a1 Massachusetts Institute of Technology
a2 London School of Economics & University of Zurich
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.
This article received the 2012 Robert H. Durr Award from the Midwest Political Science Association for “the best paper applying quantitative methods to a substantive problem.” We thank Ken Benoit, Suzanne Berger, Adam Berinsky, Catherine De Vries, Marc Girardelli, Marc Helbing, Gabe Lenz, Rick Locke, Ben Rissig, Didier Ruedin, Lily Tsai, the editors, four anonymous reviewers, and participants in seminars at Princeton, Harvard, Stanford, MIT, the University of Bern, the European University Institute, and the Midwest Political Science Meeting for helpful comments. For excellent research assistance, we thank Andreas Besmer, Matthias Christen, Roman Kuster, Fabian Morgenthaler, Emilia Pasquier, Giuseppe Pietrantuono, Rocco Pietrantuono, Livio Raccuia, Mirjam Rütsch, Laura Schmid, and Tess Wise. We especially would like to thank Marco Steenbergen for his valuable support and all the municipality officials for participating in our survey. Funding for this research was generously provided by Swiss National Science Grant No. 100017_132004. The usual disclaimer applies.