Suchergebnisse

On 23 June 2016, the British electorate voted to leave the European Union. We analyze 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 as well as low income and high unemployment. At the much finer level of wards within cities, we find that areas with deprivation in terms of education, income and employment were more likely to vote Leave. Our results indicate that a higher turnout of younger voters, who were more likely to vote Remain, would not have overturned the referendum result.

We study the impact of the 2016 Brexit referendum on UK foreign direct investment. Using the synthetic control method to construct appropriate counterfactuals, we show that by March 2019 the Leave vote had led to a 17% increase in the number of UK outward investment transactions in the remaining EU27 member states, whereas transactions in non-EU OECD countries were unaffected. These results support the hypothesis that UK companies have been setting up European subsidiaries to retain access to the EU market after Brexit. At the same time, we find that the number of EU27 investment projects in the UK has declined by around 9%, illustrating that being a smaller economy than the EU leaves the UK more exposed to the costs of economic disintegration.

Previous analyses of the 2016 Brexit referendum used region-level data or small samples based on polling data. The former might be subject to ecological fallacy and the latter might suffer from small-sample bias. We use individual-level data on thousands of respondents in Understanding Society, the UK's largest household survey, which includes the EU referendum question. We find that voting Leave is associated with older age, white ethnicity, low educational attainment, infrequent use of smartphones and the internet, receiving benefits, adverse health and low life satisfaction. These results coincide with corresponding patterns at the aggregate level of voting areas. We therefore do not find evidence of ecological fallacy. In addition, we show that prediction accuracy is geographically heterogeneous across UK regions, with strongly pro-Leave and strongly pro-Remain areas easier to predict. We also show that among individuals with similar socioeconomic characteristics, Labour supporters are more likely to support Remain while Conservative supporters are more likely to support Leave.