Abstract
While there is a strong scholarly consensus that race continues to play a central role in American politics, research on the effects of the race of candidates on electoral behavior has produced decidedly mixed results. Using American National Election Studies data, Cooperative Congressional Election Studies data, and a non-linear systems of equations approach to estimation, I show that race-based misperceptions of candidates’ ideologies have a significant indirect impact on voting decisions in elections to the U.S. House of Representatives. The indirect effects of race on voting behavior outweigh any direct effects of racial prejudice by a substantial margin. More specifically, the results suggest that white citizens will tend to perceive black candidates to be more liberal than white candidates who adopt similar policy positions, and that these race-based misperceptions disadvantage black candidates at the ballot box.
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Notes
An exception seems to be research on the election of Barack Obama to the presidency in 2008. Highton (2011), Jacobsmeier and Lewis (2013), Lewis-Beck et al. (2010), Pasek et al. (2009), Piston (2010), Schaffner (2011), and Tesler and Sears (2010) all find that race had a significant impact on Obama’s electoral fortunes. However, given the unique features of presidential election campaigns and the historic nature of Obama’s election, it would be a mistake to make generalizations about the effects of the race of candidates on elections based solely on the 2008 presidential election.
In 2004, five black representatives, all Democrats, were elected in majority-white districts. Eighteen black candidates ran in majority-white districts, including 13 Democrats, 3 Republicans, and 2 independents. The number of black representatives elected in majority-white districts actually decreased to four in 2006. In 2010, six black candidates were elected to Congress in majority-white districts, with two of those candidates being Republicans.
Although African Americans have won a number elections in majority-white districts, most of these victories have been won by black incumbents in redrawn districts that were previously majority-minority districts (Lublin 1997).
Brewer and Kramer (1985) provide a review of the causes of such accentuation.
Sniderman et al. (1993), for example, describe the use of the “likeability heuristic,” by which one’s feelings toward a group influence one’s impressions of members of that group.
There is little reason to think that the effects of race and ethnicity on perceptions of candidates’ ideologies are limited to black and white citizens’ views of black and white candidates. The perceived ideologies of Latino candidates, for example, may also be influenced by the ethnicity of those candidates. The perceptual effects of being a black candidate, however, are likely to be stronger given the particularly overwhelming identification of black Americans with the Democratic Party and liberal economic policies over the last several decades. The greater ideological and partisan variation among members of other racial and ethnic groups in the United States renders theoretical expectations regarding stereotypes of candidates from these groups much less straightforward. As such, and to avoid greatly complicating the analysis with the inclusion of many additional racial pairings and interaction terms, I focus on perceptions of black candidates in this paper and leave the analysis of perceptions of candidates of other races and ethnicities to future research.
Zilber and Niven (2000) argue that the media contributes to stereotypical views of African American politicians as being focused on issues of race.
One prominent study that examines the effects of the race of candidates on voting decisions without examining how race affects perceptions of candidates’ ideologies is Citrin et al. (1990). In an analysis of state-wide races in California in 1982, when African American Tom Bradley ran for governor, the authors find that attitudes toward governmental support for blacks is a significant predictor of vote choice, while the race of candidates is not. Unlike the present study, which examines thousands of elections, Citrin et al. (1990) is also limited in that it examines only four elections.
At a theoretical level, this is true not only in proximity-based models of voting behavior, but also in directional models. See, for example, Rabinowitz and Macdonald (1989).
In this paper, I use a candidate’s DW-Nominate score, which is based on roll-call voting behavior, as a measure of his or her ideological preferences. I refer to this measure as a candidate’s “revealed ideology.” Revealed ideologies may be affected factors such as constituency preferences and partisan considerations as well as candidates’ personal preferences, which cannot be directly observed. As candidates’ revealed ideologies, as expressed through roll call votes, affect policy most directly, a strong argument can be made that representation is enhanced when citizens have accurate perceptions of those revealed ideologies.
As noted below, the dataset that I use does not contain information on the revealed ideologies of challengers. Because of this, the factors that affect perceptions of challengers’ ideologies cannot be modeled within this framework. Hence, challenger ideology does not enter into the system until the second equation.
The inclusion of all of the excluded exogenous variables in the system in Eq. 1 renders this estimation method very similar to the two-step version of 2SLS, with the main difference being that the equations in the system are non-linear.
The question on perception of House candidates’ ideologies was asked in 1978, 1980, 1982, 1986, 1990, 1994, 1996, 1998, 2000, 2002, and 2004.
The downside of pooling the data over so many years is that if one wants to estimate regression coefficients with the greatest possible precision, those coefficients must be assumed to remain unchanged over the entire time period that is covered by the data. This assumption may be unreasonable in some cases. While it is certainly possible that levels of racial prejudice declined significantly between 1978 and 2004, the importance of race-based stereotypes in determining perceptions of candidate ideologies should be less variable over the same time period, as these stereotypes are not necessarily reflective of “simple” racial prejudice as it is commonly understood. Nevertheless, I did repeat the following analyses on two subsamples of data based on whether the survey year was between 1978 to 1986 or 1990 and 2004. The key results presented below hold within each subset of the data, albeit at a less stringent level of statistical significance. These results are available from the author.
I also ran the analysis on the CCES data from 2006 and 2008, which contain a different, and somewhat less standard, measure of perceptions of candidate’s ideologies than the ANES and 2010 CCES data. The results are available in Table OL1 in the online appendix, and they provide further support for the main hypothesis tested in this paper.
Although it would be preferable to include both incumbents and challengers in the analysis, imputed measures of challengers’ ideologies such as those developed by scholars such as Ansolabehere et al. (2001) and Burden (2004) have not been widely adopted. Beyond the lack of scholarly consensus on the reliability of these measures, the efforts of Ansolabehere et al. (2001) and others who derived challenger ideologies from the National Political Awareness Tests (NPATs) administered by Project Vote Smart in 1996 and 1998 have been hampered by the prohibitively large number of candidates refusing to fill out NPAT surveys in subsequent years. Additionally, it is likely that respondents make greater use of racial stereotypes when they know little about a given candidate. As respondents are also likely to know more about incumbents then challengers, the present analysis is at little risk of overestimating the importance of racial stereotypes in evaluations of candidates’ ideologies. Nevertheless, while the sizes of important subpopulations of respondents from two years of NPAT-based data are not large enough for precise estimation of the coefficients of interest in this paper, I did use the 1996 data described in Ansolabehere et al. (2001) along with data on the race of challengers from The Joint Center for Political and Economic Studies’ Focus Magazine to estimate the effects of race on perceptions of challengers’ ideologies. The coefficients, while not statistically significant, are in the expected directions. The results are available in Table OL2 in the online appendix.
The DW-Nominate scores used here are first dimension DW-Nominate scores, which are often interpreted as representing an economic ideological dimension, the dimension that is typically dominant in American politics. It is reasonable to think, however, that candidates’ policy positions on issues related to civil rights—positions which do not fall neatly onto the economic dimension—are important in determining both citizens’ perceptions of candidates’ ideologies and the quality of substantive representation that citizens receive (Cameron et al. 1996; Grose 2005; Swain 1995). As an alternative measure of candidates’ ideologies, Leadership Council of Civil Rights (LCCR) scores might better tap such policy positions. While it is important to note that LCCR scores, like DW-Nominate scores, are based only on votes on bills that make it to the floor for roll call votes, and hence may also fail to ideally capture differences in legislators’ preferences regarding race-related issues, Grose (2005) finds that with appropriate controls in place, black legislators have significantly more liberal DW-Nominate scores but do not have more liberal LCCR scores. Nevertheless, I did estimate models of perceptions of candidates’ ideologies using LCCR scores in place of DW-Nominate scores. The results are available from the author. The substantive results described in this paper are robust to using this alternative measure.
Although the approach that I employ here does not require direct comparison between incumbents’ locations on the DW-Nominate scale and the perceived location of incumbents on the 7-point perceived ideology scale, some may question the degree to which the subsequent regression analysis can account for differences between the two scales. I refer readers to Powell (1989) for evidence that the regression approach yields reasonable results. Moreover, studies that do attempt to directly compare placements on the two scales, such as Griffin and Flavin (2007), often find that the results are robust to a variety of scaling procedures.
Accounting for the role of education here also addresses, at least to some extent, the general advice of Sniderman et al. (1993) that we not assume that stereotypes operate in the same way for all types of citizens.
Education is clearly not the only variable that might affect the accuracy of respondents’ perceptions. In Table OL3 the online appendix, I include the age of respondents and the levels of interest that they have in elections as additional measures of political sophistication, as well as interaction terms between each of these variables and DW-Nominate and interactions between education and race. I have omitted these variables from the present analysis to make it more tractable, and to simplify the presentation of the results of the two-stage model. The inclusion of these variables has little effect on the substantive results described below. Matsubayashi and Ueda (2011) provide an interesting analysis of the effects of information levels on the use of racial stereotypes.
Partisan identification has strong effects even on beliefs regarding factual information such as death counts in wars (Berinsky 2007).
Partisan “leaners” are coded as independents. The substantive conclusions discussed below are unchanged if leaners are coded as partisans.
The coefficient on White Voter, Black Incumbent is statistically significant at the p=0.10 level, or at the p=0.05 level if a one-tailed test is used.
Systematic differences between white respondents in districts with black incumbents and white respondents in districts without black incumbents could also affect perceptions of black candidates’ ideologies, biasing the coefficient on White Respondent, Black Incumbent. In prior work (Jacobsmeier 2014), I use various methods, including coarsened exact matching (Iacus et al. 2012), to show that the race of respondents and candidates has a substantively large impact on the perception of candidates’ ideologies even when district demographics such as the percentage of citizens in each district that are black are controlled for. Multicollinearity renders including district characteristics in the ANES models impractical. In the 2010 CCES data, including the percentage of a district’s population that is black in the model (as well as a term that interacts this percentage with White Respondent, Black Candidate) does not significantly change the substantive results.
All variables are centered at their mean or median values; as such, statistical significance is indicated for situations in which variables that are interacted with DW-Nominate in the model are at their mean or median values.
Although the coefficient on DW-Nominate is quite a bit larger in the CCES model, this is due in part to the education measure being different from the one used in the ANES. The distribution of the CCES measure also affects DW-Nominate x Education term, and this accounts for some of the difference in the DW-Nominate coefficients. The substantive effects of DW-Nominate, in terms of predicted probabilities, are, on average, slightly larger in the CCES than the ANES model.
Voters need not be roughly normally distributed for this conclusion to hold. The normal distributions shown in the figure are used for illustrative purposes only.
It is worth noting here that black Republican candidates may actually be advantaged by race-based perceptual inaccuracies, although the analysis here should not be taken to indicate that voters misperceive black Democrats and black Republicans in the same way. Additionally, while voters to the left of the midpoint of BDP and BDR may actually prefer black candidates over ideologically identical white candidates, their voting decisions will not be affected.
An important caveat here is that when looking across districts, more conservative districts are very likely to be more Republican districts as well. The “all else equal” qualification is particularly important to keep in mind here, as is evident below.
Black voters are not considered, as the race of candidates was not found to have a significant effect on their perceptions of candidates.
Values of ideology, while reflecting the conditional distribution of ideology by party in the original data, were assigned to observations randomly within party affiliations. This ignores the modest correlation between level of education and ideology, but is preferable to artificially creating a strong correlation between the two variables by assigning, for example, lower values of education to more liberal respondents.
The Democrat is the incumbent in all of the districts described here, and hence the large vote shares for Democrats to some extent reflect the incumbency advantage.
It should be noted however, that scholars such as Berinsky (2007) have found that perceptual errors resulting from following elite and media cues are not always remedied by the subsequent provision of factual information contrary to those errors.
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Acknowledgments
I would like to thank Lynda Powell, Dick Niemi, Valeria Sinclair-Chapman, Dave Primo, Stu Jordan, Nicole Asmussen, Marc Hetherington, Regina Branton, Stephen Voss, Stephanie Stewart, Adam Porter, and Lambert Jacobsmeier for their helpful suggestions.
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Jacobsmeier, M.L. From Black and White to Left and Right: Race, Perceptions of Candidates’ Ideologies, and Voting Behavior in U.S. House Elections. Polit Behav 37, 595–621 (2015). https://doi.org/10.1007/s11109-014-9283-3
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DOI: https://doi.org/10.1007/s11109-014-9283-3