Published online by Cambridge University Press: 01 November 2017
Employing a comparative experimental design drawing on over 18,000 interviews across eleven countries on four continents, this article revisits the discussion about the economic and cultural drivers of attitudes towards immigrants in advanced democracies. Experiments manipulate the occupational status, skin tone and national origin of immigrants in short vignettes. The results are most consistent with a Sociotropic Economic Threat thesis: In all countries, higher-skilled immigrants are preferred to their lower-skilled counterparts at all levels of native socio-economic status (SES). There is little support for the Labor Market Competition hypothesis, since respondents are not more opposed to immigrants in their own SES stratum. While skin tone itself has little effect in any country, immigrants from Muslim-majority countries do elicit significantly lower levels of support, and racial animus remains a powerful force.
Political Science, University of Michigan (email: nvalenti@umich.edu); Communication Studies and Political Science, University of Michigan (email: ssoroka@umich.edu); Political Science, Stanford University (email: siyengar@stanford.edu); Sociology and Political Science, Norwegian University of Science and Technology (email: toril.aalberg@svt.ntnu.no); Nuffield College, University of Oxford (email: raymond.duch@nuffield.ox.ac.uk); Institute of Public Goods and Policies, Spanish Scientific Research Institute (email: marta.fraile@eui.eu); Communication, Seoul National University (email: kyuhahn@snu.ac.kr); Political Science, University of Copenhagen (email: kmh@ifs.ku.dk); Political Science, Université du Québec à Montréal (email: harell.allison@uqam.ca); Political Science, University of Bamberg (email: helbling@wzb.eu); United States Studies Centre, University of Sydney (email: simon.jackman@sydney.edu.au); Department of Media and Communication, City University of Hong Kong (email: tkobayas@cityu.edu.hk). Replication data sets are available in Harvard Dataverse at: https://dx.doi.org/10.7910/DVN/R5MEKK and online appendices are available at https://doi.org/10.1017/S000712341700031X.