In April 2016 in two contributions to this blog Ron Johnston, Kelvyn Jones and David Manley predicted the likely geography of support for Brexit in the EU referendum. In this concluding piece they compare their predictions to the result. The general pattern of their predictions turned out to be very accurate, but regional differences were more pronounced than anticipated, with variations in both late electoral registrations and turnout introducing unexpected impacts on the geography of the outcome

Johnston, Ron

Jones, Kelvyn

Manley, David

LSE Research Online

7/2/2016Predicting the Brexit vote: getting the geography right(more or less)blogs.lse.ac.uk /politicsandpolicy/the-brexit-vote-getting-the-geography-more-or-less-right/In April 2016 in two contributions to this blog Ron Johnston, Kelvyn Jones and David Manley predictedthe likely geography of support for Brexit in the EU referendum. In this concluding piece they compare theirpredictions to the result. The general pattern of their predictions turned out to be very accurate, but regionaldifferences were more pronounced than anticipated, with variations in both late electoral registrations and turnoutintroducing unexpected impacts on the geography of the outcome.In an earlier contribution to this blog we challenged the claim that the pattern of voting in the EU Referendum wasunpredictable because there was no evidence that members of particular socio-economic and/or -demographicgroups were more likely to vote one way or another. Using a large body of polling data collected by YouGov (overthe whole of 2015 and first three months of 2016) we found clear evidence suggesting that young people and thosewith higher-level educational qualifications were much more likely to support Remain, whereas older voters andthose with few or no qualifications were much more likely to support Leave.Across 380 local authorities we used used this information to estimate the percentage of voters  who would supportBrexit (Northern Ireland and Gibraltar were excluded because we lacked enough data). Our map showed thegeography of support for a Brexit and caught the interest of a number of newspapers.In a later blog, we adjusted our predictions to take turnout into account, based on the observed patterns at the 2015general election. A revised map showed a slightly larger number of local authorities where majority support forLeave was likely to occur.How accurate were the predictions?Nothing in later polling data suggested any change to the underlying patterns: older people were more likely thantheir younger counterparts to vote Leave; well-qualified people were more likely than those with no or fewqualifications to vote Remain; and young voters, especially those with few qualifications, were least likely to turn outand vote – assuming that they were on the electoral roll at all. The only difference was that whereas the poll data weused showed a clear majority of support for Remain, by polling day the gap between the two sides was very small.But unless those who switched from Remain to Leave were overwhelmingly concentrated in particular age andqualification groups this should not have affected the overall pattern. The local authorities where we predictedgreatest support for Brexit should have been those which reported most votes for it on 23 June.And that was the case. The graph shows our predicted percentage vote for Brexit on the horizontal axis, adjusted forlikely turnout, and the actual vote on the vertical axis. The relationship is close – although in virtually all cases theBrexit vote is, unsurprisingly, larger than we predicted (in statistical terms, the correlation between the two sets ofvalues of 0.82 indicates that 67 per cent of the variation in the actual pattern can be accounted for by the variation inthe predicted pattern).1/6The Geography of BrexitAlthough we got the general pattern right, there were some places where – in relative terms – we substantiallyunder-estimated support for Brexit, and others where we over-estimated it. Where were those places, and why didthey deviate from the general pattern? To answer that question we adjusted our estimates so that the overalloutcome matched that of the referendum on 23 June and then explored the outliers; these were the places wherethe actual percentage voting Brexit was either larger or smaller than we had predicted it would be on the basis of theage structure and educational qualifications of the adult population in each local authority. The map shows thoseplaces where we under- or over-estimated the outcome by five or more percentage points.2/63/6Areas in blue are places where we under-estimated Brexit support. There were fifteen where the share for Leavewas ten or more points higher than we predicted; the largest of those differences was nearly 15 percentage points,for Amber Valley District Council in Derbyshire. With two exceptions on the south coast (Portsmouth andSouthampton) and two more on the Thames estuary (Medway and Thurrock) these fifteen places have one commoncharacteristic – all are in the East or West Midlands, Yorkshire and the Humber, or the Northeast. There are none inthe Northwest or Southwest of England – nor in London, Scotland or Wales. Indeed, of the 64 local authorities wheresupport for Brexit was five percentage points or more greater than we estimated there were only two in London(Hillingdon and Newham) and two in Wales (Neath Port Talbot and Wrexham) and none in Scotland. By comparison,twelve of the 64 were in the East Midlands (30 per cent of all local authorities in that region).Areas in yellow are places were we over-estimated Brexit. There were 76 of these – in one case (EastDunbartonshire) by as much as 24.4 points. Indeed, eighteen of those local authorities were in Scotland; all 32 ofScotland’s local authorities returned a majority for Remain, and in over half of them support for Leave wassubstantially less than we anticipated. London was also a region where support for Brexit was less than predicted(only five boroughs returned a majority for Leave); thirteen of the Boroughs had an actual vote for Brexit five or morepercentage points lower than we predicted, as did nineteen of the 67 local authorities in the Southeast region.These patterns suggest substantial regional variations within the UK in support for Brexit. But there were substantialwithin-region variations as well – not everywhere in Scotland and London was as supportive of remaining in the EU,for example. Nevertheless, across London’s 32 Boroughs on average support for Leave was 7.6 percentage pointsless than we predicted and in Scotland average support across the 32 local authorities was 12.3 points less; againstthat, in the East Midlands support for Brexit was on average 2.8 points greater than predicted across the region’s 40local authorities.Higher turnout, Higher Remain voteAs well as these regional variations, there were two other significant general patterns. On average, the higher theturnout the less the support for Leave (with the regional differences held constant); turnout percentages are shownin the next the map. With each percentage point increase in turnout support for Leave fell by 0.27 points. Across the380 local authorities turnout varied from 56.3 per cent in Glasgow City to 83.6 per cent in Chiltern – which translatesinto a difference of almost 7.5 percentage points in support for the Leave campaign between the places with thehighest and lowest turnout.Finally, there were also substantial differences between local authorities in the number of people who registered aselectors there after the last annual canvass in late 2015. Lewisham’s registered electorate increased by 18.6 percent between December 2015 and June 2016, for example, and there was an increase of more than 10 per cent ineight other local authorities; four of them were London boroughs and the others were Cambridge, Lincoln, Oxfordand Slough. The average local authority’s electorate increased by 4.7 per cent. There was a significant negativerelationship between expansion of the registered electorate and support for the Leave campaign (again, holding theregional differences constant); for every increase of one percentage point in the registered electorate the Brexit votefell on average by 0.48 percentage points.4/65/6These regional differences, plus those linked to turnout variations and growth in the registered electorate, poseimportant questions to be addressed as the referendum’s results go on to be analysed in more detail. Could higherturnout in those where it was relatively low, plus greater efforts to ensure that more of those entitled to register tovote did so, have delivered victory for the Remain campaign? (It is guesstimated that as many as 6-7 million voterswere not on the electoral roll and initial polls suggest that perhaps as many as two-thirds of the youngest age cohort– 18-24 – did not cast a vote.)Modelling the Brexit VoteA general pattern emerged on 23 June very much in line with our earlier modelling. There are substantial parts of thecountry where large numbers of people have lost out from the deindustrialisation and globalisation of the last fewdecades of neo-liberal economic policies, and where the educational system has not helped large proportions of theyoung to equip themselves for the new labour market. Increasing numbers in these disadvantaged groups were wonover during the last few decades by the campaigns in parts of the print media, taken up by UKIP since the 1990s,linking their situations to the impact of immigration – uncontrollable because of the EU freedom of movement oflabour principle. The wider Leave campaign built on that foundation in 2016, producing the geography displayedhere.In 1967 Peter Pulzer wrote that ‘Class is the basis of British party politics: all else is embellishment and detail’. Theresult on 23 June clearly suggests that is still the case – class, as expressed through educational achievements,delivered Brexit. The embellishment and detail – why so many young people did not either register to vote or, ofthose who did, then express their opinion, for example – remain to be explored, as do their implications for the futureof British party politics.About the AuthorsRon Johnston is Professor in the School of Geographical Sciences at the University of Bristol  Kelvyn Jones is Professor in the School of Geographical Sciences at the University of Bristol   David Manley is a senior lecturer in the School of Geographical Sciences at theUniversity of Bristol. 6/6

Predicting the Brexit vote: getting the geography right (more or less)

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