Arbeitspapier

Suffering and prejudice: Do negative emotions predict immigration concerns?

Existing research attributes functional utility to emotions and shows that emotions can explain disparate individual behaviors and decisions. We contribute to this research by investigating the role of individuals' emotions in predicting opposition to international immigration in Germany. To this purpose, we use the less explored information on individuals' negative affect present in the Socio-Economic Panel data and construct an index of negative emotions comprising of self-reported frequency of experiencing sadness, fear, and anger. Our results indicate that a higher frequency of negative emotions is statistically significantly associated with increased immigration concerns. To infer causality, we exploit the exogenous variation in negative emotions induced by the individual's parent's death and apply fixed effects regressions with instrumental variables. While the causal estimation strategy masks the average effect, we register a weak and positive impact of negative emotions on immigration concerns for the female subsample. Additional analysis of females indicates that the causal impact is more forceful for those who are irregularly employed, older, rarely use social media, and have a less agreeable and more extroverted personality. We also show that while negative emotions predict female support of far-right political parties, they do not affect their left-wing support and concerns about xenophobic hostility, crime, and own financial situation.

Language
Englisch

Bibliographic citation
Series: GLO Discussion Paper ; No. 644 [rev.]

Classification
Wirtschaft
Micro-Based Behavioral Economics: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making‡
International Migration
Capitalist Systems: Political Economy
Subject
Negative emotions
immigration concerns
bereavement

Event
Geistige Schöpfung
(who)
Deole, Sumit S.
Huang, Yue
Event
Veröffentlichung
(who)
Global Labor Organization (GLO)
(where)
Essen
(when)
2021

Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Deole, Sumit S.
  • Huang, Yue
  • Global Labor Organization (GLO)

Time of origin

  • 2021

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