Abstract
Despite making notable gains at the local level, very few African Americans have been elected to the high-profile statewide offices of governor or U.S. senator. Previous research offers little systematic evidence on the role of racial prejudice in the campaigns of African Americans trying to reach these offices for the first time. In this paper, I introduce a new data set designed to test whether African American candidates for these offices are penalized due to their race. Comparing all 24 African American challengers (non-incumbents) from 2000 to 2014 to white challengers from the same party running in the same state for the same office around the same time, I find that white challengers are about three times more likely to win and receive about 13 percentage points more support among white voters. These estimates hold when controlling for a number of potential confounding factors and when employing several statistical matching estimators. The results conflict with earlier studies that focus on a single gubernatorial contest or elections at the U.S. House level.
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Notes
Of those eight winners, only five defeated white opponents in the general election. Barack Obama (D-IL), Tim Scott (R-SC), and Kamala Harris (D-CA) defeated non-white opponents to win their respective U.S. Senate elections.
U.S. Census Bureau, “Voting and Registration in the Election of 2016.” Data available at https://www.census.gov/data/tables/time-series/demo/voting-and-registration/p20-580.html, Table 4b.
Evidence consistent with the notion that some forms of racial animus have declined since the 1960s comes from many sources, including national surveys showing an increasing number of whites who say they would support a qualified black presidential candidate and social arrangements such as interracial marriage, integrated schools, and integrated neighborhoods (Schuman et al. 1997).
Looking exclusively at challengers only narrows the set of black candidacies by two since only Deval Patrick (D-MA) and Cory Booker (D-NJ) ran as an incumbents between 2000 and 2014.
The omitted cases are Barack Obama’s 2004 U.S. Senate campaign (against African American Republican Alan Keyes) and Tim Scott’s 2014 U.S. Senate campaign (against African American Democrat Joyce Dickerson).
In cases where there was a tie for the third most recent white candidate, both candidates were included, resulting in some black candidates having four (instead of three) white comparison observations. This explains why the number of white comparison candidates is 75 (instead of 72). The median number of years separating a white comparison election from the black candidate election is 6, with 68% of white comparison elections taking place within 6 years and 83% of white comparison elections taking place within 10 years of the black candidate election.
The surveys had an average error of 4.7% points when compared to the actual result of the election. For comparison, a FiveThirtyEight analysis of more than 8500 polls from 1998 to 2018 conducted within the final three weeks of a campaign found an average error of 5.9 percentage points. See Nate Silver, “The Polls Are All Right.” May 30, 2018. URL: https://fivethirtyeight.com/features/the-polls-are-all-right/. Additional analyses conducted using only exit polls and/or ecological inference are described in footnote 14 and reported in Appendix Online Tables 13, 14 and 15.
Although its reliability has been criticized (Freedman 1999), EI is commonly used to measure the voting behavior of groups when survey data is unavailable or unreliable. Perhaps the most prominent example of EI’s use is in voting rights court cases, which often turn on whether plaintiffs can demonstrate patterns of racially polarized voting. Other recent applications of EI to estimate vote choice for subgroups of the population include King et al. (2008) attempt to estimate support for Adolf Hitler by occupation in Weimar Germany; Barreto’s (2007) analysis of Latino support for co-ethnic candidates in U.S. mayoral elections; and Barreto et al. (2017) analysis of Latino support for Donald Trump in the 2016 U.S. presidential election.
To address concerns that differences in turnout between black versus white and white versus white contests render margin of victory comparisons inconclusive, no significant differences in turnout were found between the two types of contests. Black versus white contests had an average turnout of 45.46% of eligible voters, while turnout for white versus white contests averaged 46.13% (p = 0.39, two-tailed test).
The seven candidates (one black and six white) who did not receive a CF score were noncompetitive candidates who raised little money.
For example, the estimate of the black population for Mississippi in 1995 is the linear interpolation of the black population estimates provided by the 1990 and 2000 Census.
“Party advantage” is the state partisanship variable recoded so that Democratic partisanship is coded positive for Democratic candidates and Republican partisanship is coded positive for Republican candidates. In other words, the negative values in the table for both black and white candidates indicate that on average, they run in states whose partisanship favors the opposing party (Democrats running in Republican-dominated states and vice versa).
I also estimate models using an alternative measure of a state’s partisanship known as the Major Party Index (MPI), which takes into account the results of presidential, gubernatorial, U.S. Senate, U.S. House, and state legislative elections. For calculation details, see Ceaser and Saldin (2005). The results for all models using MPI are presented in Appendix Online Tables 5, 6, 7 and 8. Separate models substituting the state’s non-white population in place of the state’s black population are reported in Online Appendix Tables 9, 10, 11 and 12. Results of these alternate models do not substantively alter the main conclusions drawn from Tables 3 and 4.
The margin of victory among white voters is measured using exit polls, pre-election surveys, and ecological inference, which raises a question about whether results hold when this important indicator is measured in different ways. I address this issue in three ways. First, only observations that used exit polls are included. Second, the full sample is included, using ecological inference when exit polls were not available. Third, ecological inference is used for all observations. The results are robust to these specifications and are reported in Appendix Online Tables 13, 14 and 15.
I implement all variations of matching described in the rest of the paper using the MatchIt package in R (Ho et al. 2011).
Since matching requires dropping a large number of the observations, including state and party-year fixed effects is not possible due to the small number of remaining cases.
Recall that the black candidates all have matches on the other three covariates (state, party, and office sought) because I constructed the data set that way.
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I thank Jose Manuel Corichi Gomez and Kaitlin Braband for research assistance. For feedback and suggestions, I thank Tali Mendelberg, Martin Gilens, Christopher Achen, Jon Bakija, Sarah Jacobson, and participants at the Princeton American Political Behavior Workshop and the 2018 Annual Meeting of the Western Political Science Association. The data and code necessary to replicate the results of this paper are available in the Political Behavior Dataverse: https://dataverse.harvard.edu/dataverse/polbehavior.
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Tokeshi, M. Why are African American Governors and U.S. Senators so Rare? Exploring White Voters’ Responses to African American Statewide Candidates. Polit Behav 42, 285–304 (2020). https://doi.org/10.1007/s11109-018-9496-y
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DOI: https://doi.org/10.1007/s11109-018-9496-y