In May 2015, the United Kingdom voted to give the Conservatives an overall majorityin the House of Commons. In June 2016, the British people voted to leave the European Union in a landmark and highly controversial referendum. Just days later, Spain voted to increase the seat share of the conservative People’s Party at the expense of the much-vaunted Unidos Podemos alliance. And just last November, the United States of America elected Donald Trump as its 45th President.
All of these events returned arguably right-wing results, and all proved surprising and even deeply shocking to politicians, markets and the mass media. But why have recent Western vote outcomes been so surprisingly conservative?
For a popular vote to be a surprise, two things are needed. Voters must arrive at a certain outcome, and this outcome must conflict with what at least some peopleexpected it to be. In the contemporary West, the most important source of electoral expectations comes from the polls produced by political research agencies. In all of the above votes, pollsters systematically underestimated the popularity of right-wing outcomes. Hence the surprise.
Much of the flack for this discrepancy has been directed against polling organisations. There are good reasons for this: polls are generally based upon quick and dirty data, frequently relying on unrepresentative convenience samples to conserve time and money. It should not be surprising that the outcomes of these polls are occasionally something less than reliable.
But there may be something else going on here. Two popular theories suggest that even where the public is correctly polled,
shy Tories systematically downplay their willingness to vote for the Conservatives (perhaps feeling that support for this party is socially stigmatised) and
lazy Labour supporters exaggerate their willingness to vote at all.
Prof Patrick Sturgis’ inquiry into the 2015 general election polling
miss dismissed these theories, finding that if anything survey dishonesty has made recent election polls slightly more accurate. Furthermore, the unexpected Conservative vote boost was greatest where the Conservatives are most popular, suggesting that it cannot be explained by a
shaming effect. Last year this was repeated in the United States, where the difference between actual and predicted Trump votes was greatest in Republican-majority districts.
These findings are interesting, but how widely applicable are they? Do they apply, for example, to last year’s EU referendum?
What do we know about
Leavers and
Remainers? Well, areas with larger numbers of
Leave votes tended to be older, more economically disadvantaged, and, perhaps surprisingly, more likely to have dependent children– even disregarding age differences. Whilst economic disadvantage tends to be associated with not voting, increasing age is often linked with voter turnout and there is also some evidence that having children increases one’s likelihood of voting. It also appears that Leavers, when asked in surveys, were more disposed to put their trust in the decisions of ordinary people, as opposed to those of experts. So perhaps Leavers were more motivated to vote than Remainers.
To investigate this further, I downloaded and analysed Wave 7 of the British Election Study’s Internet Panel. This survey was conducted online in April and May 2016, shortly before the vote but early enough in advance to allow respondents to take considered stances.
At the time these data were collected, the survey respondents seemed to lean overall in the direction of voting
Remain, with 50.4% intending to vote to Remain and 47.6% intending to vote to leave. This is similar to the findings of many convenience-sampled polls taken at the time, suggesting that the
Brexit surprise did not stem from sampling issues.
But when we compare likelihood to vote in the EU referendum across the two camps, it becomes apparent that Leavers reported a slightly higher average likelihood to vote than Remainers. The difference is small, but then so was Leave’s margin of victory.


