Arbeitspapier

Divided We Stand: Immigration Attitudes, Identity, and Subjective Well-Being

Immigration is a crucial issue in contemporary politics, and attitudes towards immigration are highly dispersed in many countries. We treat individuals' immigration friendliness (IF) as a feature of their self-image or identity and hypothesize that, similar to other pro-social self-images, greater immigration friendliness is associated with greater subjective well-being (SWB). We further hypothesize that greater disparity of immigration attitudes yields social antagonism and as such is associated with less SWB. Finally, we hypothesize that greater disparity of immigration attitudes permits immigration-friendly individuals to differentiate themselves from others, thus raising the SWB benefit of holding an immigration-friendly self- image. Using 225,356 observations from 35 European countries, 2002-2015, we find evidence consistent with the hypotheses stated above. A 1-standard-deviation (SD) increase in IF is associated with an increase in 11-point life satisfaction (LS) by 0.15 to 0.32 points, whereas a 1-SD increase in attitude disparity is associated with a decrease in LS by 0.05 to 0.11 points.

Language
Englisch

Bibliographic citation
Series: Oldenburg Discussion Papers in Economics ; No. V-401-17

Classification
Wirtschaft
General Welfare; Well-Being
Conflict; Conflict Resolution; Alliances; Revolutions
Equity, Justice, Inequality, and Other Normative Criteria and Measurement
Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification
Subject
immigration
attitudes
identity
antagonism
social conflict
subjective well-being

Event
Geistige Schöpfung
(who)
Welsch, Heinz
Kühling, Jan
Event
Veröffentlichung
(who)
University of Oldenburg, Department of Economics
(where)
Oldenburg
(when)
2017

Handle
Last update
10.03.2025, 11:45 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Welsch, Heinz
  • Kühling, Jan
  • University of Oldenburg, Department of Economics

Time of origin

  • 2017

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