A Populist Paradox? How Brexit Softened Anti-Immigrant Attitudes

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Abstract

Recent political contests across Europe and North America have been propelled by a wave of populist, anti-immigrant resentment, and it was widely expected that these populist victories would further fan the flames of xenophobia. This article reports the results of an experiment around the Brexit referendum, designed to test how populist victories shape anti-immigrant attitudes. The study finds that anti-immigrant attitudes actually softened after the Brexit referendum, among both Leave and Remain supporters, and these effects persisted for several months. How could a right-wing, populist victory soften anti-immigrant attitudes? The authors use causal mediation analysis to understand this ‘populist paradox’. Among Leavers, a greater sense of control over immigration channelled the effects of the Brexit outcome onto anti-immigrant attitudes. Individuals' efforts to distance themselves from accusations of xenophobia and racism explains the softening of attitudes towards immigration observed among both Leavers and Remainers.

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Traditionally in the social sciences, causal mediation analysis has been formulated, understood, and implemented within the framework of linear structural equation models. We argue and demonstrate that this is problematic for 3 reasons: the lack of a general definition of causal mediation effects independent of a particular statistical model, the inability to specify the key identification assumption, and the difficulty of extending the framework to nonlinear models. In this article, we propose an alternative approach that overcomes these limitations. Our approach is general because it offers the definition, identification, estimation, and sensitivity analysis of causal mediation effects without reference to any specific statistical model. Further, our approach explicitly links these 4 elements closely together within a single framework. As a result, the proposed framework can accommodate linear and nonlinear relationships, parametric and nonparametric models, continuous and discrete mediators, and various types of outcome variables. The general definition and identification result also allow us to develop sensitivity analysis in the context of commonly used models, which enables applied researchers to formally assess the robustness of their empirical conclusions to violations of the key assumption. We illustrate our approach by applying it to the Job Search Intervention Study. We also offer easy-to-use software that implements all our proposed methods. PsycINFO Database Record (c) 2010 APA, all rights reserved.