Abstract
In this chapter, I present a discussion of the academic literature oriented toward presidential elections, Iowa elections, and the 2016 election. The literature is used to theoretically develop models of vote choice using individual-level data. The individual-level findings demonstrate that the 2016 election was not driven solely by white, working-class support. Rather, support for Donald Trump was driven by partisanship, attitudes regarding President Obama’s performance, and hardline positions on immigration. Additionally, educational attainment did not drive vote switching in 2016 either. Vote switching—casting a vote for Obama or a third-party candidate in 2012 and then for Trump in 2016—was both a function of voters’ approval of Obama’s performance as president and their attitudes about race.
I definitely think racism and sexism both played a part at both the state and national level, but I’m less clear on how much of a difference it made. Iowans tend to personally be more conservative on questions of immigration, racial justice, and religious tolerance, but also less inclined to force their personal positions on others. Trump’s campaign was founded on xenophobic anti-immigration rhetoric, so I’m sure there was some percentage of irregular Iowa voters that responded to that. Exit polls showed that voters approved of many of Clinton’s policies but not Clinton herself, and I’m sure sexism played into that, as well.
—Democratic County Party Official from southeast Iowa
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- 1.
The epigraph at the beginning of this chapter discusses the likelihood of sexism impacting the decisions of Iowa voters as well. There is certainly a theoretical reason to believe that sexism could have played a role in shaping attitudes toward Hillary Clinton and vote choice in 2016 in Iowa. There is evidence from studies of the U.S. population linking sexism and attitudes regarding Clinton (e.g., McThomas and Tesler 2016) and sexism and vote choice in 2016 (e.g., Setzler and Yanus 2018; Valentino et al. 2018a). A dataset with a large sample of Iowa voters that contained a modern sexism battery was not available to the author. A modern sexism battery is available in the VOTER Survey, but the Iowa subset of the overall sample is 82 cases when accounting for missing data (DFVSG 2017). A basic logistic regression model shows that the modern sexism index (α = 0.78) is not a statistically significant predictor of a vote for Trump for white voters in Iowa when controlling for party identification, educational attainment, and gender of the voter. Nor was the modern sexism index a statistically significant predictor of white Iowa voters having a favorable opinion of Hillary Clinton. Due to the small sample size of Iowa voters in the VOTER Survey and the inability to develop a full model of vote choice, a model examining the linkage between sexism and the 2016 election is not reported here. The basic model cited above is available from the author upon request.
- 2.
Two major themes identified from the qualitative data in Chap. 2 were the enthusiasm gap and antipathy toward Hillary Clinton. Unfortunately, the Cooperative Congressional Election Survey did not include measures of favorability or excitement to vote for specific candidates. As a result, these themes cannot be tested at the individual level.
- 3.
A detailed description of methodological approach to collecting the CCES is provided at http://cces.gov.harvard.edu.
- 4.
All data analysis was performed using R and the CCES weight “commonweight_vv_post.” Datasets with recodes, R scripts, and descriptives for the variables are available from the author upon request.
- 5.
The “for all else” category only includes those respondents who provided a candidate’s name for the survey item. It does not include self-reported nonvoters or respondents who refused to answer the question.
- 6.
A vote switch variable was also constructed for Hillary Clinton, but only 11 Iowa respondents reported switching from Romney or a third-party candidate in 2012 to Clinton in 2016 preventing any analysis of vote switching toward Clinton.
- 7.
The inclusion of the modern racism index is a better representation of racial attitudes based upon the narrative of vote switching in Iowa from 2012 to 2016 (i.e., if Iowa voters are racially conservative then why would they have voted for a black candidate in 2008 and 2012?). The narrative is more about viewing the political world through a color-blind lens as opposed to measures of racial resentment which measure antipathy that whites hold toward blacks regarding perceptions of work ethic and entitlement (see Sears and Henry 2003).
- 8.
The CCES does not have a battery of questions regarding economic policy preferences, only the retrospective and prospective assessments of economy. Although the dataset does include an item regarding the use of the military to destroy a terrorist camp, it does not include a comprehensive battery for terrorism either. The dataset does include items about preferences regarding the U.S. response to the Syrian conflict which could be used as a proxy for terrorism policy, but the items were not asked of the entire sample so there is significant missing data in those items.
- 9.
It was asserted in the epigraph at the beginning of this chapter that Iowans are conservative on issues of race and immigration. Looking at the racial attitudes and immigration measures confirms this; however, the differences were not statistically significant. The average score on the racial attitudes measure for all white CCES respondents was 0.351. For white Iowa respondents it was 0.367 (t = 1.67, p = 0.095). The average score on the immigration measure for all white CCES respondents was 0.535 and for white Iowa respondents was 0.560 (t = 1.59, p = 0.112).
- 10.
- 11.
A model was run which included the gun rights and abortion measures. The inclusion added no value to the model, the coefficients were not statistically significant, and the remainder of the model was stable compared to the model reported in Table 4.2.
- 12.
The model has a limited number of cases coded 1 on the dependent variable. “Trump Switchers” constituted about 9% of the cases, which in real terms is approximately 41 cases in all. The small number of Trump Switchers in the model prevented disaggregating the modeling by college degree or by party identification to see if there were differences between groups. Additionally, adding predictors to the model will have the effect of disaggregating cases even more creating small cell sizes for certain combinations of predictors and the dependent variable which will lead to elevated standard errors for the coefficients. If statistically significant predictors are identified even with the reduced sample size, the likelihood is very good that the effect is real and generalizable to white Iowa voters.
References
Abramowitz, Alan, and Jennifer McCoy. 2019. United States: Racial Resentment, Negative Partisanship, and Polarization in Trump’s America. Annals of the American Academy of Political and Social Science 681 (1): 137–156. https://doi.org/10.1177%2F0002716218811309.
Abramowitz, Alan I., and Steven Webster. 2016. The Rise of Negative Partisanship and the Nationalization of U.S. Elections in the 21st Century. Electoral Studies 41: 12–22. https://doi.org/10.1016/j.electstud.2015.11.001.
Achen, Christopher H., and Larry M. Bartels. 2016. Democracy for Realists: Why Elections Do Not Produce Responsive Government. Princeton, NJ: Princeton University Press.
Ansolabehere, Stephen, and Brian F. Schaffner. 2017. Cooperative Congressional Election Study, 2016: Common Content. [Computer File] Release 2: August 4, 2017. Cambridge, MA: Harvard University [producer]. http://cces.gov.harvard.edu.
Bartels, Larry M. 1988. Presidential Primaries and the Dynamics of Public Choice. Princeton, NJ: Princeton University Press.
———. 2002. Beyond the Running Tally: Partisan Bias in Political Perceptions. Political Behavior 24 (2): 117–150. https://doi.org/10.1023/A:1021226224601.
Campbell, Angus, Philip E. Converse, Warren E. Miller, and Donald E. Stokes. 1960. The American Voter. New York: John Wiley & Sons.
Cramer, Katherine J. 2016. The Politics of Resentment: Rural Consciousness in Wisconsin and the Rise of Scott Walker. Chicago: University of Chicago Press.
Democracy Fund Voter Study Group (DFVSG). 2017. Views of the Electorate Research Survey, December 2016. [Computer File] Release 1: August 28, 2017. Washington, DC: Democracy Fund Voter Study Group [producer]. https://www.voterstudygroup.org/.
Exit Polls. 2016. Exit Polls: Iowa President. Last Modified November 23, 2016. https://www.cnn.com/election/2016/results/exit-polls/iowa/president.
Filindra, Alexandra, and Noah J. Kaplan. 2016. Racial Resentment and Whites’ Gun Policy Preferences in Contemporary America. Political Behavior 38 (2): 255–275. https://doi.org/10.1007/s11109-015-9326-4.
Fiorina, Morris P. 1981. Retrospective Voting in American National Elections. New Haven, CT: Yale University Press.
Golshan, Tara. 2016. Read Donald Trump’s Most Inflammatory Speech Yet on Muslims and Immigration. Vox, June 13. https://www.vox.com/2016/6/13/11925122/trump-orlando-foreign-policy-transcript.
Hetherington, Marc J. 1996. The Media’s Role in Forming Voters’ National Economic Evaluations in 1992. American Journal of Political Science 40 (2): 372–395. https://doi.org/10.2307/2111629.
Hibbs, Douglas A. 1987. The American Political Economy: Macroeconomics and Electoral Politics. Cambridge, MA: Harvard University Press.
Hooghe, Marc, and Ruth Dassonneville. 2018. Explaining the Trump Vote: The Effect of Racist Resentment and Anti-Immigrant Sentiments. PS: Political Science & Politics 51 (3): 528–534. https://doi.org/10.1017/S1049096518000367.
Iyengar, Shanto, and Sean J. Westwood. 2015. Fear and Loathing Across Party Lines: New Evidence on Group Polarization. American Journal of Political Science 59 (3): 690–707. https://doi.org/10.1111/ajps.12152.
Keith, Bruce E., David B. Magleby, Candice J. Nelson, Elizabeth Orr, Mark C. Westlye, and Raymond E. Wolfinger. 1992. The Myth of the Independent Voter. Berkeley, CA: University of California Press.
Key, V.O. 1966. The Responsible Electorate: Rationality in Presidential Voting, 1936–1960. Cambridge, MA: Harvard University Press.
Kinder, Donald R., and Roderick Kiewiet. 1981. Sociotropic Politics: The American Case. British Journal of Political Science 11 (2): 129–161. https://doi.org/10.1017/S0007123400002544.
Klar, Samara, and Yanna Krupnikov. 2016. Independent Politics: How American Disdain for Parties Leads to Political Inaction. New York: Cambridge University Press.
Knuckey, Jonathan, and Myunghee Kim. 2015. Racial Resentment, Old-Fashioned Racism, and the Vote Choice of Southern and Nonsouthern Whites in the 2012 U.S. Presidential Election. Social Science Quarterly 96 (4): 905–922. https://doi.org/10.1111/ssqu.12184.
Lewis, Nicole. 2017. Comparing the ‘Trump Economy’ to the ‘Obama Economy.’ Fact Checker Analysis, Washington Post, December 14. https://www.washingtonpost.com/news/fact-checker/wp/2017/12/14/comparing-the-trump-economy-to-the-obama-economy/.
Lind, Dara. 2019. ‘Immigrants are Coming Over the Border to Kill You’ is the Only Speech Trump Knows How to Give. Vox, January 9. https://www.vox.com/2019/1/8/18174782/trump-speech-immigration-border.
Magleby, David B., Candice J. Nelson, and Mark C. Westlye. 2011. The Myth of the Independent Voter Revisited. In Facing the Challenge of Democracy: Explorations in the Analysis of Public Opinion and Political Participation, ed. Paul M. Sniderman and Benjamin Highton, 238–263. Princeton, NJ: Princeton University Press.
McElwee, Sean, and Jason McDaniel. 2017. Economic Anxiety Didn’t Make People Vote for Trump, Racism Did. Nation, May 8. https://www.thenation.com/article/economic-anxiety-didnt-make-people-vote-trump-racism-did/.
McKee, Seth C., Daniel A. Smith, and M.V. (Trey) Hood III. 2019. The Comeback Kid: Donald Trump on Election Day in 2016. PS: Political Science and Politics 52 (2): 239–242. https://doi.org/10.1017/S1049096518001622.
McThomas, Mary, and Michael Tesler. 2016. The Growing Influence of Gender Attitudes on Public Support for Hillary Clinton, 2008–2012. Politics & Gender 12 (1): 28–49. https://doi.org/10.1017/S1743923X15000562.
Miller, Warren E., and J. Merrill Shanks. 1996. The New American Voter. Cambridge, MA: Harvard University Press.
Neville, Helen A., Roderick L. Lilly, Georgia Duran, Richard M. Lee, and LaVonne Browne. 2000. Construction and Initial Validation of the Color-Blind Racial Attitudes Scale (CoBRAS). Journal of Counseling Psychology 47 (1): 59–70. https://psycnet.apa.org/doi/10.1037/0022-0167.47.1.59.
Nowrasteh, Alex. 2018. The White House’s Misleading & Error Ridden Narrative on Immigrants and Crime. Cato at Liberty (blog), Cato Institute, June 25. https://www.cato.org/blog/white-houses-misleading-error-ridden-narrative-immigrants-crime.
Piston, Spencer. 2010. How Explicit Racial Prejudice Hurt Obama in the 2008 Election. Political Behavior 32 (4): 431–451. https://doi.org/10.1007/s11109-010-9108-y.
Popkin, Samuel L. 1994. The Reasoning Voter: Communication and Persuasion in Presidential Campaigns. 2nd ed. Chicago: University of Chicago Press.
Reny, Tyler T., Loren Collingwood, and Ali A. Valenzuela. 2019. Vote Switching in the 2016 Election: How Racial and Immigration Attitudes, Not Economics, Explain Shifts in White Voting. Public Opinion Quarterly 83 (1): 91–113. https://doi.org/10.1093/poq/nfz011.
Schaffner, Brian F., Matthew MacWilliams, and Tatishe Nteta. 2018. Understanding White Polarization in the 2016 Vote for President: The Sobering Role of Racism and Sexism. Political Science Quarterly 133 (1): 9–34. https://doi.org/10.1002/polq.12737.
Sears, David O., and P.J. Henry. 2003. The Origins of Symbolic Racism. Journal of Personality and Social Psychology 85 (2): 259–275. https://psycnet.apa.org/doi/10.1037/0022-3514.85.2.259.
Setzler, Mark, and Alixandra B. Yanus. 2018. Why Did Women Vote for Donald Trump? PS: Political Science & Politics 51 (3): 523–527. https://doi.org/10.1017/S1049096518000355.
Sides, John, Michael Tesler, and Lynn Vavreck. 2018. Identity Crisis: The 2016 Presidential Campaign and the Battle for the Meaning of America. Princeton, NJ: Princeton University Press.
Tesler, Michael. 2012. The Spillover of Racialization into Health Care: How President Obama Polarized Public Opinion by Racial Attitudes and Race. American Journal of Political Science 56 (3): 690–704. https://doi.org/10.1111/j.1540-5907.2011.00577.x.
Valentino, Nicholas A., Carly Wayne, and Marzia Oceno. 2018a. Mobilizing Sexism: The Interaction of Emotion and Gender Attitudes in the 2016 US Presidential Election. Public Opinion Quarterly 82 (S1): 799–821. https://doi.org/10.1093/poq/nfy003.
Valentino, Nicholas A., Fabian G. Neuner, and L. Matthew Vandenbroek. 2018b. The Changing Norms of Racial Political Rhetoric and the End of Racial Priming. Journal of Politics 80 (3): 757–771. https://doi.org/10.1086/694845.
Wuthnow, Robert. 2018. The Left Behind: Decline and Rage in Rural America. Princeton, NJ: Princeton University Press.
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Green, A.D. (2020). Explaining Vote Choice in 2016: How the Attitudinal Characteristics of Iowans Shaped the Vote for Donald Trump. In: From the Iowa Caucuses to the White House. Palgrave Studies in US Elections. Palgrave Pivot, Cham. https://doi.org/10.1007/978-3-030-22499-8_4
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