A New Electorate? : Explaining the Party Preferences of Immigrant-Origin Voters at the 2017 Bundestag Election

Faculty/Professorship: Political Sociology  
Author(s): Mayer, Sabrina Jasmin  ; Goerres, Achim; Spies, Dennis Christopher
Title of the Journal: British Journal of Political Science
ISSN: 1469-2112, 0007-1234
Publisher Information: London : Cambridge Univ. Press
Year of publication: 2022
Volume: 52
Issue: 3
Pages: 1032-1054
Language(s): English
DOI: 10.1017/S0007123421000302
Immigrants now constitute a sizeable and rapidly growing group among many Western countries' electorates, but analyses of their party preferences remain limited. Theoretically, immigrants' party preferences might be explained with both standard electoral theories and immigrant-specific approaches. In this article, we rigorously test both perspectives against each other using the most recent data from Germany. Applying the Michigan model, with its three central explanatory variables – party identification, issue orientations and candidate evaluations – to the party preferences of immigrant-origin and native voters, we find that this standard model can explain both groups well. In contrast, we find no direct effects of the most prominent immigrant-specific variables, and neither do these meaningfully moderate the Michigan variables. However, we find strong formative effects on the presence of political attitudes and beliefs: immigrants with a longer time spent in Germany, a stronger German identity and less experience of discrimination report significantly fewer item non-responses for the Michigan model's main explanatory variables.
GND Keywords: Deutschland. Deutscher Bundestag; Bundestagswahl; Wähler; Migrationshintergrund; Wahlverhalten; Geschichte 2017
Keywords: immigrants, political preferences, voting behaviour, political integration, Germany, Michigan model
DDC Classification: 320 Political Science  
RVK Classification: MG 15480   
Peer Reviewed: Ja
International Distribution: Ja
Type: Article
URI: https://fis.uni-bamberg.de/handle/uniba/55916
Release Date: 13. October 2022