University of Illinois at Springfield



Do White In-Group Processes Matter, Too?? White Racial Identity and Support for Black Political CandidatesGregory A. PetrowUniversity of Nebraska OmahaJohn TransueUniversity of Illinois SpringfieldTimothy VercellottiWestern New England UniversityKeywords: vote choice, white racial identity, prejudice, racial resentment, Barack Obama, race and electionsScholars find that negative evaluations of blacks lead whites to vote against black political candidates. However, can an in-group psychological process have the same effect? We consider white racial identity to be a strong candidate for such a process. We argue that the mere presence of a black candidate cues the identity, reducing support for these candidates among whites. We test this hypothesis on vote choice in seven instances. Five of them involve simple vote choice models: the 2008 and 2012 Presidential elections, and three elections in 2010: The Massachusetts Gubernatorial election, black candidates for the U.S. House, and black candidates for the U.S. Senate. The other two are tests of the notion that white racial identity reduced President Obama’s approval, thus reducing support for all Democratic Congressional candidates in the 2010 Midterm and 2012 Congressional elections. We find support for these notions in all seven cases, across these seven elections, using four different survey research datasets, and four different measures of white identity. Comparisons with other presidential elections show that white identity did not significantly affect mono-racial elections. Furthermore, we find the white identity and racial resentment results to be very similar in terms of their robustness and apparent effect sizes. This indicates in-group evaluations, and those that focus on out-groups, operate independently of one another.Whether or not race-related feelings and beliefs cost black candidates the votes of whites in U.S. elections is a very important question for political behavior scholars. Most blacks are the descendants of slaves, and the legacy of slavery continues, as blacks suffer in comparison to whites in most of the ways the two racial groups can be compared (see Kinder and Dale-Riddle 2012 for a summary). A political avenue by which blacks may redress this inequality is by electing other blacks to office; that is, if the white majority will elect them. Of significant concern is that most of the progress blacks have made since the 1960s in holding public office has been in majority-minority contexts. While blacks are 12% of the U.S. population, they only hold 2% of all elected offices (e.g. Kinder and Dale-Riddle 2012).The academic study of white racial prejudice and voting is expanding quickly. This literature can be divided into two eras: the pre-Obama era, and the post-Obama era. Before the election of President Obama, there were relatively few studies of this question, and they tended to yield mixed results. Some scholars found that whites were not reluctant to vote for black candidates (Bullock 2000, Citrin, Green and Sears 1990, Highton 2004, Voss and Lublin 2001), while others found they were reluctant (Bullock and Dunn 1999, Gay 1997, Reeves 1997, Terkildsen 1993). The election of President Obama has generated more interest in this question. Most scholars find that he did lose support among whites due to racial factors, or racial prejudice (Tesler and Sears 2010; Highton 2011; Jackman and Vavreck 2010; Lewis-Beck, Tien and Nadeau 2010, Pasek et al. 2009; Piston 2010; Redlawsk, Tolbert and Franko 2010; Schaffner 2011; and, Stephens-Davidowitz 2011). Only a few scholars do not reject the null hypothesis (e.g. Martinez and Craig 2010).In these studies what motivates white voters to oppose black candidates is either negative attitudes toward the outgroup, or negative out-group evaluations compared to positive in-group evaluations (such as Piston (2010) finding that when whites hold more positive attitudes toward whites relative to blacks, they voted against Obama). The focus on negative attitudes means that there has been less scholarly work on in-group processes. We pose the question – can an in-group identification produce the same result? Do whites oppose black candidates, simply because they favor their own group? Social identity theorists argue that the power of group identity stems from individuals extending their sense of self to include others (e.g. Brewer and Gardner 1996; Tajfel 1982). Consequently, this sense of “we-ness” leads individuals to benefit the self by favoring their in-groups. White racial identity is a strong candidate for such an in-group factor. White racial identity is a social identity. Social identity is the sense we have that there are others like us, with whom we share a collective fortune, because of a common group membership (e.g. Brewer 2007, Brewer and Gardner 1996; Conover 1984; Huddy 2013).There has been only one previous study of the relationship between white racial identity and vote choice. In her dissertation, Ashley Jardina (2014) finds that white racial identity leads whites to vote against President Barack Obama in 2012. However, we expand the analysis to the 2008 election, and we also test to see how white identity may matter in the mono-racial elections between 1984 and 2000. Our analysis includes variation in what we claim activates white racial identity: a black candidate running against a white one.How White Racial Identities come to be Politically ConsequentialMost group and social identities are politically inconsequential –they do not affect political attitudes or behaviors. Racial identity can only affect vote choice if it becomes politically consequential. How does a group identity become politically consequential? The first condition for individuals is that group identifiers must belong to the group they identify with (Conover 1984, 1988). Second, a substantial share of the group identifiers must identify with the group strongly. This is caused by a variety of factors. Those with strong identities perceive greater threat to their group (Huddy 2013). Threat can be in the form of perceived economic or symbolic interests. These interests are usually threatened in the form of losses – a group is losing compared to where it used to be, or is losing in comparison to other groups. These “loses” can be symbolic, or economic (Huddy 2013). These threat attitudes are concentrated among the people who strongly identify with their group. Some experiments show that when identity is cued, the common fate perception increases (Huddy 2013). Third, the group needs to be a social one – that is, a group that is generally salient to the society (e.g. race or gender, as opposed to belonging to something like a bowling league). Finally, among the stronger identifiers, the identity has political meaning. Referring to these criteria, the major racial and ethnic groups (e.g. whites, blacks and Latinos) are widely salient in society. The result is that those with certain skin complexions will be regarded as “white,” leading some people to self-identify with the racial group. But race is not only socially salient -- it is politically salient as well. It is widely known that most racial minorities vote with the Democratic Party and most whites vote with the Republican Party. This is an indicator of a political system that is generally racialized, such that the majority of whites endorse one set of interests, while the majority of minorities endorse a competing set of pared to the other racial and ethnic groups, whites claim the greatest perceived social status (Sidanius and Pratto 1999). Social identity theory predicts that this creates a powerful incentive for many whites to identify strongly with their group. People are more likely to identify with groups that the society values, because doing so increases people’s sense of self-esteem. No racial group in the U.S. is as valued as whites, with many even equating “white” and “American” as equivalent (Devos and Banaji 2005; Theiss-Morse 2009).Strong identities lead people to be on the look-out for threats to their group (e.g. Huddy 2013). As alluded to earlier, the threats can be in the form of economic or even perceived cultural challenges. Therefore, strongly identifying whites will perceive racial threat from blacks because of the contentious racial history. The history of race in the U.S., and especially the legacy of slavery, leads to blacks serving as whites’ competitive out-group (e.g. Ignatiev 1995; Key 1949; Roediger 2007; Tocqueville 1841). Indeed, policies that benefit blacks are seen by whites as hurting whites (Kinder and Sanders 1996). Electing African Americans to public office can be seen as a threat to whites because public officials make decisions regarding how to distribute public goods. In addition, electing blacks to public office is a sign that stigma against them is decreasing, creating a relative sense of the loss of white cultural advantage.The theoretical conceptualizations of white racial identity are varied. In psychology, many models regard them as existing in various stages or phases (e.g. Helms 1990). All of the models conceive of identity strength varying from weak to strong, but separating the different identity types are the meanings that the individuals ascribe to their racial group memberships. For example, while some white identifiers may recognize their racial group’s privileged position (thus holding liberal racial views), others may believe that whites compete against racial minorities on an uneven playing field which is pitched against them (Goren and Plaut 2012). Setting these different views of identity aside, scholars find that in general, whites with stronger racial identities hold more racially conservative attitudes (e.g. anti-black affect and feelings). However, while these studies generally reach this conclusion, the vast majority of them are conducted using convenience samples, limiting their generalizability to any populations (Arriola and Cole 2001; Branscombe, Schmitt and Schiffhauer 2007; Carter 1990; Carter, Helms and Juby 2004; Chow, Lowery and Knowles 2008; Croll 2007; Goren and Plaut 2012: Helms 1990; Knowles, Lowery, Schulman and Schaumberg 2013; Knowles and Lowery 2012; Knowles, Lowery, Unzueta, Knowles and Goff 2006; Levin, Sidanius, Rabinowitz and Federico 1998; Lowery, Chow and Unzueta 2014; Lowery, Knowles and Unzueta 2007; Lowery, Chow, Knowles and Unzueta 2012; Mack et al. 2002; Morrison, Plaut and Ybarra 2010; Pope-Davis and Ottavi 1994). A few are conducted using random samples (Citrin and Sears 2014; Hutchings et al. 2011; Levin and Sidanius 1999; Sears and Henry 2005; Sears and Savalei 2006). These particular studies produce mixed evidence in support of white identity affecting racial attitudes. Other scholars find even less evidence that white racial identity influences contemporary American politics. Because whites are the dominant racial group, and most whites live in racially segregated, majority-white settings, white racial meaning may be “hidden” (Doane 2005). Scholars find that most whites do not rank their racial identities as being important to their sense of self (Jaret and Reitzes 1999). Wong and Cho (2005) find limited effects for white identity on racial policy preferences. Citrin, Green, and Sears (1990, 76) show that the presence of a black candidate is not sufficient to activate all aspects of group conflict. Instead, “…the personal attributes of the black candidate and the electoral context do condition the reaction of white voters.” There is only one previous test of the relationship between white racial identity and vote choice (Jardina 2014).Activating White Racial IdentityWhite racial identity may be salient in two ways.? The first is a kind of chronic salience, whereby it always affects whites’ political behaviors in elections involving the major two party candidates.? In this way it would operate like party identification or ideology – it generally affects vote choice, regardless of the contextual aspects of elections. However, theories of social identity emphasize how the cueing or priming of identity is important (see Huddy 2013 for a thorough review of the literature).? In other words, the identity may not be chronically salient, but only salient when it is cued or primed by something in the environment.? When the identity is cued or activated, the associated attitudes and feelings become salient and affect behaviors and attitudes.? In other words, group identity is dynamic because its salience and meaning vary depending upon people’s environments. White racial identity may only affect white political behavior in some elections, but not others.Political scientists have long considered that black elected officials can cue racial thinking for whites (e.g. Hajnal 2001, Bobo and Gilliam 1990, Gay 2001, Reeves 1997).? Cueing an identity can activate a reflex to differentiate the self from the out-group. There are two aspects to this differentiation: notions of how the individual is similar to the in-group and different from the out-group (e.g. Brewer and Gardner 1996). A salient identity makes the aspects of the self that an individual shares with group members the most cognitively accessible, with individuals also comparing their personal and group characteristics to out-groups to bolster their positive in-group evaluations (Brewer and Gardner 1996; Tajfel 1982). As blacks increasingly compete for and are elected to positions as chief executives, in particular, such elections may serve as the strongest politicized racial cues because the elections are high-stimulus in nature. Electing the first black President of the United States may be the most potent politicized racial cue of all – so potent, in fact, as to constitute its own kind of racial conditioning of the political system.In addition to the cue provided by the skin color of black politicians, when those politicians run for election or re-election, their campaigns often result in more racial campaign messages, which serve as a kind of double-cue of racial thinking (Levy et al. 2010; McIlwain and Caliendo 2011).? Remembering that identity has different meanings depending on specific cues and contexts, black candidates and black elected officials will cue the?explicitly political meanings?of individuals’ white racial identities.? These candidates and elected officials represent the explicitly political agendas of these groups, as well as potent symbols of group status.? Electing a black candidate is an implicit step in raising the status of the group. As evidence of this cueing, Petrow (2010) finds that whites who endorse white identity are more likely to vote in Congressional districts with black candidates than in other Congressional districts. Also, Kinder and Dale-Riddle (2012) argue that a black candidate sends a cue that is so simple and so clear that its effect on elections is inevitable.Partisan and ideological associations with white racial identity are important components of the explicitly political meanings to the white electorate. Since the passage of the civil rights agenda in the 1960s, the political parties’ positions on race have become distinct to Americans (Carmines and Stimson 1981; 1986; Green, Palmquist and Schickler 2002). This distinction has transformed the Republican Party into the home for many whites who hold anti-black attitudes and affect (Valentino and Sears 2005). This leads to the prediction that black Democrats will cue more of a sense of racial threat than white Democrats, or even black Republicans, because white voters could believe that black Democrats are the greatest threat to white interests. Some scholars (Edsall and Edsall 1992; Ellis and Stimson 2012; Kellstedt 2003; Carmines and Stimson 1989) claim that the degree to which white Americans see the Democratic Party as favoring blacks over whites means that the Democratic Party has been racialized. Based on the existing literature, we test three hypotheses about the effect of white identity on vote choice in elections.H0: Null. Past investigations and theorizing have found no effect of white identification on vote choice, approval, and/or similar attitudinal variables. The null hypothesis simply states that the strength of white identity does not affect vote choice or presidential approval under any conditions.H1: Racialization of the Democratic Party. Identifying more strongly with whites will diminish support for Democratic presidential and Congressional candidates on average.H2: Candidate activation. When a white candidate runs against an African-American, white identity influences whites' vote choice.We proffer one additional hypothesis. Scholars find that Presidential approval affects voting for Congress (e.g. Campbell 1993). We hypothesize that white identity will reduce voting for President Obama, and the same logic leads us to expect that the factor will reduce his approval evaluations. We thus predict that white identity will lower his approval evaluations, and thus indirectly reduce support for Congressional Democrats across the country.H3: Indirect racialization. White identity reduces President Obama’s approval, thus indirectly reducing support for Democratic candidates in Congressional elections.DATA AND METHODSWe test our hypotheses in five electoral contests: the 2008 and 2012 Presidential elections, the 2010 and 2012 Congressional elections, and the 2010 Massachusetts Gubernatorial election. For the 2008 election we analyze data from the Cooperative Congressional Election Study (CCES; Ansolabehere 2008), for the 2010 and 2012 elections we use data from the American National Election Study (ANES), and for the Massachusetts Gubernatorial election we use data from the Massachusetts Statewide Survey (MSS) conducted by the Western New England University Polling Institute. In 2008 Barack Obama ran for President as the first black major party candidate in American history, and in 2012 he ran for re-election. In 2010, Deval Patrick ran for re-election as governor of Massachusetts after completing a term as the first black governor elected in that state. In 2010, three African Americans ran for U.S. Senate seats in the general election, all as Democrats: Kendrick Meek in Florida, Alvin Greene in South Carolina, and Mike Thurmond in Georgia (they all lost). In addition, 41 blacks ran for the U.S. House and were elected as voting members (two additional members were non-voting delegates, and all but two voting members were Democrats; Dade 2011). Finally, Barack Obama served as President during the 2010 and 2012 Congressional elections, leading us to believe that white identity could affect his Presidential approval. Since Presidential approval is a powerful determinant of Congressional voting in midterm Congressional elections (Tufte 1975), we test for the indirect effect of white identity impacting President Obama’s approval and indirectly affecting congressional vote choice, thus racializing Congressional election outcomes in the U.S. in 2010 and 2012 on average. In Appendix A we report the question wording for our respective measures of white racial identity (both the exact question wordings and resulting histograms), as well as methodological details for the surveys. Theory predicts that in addition to vote choice, our measures of white identity should predict related constructs. We estimate bi-variate relationships with these constructs in the spirit of demonstrating this construct validity. Specifically, theory predicts that white identity correlates with: Positive white stereotypes over blacks, feeling less close to blacks, having warmer feelings for whites, and colder feelings for blacks and Latinos. The ANES and CCES datasets also include some other constructs that should correlate with white identity as well, and so we include them in the analyses too (unfortunately, the MSS data lack the measures we need to test for construct validity). We find that for these two datasets the measures of white identity meet the criteria of construct validity, and we report the results of the tests in Appendix B.RESULTSVote Choice ModelsWe hypothesize that white identity directly costs black candidates votes, and also, that it does so in Congressional elections by reducing Presidential approval. We begin with the vote choice models. All analyses include only the white respondents. We employ sample weights and clustered standard errors in all models. We begin by reviewing results for the relationships between white identity and Presidential vote choice. The null hypothesis predicts that white identity will never lead whites to vote against Democrats for President, hypothesis one predicts white identity will always lead whites to oppose Democrats for President, and hypothesis two predicts it will when the Democrats run a black candidate for President. To review the results we turn to Table 1. As with this and all subsequent tables, we report only the most analytically important coefficients here, and the complete tables in Appendix C.Table 1. White Racial Identity among Whites and Democratic Presidential Vote Choice in 1984 thru 2000 and 2008 thru 2012: Logistic Regressions1984198819921996200020082012Mondale v. ReaganDukakis v. GHW BushClinton v. GHW BushClinton v. DoleGore v. GW BushObama v. McCainObama v. RomneyWhite Identity-.04 (.19)-.08 (.21).10 (.25)-.16 (.32)-.13 (.34)-.55* (.26)-.16** (.06)Racial controlsRacial ResentmentNot available-.07* (.03)-.36* (.17)Not available-.28 (.32)-.69* (.30)-.45** (.17)Intercept4.96** (.96)2.48* (1.01)5.61** (1.49).49 (1.44)4.24* (1.84)10.89** (2.69)5.37** (1.32)Pseudo-R2.51.47.56.58.61.78.71N10249949305877645262478Bivariate White Identity coefficient-.02(.13)-.29* (.14)-.04 (.17)-.45**(.14)-.25(.19)-.21*(.08)-.09** (.03)*p<.05, **p<.01See Appendix C for full coefficient reportAll dependent variables coded as 2 party vote1984 to 2000: Analysis of American National Election Study data. The white identity measure is the dichotomous “Feel close to Whites” measure.2008: Cooperative Congressional Election Study Data. See Appendix A for white identity wording.2012: American National Election Study data. See Appendix A for white identity wording.1984 standard errors clustered on counties; 1988 and 1992 on census tracts; 1996 and 2000 counties; 2008 and 2012 Congressional DistrictsStarting with 1992, all models employ sample weightsControl variables in all models: Party identification, ideological identification, economic evaluations, gender, education, income, age, church attendance, and region (Deep South) Control variables in all models but 2008: Egalitarianism and limited government.Control variables in 2008 only: Support withdrawing from Iraq and a carbon tax.Control variable in 2012 only: Oppose Health Care Reform Act We model the relationship between white identity and voting for the Democrat for President for the elections of 1984 to 2000, and then 2008 and 2012. The 2004 and 2008 ANES lacked identity measures. For 2008 we analyze data from the Cooperative Congressional Election Study. One can see in the top row of the table only the latter two coefficients are negative and statistically significant – whites with stronger levels of white identity voted against Barack Obama in 2008 and 2012. We include racial resentment as a control variable when available (Tesler and Sears 2010, Kinder and Sanders 1996). It led whites to vote against Michael Dukakis in 1988, Bill Clinton in 1992, and then Barack Obama in 2008 and 2012. We also report the bivariate coefficients between white identity and vote choice for comparison purposes.We plot the white identity coefficients (from the full models) and their corresponding 95% confidence intervals in Figure 1. One can see that before 2008, the coefficients centered around zero, and had very wide confidence intervals. However, in 2008 and 2012, the coefficients center below zero, and the confidence intervals stop before reaching the zero point, which reflects statistical confidence that these results hold for the population. In other words, the hyper-racialized thesis does not hold, as white identity only correlates with vote choice when Barack Obama is the candidate. The null hypothesis does not hold as well.The coefficients are in the units of logits, and thus are not intuitively interpretable. To provide a sense of the substantive impact we translate the Obama coefficients into predicted probabilities of voting for him in these two elections given stronger levels of white identity, while holding the values of the other variables in the analyses at their mean levels. We report the resulting predicted probability plots in Appendix D, as Figures D1 for 2008 and D2 for 2012. To summarize those results, we find that white racial identity reduced the predicted probability of the Obama vote in 2008 by about 30% (from 80% to 50%), and in 2012 by about 10% (from 45% to 35%).Our next case involving white identity affecting vote choice involves another African American executive – the governor of Massachusetts, Deval Patrick. Governor Patrick was first elected in 2006 and then re-elected in 2010. Here we have two dependent variables: a pre-election measure of support for him (in late October), and a post-election self-reported vote (see Table 2). Table 2: White Racial Identity among Whites, Democratic Vote Choice and Candidate Preference for Massachusetts Governor in 2010 among Whites, Logistic RegressionVariablePatrick Candidate Preference 2010Patrick Vote 2010White Identity^-.38** (.14)-.27* (.13)Intercept^-.26 (.77).77 (1.51)N^390204Pseudo R2 .42.47Bivariate White Identity coefficient-.17* (.08)-.15 (.09)**p<.01, *p<.05Data source: 2010 Massachusetts State Survey.See Appendix C for full coefficient reportResults incorporate sample weights for gender, age, and race.Models cluster standard errors on counties.^Control variables in these two models: Massachusetts right direction, party identification, education, income, female and age.The survey interviewers at Western New England University who conducted the Massachusetts State Survey re-interviewed more than 200 of the respondents from the pre-election survey to ask them whom they actually voted for (the white identity measure is from wave 1). This allows us to analyze both the pre-election candidate preference (from wave one), as well as the self-reported vote choice (from wave two). In both cases, stronger white identity predicts opposition to Governor Patrick. In the last row of the table we report the bivariate coefficient for comparison purposes.To assess the substantive magnitudes of these relationships, we estimate how the predicted probabilities of Patrick’s pre-election support and Election Day vote choice share vary according to stronger levels of white racial identity. When estimating this relationship, we hold the other variables in the analysis constant at their means. We find that moving from the weakest level of white identity to the strongest reduces Patrick’s support by about 15% on both measures. Because half of all respondents chose the strongest white identity category, this represents a meaningful reduce in his electoral support. We display these results visually in Appendix D, Figure D3.We now turn to an analysis of voting for Congress in the 2010 midterm elections. We consider elections for the U.S. Congress in which black candidates oppose white ones. In Table 3 we report results from the 2010 Congressional elections. We begin with white voters in states with black U.S. Senate candidates (South Carolina, Georgia and Florida). All black candidates were also Democrats, and the dependent variable is respondents’ self-report of supporting the Democratic candidate for U.S. Senate in an October pre-election survey conducted by the ANES. In columns one and two, we include a term for the interaction between the three states with U.S. Senate contests featuring black candidates and white racial identity. The results are collinear, and so we mean-center the interaction components to reduce collinearity (e.g. Jaccard and Turrisi 2003). In the first column the model includes only the three variables of interest –white identity, black U.S. Senate candidates, and the interaction. However, the second column reports the model we are the most interested in, because that model includes a bevy of control variables. We expect the interaction coefficients to be negative. We find that they are. Compared to elections without black candidates, and compared to elections with black candidates but where respondents endorse the lowest white identity category, whites with stronger white identities will be more likely to oppose black candidates.Table 3: White Racial Identity among Whites and 2010 U.S. Congress Candidate Preference among Whites, Logistic Regression VariableDemocratic U.S. Senate Candidate PreferenceDemocratic U.S. Senate Candidate Preference^Democratic U.S. House Candidate PreferenceDemocratic U.S. House Candidate Preference^U.S. Congress InteractionsWhite Identity X Black U.S. Democratic Congressional candidate-1.17* (.49)-1.37**(.47)-2.60*(1.22)-2.34** (.86)Interaction Effect ComponentsBlack Democratic U.S. Congressional candidate-.32 (.32)2.08* (1.04)1.63* (.64)2.18** (.63)White Identity-.29 (.20).00 (.22)-.34 (.18)-.04 (.25)Political PredispositionsDemocratic Party ID.46** (.10).64** (.10)Liberal Ideology ID.23 (.17).13 (.15)Racial Resentment-.01 (.05).01 (.04)Intercept-.02 (.16).59 (2.37)-.19*(.08)-.53 (1.46)N596581790771Pseudo R2.02.50.01.50**p<.01 two tailed test, *p<.05 two tailed testData source: 2010 ANES. Results incorporate ANES sample weight.See Appendix C for full coefficient reportU.S. Senate models cluster standard errors on States, U.S. House models cluster standard errors on Congressional Districts.All interaction terms centered at 0 to reduce collinearity.^Control variables: Presidential approval, economic stimulus evaluations, Democratic legislative agenda evaluations, education, income, gender, region (South), church attendance and age.U.S. Senate elections, all three black candidates were DemocratsU.S. House elections, 16 major party candidates were black, 14 of them DemocratsWe perform similar analyses for U.S. House elections in 2010. We find that the two interactions between white identity and black U.S. House candidates are also negative and statistically significant. We plot the results from the table to see how the predicted probability of supporting black Democratic candidates varies with levels of white identity (for the model including the control variables). We set the other variables in the analyses to their means. We begin by plotting the results from the U.S. Senate vote choice model. We use the second U.S. Senate vote choice interaction term from Table 3 to plot the predicted probability of voting for black Democratic U.S. Senate candidates. We then use the white identity coefficient from the same table to plot how the predicted probability of supporting non-black Democratic candidates for the U.S. Senate varies with levels of white identity. This results in Figure 2.For the black U.S. Senate candidates, the solid line with the negative slope indicates that accompanying each stronger level of white identity is a statistically significant decrease in support for black Democratic candidates compared to the weakest category of white identity (feeling “not at all” close to whites). In elections with black U.S. Senate candidates, white identity appears to reduce the predicted probability of supporting such candidates by about 60%. In contrast, when Democratic candidates are not black, the line is flat and dotted, indicating there are no statistically significant changes from the weakest category of white identity to the strongest.As with the other analyses, we plotted the effect of white identity on the predicted probability of supporting a Democratic candidate for the U.S. House, for voters with both black and non-black major party candidates. This results in Figure 3. We generate the results for this figure by holding all other variables at their means. As with the U.S. Senate results, we represent the negative slope of the predicted probability of support for black U.S. House candidates with a solid line, indicating that the lower levels of white support, corresponding with stronger levels of white identity, are statistically different from the weakest white identity level. The predicted probability of supporting non-black U.S. House Democratic candidates varies only slightly with stronger levels of white identity, and we find no statistically significant differences, as reflected by the flat and dotted line. Therefore we can reject the null hypothesis of no effect of white id, and also hypothesis one, which claimed that higher white identification diminishes support for all Democratic candidates. The evidence supports hypothesis two – black candidates activate white racial identity among whites.As with the results from 2008 and 2012 for the Obama vote, and 2010 for the Patrick vote, we consider how the distribution of the white identity variable could affect that variable’s contribution to the final election outcome. When responding to this survey item, 55% of whites choose the two strongest white identity categories. Similarly to the other operationalizations of white identity, this measure reflects large numbers of whites’ willingness to claim a strong racial identity, which then causes the identity to have a substantive effect on the final vote outcome.Presidential Approval as a Mediating VariableOur previous results estimated the direct effect of white identity on vote choice. However, a potent indirect effect exists as well – people’s approval levels of the President affects whether or not they vote for the President’s party’s candidates for Congress (e.g. Tufte 1975). Since we found that white identity led whites to vote against Barack Obama, we test whether it also led them to approve of him less. Given Kinder and Dale-Riddle’s (2012) and Tufte's (1975) claims, we test whether white identity affected support for all Democratic Congressional candidates across the country. Following the structure of our earlier analysis, we begin by testing whether white identity affected Presidential approval of previous Presidents. We run regressions in which Presidential approval is the dependent variable, and we report our results in Table 4. If the racialization hypothesis holds, we expect white identity will increase approval for Republican presidents, and decrease it for Democratic presidents. Alternatively, if a black president activates white identity, then we would expect to see that it only affects Presidential approval when Barack Obama is President. In the last row of the table we report the bivariate white identity coefficients for comparison purposes.Table 4. White Racial Identity among Whites and Presidential Approval in 1984 thru 2000; 2008 thru 2012: OLS 19841988199219962000200820102012Ronald ReaganRonald ReaganGeorge HW BushBill ClintonBill ClintonGeorge W BushBarack ObamaBarack ObamaWhite Identity-.04 (.06).01 (.07)-.03 (.07).07 (.08).06* (.03)-.04 (.06)-.12** (.04)-.04* (.02)Racial ResentmentNot available.02* (.01).08 (.04)Not available.01 (.03).08 (.05)-.06* (.02)-.08*(.03)Intercept1.14** (.29)2.05** (.28).65 (.38)2.32** (.48).56** (.14).24 (.40)10.16** (.39)3.85** (.31)R2.50.37.41.57.36.55.68.68N14901601151369110475868833176Bivariate White Identity coefficient.06 (.08).22* (.09).07 (.09)-.20(.10).02(.03).02(.05)-.12** (.03)-.07** (.02)*p<.05, **p<.01See Appendix C for full coefficient reportAnalysis of American National Election Study data for all election years but 2008; and in 2008, the Cooperative Congressional Election Study. In the ANES before 2010, the white identity measure is the dichotomous “Feel close to Whites” measure. In the CCES and the ANES in 2010 and 2012, it is the ones we report in Appendix A.1984 standard errors clustered on counties; 1988 and 1992 on census tracts; 1996 and 2000 counties; 2008, 2010 and 2012 Congressional DistrictsStarting with 1992, all models employ sample weightsControl variables in all models: Party identification, ideological identification, economic evaluations, education, income, age, marital status, church attendance, region (South)Control variables in all models but 2008 and 2010: Egalitarianism and limited governmentControl variable in 2010 and 2012: Oppose Affordable Care ActControl variable in 2008 only: Support Iraq withdrawControl variables in 2010 only: Oppose Democratic legislative agenda and oppose the economic stimulus bill In this table we report predictors of Presidential approval for the election years of 1984 through 2000, as well as 2008 to 2012. We do not report 2004 because the ANES dropped measures of identity in that survey. We find in the top row of the table only one statistically significant result before 2010: In 2000, whites with higher levels of white identity approved more of Bill Clinton. Given our first hypothesis, we would expect the coefficient to be negative. However, when Barack Obama is President in 2010 and 2012, the coefficient is negative and statistically significant with a two-tailed test at the p<.01 level in 2010 and p<.05 level in 2012. We plot the coefficients and 95% confidence intervals from the fully specified models in Figure 4. We now consider the empirical implications for Congressional vote choice when white identity reduces the Presidential approval of a black President. We know from a vast trove of previous findings that Presidential approval affects electoral support for the Congressional candidates from the President’s party (e.g. Campbell 1993). One way to test this kind of mediating hypothesis is with a Structural Equation Model (SEM) in which white identity affects approval in the first stage of the model, approval affects vote choice in stage two, and an indirect effect on electoral support for all Congressional Democratic candidates is manifested through lower approval. This leads us to Table 5, in which we report the results of four models. In the first two, we analyze 2010 ANES data, using the October pre-election horserace question as the dependent variable. The first column is for the U.S. House results, and the second for the U.S. Senate. In the latter two columns we analyze the 2012 ANES data, using self-reported vote choice as the dependent variables.Table 5: Indirect Paths of White Racial Identity among Whites and White Candidate Preference for the U.S. Congress in 2010 and U.S. Congress Vote Choice in 2012, Structural Equation ModelsEndogenous VariablesExogenous VariablesU.S. House 2010^U.S. Senate 2010^U.S. House 2012^U.S. Senate 2012^President Obama ApprovalWhite Identity-.12** (.04)-.12** (04)-.04** (.01)-.05** (.02)Racial Resentment-.06** (.02)-.06** (.02)-.09** (.03)-.08** (.03)R2.68.68.68.68Democratic Congressional VotingPresident Obama Approval.04** (.01).33** (.11)1.00** (.18).51** (.08)R2.48.61.52.69N8838833,1933,193Indirect Paths to Democratic Congressional Voting thru ApprovalWhite IdentityRacial Resentment-.01*(.00)-.00* (.00)-.04* (.02)-.02* (.01)-.04** (.01)-.09** (.03)-.02** (.01)-.04* (.02)**p<.01, *p<.05^ 2010 results for October 2010 candidate preference; 2012 results for post-election vote choiceData sources: 2010 and 2012 ANESError terms of President Obama Approval and Democratic Congressional Voting correlated for all models but U.S. House 2010Results incorporate ANES sample weight.2010 models and 2012 U.S. House model cluster standard errors at the state level; 2012 U.S. Senate model clusters standard errors at the Congressional District level U.S. House Candidate Preference Model 2010: chi2 = 94.50 (p<.01) df=56, CFI = .78, TLI = .69, RMSEA = .028U.S. Senate Candidate Preference Model 2010: chi2 = 118.03 (p<.01) df=55, CFI = .64, TLI = .48, RMSEA = .036U.S. House Vote Choice Model 2012: chi2 = 376.81 (p<.01) df=102, CFI = .60, TLI = .47, RMSEA = .032U.S. Senate Vote Choice Model 2012: chi2 = 425.88 (p<.01) df=105, CFI = .48, TLI = .34, RMSEA = .031See Appendix C for tables with complete coefficient reports for control variablesIn all four models we use SEMs to consider the indirect path of white identity operating on Congressional vote choice, as mediated by Presidential approval. In other words, we report results for two endogenous variables – Presidential approval, and also Congressional vote choice. Both variables are ordinal, so we use Mplus to adjust for the variables’ not being interval. We also employ the ANES’ survey weights. We report the indirect effect coefficients at the bottom of the table.In the first row we report the coefficients for the effects of white identity on presidential approval in 2010 and 2012, with coefficients estimated separately for the Senate election models and the House election models. White identity correlated negatively with President Obama’s approval in all four models, with the coefficients statistically significant at the p<.01 level with a two tailed test. We include racial resentment as a control variable, and it, too, correlates negatively with the President’s approval.We next consider how President Obama’s approval impacts voting in Congressional elections. All four coefficients are substantively large and statistically significant at the p<.01 level, indicating that in the Congressional elections in both 2010 and 2012, people’s approval levels of the President were a large force in determining which party to support in the election. At the bottom of the table we find that in all four cases the indirect effect coefficients for white identity on Democratic Congressional vote choice are all negative and statistically significant at the p<.01 or p<.05 level with a two tailed test. We also present the same indirect effects for racial resentment and find that they are generally of the same magnitude, and also statistically significant in all four cases.At the very bottom of the table we report model fit statistics. The root mean square error of approximation (RMSEA) statistics all indicate that the models fit the data well (an RMSEA of below .05 is considered good model fit; MacCallum, Browne and Sugawara (1996)). We expect that the unexplained variance for Presidential approval and Congressional vote choice will be correlated. We know that Presidential approval and Congressional voting share a strong relationship, and we acknowledge that even after modeling the causes of both, as we do here, other factors probably remain unaccounted for by the model. Those factors are manifest in the error terms for the two variables, and they should be related to one another. Therefore, we correlate the errors of the two endogenous variables. When we fail to do so, the model fit suffers in three of the four models. Please see Appendix E where we describe the different model variations we estimated, and where we also report the model fit statistics for the second-best fitting models that we estimated.The next results we report are for the magnitudes of the relationships between white identity and support for Congressional Democrats. To present the magnitudes of the results in a more accessible format, we plot how the predicted averages of supporting Democratic U.S. House and Senate candidates in the ANES 2010 pre-election survey, and the predicted vote choice in the ANES 2012 post-election survey, varied according to levels of white identity. Because the pre-election Democratic candidate support variables are coded as 0 (supporting a Republican or third party candidate) or 1 (supporting a Democrat), the average is akin to a predicted probability of supporting the Democratic candidate. We report this result as a range between 0 and 100 to ease interpretation. The variance in support for these candidates, given levels of white identity, reflects the indirect path of white identity on the election support, as mediated by Presidential approval. These values are averaged over all of the other variables in the models.We report the resulting predicted probability plots in Appendix D, Figures D4 (for 2010) and D5 (for 2012). In Appendix D we also include some text to guide the interpretation of the figures. To summarize those results, we find that in 2010 white identity reduced the predicted probability of supporting Democratic U.S. House and Senate candidates by about 20% (from about 60% to 40%), and in 2012 by about 15% (from about 55% to 40%).DISCUSSION AND CONCLUSIONThere is little research on white identity and vote choice, and there is none that tests for how variations in racial cues lead to its activation. There are studies of how white racial identity relates to other constructs. Policy and/or social attitudes—not vote choice—are the dependent variables in Wong (2010), Kinder and Kam (2009), Citrin and Sears (2014), Wong and Cho (2005) and the experiments reviewed in Hutchings and Jardina (2009). Vote choice is a dependent variable in Tesler and Sears (2010) and Kinder and Dale-Riddle (2012), but those authors do not test for the independent influence of in-group identification except to the extent that their unidimensional scales (racial resentment and ethnocentrism, respectively) pick it up. Jardina (2014, p 138 and 251) comes closest to our analyses. She tests for the influence of white identity and controls for racial resentment. She also concludes that white in-group identity affected vote choice in the 2012 presidential election. However, without the replication of 2008 and the comparison to the mono-racial elections in the 1984 – 2000 elections, her vote choice analysis does not include variation in what we claim activates white identity: a black candidate running against a white candidate.Thus, this study is the first to test for relationships between white racial identity and vote choice across a range of elections. The central contribution of this study is that white in-group evaluations lead whites to oppose black candidates.? White identity involves no explicit out-group evaluations at all.? All of the results we observe in this study, in which whites penalize black political candidates, are due solely to whites’ affinity for their own group – their desire to benefit their own group, without reference to any out-groups.? This view corresponds with the work of the psychologist Marilynn Brewer (1999) – in-group “love” in and of itself can lead to out-group “hate.” To clarify both our meaning and hers, “hate” involves the actions that the in-group takes against the out-group. Previous scholars have found that negative feelings and attitudes toward out-groups lead to acts against them, but Brewer (1999) argues that positive in-group evaluations in and of themselves can lead to the same outcomes. Our findings here support that view. This work builds on the work of scholars like Sears and Tesler (2010) and Piston (2010) who find that negative evaluations of other groups, vis-à-vis our positive evaluations of our own group, can lead whites to vote against black candidates. Our work extends their analyses to an additional causal process: in-group identity. The social identity literature shows that in-group processes are distinct from out-group processes (Brewer 1999). That is, there are two dimensions—attitudes toward the in-groups and attitudes toward out-groups—rather than one dimension, where attachment to an in-group can only mean greater distance from out-groups. Our analyses show this empirically. Racial resentment and white in-group identity have independent effects; they are not two ends of a single spectrum. In 1992 racial resentment is statistically significant in predicting voting against Bill Clinton for President, but white identity is not. However in 2008 and 2012 white identity is statistically significant and substantively important in the same elections when racial resentment is also statistically significant. The magnitudes of the results for the two factors are also comparable, and the white identity results are at least as robust as the ones for racial resentment. Racial resentment tends to be a variable that deflates the impacts of other racial factors, but white in-group identity’s associations with voting in elections with black candidates remains large and robust. This is evidence they are conceptually distinct. Racial resentment is an attitude, which focuses on the out-group. White racial identity correlates with racial resentment (as we report in Appendix B), but it also leads to a whole constellation of beliefs about the in-group.As with the effects of racial resentment on vote choice, black political candidates cue (or activate) white racial identity (Kinder and Dale-Riddle 2012, Jardina 2014). Tesler and Sears (2010), in their Table 3.1, statistically isolate the effect of racial resentment from other elements of Presidential vote choice models across several elections. They persuasively demonstrate that racial resentment becomes more influential in contests involving Barack Obama. We find that while white racial identity does not correlate with vote choice in most elections, it does when black candidates are on the ballot. Obama's elections did activate white racial identity. We find the most satisfying theoretical basis for this explanation comes from Kinder and Dale-Riddle (2012, 25) when they write, "In the short run, which aspects of identity and attitude become important--which are activated--depend on political circumstances…. Even more effective is to embody membership, as Barack Obama embodied race in 2008. … Whatever Obama said about society and government and about problems and policies, at the end of the day, every time American voters caught a glimpse of him, he was black."Our analysis ends in 2012, but readers will likely wonder about its applicability to 2016. We found that white identity affected support for Congressional candidates even though President Obama was not a candidate in those elections. Sides and Ferrell (2016) found that white racial identity correlated with support for Donald Trump in the Republican primaries. This leads us to wonder if white in-group identity’s influence will persist after President Obama leaves office. Some analysts suggest that one reason for Donald Trump’s victory is the activation of white in-group identity. However, the 2016 election is confounded because while the election included both racial rhetoric and charges of racism, it was also a referendum on a sitting black President. We do not know whether white in-group identity can be activated by rhetoric only.We tested four hypotheses for possible effects of white identity – white identity would lead white voters to oppose all Democrats, no Democrats at all, only when the identity was cued by a black candidate, or indirectly by lowering President Obama’s approval. We estimated the effects of white identity on Presidential vote choice and Presidential approval in Presidential elections going back to Ronald Reagan’s re-election in 1984, and only for President Obama do we find negative effects. This leads us to reject hypotheses zero (the null) and one (white identity would lead whites to oppose all Democrats). We also find effects for white identity on voting in Deval Patrick’s 2010 gubernatorial re-election campaign in Massachusetts, and for U.S. Senate and U.S. House when candidates are black. Hypothesis two thus stands – that black candidates cue the identity and make it salient, causing white voting discrimination. Furthermore, we find support for hypothesis three (the indirect effect on vote), because in 2010 and 2012 white identity apparently reduces President Obama’s approval, which then indirectly reduces support for Democratic candidates in the Congressional elections.We note several limitations to these findings. First, the 2010 analyses rely solely on pre-election candidate support measured in October. As a result, it is possible that for the actual vote choice, the results may have been weaker. However, we believe our interpretation is valid for several reasons. First, we replicate the 2010 indirect effect of white identity on voting for Democratic Congressional candidates using the 2012 data, which does involve vote choice. Second, the pre-election candidate support in 2010 was measured less than a month before the election, and so it is likely that the vast majority of voters had already made up their minds as to whom they would vote for.Second, in results we do not report here due to space limitations, the correlations that we find between white identity and Congressional candidate support in 2010 are not statistically significant in 2008 or 2012. We speculate that in Presidential election years, the campaign and turnout stimulus of the Presidential election swamps the effects of white identity on Congressional vote choice (e.g. Campbell 1993). However, in midterm elections, in which information about candidates is much less plentiful, a black candidate’s racial group membership serves as a stronger cue. Or perhaps the effects of white identity under a black President affect Congressional elections when the public cannot vote on the President directly, but are focused on the President when he is on the ballot. Third, we find white identity correlates negatively with both pre-election support for Deval Patrick, and also the vote choice, as reported by respondents after the election. The vote choice result is especially notable given the small sample size. Unfortunately, a full slate of control variables is not available in those models; most importantly, the model lacks ideological identification and racial resentment. While white racial identity is our only racial variable in the models, the results are consistent with the results from the more complex models, and so we have some confidence in the results. A fourth limitation of the study is that the black Democrats running for the U.S. Senate in 2010 were non-competitive candidates. Starting with Florida, that Senate race featured a strong white Independent candidate, former Republican Governor Charlie Crist, who opposed both Republican candidate Marco Rubio (of Cuban-American descent) and Democratic candidate Kendrick Meek (who is African-American). The Election Day vote shares were: Rubio with 49%, Crist with 30%, and Meek with 20% (Federal Election Commission 2010). In the races for U.S. Senate in Georgia and South Carolina, the margin of victory for the white Republican candidate over the black Democratic candidate was 19 percentage points in Georgia and 34 percentage points in South Carolina (Federal Election Commission 2010). Because all three Senate races were non-competitive, then the Senate results we find can only be generalized to non-competitive U.S. Senate races with black Democratic candidates. However, we find apparent effects for white identity in the Presidential elections of 2008 and 2012, and the Massachusetts Gubernatorial election of 2010, and these elections were competitive. Perhaps the apparent effect of white identity in U.S. Senate elections with black Democratic candidates would be even stronger in competitive elections.WORKS CITEDAmerican Association for Public Opinion Research. 2011. Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys. 7th edition. AAPOR.Ansolabehere, Stephen. 2008. Cooperative Congressional Election Study 2008. [computer file] (Study Global ID hdl:1902.1/14003).Arriola, Kimberly R. Jacob and Elizabeth R. Cole. 2001. “Framing the Affirmative-Action Debate: Attitudes toward the Out-Group Members and White Identity.” Journal of Applied Social Psychology 31(12): 2462-2483.Barone, Michael and Chuck McCutcheon. 2011. The Almanac of American Politics 2012. Chicago: University of Chicago Press.Bobo, Lawrence, and Gilliam, Franklin D. Jr. 1990. “Race, Sociopolitical Participation, and Black Empowerment.” American Political Science Review 84(2):377-93.Bollen, Kenneth A. 1989. Structural Equations with Latent Variables. New York: Wiley.Branscombe, Nyla R.. Michael T. Schmitt and Kristin Schiffhauer. 2007. “Racial Attitudes in Response to Thoughts of White Privilege.” European Journal of Social Psychology 37: 207-15.Brewer, Marilynn B. 1999. “The Psychology of Prejudice: Ingroup Love or Outgroup Hate?” Journal of Social Issues, 55(3): 429-44.Brewer, Marilynn B. and Wendi Gardner. 1996. “Who is This ‘We’? Levels of Collective Identity and Self Representations.” Journal of Personality and Social Psychology 71(1):83-93.Bullock, Charles S. III. 2000. “Partisan Changes in the Southern Congressional Delegation and their Consequences.” in David W. Brady, John F. Cogan, and Morris Fiorina (eds.), Continuity and Change in House Elections, pp. 39-64, Stanford, CA: Stanford University Press.Bullock, Charles S. III, and Richard E. Dunn. 1999. “The Demise of Racial Redistricting and the Future of Black Representation.” Emory Law Journal 48: 1209-53.Campbell, James. 1993. The Presidential Pulse of Congressional Elections. University of Kentucky.Carmines, Edward G. and James A. Stimson. 1989. Issue Evolution: Race and the Transformation of American Politics. Princeton University Press.Carmines, Edward G. and James A. Stimson. 1986. “On the Structure and Sequence of Issue Evolution.” American Political Science Review 80(3): 901-920.Carmines, Edward G. and James A. Stimson. 1981. “Issue Evolution, Population Replacement, and Normal Partisan Change.” American Political Science Review. 71(1): 107-118.Carter, Robert. 1990. “The Relationship between Racism and Racial Identity Development among White Americans: An Exploratory Investigation.” Journal of Counseling and Development 69: 46-50.Carter, Robert, Janet E. Helms and Heather L. Juby. 2004. “The Relationship between Racism and Racial Identity for White Americans: a Profile Analysis.” Journal of Multicultural Counseling and Development 32 (January): 2-17.Chow, Rosalind M., Brian S. Lowery and Eric D. Knowles. 2008. “The Two Faces of Dominance: The Differential Effect of In-Group Superiority and Out-Group Inferiority on Dominant-Group Identity and Group Esteem.” Journal of Experimental Social Psychology 44: 1073-81.Citrin, Jack and David O. Sears. 2014. American Identity and the Politics of Multiculturalism. Cambridge University Press.Citrin, Jack, Donald Phillip Green and David O. Sears. 1990. “White Reactions to Black Candidates: When Does Race Matter?” The Public Opinion Quarterly 1(Spring): 74-96.Coates, Ta-Nehisi. 2014. “Bill Clinton was Racialized, Too.” The Atlantic. [] (Accessed November 1, 2014.)Congressional Black Caucus. 2012. “Directory.” (July 10, 2012).Conover, Pamela Johnston. 1984. “The Influence of Group Identification on Political Participation and Evaluation.” Journal of Politics 46(August): 760-85.Conover, Pamela Johnston. 1988. “The Role of Social Groups in Political Thinking.” British Journal of Political Science 18 (January): 51-76.Croll, Paul R. 2007 “Modeling Determinants of White Racial Identity: Results from a New National Survey.” Social Forces 2 (December): 613-42.Dade, Corey. 2011. “GOP's Rep. Allen West Draws Black Caucus Spotlight.” January 5. (July 10, 2012).Devos, Thierry and Mahzarin R. Banaji. 2005. “American = White?” Journal of Personality and Social Psychology 88(3): 447-66.Doane, Ashley W. 2005. “Dominant Group Ethnic Identity in the United States.” Sociological Quarterly 38(3): 375-97.Edsall, Thomas Byrne and Mary D. Edsall. 1992. Chain Reaction: The Impact of Race, Rights, and Taxes on American Politics. W.W. Norton and Company.Ellis, Christopher and James A. Stimson. 2012. Ideology in America. Cambridge University Press.Federal Election Commission. 2010. “Federal Elections 2010: Election Results for the U.S. Senate and the U.S. House of Representatives.” Retrieved from , Claudine. 2001. “The Effect of Black Congressional Representation on Political Participation.” American Political Science Review 95(3):589-602.Gay, Claudine. 1997. Taking Charge: Black Electoral Success and the Redefinition of American Politics. Ph.D. diss. Department of Political Science. Harvard University.Goren, Matt J. and Victoria C. Plaut. 2012. “Identity Form Matters: White Racial Identity and Attitudes Toward Diversity.” Self and Identity 11: 237-54.Green, Donald, Bradley Palmquist and Eric Schickler. 2002. Partisan Hearts and Minds: Political Parties and the Social Identities of Voters. New Haven, CT: Yale University Press.Hajnal, Zoltan L. 2001. “White Residents, Black Incumbents, and a Declining Racial Divide.” American Political Science Review, 95(3): 603-18.Helms, John E. 1990. Black and White Racial Identity Attitudes: Theory, Research and Practice. Westport, CT: Greenwood.Highton, Benjamin. 2004. “White Voters and African American Candidates for Congress.” Political Behavior 26 (March): 1-25.Highton, Benjamin. 2011. “Prejudice Rivals Partisanship and Ideology When Explaining the 2008 Presidential Vote Across the States.” PS: Political Science & Politics 44(3): 530-35.Huddy, Leonie. 2013. “From Group Identity to Political Cohesion and Commitment.” Oxford Handbook of Political Psychology. Eds. Leonie Huddy, David O. Sears and Jack Levy. Oxford University Press.Hutchings, Vincent L., Cara Wong, James Jackson and Ronald Brown. 2011. “Explaining Perceptions of Competitive Threat in a Multi-Racial Context.” Race, Reform and Regulation of the Electoral Process: Recurring Puzzles in American Democracy. Eds. Charles E. Guy-Uriel, Heather K. Gerken and Michael S. Kang. Cambridge University Press.Ignatiev, Noel. 1995. How the Irish became White. New York: Routledge.Jaccard, James and Robert Turrisi. 2003. Interaction Effects in Multiple Regression Second Edition. Sage Publications. Thousand Oaks, California.Jackman, Simon and Lynn Vavreck. 2010. “Obama’s Advantage? Race, Partisanship and Racial Attitudes in Context.” Presented at the Annual Meeting of the Midwest Political Science Association, Chicago, Illinois, April.Jardina, Ashley Elizabeth. 2014. The Demise of Dominance: Group Threat and the New Relevance of White Identity for American Politics. Ph.D. Dissertation.Jaret, Charles and Donald C. Reitzes. 1999. “The Importance of Racial-Ethnic Identity and SocialSetting for Blacks, Whites and Multiracials.” Sociological Perspectives 42 (4): 711-37.Kellstedt, Paul M. 2003. The Mass Media and the Dynamics of American Racial Attitudes. Cambridge University Press.Key, Valdimer Orlando. 1949. Southern Politics in State and Nation. New York: A.A. Knopf.Kinder, Donald R. and Allison Dale-Riddle. 2012. The End of Race? Obama, 2008, and Racial Politics in America. New Haven, CT: Yale University Press.Kinder, Donald R. and Lynn Sanders. 1996. Divided by Color. Chicago: University of Chicago Press.Knowles, Eric D., Brian S. Lowery, Elizabeth P. Shulman, and Rebecca L. Schaumberg. 2013. “Race, Ideology, and the Tea Party: A Longitudinal Study.” PLOS ONE 8(6): 1-11.Knowles, Eric D. and Brian S. Lowery. 2012. “Meritocracy, Self-Concerns and Whites’ Denial of Racial Inequity.” Self and Identity 11: 202-22.Levin, Shana and Jim Sidanius. 1999. “Social Dominance and Social Identity in the United States and Israel: Ingroup Favoritism or Outgroup Derogation?” Political Psychology 20 (March): 99-126.Levin, Shana, Jim Sidanius, Joshua L. Rabinowitz, and Christopher Federico. 1998. “Ethnic Identity, Legitimizing Ideologies, and Social Status: A Matter of Ideological Asymmetry.” Political Psychology 19(2): 373-404.Levy, Dena, Nicole R. Krassas, Vinessa Buckland, Katherine Dillon, and Justin Glownia. 2010. “Time for a Change? Media Coverage of the 2008 Presidential Election.” Presented at the Annual Meeting of the Midwest Political Science Association, Chicago, Illinois, April 21-25.Lewis-Beck, Michael S.; Charles Tien and Richard Nadeau. 2010. “Obama’s Missed Landslide: A Racial Cost?” PS: Political Science & Politics 42 (January) 69-76.Lowery, Brian S., Eric D. Knowles, Rosalind M. Chow and Miguel M. Unzueta. 2012. “Paying for Positive Esteem: How Inequity Frames Affect Whites’ Responses to Redistributive Policies.” Journal of Personality and Social Psychology 102 (2): 323-36.Lowery, Brian S., Eric D. Knowles and Miguel M. Unzueta. 2007. “Framing Inequity Safely: Whites’ Motivated Perceptions of Racial Privilege.” Personality and Social Psychology Bulletin 33(9): 1237-50.Mack, Dan A., C. Douglas Johnson, Troy D. Green, Anthony G. Parisi, and Kecia M. Thomas. 2002. “Motivation to Control Prejudice as a Mediator of Identity and Affirmative Action Attitudes.” Journal of Applied Social Psychology 32(5): 934-64.Martinez, Michael D. and Stephen C. Craig. 2010. “Race and 2008 Presidential Politics in Florida: A List Experiment.” The Forum 8 (2): 1-14.MacCallum, Robert Charles, Browne, Michael W., & Sugawara, Hazuki M. 1996.?“Power Analysis and Determination of Sample Size for Covariance Structure Modeling.”?Psychological Methods?1: 130-149.McIlwain, Charlton D. and Stephen Maynard Caliendo. 2007. “Racialized Media Framing in Federal Elections, 1992-2006.” Presented at the annual meeting of the Midwest Political Science Association, April 12-15.Morrison, Kimberly Rios, Victoria C. Plaut and Oscar Ybarra. 2010. “Predicting whether Multiculturalism Positively or Negatively Influences White Americans’ Intergroup Attitudes: The Role of Ethnic identification.” Personality and Social Psychology Bulletin 36:?1648-1661.Muthen, Linda K. and Bengt O. Muthen. 2007. M-Plus: Statistical Analysis with Latent Variables, Users Guide. Los Angeles: .Paccagnella, Omar. 2006. “Centering or Not Centering in Multi-level Models? The Role of the Group Mean and the Assessment of Group Effects.” Evaluation Review 30 (February): 66-85.Pasek, Josh, Alexander Tahk, Yphtach Lelkes, Jon A. Krosnick, B. Keith Payne, Omair Akhtar, and Trevor Tompson. 2009. “Determinants of Turnout and Candidate Choice in the 2008 Presidential Election.” Public Opinion Quarterly 73(5): 943-994.Petrow, Gregory A. 2010. “The Minimal Cue Hypothesis: How Black Candidates Cue Race to Increase White Voting Participation.” Political Psychology 31 (December): 915-50.Piston, Spencer. 2010. “How Explicit Racial Prejudice Hurt Obama in the 2008 Election.”Political Behavior 32(4): 431-451.Pope-Davis, Donald B. and Thomas M. Ottavi. 1994. “The Relationship Between Racism and Racial Identity Among White Americans: A Replication and Extension.” Journal of Counseling and Development, 72: 293-97.Redlawsk, David P., Caroline J. Tolbert and William Franko. 2010. “Voters, Emotion and Race in 2008: Obama as the First Black President.” Political Research Quarterly 63(4): 875-89.Reeves, Keith. 1997. Voting Hopes or Voting Fears? White Voters, Black Candidates, and Racial Politics in America. Oxford: Oxford University Press.Roediger, David R. 2007. Wages of Whiteness: Race and the Making of the American Working Class. London and New York: Verso.Rowe, Wayne, Sandra K. Bennett, and Donald R. Atkinson. 1994. “White Racial Identity Models: A Critique and Alternative Proposal.” Counseling Psychology 22: 129-46.Schaffner, Brian F. 2011. “Racial Salience and the Obama Vote.” Political Psychology 32 (6): 963-88.Sears, David O. and P.J. Henry. 2005. “Over Thirty Years Later: A Contemporary Look at Symbolic Racism.” Advances in Experimental Social Psychology. 37: 95-150.Sears, David O. and Victoria Savalei. 2006. “The Political Color Line in America: Many ‘Peoples of Color’ or Black Exceptionalism?” Political Psychology 27 (December): 895-924.Sidanius, Jim and Felicia Pratto. 1999. Social Dominance: An Intergroup Theory of Social Hierarchy and Oppression. Cambridge University Press.Sides, John and Henry Ferrell. 2016. The Science of Trump: Explaining the Rise of an Unlikely Candidate. Amazon Digital Services LLC.Stephens-Davidowitz, Seth. 2011. “The Effects of Racial Animus on Voting: Evidence Using Google Search Data.” Unpublished typescript.Tajfel, Henri. 1982. “Social Psychology of Intergroup Relations.” Annual Review of Psychology 33: 1-30.Terkildsen, Nayda. 1993. “When White Voters Evaluate Black Candidates: The Processing Implications of Candidate Skin Color, Prejudice, and Self Monitoring.” American Journal of Political Science 37(4): 1032-53.Tesler, Michael and David O. Sears. 2010. Obama’s Race: The 2008 Election and the Dream of a Post-Racial America. University of Chicago Press.Tocqueville, Alexis de. 1841. De le democartie en Amerique, Bruxelles: L. Hauman et Cie.Tufte, Edward R. 1975. “Determinants of the Outcomes of Midterm Congressional Elections.” American Political Science Review 69 (September): 812-26.Valentino, Nicholas A., and David O. Sears. 2005. “Old Times There Are Not Forgotten: Raceand Partisan Realignment in the Contemporary South.” American Journal of Political Science 49(3): 672-688.Voss, D. Stephen and David Lublin. 2001. “Black Incumbents, White Districts: An Appraisal of the 1996 Congressional Elections.” American Politics Research 29: 141-82.Wong, Cara and Grace E. Cho. 2005. “Two Headed Coins or Kandinskys: White Racial Identification.” Political Psychology 26 (5): 699-720.APPENDIX AFor the 2008 election we analyze data from the Cooperative Congressional Election Study (CCES; Ansolabehere 2008), for the 2010 and 2012 elections we use data from the American National Election Study (ANES), and for the Massachusetts Gubernatorial election we use data from the Massachusetts Statewide Survey (MSS) conducted by the Western New England University Polling Institute. WHITE IDENTITY VARIABLE DESCRIPTIONSWe measured white identity using the following four questions. Interviewers asked the questions of all respondents, but in the analyses here we use only white respondents. We report the question wording and also a histogram with the resulting frequency distribution.From the 2008 CCES:How strongly to do you identify with white people? Very strongly, somewhat strongly, not very strongly, not at all strongly.From the 2010 ANES:How close do you feel to [whites] in terms of ideas and interests? Extremely close, very close, moderately close, a little close or not at all close?From the MSS:How strongly do you identify with white people? Would you say: Very strongly, somewhat strongly, not very strongly, not at all, or, I do not know how strongly I identify with white people.From the 2012 ANES:How important is being white to your identity? Extremely important, very important, moderately important, a little important, or not at all important. OTHER VARIABLE DESCRIPTIONSFor the 2010 ANES we coded respondents as voting in states that did or did not have black candidates for the U.S. Senate (Barone and McCutcheon 2011). We did the same for respondents’ Congressional districts (for both 2010 and 2012), coding them either having, or not having, a black member of the U.S. House in 2011, such that black members of Congress were successful black candidates for the House in 2010 (Congressional Black Caucus 2012).The dependent variables for all of our models are dichotomous – they are all either self-reported post-election vote choice, or pre-election candidate support. Results from the 2008 CCES and 2012 ANES surveys use post-Election Day vote choice. Results from the 2010 MSS include both pre-Election Day support, as well as post-Election Day vote choice. The 2010 ANES interviews were in late October, but there were no post-Election Day re-interviews, and so these dependent variables are all pre-Election Day candidate support.For the 2008 Presidential, 2012 Presidential, and 2010 Massachusetts Gubernatorial elections, all of the respondents were choosing whether or not to vote for a black candidate. For the 2010 Midterm elections, some respondents were in U.S. States or Congressional districts featuring black Democratic candidates, while most were not. In these cases, we use self-reported support for Democratic U.S. Senate and House candidates as dependent variables, but we employ an interaction term between white identity and facing a black candidate to capture the impact of the racial identity in elections with black candidates. For all of these models we estimate a logistic regression.Finally, we expect that as white identity strengthens for white Americans, approval ratings for President Obama are likely to be lower, which will in turn decrease support for all Democratic congressional candidates. In this model, no interaction term is needed. However, in addition to estimating a single equation regression (see Table 4), we also estimate a Structural Equation Model (SEM) with Presidential Approval and support for Democratic candidates as endogenous variables, using a polychoric covariance matrix to account for the dichotomous nature of the vote choice dependent variable (e.g. Bollen 1989). We estimate the indirect effect of white identity on voting for Democratic Congressional candidates, as it operates through Presidential approval, and we used Mplus 7 to estimate the coefficient for the indirect effect (Muthen and Muthen 2007).APPENDIX BTable B1: American National Election Study 2012 Bivariate Regression Coefficients between White Identity and Other ConstructsBlack Feeling^White Feeling^Hispanic Feeling^Black Sympathy^^Black Admiration^^Link White^^Obama Favors Blacks^^Obama Muslim^^^Racial Resentment^White-Black Stereotypes^-1.77** (.48)3.76** (.34)-1.80** (.39)-.01 (.02)-.06** (.02).11** (.02).07** (.02).14** (.04).11** (.02).66** (.06)n= 3247324732473247324732473247324732473247*p<.05, two tailed test; **p<.01, two tailed test^ OLS Regression^^Ordered Probit^^^LogitWe assess the construct validity of the ANES measure of white identity. We run bivariate regressions employing 10 dependent variables. Nine of the coefficients are statistically significant. Stronger levels of white identity predict: Colder feelings toward blacks, warmer feelings toward whites, colder Hispanic feelings, less admiration for blacks, greater linked fate with whites, the belief that Obama favors blacks over whites, the belief that Obama is a Muslim, racial resentment, and more positive white stereotypes over blacks. One coefficient for feelings of sympathy for blacks is not statistically significant.American National Election Study Construct Validity Variables“feelings toward blacks, whites and Hispanics”:I'd like to get your feelings toward some of our political leaders and other people who are in the news these days. I'll read the name of a person and I'd like you to rate that person using something we call the feeling thermometer. Ratings between 50 degrees and 100 degrees mean that you feel favorable and warm toward the person. Ratings between 0 degrees and 50 degrees mean that you don't feel favorable toward the person and that you don't care too much for that person. You would rate the person at the 50 degree mark if you don't feel particularly warm or cold toward the person. Still using the thermometer, how would you rate the following groups:BlacksWhiteHispanics“Feelings of sympathy for blacks”:How often have you felt sympathy for Blacks? Always, about half the time, some of the time, or never?“Feelings of admiration for blacks”: How often have you felt admiration for Blacks? Always, about half the time, some of the time, or never?“Linked fate with whites”:Do you think that what happens generally to white people in this country will have something to do with what happens in your life? Yes or no?“the belief that Obama favors blacks over whites”:Do the policies of the Obama administration favor whites over blacks, favor blacks over whites, or do they treat both groups the same?“the belief that Obama is a Muslim”: Now we would like to ask you some questions about the religion of the presidential candidates. Would you say that [Obama] is Protestant, Catholic, Jewish, Muslim, Mormon, some other religion, or is he not religious? Codes so 1=Muslim, 0=rest.Table B2: Cooperative Congressional Election Study 2008 Bivariate Regression Coefficients between White Identity and Other ConstructsMcCain AngerPerceived Anti-Black DiscriminationWhite PrideBlack AngerMcCain Feeling ThermometerObama Feeling Thermometer over McCainToo Little White InfluenceToo Little Black InfluenceRacial ResentmentMore angry at blacks than whitesRacial ThreatBlacks Cause Racial TensionLogitOrdered ProbitOrdered ProbitOrdered ProbitOLSOLSOrdered ProbitOrdered ProbitOLSOLSLogitOrdered Probit-.21* (.09)-.10* (.04).22** (.06).12* (.06)2.67* (1.12)-5.74* (2.60).22** (.06)-.14** (.04).22** (.04).12** (.04).22* (.11).18** (.04) 744749670693713665748745752666728751**p<.01, two tailed test; *p<.05, two tailed testWe report results from 10 bivariate analyses which demonstrate that the white identity variable correlates with 10 constructs that one expects to be related to a valid measure of white identity. First, whites with stronger white identities reported feeling less anger toward John McCain. They were less likely to perceive that blacks face discrimination. Third, whites with stronger white identities feel more white pride, and also, greater anger toward blacks. These whites also feel warmer feelings for John McCain as measured with a feeling thermometer, and stronger white racial identities correlate with warmer feelings for McCain in comparison to Barack Obama. Stronger white identities correlate positively with whites believing that whites have too little influence in society, and negatively with the belief that blacks have too little influence. The variable predicts higher levels of racial resentment, as well as a greater likelihood of answering that one feels angry at blacks, relative to whites. The CCES measured racial threat by asking if people thought black civil rights leaders were “moving too fast,” and stronger white racial identities predict that one agrees. Finally, stronger white identities increase the likelihood that whites will answer that blacks are mainly responsible for creating racial tension.APPENDIX CTable C1. White Racial Identity among Whites and Democratic Presidential Vote Choice in 1984 thru 2000 and 2008 thru 2012: Logistic Regression1984198819921996200020082012Mondale v. ReaganDukakis v. GHW BushClinton v. GHW BushClinton v. DoleGore v. GW BushObama v. McCainObama v. RomneyWhite Identity-.04 (.19)-.08 (.22).10 (.25)-.16 (.32)-.13 (.34)-.55* (.26)-.16** (.06)Racial controlsRacial ResentmentNot available-.07* (.03)-.36* (.17)Not available-.28 (.32)-.69* (.30)-.45** (.17)Political issues and valuesEgalitarianism.56** (.11).33** (.12).52** (.19).65* (.27).06 (.20).41** (.15)Limited Government-.16* (.07)-.37** (.09)-.12 (.16)-.61** (.16)-.73** (.19)-.93** (.24)Withdraw Iraq3.03** (.57)Support Carbon Tax2.34** (.66)Oppose Health Care Reform Act-.83** (.11)Republican Party Identification-.83** (.07)-.84** (.06)-.90** (.07)-.79** (.10)-.88** (.10)-.84** (.09)-.77** (.07)Conservative Ideological Identification-.47** (.09)-.20** (.06)-.32** (.11)-.36* (.16)-.87** (.14)-.49 (.37)-.39** (.08)Retrospective Economy-.65** (.15)-.40** (.12)-.74** (.15).70** (.23).30* (.15)-.42 (.23).81** (.10)Prospective Economy-.31 (.18).00 (.08).06 (.17).55* (.24).06 (.19).14 (.45).29 (.20)DemographicsFemale-.06 (.25)-.20 (.22)-.40 (.24)-.16 (.34)-.13 (.28)-.22 (.55).14 (.26)Education.02 (.05).02 (.07)-.02 (.09)-.24* (.09).37** (.12).25 (.20).05 (.09)Income-.02 (.02)-.03 (.02)-.00 (.02).03 (.02)-.03 (.05)-.34 (.19)-.03** (.01)Age.01 (.01).01 (.01).01 (.01)-.01 (.01).01 (.01)-.03 (.02)-.01 (.02)Church Attendance-.06 (.06)-.03 (.07)-.32** (.08)-.35** (.13)-.16 (.10)-.18 (.16)-.28** (.04)Deep South-.50* (.21)-.43* (.20)-.10 (.25).01 (.30)-.70* (.34).36 (.49)-.36 (.25)Intercept4.96** (.96)2.48* (1.01)5.61** (1.49).49 (1.44)4.24* (1.84)10.89** (2.69)5.37** (1.32)Pseduo-R2.51.47.56.58.61.78.71N10249949305877645262478*p<.05, **p<.01All dependent variables coded as 2 party vote1984 to 2000: Analysis of American National Election Study data. The white identity measure is the dichotomous “Feel close to Whites” measure.2008: Cooperative Congressional Election Study Data. See Appendix A for white identity wording.2012: American National Election Study data. See Appendix A for white identity wording.1984 standard errors clustered on counties; 1988 and 1992 on census tracts; 1996 and 2000 counties; 2008 and 2012 Congressional DistrictsStarting with 1992, all models employ sample weightsDeep South: Respondents in former Confederacy states of South Carolina, Mississippi, Florida, Alabama, Georgia, Louisiana, Texas, Virginia, Arkansas, Tennessee, and North Carolina.Table C2: White Racial Identity among Whites, Democratic Vote Choice and Candidate Preference for Massachusetts Governor in 2010 among Whites, Logistic RegressionVariablePatrick Candidate Preference 2010Patrick Vote 2010White Identity-.38** (.14)-.27* (.13)Massachusetts Right Direction1.46** (.36)1.61** (.51)Republican Party ID-1.27** (.10)-1.39** (.19)Education-.00 (.08)-.25 (.14)Income.23 (.27).11 (.56)Female-.68** (.27)-.78 (.57)Age.04 (.15).20 (.25)Intercept-.26 (.77).77 (1.51)N390204Pseudo R2.42.47**p<.01, *p<.05Data source: 2010 Massachusetts State Survey.Results incorporate sample weights for gender, age, and race.Models cluster standard errors on counties.Table C3: White Racial Identity among Whites and 2010 U.S. Congress Candidate Preference among Whites, Logistic RegressionVariableDemocratic U.S. Senate Candidate PreferenceDemocratic U.S. House Candidate PreferenceU.S. Congress InteractionsWhite Identity X Black Democratic U.S. Congressional candidate-1.37** (.47)-2.34** (.86)Interaction Effect ComponentsBlack Democratic U.S. Congress candidate2.08* (1.04)2.18**(.63)White Identity.00 (.22)-.04 (.25)Political and Economic EvaluationsObama Approval.24^ (.14).13 (.11)Negative Economic Stimulus Evaluation-.31* (.15)-.40** (.12)Negative Economic Evaluation-.02 (.15)-.15 (.13)Disapprove Democratic Legislative Agenda-.29** (.11)-.15 (.08)Political PredispositionsDemocratic Party ID.46** (.10).64** (.10)Liberal Ideology ID.23 (.17).13 (.15)Racial Resentment-.01 (.05).01 (.04)DemographicsEducation.13 (.22).13 (.18)Income-.05 (.04).01 (.03)Female-.05 (.31)-.00 (.37)Deep South-2.30* (.92)-1.35** (.50)Church Attendance.03(.08)-.07(.06)Age.01 (.01).00 (.01)Intercept.59 (2.37)-.53 (1.46)N581771Pseudo R2.50.50**p<.01 two tailed test, *p<.05 two tailed test, ^p<.10, two tailed testData source: 2010 ANES. Results incorporate ANES sample weight.U.S. Senate models cluster standard errors on States, U.S. House models cluster standard errors on Congressional Districts.All interaction terms centered at 0 to reduce collinearity.Deep South: Respondents in former Confederacy states of South Carolina, Mississippi, Florida, Alabama, Georgia, Louisiana, Texas, Virginia, Arkansas, Tennessee, and North Carolina.U.S. Senate elections, all three black candidates were DemocratsU.S. House elections, 16 major party candidates were black, 14 of them DemocratsTable C4. White Racial Identity among Whites and Presidential Approval in 1984 thru 2000; 2008 thru 2012: OLS 19841988199219962000200820102012Ronald ReaganRonald ReaganGeorge HW BushBill ClintonBill ClintonGeorge W BushBarack ObamaBarack ObamaWhite Identity-.04 (.06).01 (.07)-.03 (.07).07 (.08).06* (.03)-.04 (.06)-.12** (.04)-.04* (.02)Racial ResentmentNot available.02* (.01).08 (.04)Not available.01 (.03).08 (.05)-.06* (.02)-.08*(.03)Political Predispositions and EvaluationsRepublican Party Identification.29** (.02).32** (.02).34** (.02)-.28** (.03)-.08** (.01).26** (.03)-.28** (.03)-.26** (.02)Conservative Ideological Identification.13** (.03).06** (.02).07* (.03)-.19** (.04)-.04** (.01)-.04 (.07)-.11 (.07)-.05* (.02)Egalitarianism-.28** (.03)-.07 (.04)-.07 (.06).16* (.07).03 (.02)Not availableNot available.03 (.03)Limited Government-.01 (.02).10** (.03)-.03 (.05)-.18* (.07)-.04* (.02)Not availableNot available-.45** (.10)Retrospective Economy.48** (.05).28** (.04).45** (.04).43** (.05).03** (.01).40** (.11).37** (.06).28** (.04)Prospective Economy.23** (.05).06* (.03).17** (.06).21** (.07).02 (.02).12 (.09).11** (.03)Current Economy.26** (.03)Withdraw Iraq-.71** (.16)Ck Oppose Affordable Ca Care Act-.44* (.06)-.38** (.04)Oppose Democratic Legislative Agenda-.10** (.03)Oppose Economic Stimulus Bill -.25** (.04)Demographics and ControlsEducation-.01 (.01)-.09** (.02)-.09** (.02)-.05 (.03).01 (.01)-.04 (.05).09* (.03)-.03(.02)Income.01 (.01).01* (.01).00 (.01).01 (.01).01** (.00).02 (.04)-.01 (.01)-.01**(.00)Age-.00 (.00)-.01** (.00)-.00 (.00).00 (.00).00* (.00)-.00 (.00)-.00 (.00)-.00(.01)Church Attendance.04 (.02).07** (.02).06** (.02)-.03 (.04)-.02** (.01).11** (.03)-.01 (.03)-.04**(.01)Deep South.15 (.08).19** (.07).11 (.08).10 (.12)-.03 (.02).13 (.14).08 (.10)-.08(.05)Face to face interview mode.07(.06)Intercept1.14** (.29)2.05** (.28).65 (.38)2.32** (.48).56** (.14).24 (.40)10.16** (.39)3.85** (.31)R2.50.37.41.57.36.55.68.68N14901601151369110475868833176*p<.05, **p<.01Analysis of American National Election Study data from all election years but 2008; and in 2008, the Cooperative Congressional Election Study. In the ANES before 2010, the white identity measure is the dichotomous “Feel close to Whites” measure. For the CCES and the ANES in 2010 and 2012, see Appendix A.1984 standard errors clustered on counties; 1988 and 1992 on census tracts; 1996 and 2000 counties; 2008, 2010 and 2012 Congressional DistrictsStarting with 1992, all models employ sample weightsDeep South: Respondents in former Confederacy states of South Carolina, Mississippi, Florida, Alabama, Georgia, Louisiana, Texas, Virginia, Arkansas, Tennessee, and North Carolina.Table C5: Indirect Paths of White Racial Identity among Whites and White Candidate Preference for the U.S. Congress in 2010 and U.S. Congress Vote Choice in 2012, Structural Equation ModelsEndogenous VariablesExogenous VariablesU.S. House 2010^U.S. Senate 2010^U.S. House 2012^U.S. Senate 2012^President Obama ApprovalWhite Identity-.12** (.04)-.12** (04)-.04** (.01)-.05** (.02)Racial Resentment-.06** (.02)-.06** (.02)-.09** (.03)-.08** (.03)Republican Party ID-.28** (.04)-.28** (.04)-.26** (.01)-.26** (.01)Conservative Ideology ID-.11** (.04)-.11** (.04)-.05** (.02)-.05** (.02)Negative Economic Stimulus Evaluations-.25** (.04)-.25** (.03)Negative Democratic Legislative Agenda Evaluations-.11** (.04)-.10** (.04)Negative Affordable Care Act Evaluations-.45** (.11)-.44** (.11)-.38** (.03)-.38** (.03)Positive Current National Economic Evaluations.37**(.04).37**(.04).26** (.03).25** (.03)Positive Retrospective National Economic EvaluationsPositive Prospective National Economic EvaluationsNot availableNot availableNot availableNot available.28** (.04).11** (.03).29** (.04).12** (.03)Limited GovernmentNot availableNot available-.45** (.08)-.46** (.08)EgalitarianismNot availableNot available.03 (.03).03 (.03)Income-.01 (.01)-.01 (.01)-.01** (.00)-.01** (.00)Age-.00 (.00)-.00 (.00)-.00 (.01)-.00 (.01)Female.05 (.10).05 (.10).08** (.03).08** (.03)Education.09 (.05).09 (.05)-.03* (.02)-.03* (.02)Deep South.08 (.14).08 (.14)-.09 (.06)-.09 (.06)Church Attendance-.01(.03)-.01(.03)-.04** (.02)-.04**(.02)Face to Face Interview Mode.07 (.05).07 (.05)Intercept10.16**(.47)10.16**(.47)3.85** (.25)3.85** (.25)R2.68.68.68.68Democratic Congressional VotingPresident Obama Approval.04** (.01).33** (.11)1.00** (.18).51** (.08)Republican Party ID-.09** (.01)-.17** (.06)-.05 (.04)-.26** (.05)Conservative Ideology ID-.01 (.01)-.13 (.08)-.12 (.08)-.11 (.06)Negative Democratic Legislative Agenda Evaluations -.14* (.06)Negative Economic Stimulus Evaluations-.04** (.01)Positive Current National Economic Evaluations -22* (.10)Positive Retrospective National Economic EvaluationsPositive Prospective National Economic EvaluationsNot availableNot availableNot availableNot available-.12* (.06)-.06 (.06)Income.02 (.02)-.02 (.02).00 (.01).01 (.01)Age.00 (.01).01 (.01).03 (.02).07** (.02)Female-.01 (.03)-.05 (.22)-.07 (.10).11 (.09)Education.02 (.02).05 (.12).10 (.06).05 (.06)Deep South-.12** (.03)-.51* (.22)-.26 (.19).01 (.20)Church Attendance-.01(.01).02(.04)-.11** (.04)Face to Face Interview Mode-.41** (.10)-.09 (.13)Threshold-4.96** (1.01)-1.63 (1.31).96 (.82).82 (.74)R2.48.61.52.69N8838833,1933,193Indirect Effects on Democratic Congressional Voting thru ApprovalWhite IdentityRacial Resentment-.01*(.00)-.00* (.00)-.04* (.02)-.02* (.01)-.04** (.01)-.09** (.03)-.02** (.01)-.04* (.02)**p<.01, *p<.05^ 2010 results for October 2010 candidate preference; 2012 results for post-election vote choiceData sources: 2010 and 2012 ANESError terms of President Obama Approval and Democratic Congressional Voting correlated for all models but U.S. House 2010Results incorporate ANES sample weight.2010 models and 2012 U.S. House model cluster standard errors at the state level; 2012 U.S. Senate model clusters standard errors at the Congressional District level U.S. House Candidate Preference Model 2010: chi2 = 94.50 (p<.01) df=56, CFI = .78, TLI = .69, RMSEA = .028U.S. Senate Candidate Preference Model 2010: chi2 = 118.03 (p<.01) df=55, CFI = .64, TLI = .48, RMSEA = .036U.S. House Vote Choice Model 2012: chi2 = 376.81 (p<.01) df=102, CFI = .60, TLI = .47, RMSEA = .032U.S. Senate Vote Choice Model 2012: chi2 = 425.88 (p<.01) df=105, CFI = .48, TLI = .34, RMSEA = .031Deep South: Respondents in former Confederacy states of South Carolina, Mississippi, Florida, Alabama, Georgia, Louisiana, Texas, Virginia, Arkansas, Tennessee, and North Carolina.APPENDIX DPredicted Probability plots for Congressional ElectionsConsider Figure D4. When whites report feeling “Not at all” close to whites, for both the House and Senate, the probability of declaring support for the Democratic candidate appears to be about 60%. The predicted probability of support then appears to drop (although not monotonically), reaching about 40% for both the House and Senate at the “Very” close to whites category. In other words, whites who indicated that they felt “very close” to whites were statistically less likely (at the p<.05 level) to report support for Democrats, compared to whites who responded they felt “not at all” close to whites. The same holds true for those feeling “moderately” and “extremely” close to whites. While it appears that those who answered that they felt “a little” close to whites also reported lower levels of Democratic candidate support, those differences are not statistically significant – as we indicate with the dotted line. The analysis indicates that white identity reduces the predicted probability of support for Democratic U.S. House and Senate candidates in the 2010 midterm elections by about 20%.In Figure D5 we plot analogous results from the analysis of 2012. In this case, self-reported vote choice from the 2012 ANES survey is the dependent variable. The weakest category of white identity is for those whites who answered “Not at all” to the question of how important being white is to their identities. The top line has a negative slope, indicating that whites with progressively stronger white identities were less likely to self-report voting for Democratic U.S. Senate candidates – representing the indirect effect of white identity on vote choice, operating through Presidential approval. Whites who responded to the white identity question with “a little” did not have a statistically significantly lower likelihood of voting for Democratic candidates compared to the weakest white identity category (as reflected by the dotted line). However, those who chose the three strongest white identity categories (moderately, very and extremely) were statistically less likely to vote for Democrats (as reflected by the solid line). The line below that is for the predicted probability of voting for Democratic U.S. House candidates in 2012. The slope of the decreases in the predicted probabilities given stronger levels of white identity is nearly parallel compared to the decreases for the U.S. Senate. The white identity categories with the statistically significant reductions in the predicted probability of candidate support are identical to those of the U.S. Senate results. It appears white identity reduced the predicted probability of voting for Democrats for the U.S. House and Senate in 2012 by about 15% (from 55% to 40%). APPENDIX EAdditional SEM model configurationsFor the 2010 SEMs, we estimated 16 different model configurations for both the U.S. House and Senate vote choice models (32 different models total). For the 2012 SEMs, we estimated 12 different model configurations for each (24 total). In Tables 5 and C5 we report the results for the four models with the strongest overall model fits.The 2010 SEMsIn the “full model” we allowed Affordable Care Act evaluations, economic evaluations and evaluations of the 2010 Democratic legislative agenda to directly affect vote choice. In the next model we dropped health care from the vote choice model (forcing the full effect to operate through Presidential approval). Then we dropped the economic evaluation variables. Then we dropped the Democratic legislative agenda evaluations. This results in four different models. We then ran these four models clustering the standard errors at the state level, and then again at the Congressional District level (resulting in eight models). We then ran these eight models two more times, correlating the endogenous errors, and then not correlating them (for a total of 16 models).For the U.S. House model, the next-strongest model fit correlated the errors and clustered at the state level, dropping the Affordable Care Act variable and the economic evaluation variables from the vote choice model. The resulting model fit statistics are: chi2 = 93.71 (p<.01) df=56, CFI = .78, TLI = .68, RMSEA = .028. The white identity indirect effect coefficient is not statistically significant at the p<.05 level in this model. The chi-square statistic indicates this model is a better fit, while the TLI indicates that the model we report in the table is a better fit. The other model statistics are identical. For the U.S. Senate model, the next-strongest model fit clustered the standard errors at the state level, did not correlate the endogenous errors, and dropped health care and economic evaluations from the vote choice model. The model fit statistics are: chi2 = 118.59 (p<.01) df=55, CFI = .64, TLI = .47, RMSEA = .036. The white identity indirect effect coefficient is statistically significant at the p<.05 level in this model. The chi-square from this model indicates a worse fit compared to the one we report, as does the TLI, while the others are identical.The 2012 SEMsIn the “full model” we allowed evaluations of the Affordable Care act and economic evaluations to directly affect vote choice. In the next model we dropped the health care variable from the vote choice model (forcing the full effect to operate through approval). In the next model we dropped economic evaluations from the vote choice model. This results in three models. We then ran them clustering at the state level, and then the Congressional District level (resulting in six models). We then ran those six models correlating the endogenous error, and not doing so (resulting in twelve models).For the U.S. House model, next strongest-fitting model is identical to the model we report in Table 5, but the Affordable Care Act variable is allowed to affect vote choice directly. The model fit statistics are: chi2 = 377.311 (p<.01) df=102, CFI = .59, TLI = .46, RMSEA = .029. The white identity indirect effect coefficient is not statistically significant at the p<.05 level in this model. All of the model fit statistics we report here indicate a worse fit, compared to the model we report in the table.For the U.S. Senate model, the next-strongest fitting model is identical to the one in Table 5, excepting that the economic evaluations are allowed to affect vote choice directly. The model fit statistics are: chi2 = 428.67 (p<.01) df=105, CFI = .47, TLI = .31, RMSEA = .032. The white identity indirect effect coefficient is statistically significant at the p<.05 level in this model. All of the model fit statistics we report here indicate a worse fit, compared to the model we report in the table. ................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download