2017
DOI: 10.1093/epolic/eix012
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Who voted for Brexit? A comprehensive district-level analysis

Abstract: On 23 June 2016, the British electorate voted to leave the European Union. We analyse vote and turnout shares across 380 local authority areas in the United Kingdom. We find that exposure to the EU in terms of immigration and trade provides relatively little explanatory power for the referendum vote. Instead, we find that fundamental characteristics of the voting population were key drivers of the Vote Leave share, in particular their education profiles, their historical dependence on manufacturing employment … Show more

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Cited by 429 publications
(399 citation statements)
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“…The reasons for these rather counter-intuitive observations are complex, and involve cultural or political aspects as well as economic influences (Becker, Fetzer, & Novy, 2017).…”
Section: Methodsologymentioning
confidence: 99%
“…The reasons for these rather counter-intuitive observations are complex, and involve cultural or political aspects as well as economic influences (Becker, Fetzer, & Novy, 2017).…”
Section: Methodsologymentioning
confidence: 99%
“…Another reason to focus on subgroups is the demographic composition of the Brexit referendum vote. It has been shown, for example, that older and less educated voters in particular were more likely to vote 'Leave' (Becker et al, 2016;Goodwin and Heath, 2016;Rosenbaum, 2017) and, relative to their younger counterparts, older people place a higher importance on the issue of immigration as the UK negotiates its way out of the EU (Bulman, 2017). Our findings will show whether immigration-induced changes in subjective well-being are congruent with these voting and policy preference patterns.…”
Section: Introductionmentioning
confidence: 99%
“…We discuss these in detail in section 3 and consider how future work might tackle some of these issues and how they apply to these results. It is important to note that the predicted sectoral impacts are model dependent and so we would urge caution in 2 See, for example, some of the contributions in Baldwin (2016) and Becker, Fetzer and Novy (2017). placing strong weight on the estimated impact for any particular sector.…”
mentioning
confidence: 99%