Hostname: page-component-6898cfcb55-zkb6p Total loading time: 0 Render date: 2026-11-11T05:06:36.472Z Has data issue: false hasContentIssue false

Who Gets a Swiss Passport? A Natural Experiment in Immigrant Discrimination

Published online by Cambridge University Press:  07 February 2013

JENS HAINMUELLER*
Affiliation:
Massachusetts Institute of Technology
DOMINIK HANGARTNER*
Affiliation:
London School of Economics & University of Zurich
*
Jens Hainmueller is Associate Professor, Department of Political Science, 77 Massachusetts Avenue, Cambridge, MA 02139 (jhainm@mit.edu).
Dominik Hangartner is Lecturer, Department of Methodology, Houghton Street, London WC2A 2AE, and Institute of Political Science, Affolternstrasse 56, 8050 Zurich (d.hangartner@lse.ac.uk).
Rights & Permissions [Opens in a new window]

Abstract

We study discrimination against immigrants using microlevel data from Switzerland, where, until recently, some municipalities used referendums to decide on the citizenship applications of foreign residents. We show that naturalization decisions vary dramatically with immigrants’ attributes, which we collect from official applicant descriptions that voters received before each referendum. Country of origin determines naturalization success more than any other applicant characteristic, including language skills, integration status, and economic credentials. The average proportion of “no” votes is about 40% higher for applicants from (the former) Yugoslavia and Turkey compared to observably similar applicants from richer northern and western European countries. Statistical and taste-based discrimination contribute to varying naturalization success; the rewards for economic credentials are higher for applicants from disadvantaged origins, and origin-based discrimination is much stronger in more xenophobic municipalities. Moreover, discrimination against specific immigrant groups responds dynamically to changes in the groups’ relative size.

Information

Type
Research Article
Copyright
Copyright © American Political Science Association 2013
Figure 0

TABLE 1.Ballot Box Municipalities with Naturalization Referendums

Figure 1

TABLE 2.Ballot Box Municipalities in Comparison

Figure 2

FIGURE 1.Opposition to Naturalization RequestsNote: Distribution of proportion of “no” votes across naturalization referendums in each ballot box municipality. Width of box measures the interquartile range, the vertical line decodes the median.

Figure 3

TABLE 3.Effect of Applicant Characteristics on Opposition to Naturalization Request

Figure 4

FIGURE 2.Effect of Applicant Characteristics on Opposition to Naturalization RequestsNote: Marginal effect estimates with robust 95% confidence intervals based on OLS regression of proportion of “no” votes on applicant characteristics and municipality and decade fixed effects (Model 1 in Table 3). The reference categories are as follows: applicants with age <20 years, low education, in low skilled jobs, “sufficient” command of one of the Swiss languages, who are familiar with “Swiss traditions and customs,” and originating from a richer northern and western European country. The average proportion of “no” votes is 37%.

Figure 5

TABLE 4.Effect of Applicant Characteristics on Opposition to Naturalization Request in Large and Small Municipalities

Figure 6

TABLE 5.Effect of Applicant Characteristics on Opposition to Naturalization Request: Matching Results and Sensitivity Analysis

Figure 7

TABLE 6.Statistical Discrimination: Interaction Effect of Economic Credentials and Country of Origin on Opposition to Naturalization Request

Figure 8

TABLE 7.Taste-Based Discrimination: Interaction Effect of Xenophobic Preferences and Country of Origin on Opposition to Naturalization Request

Figure 9

FIGURE 3.Municipality Specific Country of Origin Effects and Local XenophobiaNote: Marginal effect estimate for the interaction of Yugoslavian and Turkish origin and municipal anti-immigrant vote share based on multilevel regression. The plot builds on the estimates of multilevel Model 2 of Table 7 which regresses the proportion of “no” votes on applicant characteristics, municipal characteristics, and (de-meaned) anti-immigration vote share in the 1982 referendum. Random intercepts and slopes for the country of origin indicator allowed to vary unrestrictedly by municipality. Random effects for each municipality are shown along with 90% prediction intervals.

Figure 10

FIGURE 4.Immigration Trends in SwitzerlandNote: Plot shows the shares of immigrants from different origins on the total foreign-born population (Source: PETRA Database from Swiss Federal Office of Statistics).

Figure 11

TABLE 8.Dynamics of Country of Origin Effects

Supplementary material: PDF

Hainmueller Supplementary Material

Appendix

Download Hainmueller Supplementary Material(PDF)
PDF 4.2 MB
Submit a response

Comments

No Comments have been published for this article.