Are Group Cues Necessary? How Anger Makes Ethnocentrism Among Whites a Stronger Predictor of Racial and Immigration Policy Opinions


Research shows that group conflict sets ethnocentric thinking into motion. However, when group threat is not salient, can ethnocentrism still influence people’s political decision-making? In this paper, I argue that anger, unrelated to racial and ethnic groups, can activate the attitudes of ethnocentric whites and those that score low in ethnocentrism thereby causing these attitudes to be a stronger predictor of racial and immigration policy opinions. Using an adult national experiment over two waves, I induced several emotions to elicit anger, fear, or relaxation (unrelated to racial or ethnic groups). The experimental findings show that anger increases opposition to racial and immigration policies among whites that score high in ethnocentrism and enhances support for these policies among those that score low in ethnocentrism. Using data from the American National Election Study cumulative file, I find a similar non-racial/ethnic anger effect. The survey findings also demonstrate that non-racial/ethnic fear increases opposition to immigration among whites that don’t have strong out-group attitudes.

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  1. 1.

    “Tough Times? Blame Minorities!” Southern Poverty Law Center, October 14, 2008.

  2. 2.

    In fact, research shows that anger plays an important role in whites’ opinions toward affirmative action (Kinder and Sanders 1996; Kuklinski et al. 1997) and likely underlies people’s opinions toward undocumented immigrants (Lee and Fiske 2006).

  3. 3.

    Scholars have devoted little attention to the role of blame attributions in the immigration debate. Much of the research on immigration focuses on the threat immigrants (mostly Hispanic immigrants) pose to American citizens (Brader et al. 2008; Burns and Gimpel 2000; Citrin et al. 1997; Hood and Morris 1997; Hopkins 2010; Huddy and Sears 1995; Rocha et al. 2011; Sniderman et al. 2004). This research oftentimes examines the effects of economic threats (realistic and material) and cultural threats (symbolic and identity) on people’s willingness to support immigration.

  4. 4.

    Valentino et al. (2013) find that the U.S. media coverage of immigration focuses more on Hispanics than other immigrant groups like Asians, Africans, or Muslims. Perhaps Americans hold Hispanic immigrants more responsible for the immigration problem than other immigrant groups.

  5. 5.

    They should also acquire their attitudes during anger-inducing experiences. An example of an anger-inducing event is the beating of Rodney King by several white police officers. Many people considered this act racially motivated.

  6. 6.

    Brader et al. (2008) acknowledge that their anxiety measure “is not well suited to detecting anger as distinct from anxiety because it only contains one anger term. Thus, one could reinterpret the scales as negative and positive affect, rather than as anxiety and enthusiasm” (p. 968).

  7. 7.

    Several subjects were dropped from the analysis because they failed to follow instructions. The results are essentially the same if these respondents are included.

  8. 8.

    There was a re-contact success rate of 60 %. If some respondents were turned off by the measures of group attitudes in the pre-test, they might opt out of the second wave. This withdrawal of participants could dampen effects. Fortunately, the mortality rate was equivalent across the two waves- no biases occurred between waves 1 and 2 on the feeling thermometer rating of whites (Chi squared 60.2, p = .153), blacks (chi-squared 68.2, p = .569), Hispanics (chi-squared 90.6, p = .175), and Asians (chi-squared 72.7, p = .389).

  9. 9.

    The distribution of ethnocentrism (Mean = .13 S.D. = .18) shows that whites on balance are ethnocentric. This result is consistent with Kinder and Kam’s (2009) finding.

  10. 10.

    The facial images are presented in the supporting information document. The facial images are of a middle age white woman. Facial expressions are shown to trigger the same emotion in the viewer (Ekman 1993). The pictures are drawn from Ekman’s archive of emotional expressions (Ekman and Friesen 1976).

  11. 11.

    For the relaxed condition, there is no image. Paul Ekman’s archival of emotional expression does not include an image of someone who is relaxed. The prompt for the relaxed condition states “Now we would like you to describe in general things that make you feel RELAXED. It is okay if you don't remember all the details, just be specific about what exactly it is that makes you RELAXED and what it feels like to be RELAXED. Please describe the events that make you feel the MOST RELAXED, these experiences could have occurred in the past or will happen in the future. If you can, write your description so that someone reading it might even feel RELAXED.”

  12. 12.

    I also find that respondents in the anger conditions are more likely to write about race and immigration than subjects in the fear and control conditions. These results are in the supporting information document.

  13. 13.

    The racial policy opinions index is a combination of support for government assistance to blacks and affirmative action (preferential treatment of blacks). This measure, along with all other variables, is described in the supporting information document.

  14. 14.

    The effect is significant among 3 % of the sample that score high in ethnocentrism and 5 % of the sample that score low in ethnocentrism.

  15. 15.

    I also find that the marginal effect of anger is statistically distinguishable from the marginal effect of fear (one-tailed p < .025). To determine if these differences are statistically significant, I take the difference between the marginal effects of anger and fear and calculate its 95 % CI (across the ethnocentrism scale). The test shows that marginal effect of anger is statistically different from the marginal effect of fear among whites that score at the high end of the ethnocentrism scale (.6 and higher) and those that score low in ethnocentrism (−.1 and lower).

  16. 16.

    The immigration policy opinion item is whether respondents support prohibiting children of illegal immigrants from attending U.S. public schools. This measure captures whites’ views toward policies that directly benefit illegal immigrants by providing their children with educational opportunities.

  17. 17.

    The anger effect is significant among 33 % of respondents in the analysis. That is, the effect is significant among 1 % of the sample that score high in ethnocentrism and 9 % of the sample that score low in ethnocentrism (i.e. racial liberals) The anger effect is also significant among whites that score at the mid-point of the scale.

  18. 18.

    The marginal effect of anger is statistically different from the marginal effect of fear (one-tailed p < .05) among whites that score at the very high end of the ethnocentrism scale and those that score low in ethnocentrism.

  19. 19.

    I exclude 2008 and 2012 from my analysis because the emotion measures are directed at the presidential candidates, and one of the candidates is Barack Obama, an African American. Since my argument is that non-racial/ethnic anger should heighten the effect of ethnocentrism on racial and immigration policy opinions, it is important that blacks, Latinos, or Asians are not the targets of the emotion measures.

  20. 20.

    The measure of ethnocentrism is based upon the feeling thermometers of three groups (whites, blacks and Hispanics). The 1996 ANES only asked participants about these three groups and not Asians. When I use the ethnocentrism measure based upon whites, blacks, Hispanics, and Asians (by excluding 1996 from the analysis), the results are the same.

  21. 21.

    The anger effect is significant among 9 % of the sample that are ethnocentric and 8 % of the sample that score low in ethnocentrism.

  22. 22.

    There is no significant difference between the marginal effect of anger and fear across the ethnocentrism scale.

  23. 23.

    I collapse the dependent variable because some people perceive “keeping the status quo” category as a pro-immigrant stance. That is, people believe that the “status quo” is allowing a large number of immigrants into the country. Hopkins (2010) applies a similar approach when using the same measure of immigration policy opinion. When the variable is coded as a 3-category variable (1 = decrease, .5 = keep the same, and 0 = increase), the results are essentially the same.

  24. 24.

    I calculate the predicted probabilities by manipulating the emotion variables while holding all the other independent variables at their observed values in the data and then averaging over all of the cases (See Hanmer and Kalkan 2013 for a more detailed description of this approach).

  25. 25.

    The anger effect is significant among 18 % of that sample that are ethnocentric and 13 % of the sample that score low in ethnocentrism. These results are available in the supporting information document.

  26. 26.

    These results are available in the supporting information document.


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The author thanks Heather Hicks, Ho Youn Koh, Sanata Sy-Sahande, and Kerry Jones for excellent research assistance, and Eric Groenendyk, Cindy Kam, Jennifer Merolla, James Gimpel, the attendees at the American Politics Colloquium at Syracuse University and the Symposium on Politics of Immigration, Race, and Ethnicity (SPIRE) at Rutgers University for helpful feedback. The data and replication code can be found at Political Behavior’s Dataverse webpage.

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Correspondence to Antoine J. Banks.

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Banks, A.J. Are Group Cues Necessary? How Anger Makes Ethnocentrism Among Whites a Stronger Predictor of Racial and Immigration Policy Opinions. Polit Behav 38, 635–657 (2016).

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  • Ethnocentrism
  • Emotions
  • Racial and immigration policy opinions