Abstract
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 socio-economic characteristics, Labour supporters are more likely to support Remain while Conservative supporters are more likely to support Leave.
Highlights
Populism has been on the rise across Europe and the United States in recent years, culminating in the election of Donald Trump as US President and the Brexit vote in the 2016 EU referendum
Pollock (2017) uses the Innovation Panel to argue that the rise in populism and the vote in favor of Brexit can be attributed to generational shifts away from mainstream political parties over the past three decades
Our findings indicate that Labour voters with observables that put them in the Leave camp – male, older, less educated, less likely to be in employment, etc. – are significantly more likely to express a preference for the status quo of remaining in the EU
Summary
Populism has been on the rise across Europe and the United States in recent years, culminating in the election of Donald Trump as US President and the Brexit vote in the 2016 EU referendum. The Brexit vote came as a shock to many observers and triggered early attempts to understand the voting patterns.. The Brexit vote came as a shock to many observers and triggered early attempts to understand the voting patterns.1 These studies relied almost exclusively on aggregate data at the level of voting areas. Regressing vote shares across voting areas on average population characteristics risks falling into the ecological fallacy trap of inferring individual associations from aggregate data (see Robinson, 1950). We address whether ecological fallacy may be driving the associations documented in the aggregated data. We investigate the classification errors that this predictive model makes by region and voters’ closeness to political parties. We document that the predictive models exhibit a significant gain in accuracy when exploiting both individual and regional variables. Underlying regression results and further details are relegated to an appendix
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