoral college victory of the fifty-six Presidential elections which had an outright electoral college victory. Simple shift of two points nationally in Hillary Clinton’s direction would have changed the outcome. (“What a Difference…”) Of course, when the election is this tight, any single event can be the difference. To analyze why President-elect Trump won, we need to look at systemic causes, not just temporary news stories.

Simple caricatures of explanations like racism, “fake news”, James Comey letter, or Russian “hacking” do not provide an explanation as to why Donald Trump was victorious. For starters, as I will show in depth later on, Donald Trump won because he flipped voters and states that voted for President Obama twice. While “fake news” was popular on the right, it also existed on the left, and it has existed since the beginning of the Internet. Neither “fake news” nor a mistrust in media is a new phenomenon. Beyond that, there simply is no evidence, beyond speculation, that “fake news” has an impact on the election result. The James Comey FBI letter to Congress in late October is often cited as the reason Donald Trump won. The FiveThirtyEight polls only election model already had the chances of a Donald Trump victory climbing before the letters release on October 28. Although his rise did accelerate in the days after, this rise started the day after the release. That would have been too early for any polls to catch any Comey related shift and since the model was polls-only, neither would the model. Exit polls also showed that voters who decided within the week before the election made the predictive margin between the two candidates within the margin of error. While the previous explanations do not hold water, the claim that Russia tipped the election is plausible. October is when the hacked Russian emails were at their prime and the exit polls show that was Trump’s best month but that is as strong as the evidence gets (“Google Trends”).

The viewpoints most associated with the stereotypical Trump supporter are anti-immigration, protectionist, and “Islamophobic,” although these stereotypes do not always hold true. For instance, in the Alabama Republican Primary, Donald Trump won the plurality of primary voters who wanted a legal path to citizenship for illegal immigrants and came in second among those who opposed a ban on Muslim immigration (“Republican Exit Polls”).

In the 2012 Presidential election, Mitt Romney won 52% of men and 44% of women. Four years later, Donald Trump matched Mitt Romney’s performance with men but underperformed relative to women by three points. Donald Trump underperformed Mitt Romney by one point among those aged 18 to 29 (Romney’s 37% v Trump’s 36%), four points among those aged 30 to 44 (45 v 41), and underperformed among those over 65 years old by four points (56 v 52), but he did improve upon those 45 to 64 (51 v 52).  President-elect Trump also outpaced Mitt Romney with African Americans (8 v 6) and Latinos (28 v 27), and Asians (8 v 6) while underperforming with whites (57 v 59). The Trump coalition was also significantly less educated and poorer than the Romney voter. Compared to Mitt Romney, he also pulled in fewer self-identified moderates (41 v 40), liberals (11 v 10), and conservatives (82 v 81). Similarly he gained fewer voters who self-identified as Republican (93 v 88) and Independent (50 v 46) but more who identified as Democrat (7 v 8) (“2012 Exit Polls” and “Exit Polls 2016”).

All in all, the Trump coalition was more male and less female, more diverse, less ideological and partisan, less educated and poorer. Some of these fit the stereotypical Trump voter but some of them do not. It was not the group you would expect. Sure, many thought his supporters would be less female, less educated and maybe poorer but not more diverse. His supporters were also less likely to come from more “extreme” ages. All this suggests that his voters were willing to overlook features of his candidacy which one would expect to turn off people from their identity group in favor of his broader message. For example, a Hispanic voter may not like his immigration message but they still care more about their paycheck and their family than they do about other Hispanics who have immigrated illegally or plan on immigrating.

Looking more deeply at education, we know that Hillary Clinton improved over Barack Obama’s 2012 performance in 48 of the 50 most well educated counties, measured by percentage with an undergraduate degree, by at least 50,000 people. On the other hand, Donald Trump gained ground relative to Romney in 47 of the 50 least educated counties in terms of the rate of having an undergraduate degree (“Education, Not Income…”). To quote statistician Henry Enten, “[Trump] won every single income group among those with no college degree by between 32 percentage points and 49 percentage points” (Enten). Looking back at the messages, this should be no surprise. Hillary Clinton’s message was not attempting to appeal to the working class, rather to the “coalition of the ascendant” (young people, minorities, well-educated and immigrants) by making them unwilling to associate with Donald Trump, while Trump’s message was actively trying to bring people into his coalition. Youngstown, Ohio is the perfect example of this. It has a high school graduation rate of 65%, and it was within three points of being a tie in 2016 while President Obama won it by twenty points in 2012 (Trill and “Why Trump Won…”). As I will further explain below, both Donald Trump and Barack Obama were viewed as the working class candidate which is why this shift happened. Trump had the same appeal Obama had, while Clinton was stuck with the same problems as Romney.

“Lacks the temperament to be President.” “Not honest and trustworthy.” An “unfavorable view.” “Unqualified.” This is how the plurality of the electorate described Donald Trump. Fifteen to twenty percent of the population that described Trump in each way still voted for him. This suggests that many voters wanted to vote against Hillary. They did not like Trump, but they opposed Clinton. This was a change election, an election where voters want to choose a different direction (“Exit Polls 2016”).

Donald Trump overwhelmingly lost those who thought the country was on the right track, but overwhelmingly won those who thought it was on the wrong track. He overwhelmingly won those who thought the state of the economy was poor while losing those who thought the state of the economy was good. Similarly, he overwhelmingly won those who were worse off today than they were four years ago and lost those who thought they were better off. In short, if you thought America was on the right track you voted for a third Obama term, a continuation of his policies, but if you thought the country needed a different direction you were on the “Trump train”.

Looking at the data, one finds that Trump’s support because of economic anxiety is not just a self-created illusion. While unemployment was not a strong indicator of voting patterns (in fact, there was no correlation), the percentage of “routine jobs”  was. Routine jobs are those most open to replacement via outsourcing and technology leading to economic anxiety. Counties with less than 40% of their jobs being routine averaged a margin of victory for Clinton by over thirty points, but counties where over half the jobs were routine averaged a margin of victory of almost thirty-five points for Trump (Kolko).

Knowing this, it is no wonder why Trump won Maine’s Second Congressional District by eight points when it voted for President Obama by 12 points or why the Wyoming River Valley in Pennsylvania voted for Barack Obama by double digits but supported Donald Trump (“Why Trump Won…”).

This shift does not make sense when you think of it on the traditional left-right ideological spectrum, but it does when you think of it in terms of support for the working class. Both President Obama and President-Elect Trump were viewed as the candidate of the working class while their opponents supported “globalism” and opposed bailing out the auto industry. These voters were consistent from 2008 to 2012 to 2016. They voted for the candidate they perceived to support the working class the most.

Donald Trump flipped Wisconsin, Iowa, Ohio, Florida, and Pennsylvania from the blue column to the red one. President Obama won all these states twice. Trump also won Indiana and North Carolina, states Barack Obama won in 2008. In Philadelphia’s third ward, Barack Obama beat Mitt Romney by a margin of 9,946 votes. Four years later, Hillary Clinton only won 3,139 votes, or 807 votes less than Barack Obama received in a state where Clinton lost by just over 40,000 votes. These incremental improvements upon what Mitt Romney did lead to Trump’s victory. Throughout the Rust Belt, Donald Trump built upon Mitt Romney’s coalition by taking bits and pieces of the Obama Coalition. If only one out of every one-hundred Trump voters switched to Clinton, he would have lost (“What a Difference…”).

Nate Cohn, editor at the New York Times Upshot and data analyst, said, “this election was decided by those who voted for Obama in 2012…Clinton suffered her biggest losses where Obama was strongest among white voters” (“Clinton Suffered…”. That is why Donald Trump won Elliott County in Kentucky. It was the first time a Republican won the ninety-five percent white county in 148 years (Fischer-Baum). Similarly, Trump won Ashtabula County in Ohio by more than thirty points while a Republican had not won since 1984, improving on Mitt Romney’s margin by thirty points (Education). All this suggests that, racism simply is not a sufficient explanation. Rather, support for candidates who appear to be sympathetic to the working class is a much stronger explanation. Donald Trump opposes free trade which is viewed as taking away working class jobs while Obama supported the auto bailouts and was skeptical of NAFTA in 2008. Both supported large infrastructure programs which would benefit the working class while their opponents supported free trade and globalism or opposed the auto bailouts.

Last year Yuval Levin released a book entitled “The Fractured Republic” in which he argued nostalgia for the past was a driver of American politics (Levin). The 2016 American Values Survey found that over seventy percent of Donald Trump supporters thought we were better off fifty years ago than we are today  (Cooper).  While many interpreted this as based in racial and demographic fears, let me offer a different and more nuanced interpretation. As Levin points out in his book, America was far more monolithic and centralized. This was a time before our current free trade regime, the decline of big labor and when trust in Washington, D.C. was high (Levin).  “Making America Great Again” was the same as “Hope and Change”. Although crude, this was a call for returning to historic norms. Fifty years ago, trust in government was upwards of seventy to eighty percent. Today, the same polls find it below twenty percent (Fingerhut). Forty-six years ago, manufacturing made up over a quarter of the workforce while it made  up just over ten percent in 2012 (Percent of Employment).

While many interpretations of the Trump voter can be made, I think the evidence points to one overarching generalization. The Trump voter wants a return to the 1950’s and 1960’s in terms of their economic position and trust in government. That is why many of them voted for Obama at least once and voted for Donald Trump in 2016. I think nothing else captures this better than the fact that Donald Trump won 76% of the counties with a Cracker Barrel Old Country Store (Sabato).

 

 

Works Cited

Levin, Yuval. The Fractured Republic: Renewing America’s Social Contract in the Age of Individualism. New York: Basic , A Member of the Perseus  Group, 2016. Print.

“2012 Exit Polls.” CNN. Cable News Network, 10 Dec. 1012. Web. 08 Jan. 2017. <http://www.cnn.com/election/2012/results/race/president/&gt;.

Cohn, Nate. “Clinton Suffered Her Biggest Losses in the Places Where Obama Was Strongest among White Voters. It’s Not a Simple Racism Story” Twitter. Twitter, 08 Nov. 2016. Web. 14 Dec. 2016. <https://twitter.com/Nate_Cohn/status/796243185739632640&gt;.

Cohn, Nate. “Why Trump Won: Working-Class Whites.” The New York Times. The New York Times, 9 Nov. 2016. Web. 07 Jan. 2017. <https://www.nytimes.com/2016/11/10/upshot/why-trump-won-working-class-whites.html&gt;.

Cooper, Betsy, Daniel Cox, Rachel Lienesch, and Robert P. Jones. “The Divide Over America’s Future: 1950 or 2050?” PRRI.org. Public Religion Research Institute, 25 Oct. 2016. Web. 14 Jan. 2017. <http://www.prri.org/research/poll-1950s-2050-divided-nations-direction-post-election/&gt;.

Enten, Harry. “Even Among The Wealthy, Education Predicts Trump Support.” FiveThirtyEight. FiveThirtyEight, 29 Nov. 2016. Web. 14 Dec. 2016. <https://fivethirtyeight.com/features/even-among-the-wealthy-education-predicts-trump-support/&gt;.

“Exit Polls 2016.” CNN. Cable News Network, 23 Nov. 2016. Web. 8 Jan. 2017. <http://www.cnn.com/election/results/exit-polls&gt;.

Fingerhut, Hannah. “Trust in Government: 1958-2015.” Pew Research Center for the People and the Press. Pew Research Center, 23 Nov. 2015. Web. 08 Jan. 2017. <http://www.people-press.org/2015/11/23/1-trust-in-government-1958-2015/&gt;.

Fischer-Baum, Reuben. “A Kentucky County Ended Its Historic Democratic Streak To Vote For Trump.” FiveThirtyEight. FiveThirtyEight, 10 Nov. 2016. Web. 10 Dec. 2016. <https://fivethirtyeight.com/features/a-kentucky-county-ended-its-historic-democratic-streak-to-vote-for-trump/&gt;.

“Google Trends.” Google Trends. Alphabet, n.d. Web. 08 Jan. 2017. <https://www.google.com/trends/explore?date=today%2B12-m&q=podesta%2Bemails%2C%2Fm%2F01zty6%2C%2Fm%2F027m_21&gt;.

Kolko, Jed. “Trump Was Stronger Where The Economy Is Weaker.” FiveThirtyEight. FiveThirtyEight, 10 Nov. 2016. Web. 14 Dec. 2016. <https://fivethirtyeight.com/features/trump-was-stronger-where-the-economy-is-weaker/&gt;

“Percent of Employment in Manufacturing in the United States (DISCONTINUED).” St. Louis Fed. N.p., 10 June 2013. Web. 08 Jan. 2017. <https://fred.stlouisfed.org/series/USAPEFANA&gt;.

“Republican Exit Polls.” CNN. Cable News Network, n.d. Web. 08 Jan. 2017. <http://www.cnn.com/election/primaries/polls&gt;.

Sabato, Larry J., Kyle Kondik, and Geoffrey Skelley. “16 For ’16.” Centerforpolitics.org. University of Virginia, 17 Nov. 2016. Web. 14 Dec. 2016. <http://www.centerforpolitics.org/crystalball/articles/16-for-16/&gt;.

Silver, Nate. “2016 Election Forecast.” FiveThirtyEight. N.p., 08 Nov. 2016. Web. 08 Jan. 2017. <https://projects.fivethirtyeight.com/2016-election-forecast/&gt;.

Silver, Nate. “Education, Not Income, Predicted Who Would Vote For Trump.” FiveThirtyEight. FiveThirtyEight, 28 Nov. 2016. Web. 18 Dec. 2016. <http://fivethirtyeight.com/features/education-not-income-predicted-who-would-vote-for-trump/&gt;.

Silver, Nate. “What A Difference 2 Percentage Points Makes.” FiveThirtyEight. FiveThirtyEight, 10 Nov. 2016. Web. 14 Dec. 2016. <https://fivethirtyeight.com/features/what-a-difference-2-percentage-points-makes/&gt;.

Trill, Tyler. “Three Valley Schools Receive failing Grades from State.” WKBN.com. N.p., 14 Jan. 2016. Web. 08 Jan. 2017. <http://wkbn.com/2016/01/14/three-valley-schools-receive-failing-grades-from-state/&gt;.

 

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Posted by Roman Bilan

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