Stephen L. Morgan’s research while affiliated with Harvard University and other places

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Publications (66)


Economic Populism and Bandwagon Bigotry: Obama-to-Trump Voters and the Cross Pressures of the 2016 Election
  • Preprint

June 2019

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30 Reads

Stephen L. Morgan

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Jiwon Lee

Through an analysis of validated voters in the 2016 American National Election Study, this article considers the voters who supported Obama in 2012 and Trump in 2016. More than 5.7 million in total, Obama-to-Trump voters were essential to Trump’s victory in the Electoral College. They were more likely to be white, working class, and resident in the Midwest. They had lower levels of political interest, were centrist in both party affiliation and ideology, and were late deciders for the 2016 election. On economic interests, they were centrists, except for trade policy, which they viewed, on average, as a greater threat than other voters. They claimed to have more experience with economic vulnerability than Democratic loyalists of comparable social standing. On racial attitudes, including the racialized economic topic of immigration, they had a profile similar to Republican loyalists. While their support of Trump may be attributable to surging white nativism, this article argues for an alternative explanation. Voters who were attracted by Trump’s economic populism only joined his coalition if they could accept his racialized rhetoric. As a result, the Trump bandwagon predominantly attracted generically bigoted voters with racial attitudes similar to Republican loyalists.


Correct Interpretations of Fixed-effects Models, Specification Decisions, and Self-reports of Intended Votes: A Response to Mutz
  • Article
  • Full-text available

December 2018

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31 Reads

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8 Citations

Socius Sociological Research for a Dynamic World

The author thanks Professor Mutz for her informative reaction to his article. In this six-part response, the author first addresses Professor Mutz’s new claim that “Morgan’s interpretation suggests a misunderstanding of the panel models.” The author explains that this concern with his understanding can be set aside because Mutz’s interpretations of her own fixed-effects models are incorrect. The author then discusses very briefly four areas of disagreement that readers will want to judge on their own: the value of prejudice-incorporating explanations in comparison with status threat–only explanations, measurement assumptions about support for free trade, the value of adjustments for party identification, and how best to consider the political preferences of nonwhite voters when evaluating the status-threat explanation. The author concludes with a defense of two of his own prior published articles that Mutz critiques in her comment in an apparent attempt to widen the field of contestation.

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Table 3 . A Fair Critic's Alternative Conditioning Analysis for What Education Represents. Average Marginal Effect of Having Less Than a Bachelor's Degree When Conditioning on:
Table 4 . Fixed-effect linear Regression Models of Relative Thermometer Ratings of the Republican Candidate in 2012 and 2016.
Status Threat, Material Interests, and the 2016 Presidential Vote

July 2018

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91 Reads

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63 Citations

Socius Sociological Research for a Dynamic World

The April 2018 article of Diana Mutz “Status Threat, Not Economic Hardship, Explains the 2016 Presidential Vote,” was published in the Proceedings of the National Academy of Sciences and contradicts prior sociological research on the 2016 election. Mutz’s article received widespread media coverage because of the strength of its primary conclusion, declaimed in its title. The present article is a critical reanalysis of the models offered by Mutz, using the data files released along with her article. Contrary to her conclusions, this article demonstrates that (1) the relative importance of economic interests and status threat cannot be estimated effectively with her cross-sectional data, and (2) her panel data are consistent with the claim that economic interests are at least as important as status threat. The preexisting sociological literature has offered interpretations that incorporate economic interests and, as a result, provides a more credible explanation of the 2016 election.


Table 1 : Components of Trump's voters in 2016. 
Trump Voters and the White Working Class

April 2018

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2,530 Reads

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87 Citations

Sociological Science

To evaluate the claim that white working-class voters were a crucial block of support for Trump in the 2016 presidential election, this article offers two sets of results. First, self-reports of presidential votes in 2012 and 2016 from the American National Election Studies show that Obama-to-Trump voters and 2012 eligible nonvoters composed a substantial share of Trump’s 2016 voters and were disproportionately likely to be members of the white working class. Second, when county vote tallies in 2012 and 2016 are merged with the public-use microdata samples of the 2012-to-2016 American Community Surveys, areal variations across 1,142 geographic units that sensibly partition the United States show that Trump’s gains in 2016 above Romney’s performance in 2012 are strongly related to the proportion of the voting population in each area that was white and working class. Taken together, these results support the claim that Trump’s appeal to the white working class was crucial for his victory.


Trump Voters and the White Working Class

March 2018

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25 Reads

To evaluate the claim that white, working-class voters were a crucial block of support for Trump in the 2016 presidential election, this article offers two sets of results. For the first, self-reports of presidential vote in 2012 and 2016 from the American National Election Studies (ANES) show that Obama-to-Trump voters and 2012 eligible non-voters composed a substantial share of Trump's 2016 voters. These voters were also more likely to be members of the white working class. Because the ANES has a somewhat coarse occupation-based measure of the working class, and has only a modest sample size, a complementary analysis is offered that merges county vote tallies in 2012 and 2016 with the public-use microdata samples of the 2012-2016 American Community Surveys. For this second piece of analysis, areal variation across 1,142 geographic units that sensibly partition the United States shows that Trump's gains in 2016 above Romney's performance in 2012 are strongly related to the proportion of the voting population in each area that is white and working class. This strong relationship holds in the six states that Trump flipped in his 2016 victory, and it varies little across other agglomerations of competitive and non-competitive states. Taken together, these results support the claim that Trump's appeal to the white working class was crucial for his victory.


Table 1 : The class schema utilized for both the CPS-VRS and GSS analyses.
Figure 2: Differences by education group in voter turnout rates in 18 competitive states among respondents not currently in the labor force, 2004 to 2016. Non-Hispanic whites are shown in red, and all others are shown in gray. 
The White Working Class and Voter Turnout in U.S. Presidential Elections, 2004 to 2016

November 2017

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301 Reads

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39 Citations

Sociological Science

Through an analysis of the 2004, 2008, 2012, and 2016 Current Population Surveys as well as the 2004 through 2016 General Social Surveys, this article investigates class differences and patterns of voter turnout for the last four U.S. presidential elections. After developing some support for the claim that a surge of white, working-class voters emerged in competitive states in 2016, a portrait of class differences on political matters among white, non-Hispanic, eligible voters between 2004 and 2016 is offered to assess the electoral consequences of this surge. These latter results are consistent with the claim that racial prejudice, anti-immigrant sentiment, concerns about economic security, and frustration with government responsiveness may have led many white, working-class voters to support an outsider candidate who campaigned on these themes. However, these same results give no support to the related claim that the white working class changed its positions on these matters in response to the 2016 primary election campaign or in the months just before the general election.


The White Working Class and Voter Turnout in US Presidential Elections, 2004—2016

October 2017

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9 Reads

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2 Citations

Through an analysis of the 2004, 2008, 2012, and 2016 Current Population Surveys, as well as the 2004 through 2016 General Social Surveys, this article investigates class differences and patterns of voter turnout for the last four US presidential elections. After developing some support for the claim that a surge of white working-class voters emerged in competitive states in 2016, a portrait of class differences on political matters among white non-Hispanic eligible voters between 2004 and 2016 is offered to consider the consequences of this compositional shift. These latter results are consistent with the claim that racial prejudice, anti-immigrant sentiment, concerns about economic security, and frustration with government responsiveness may have led many white working-class voters to support an outsider candidate who campaigned on these themes. However, these same results give no support to the related claim that the white working class changed its positions on these matters in response to the 2016 primary election campaign or in the months just before the general election.



EGP class descriptions.
Social Class and Party Identification During the Clinton, Bush, and Obama Presidencies

August 2017

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13 Reads

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13 Citations

Sociological Science

Through an analysis of the 1994 through 2016 General Social Surveys, this article demonstrates that a substantial proportion of eligible voters within the working class turned away from solid identification with either the Democratic Party or the Republican Party during the Obama presidency. Even before the 2016 election cycle commenced, conditions were uncharacteristically propitious for a Republican candidate who could appeal to prospective voters in the working class, especially those who had not voted in recent presidential elections but could be mobilized to vote. These findings support the contested position that variation in party identification is a genuine leading indicator of electoral outcomes and perhaps also, in this case, of party realignment.



Citations (54)


... Testing for differences between group means is highly relevant in psychology and related disciplines. Especially when an experiment has been conducted where a randomization procedure guarantees that participants are similar to each other regarding all background variables, a simple comparison of group means is adequate to estimate the causal effect of treatments (Morgan & Winship, 2015). In such scenarios, the t-test has been firmly established for a very long time to compute differences between group means and provide not only p-values but also confidence intervals for inference (Cressie & Whitford, 1986). ...

Reference:

Same or Different? Comparing the Coverage Rate of Five Different Approaches for Testing the Difference of Two Groups Means
Counterfactuals and Causal Inference: Methods and Principles for Social Research
  • Citing Book
  • December 2014

... In other words, by design, the APC-I method does not estimate the kind of linear or nonlinear cohort effects in traditional APC models because the latter's assumption that cohort effects can occur independently and additively of age and period effects lacks theoretical grounding and is thus arbitrary and questionable. 2 Our questioning of the validity of the accounting framework is not new (Hobcraft et al., 1982;Holford, 1983) and has been echoed in recent methodological work (see, e.g., Morgan, 2022;Morgan & Lee, 2021;Neil & Sampson, 2021). ...

A double-diamond retrospective on modeling change in attitudes and opinions
  • Citing Article
  • October 2022

Social Science Research

... Although there is clearly a relationship between political party and orientation, they are different con- cepts as both the Republican and the Democratic Party are composed of a variety of ideological camps and coalitions (Noel, 2016). 2 All models include controls for factors commonly associated with views of capital punishment. We operationalize racial animus with a measure of symbolic racism (see Morgan, 2022). Respondents were prompted with the following: "Irish, Italians, Jewish and many other minorities overcame prejudice and worked their way up. ...

Prejudice, Bigotry, and Support for Compensatory Interventions to Address Black–White Inequalities: Evidence from the General Social Survey, 2006 to 2020

Sociological Science

... In other words, by design, the APC-I method does not estimate the kind of linear or nonlinear cohort effects in traditional APC models because the latter's assumption that cohort effects can occur independently and additively of age and period effects lacks theoretical grounding and is thus arbitrary and questionable. 2 Our questioning of the validity of the accounting framework is not new (Hobcraft et al., 1982;Holford, 1983) and has been echoed in recent methodological work (see, e.g., Morgan, 2022;Morgan & Lee, 2021;Neil & Sampson, 2021). ...

A Rolling Panel Model of Cohort, Period, and Aging Effects for the Analysis of the General Social Survey
  • Citing Article
  • November 2021

Sociological Methods & Research

... Although previous studies showed that the STEM attrition rates were higher among women than among men (Bieri Buschor et al., 2014;Weeden et al., 2020), we did not find that STEM workforces shrank more among women than men. Our results show that among the LEHMS and the white-collar STEM careers, there were comparable shrinkages in both gender groups, and that the women bluecollar STEM workforce maintained its size. ...

Pipeline Dreams: Occupational Plans and Gender Differences in STEM Major Persistence and Completion
  • Citing Article
  • June 2020

Sociology of Education

... Moreover, a substantial part of the literature has highlighted that conspiracy beliefs and mentality is favoured by pathological factors such as anxiety, paranoia and schizotypy as well as political factors such as perceived powerlessness and anomie (see Goreis & Voracek, 2019). Political science research conducted in the United States even points at specific elements of local cultures that favour the emergence of conspiracy beliefs, such as a paranoid style among mass opinion (Oliver & Wood, 2014) or ethnic prejudice (Morgan & Lee, 2019). ...

Economic Populism and Bandwagon Bigotry: Obama-to-Trump Voters and the Cross Pressures of the 2016 Election

Socius Sociological Research for a Dynamic World

... However, the empirical disentanglement of the relative importance of the factors behind these two hypotheses is not easy, as witnessed by the sharp confrontation between Mug and Morgan in 2018 about the possible explanation of Trump's victory (Morgan, 2018b(Morgan, , 2018aMutz, 2018aMutz, , 2018b, and more generally by the series of works by Colantone and Stanig (2018c. This study aims to investigate the reasons for the rise of abstention and the success of left-wing and rightwing populist parties in Italy, relating electoral results to demographic and socio-economic factors. ...

Correct Interpretations of Fixed-effects Models, Specification Decisions, and Self-reports of Intended Votes: A Response to Mutz

Socius Sociological Research for a Dynamic World

... Political speeches in various settings were the subject of this research. Some have examined the US presidential speeches in the context of the "War on Terror" narrative (Rashidi and Souzandehfar 2010;Sarfo and Krampa, 2012;Morgan, 2018) and the US election campaign speeches (Rahimi et al., 2010;Wang, 2010). Other studies have examined political speeches in Pakistan (Memon et al. 2014;Iqbal, 2013) and Africa (Alo, 2012). ...

Status Threat, Material Interests, and the 2016 Presidential Vote

Socius Sociological Research for a Dynamic World

... An intraclass correlation coefficient test (Two-way random effects, absolute agreement, single rater/measurement: ICC (2,1)) was performed to determine the reliability and repeatability of the linear distances ( [51,54]. To prevent false significant comparisons due to the small sample size [55], statistical significance was set at 5% (p ≤ 0.05) and 0.5% (p ≤ 0.005) [56]. ...

Redefine statistical significance

... Among our controls are five demographic characteristics. Support for Trump is often shown to be higher among voters who are White, male, older, religious, and less educated (e.g., Morgan & Lee, 2018;Tyson & Maniam, 2016). Race and gender are potentially as fundamental to shaping world view as personality. ...

Trump Voters and the White Working Class

Sociological Science