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Economic Explanations for Opposition to Immigration: Distinguishing between Prevalence and Conditional Impact

Authors


  • Neil Malhotra is Associate Professor of Political Economy, Graduate School of Business, Stanford University, 655 Knight Way, Stanford, CA 94305 (neilm@stanford.edu). Yotam Margalit is Assistant Professor of Political Science, Columbia University, 420 W. 118th St., New York, NY 10027 (ym2297@columbia.edu). Cecilia Hyunjung Mo is Assistant Professor of Political Science, Vanderbilt University, PMB 0505, 230 Appleton Place, Nashville, TN 37203–5721 (cecilia.h.mo@vanderbilt.edu).

  • We thank John Sides, Alexander Kuo, Keith Krehbiel, Dan Hopkins, Jens Hainmueller, and Rafaela Dancygier for providing valuable feedback on earlier drafts. We are also grateful for excellent feedback from the editor and three anonymous reviewers. We acknowledge Philip Garland and Cissy Segujja for their assistance with data collection and Fred Wolens for excellent research assistance. We thank seminar participants at Columbia University, University of Pittsburgh, UCLA, UCBerkeley, and the Comparative Approaches to Immigration and Ethnic Diversity Conference at Princeton University for valuable feedback. Previous versions of this article were presented at the annual meeting of the American Political Science Association, the annual meeting of the Midwest Political Science Association, and the annual meeting of the International Society of Political Psychology.

Abstract

What explains variation in individuals’ opposition to immigration? While scholars have consistently shown cultural concerns to be strong predictors of opposition, findings regarding the labor-market competition hypothesis are highly contested. To help understand these divergent results, we distinguish between the prevalence and conditional impact of determinants of immigration attitudes. Leveraging a targeted sampling strategy of high-technology counties, we conduct a study of Americans’ attitudes toward H-1B visas. The plurality of these visas are occupied by Indian immigrants, who are skilled but ethnically distinct, enabling us to measure a specific skill set (high technology) that is threatened by a particular type of immigrant (H-1B visa holders). Unlike recent aggregate studies, our targeted approach reveals that the conditional impact of the relationship in the high-technology sector between economic threat and immigration attitudes is sizable. However, labor-market competition is not a prevalent source of threat and therefore is generally not detected in aggregate analyses.

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