The importance of place

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1. The importance of place Explaining the characteristics underpinning the Brexit vote across different parts of the UK Stephen Clarke & Matt Whittaker July 2016…
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  • 1. The importance of place Explaining the characteristics underpinning the Brexit vote across different parts of the UK Stephen Clarke & Matt Whittaker July 2016 @mattwhittakerRF /@stephenlclarke/ @resfoundation 1
  • 2. In analysing the EU referendum vote, geography matters 2 • Post-referendum analysis has highlighted the importance of demographic, economic and cultural factors on individuals’ vote • In this note, we consider the importance of place; highlighting the extent to which those same factors matter across 378 of Britain’s 380 local authorities • We test the strength of the relationship between these different factors and the vote while holding all else constant (using a series of regression models) for England,Wales and Scotland • We highlight some of the more important economic factors in Section 1; demographics in Section 2; and cultural issues in Section 3 • We provide a full description of the regression results in Section 4
  • 3. 3 1 PLACE AND ECONOMICS Pay, employment and housing tenure
  • 4. No relationship between voting patterns and median hourly pay change since the early 2000s Earnings were subject to a pre- crisis slowdown across much of the distribution, followed by a six year squeeze that was relatively evenly felt Simple correlation finds no evidence to suggest depth of the pay squeeze affected the vote Source: ONS, NOMIS 4
  • 5. Though the strength of the leave vote does appear to vary with the pay level In the main, local authorities with higher levels of median pay recorded lower votes for leave Simple correlation implies relatively strong relationship Source: ONS, NOMIS 5
  • 6. But there are exceptions… with a clear division between higher and lower paying groups Can split lower paying areas into those with high leave votes and those with relatively low leave votes Can similarly split higher paying areas into those with low leave votes and those with relatively high leave votes Source: ONS, NOMIS 6
  • 7. Four groups of interest 7
  • 8. No obvious correlation with employment levels, and no clear differences across the four groups Higher paying, relatively high leave areas marginally more likely to have higher employment rates than higher paying, low leave areas, but the differences are slight Source: ONS, NOMIS 8
  • 9. But employment-vote relationship becomes much clearer when we control for student numbers Moving beyond the simple scatter chart, regression analysis shows that employment is important once the number of students in an area is controlled for Dots now show clusters of LAs Source: ONS, NOMIS 9
  • 10. Home ownership levels also appear to matter, with high owning areas more likely to vote leave Big distinction between ownership in the two higher paying groups: low leave areas record much lower levels of ownership than relatively high leave areas But this distinction is less marked between the two lower paying groups Source: ONS, NOMIS 10
  • 11. 11 2 PLACE AND DEMOGRAPHICS Age, student population and immigration
  • 12. As already touched on, the link with the number of current students runs in the opposite direction Students form a higher proportion of the population in low leave vote areas, marking a clear difference between some of the lower paying areas Higher paying, relatively high leave vote tend to have relatively few students Source: ONS, NOMIS 12
  • 13. As does the size of the migrant population – i.e. the higher the proportion of migrants in the local population the lower the leave vote Clear distinction between higher paying, low leave and higher paying, relatively high leave areas But distinction not obvious in relation to the two lower paying groups Source: ONS, NOMIS 13
  • 14. Yet on the face of it, there is no clear relationship between the change in migrant population and leave vote Source: ONS, NOMIS 14 Based on a simple correlation, the extent to which the migrant population has changed in an area since 2004 has little correlation with the leave vote Data limitations mean a number of local authorities are missing from this analysis
  • 15. But the change in the migrant population does have an effect once we take into account the size of the migrant population in an area Source: ONS, NOMIS 15 Regression analysis controls for the number of migrants already in an area The leave vote was higher in areas that started the period with relatively few migrants but which saw sizeable increases – includes Redditch, Maidstone, Gravesham and Lincoln
  • 16. 16 3 PLACE AND CULTURE Cohesion and education
  • 17. Higher leave vote in areas that report lower levels of ‘cohesion’ (where different backgrounds ‘get on’) Difference is most marked between the two lower paying groups: lower paying, high leave areas record lower cohesion than lower paying, relatively low leave areas Findings remain even after holding all other factors constant Source: DCLG, Hub Interchange 17
  • 18. Simple correlation highlights apparently very strong correlation with education levels Having a qualification equivalent to NVQ level 4 (i.e. degree level) or higher is key difference Separates both the two higher paying groups and the two lower paying groups Source: ONS, NOMIS 18
  • 19. Source: ONS, NOMIS 19 With education showing correlation with culture, demographics and economics – ‘cohesion’ Clear distinction between levels of ‘cohesion’ in areas with highest and lowest proportions with NVQ4+ Lower-skilled, less-cohesive, high-leave areas include Thurrock, Boston & Burnley
  • 20. Source: ONS, NOMIS 20 With education showing correlation with culture, demographics and economics – non UK-born population Similar strength of correlation between education and level of migrant population in the local authority Higher-skilled, higher-migrant, low-leave areas include Westminster, Hammersmith & Fulham and Camden
  • 21. Especially strong relationship between education and pay Lower-skilled, high-pay, higher- leave areas include Havering, Brentwood and Bromley Source: ONS, NOMIS 21 With education showing correlation with culture, demographics and economics – pay levels
  • 22. 22 4THE KEY DRIVERS Regression results
  • 23. Regression analysis isolates the impact of each variable when holding all others constant 23 • The simple correlations set out above depict those factors that are related to the strength of the leave vote in each local authority • These factors are shown to be important in a number of regression models.We isolate the explanatory value of each different factor, holding all other factors constant • Technically, we use a clustered standard errors approach • Due to data availability, most of our findings relate to England only, but we run separate models with fewer variables to identify the Scottish andWelsh ‘effects’
  • 24. Significant factors include economic, demographic and cultural factors (England) 24 Regression analysis controls for all other factors to highlight the explanatory value of each different factor in turn ‘Significant’ results are those with p values of 0.1 or lower Statistically significant variables (2015 unless stated) Non-significant variables (2015 unless stated) Employment rate Students Degrees 'Cohesion' (2008) Change in non-UK born (04-15) Home owner population (2011) Median hourly pay Change in median pay (02-15) Non-UK born Proportion of older to younger Change in manufacturing employment ('95-'15) Posititvely correlated (increases leave vote) Negatively correlated (reduces leave vote)
  • 25. Significant factors include economic, demographic and cultural factors (England) 25 • Results show, for example, that a 10ppt increase in the employment rate is associated with a 1.4ppt reduction in leave vote (all else constant) • Likewise, a 10ppt increase in the share of the population with NVQ4+ qualifications is associated with a 4.8ppt reduction in the leave vote • In contrast, a 10ppt increase in home ownership rates increases the leave vote by 4.1ppt Statistically significant variables (2015 unless stated) Ppt change in leave vote assoc. w/ 10ppt increase in variable Average across English LAs Employment rate -1.4 75.4% Students -5.0 5.4% Degrees -4.8 36% 'Cohesion' (2008) -4.1 77% Change in non-UK born (04-15) 3.1 4.2% Home owner population (2011) 4.1 66% Negatively correlated (reduces leave vote) Posititvely correlated (increases leave vote)
  • 26. 26 Relative to the SouthWest (which voted broadly in line with the UK average), regional ‘effects’ are visible Holding constant factors such as pay, education, migration and cohesion, local authorities in Scotland recorded leave votes that were 12ppts lower than in the South West In contrast, areas in theWest Midlands recorded leave votes that were 3.6ppts higher than in the SouthWest ppt change in leave vote associated with the region Statistically significantly different from South West vote Scotland -12.01*** North West -2.876*** Wales -2.771*** Yorkshire and the Humber 1.632*** East Midlands 1.727*** North East 2.077** West Midlands 3.624*** Not statistically significantly different from South West vote London 0.565 South East 0.694 East 0.202 *** p<0.01, ** p<0.05, * p<0.1
  • 27. 27 Full regression results England Including Wales Including Wales & Scotland Median hourly pay ex. overtime (logged) -2.068 -3.298 4.218 Change in median pay (2002-15) -0.00386 -0.00930 -0.0511** 16-64 employment rate (2015) -0.141* -0.288*** -0.174* Proportion of 50+ year-olds to 16-49 year olds (2015) 0.0154 -0.0182 0.0314 Students as proportion of population (2015) -0.502** -0.828*** -0.836*** Proportion of people with NVQ4 or higher (2015) -0.488*** -0.598*** -0.643*** Change in proportion of people in employment in manufacturing (1995-15) 0.0746 0.0623 -0.0223 Proportion of population who are migrants (2015) -0.0611 -0.0754 -0.241** Change in the proportion of population who are migrants (2004-15) 0.312** 0.409*** 0.635*** Proportion of population who own home (2011) 0.342*** 0.301*** Proportion of population who believe people from different backgrounds get on well in local area (2008) -0.414*** Relative to South West East 0.672 0.533 0.202 East Midlands 1.657*** 0.947** 1.727*** London -0.00474 1.207 0.565 North East 2.507*** 2.866*** 2.077** North West -3.487*** -2.646*** -2.876*** South East 0.159 0.724 0.694 West Midlands 2.944*** 3.494*** 3.624*** Yorkshire and the Humber -0.0389 1.586*** 1.632*** Wales -3.682*** -2.771*** Scotland -12.01*** Constant 98.06*** 91.13*** 82.99*** Observations 235 251 271 R-squared 0.869 0.837 0.837 All models run with standard errors clustered by region *** p<0.01, ** p<0.05, * p<0.1
  • 28. 28 5 CONCLUSION
  • 29. Economics clearly matter, but by no means the only consideration 29 • Evidence that the geographical distribution of living standards influenced the referendum vote, with employment having a significant effect • But recent changes in pay appear not to have had a significant effect, implying that living standard issues are long-established • Demographics also matter, with areas with lots of students being more likely to vote remain • Cultural and geographical factors play a key role, represented by the importance of feelings of cohesion within the local area, and by the tendency for different regions to vote differently even after controlling for all other factors • The level of migration doesn’t seem to matter but the pace of change over the past decade or so does • The strength of the correlation with higher qualification levels in an area is particularly telling, with this variable closely associated with both economic and wider cultural factors
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