New Findings on Key Factors Influencing the UK’s Referendum on Leaving the EU

Abstract

Summary The UK’s EU in/out referendum raised significant debate and speculation of the intention of the electorate and its motivations in voting; much of this debate was informed by simple data analysis examining individual factors, in isolation, and using opinion polling data. This, in the case of the EU referendum where multiple factors influence the decision simultaneously, failed to predict the eventual outcome. On June 23, 2016, Britain’s vote to leave the EU came as a surprise to most observers, with a bigger voter turnout than that of any UK general election in the past decade. In this research, we apply multivariate regression analysis and a Logit Model to real voting data to identify statistically significant factors influencing the EU referendum voting preference simultaneously as well as the odd ratio in favor of Leave. Visualizations of the key findings are also provided with heat maps and graphs. We find that higher education is the predominant factor dividing the nation, with a marginal effect on the referendum decision being stronger than any other factors particularly in England and Wales, where most Leave voters reside. An increase of about 3% in the proportion of British adults accessing to higher education in England and Wales could have reversed the referendum result in the UK. We also find that areas in England and Wales with a lower unemployment rate tend to have a higher turnout to support Leave while areas in Scotland and Northern Ireland with a higher proportion of university-educated British adults have a higher turnout to support Remain. Further we find that areas with high proportions of British male adults show a higher percentage of Leave votes. A higher proportion of elderly British contributes to a higher percentage of Leave votes, but does not lead to Leave outcomes on their own.