Explaining Labour's Red Wall loss
The loss of Labour’s Red Wall has gathered much media attention following the 2019 election result. At a first glance, it would appear that these seats abandoned Labour primarily because of the 2016 referendum result. However, there are other trends that should be noted when aiming to fully understand why this once Labour heartland turned blue. This blog defines Labour’s Red wall as the 40 former safe seats Labour lost, out of all the 54 seats, lost to the Tories in 2019. These 40 seats have a long history of voting Labour and only a decade ago could not be described “safeish” Labour constituencies. This article highlights wider socio-economic trends these seats share, alongside also displaying how Labour has experienced a long-term problem within these constituencies. Therefore, this blog post argues that whilst the EU referendum allowed these seats to quickly turn blue post-2016 this phenomenon would not have been possible without the longer-term trends that preceded it.
Swing (Butler’s measurement):
Firstly, looking at table 1 it can be said that swing from Labour to Conservative in these seats was quite intense. Indeed, some constituencies displayed well above double figures and in some of these cases such alterations in the parties’ vote shares occurred in well-known long-standing Labour heartlands. Such seats included Blyth Valley, Bolsover, Dudley, Rother Valley and Sedgefield, Blair’s former constituency. Importantly, this swing occurred through both a sharp decline in the Labour vote and a significant increase in the Conservative vote share. This would indicate that in these areas there was a heavy direct transfer of votes between the Conservative and Labour Party. Crucially, this indicates quite substantial political changes have occurred within these constituencies. Understanding the decline in Labour’s vote, along with the rise of the Conservative vote, is therefore key in comprehending the deeper reasons to why these areas changed.
Understanding the causes of this swing:
Table 2: A logistic regression model estimating the effects of variables on the probability of Conservative and Labour winning a seat within England & Wales in the 2019 election.
It shows that Brexit and socio demographic factors shaped how likely a main party was to win MPs in 2019.
The Brexit Issue:
The most obvious difference, and most common explanation, to the swing experienced in these seats is the result of the 2016 referendum, and in particular these areas heavy propensity to have voted Leave. These areas not only voted to Leave the EU, but did so emphatically, with on average over 60% of the electorate wanting out. Significantly, this was 10% over the national average. This is vitally important as table 2 shows the more a constituency voted to Leave the EU the greater the increase in the Conservative vote share was, and from this the party had a much improved chance of winning a constituency off Labour. Moreover, the greater the extent an area voted to Leave the larger the chance was Labour would experience a decrease in their vote share. Moreover, as we shall see later, Labour’s lead in these constituencies rapidly declined post-Brexit, again signalling how Brexit was at least a catalyst for the fall of its Red Wall.
The need to acknowledge socio-demographic trends:
It is also useful to note that these areas shared similar population traits.
These areas tended to have a larger share of its population within older cohorts. Alongside this, these areas also had fewer voters who were within the youngest demographics. Crucially, table 2 shows these trends to be statistically significant.
As these areas have ageing populations they are most likely to have various challenges that come with this. For example, these areas might experience a tougher burden on a nationally strained NHS, which from this might bring rising concerns around factors that may pressurise these services, such as migration. Moreover, if residents within these constituencies felt that Brexit would divert more money to the NHS it is possible that such areas would have changed their vote so Brexit would be implemented and politicians could then start to better address the growing NHS issues.
Further, these constituencies have fewer individuals having obtained higher level qualifications. Moreover, a greater proportion of the electorate reported as having no qualifications. Further to this, the proportion of children at local schools who received free school meals (FSM) was a lot higher than the 2019 average. Moreover, these pupils are currently less likely to go onto obtain higher level qualifications, such as A-level qualifications, and a result these areas tend to record a poorer social mobility scores, indicating Labour lost in areas that are on the wrong side of education inequality.
Workforce and economic profile:
Additionally, these constituencies on average were more deprived than the English national average. Furthermore, many of these areas had recorded higher levels of deindustrialisation, with less of the workforce working in manufacturing sectors than was the case in past successive decades, at least according to the census’ conducted from 1980-2010. These areas also experienced higher than average levels of unemployment, again indicating they have suffered from de-industrialisation trends.
The decline of such sectors has led to these economies being more reliant on lower management, lower-skilled and routine jobs. Subsequently, these areas have also been accustomed to lower than average wage levels, along with lower property price and ownership levels. Subsequently, these areas recorded fewer people being paid the living wage, thus leading to higher levels of deprivation and child poverty. Therefore, as the model outlined in table 2 shows all these trends to be significant Labour can be said to have lost red wall seats partly because they were economically more insecure and deprived. Further, this indicates that Labour’s losses occurred in areas that have lost out in the development of globalisation and have found themselves left-behind.
Some on the left have argued that turnout could potentially explain Labour’s losses. However table 1 shows that this argument can realistically only be made for 7 out of 40 the Red Wall seats Labour lost. This is because in the other 33 seats Labour lost the percentage majority the Conservative Party has is higher than the decrease in turnout these seats experienced, with a fair few seats having majorities significantly higher than the turnout decrease they experienced. Further to this, the average turnout decrease these areas experienced were on marginally larger than compared to the national average, 0.3% of the electorate to be exact. Moreover, the regression analysis presented in table 2 earlier showed this decline in turnout not to be significant enough to explain the election outcome. As a result, it is more likely the political and socio-economic factors discussed earlier explain Labour’s Red Wall losses far more than electoral turnout does.
The differences between Labour’s retained seats and their Red Wall losses:
One story that was missed behind the crumbling of Labour’s Red Wall was Labour had kept 14 of the seats they gained in the 2017 election. Initially, when thinking about the scale of Labour’s losses it could have been assumed most of this came from seats they marginally won in the 2017 election. However, Labour went onto to keep many of these seats, despite their nationally poor performance and the fact some of these seats were former Conservative strongholds.
Interestingly, these areas were not Leave areas, and were in stark contrast to the leave vote witnessed in Labour’s Red Wall. The gained 2017 constituencies Labour kept were mostly Remain areas, much more so than the national average. Consequently, the difference in the referendum vote was quite large gap between Labour’s new seats and their former Red Wall seats, around 18%. Moreover, these seats experienced a much weaker decline in the Labour vote share, with the Tories losing more votes, thus creating a slight swing to Labour, the polar opposite to Labour’s Red Wall.
Significantly, these constituencies displayed quite different profiles. The areas Labour hung onto comprised of greater amounts of younger voters and fewer retired individuals. They also had more highly qualified voters who worked in higher paid and professional occupations. As a result, these areas displayed lower levels of deprivation, people working in jobs paying less than the living wage, attainment inequality and long-term unemployment. Therefore, whilst Labour lost the areas left-behind behind by globalisation they arguably have secured a different and newer base amongst constituencies that have befitted more from globalisation trends.
A longer-Term perspective:
The changes described above have not just been created by Brexit as these trends were developing pre-2016. Labour’s once safe majorities have been declining since the 1997, with their lead having declined quite substantially before the 2016 referendum in the 2010 and 2015 elections. This trend accelerated again after the 2016 referendum, but these seats may have not changed without the gradual decline of Labour’s lead in previous successive elections. Moreover, Labour has closed the gap on the Tories in the seats they won in 2017, and later kept in 2019, particularly in areas like Brighton and Canterbury. Significantly, this indicated the parties’ bases have been changing because of wider socio-economic reasons and that Brexit was a catalyst for the change rather than the root cause of it.
Causes of long-term changes:
Table 7 shows that the longer-term trends discussed have not solely been caused by Brexit. Undoubtedly, Brexit was a big factor in shifting new constituencies to both Conservative and Labour, but this new divide was shaped by socio-economic forces as well. Younger individuals helped Labour gain their new 14 constituencies, whilst older voters helped shift support over the Conservatives. As Labour’s Red Wall comprised of many older voters this likely helped the Tories gain 40 new seats. Further, areas that had a high number of voters without qualifications this also helped the Conservatives gain these new seats, at least according the model outlined in table 7. Finally, the fact Red Wall seats comprised of more low-paid routine workers also assisted the Tories’ gains, whilst areas with more professional workers helped Labour secure new bases of support. Therefore, contrasting demographics have helped create long-term trends that have allowed the parties to gain new bases, and in particular the Red Wall areas gained from demographics who most favoured Brexit and were most exposed to the negative effects of modern global economic developments.
How easy are these seats to win back?
Overall, most of these seats will not be easy for Labour to regain. These long-term socio-economic trends will need to be reversed, and in some cases by quite some margin. Whilst some of Labour’s Red Wall have small Conservative majorities there are a few seats that have awarded the Tories hefty majorities. Indeed, 17 out of the 40 seats now have Tory majorities of more than 10% of the electorate. Additionally, the 6 seats Labour lost in 2017 also shows a large growth in the Conservative Party’s majority, showing if Labour does not reverse these trends soon things could become worse for them in these seats. Therefore, Labour may need two successive good election performances to win these seats back.
To request the data tables you can email the author James Prentice, James.Prentice@live.co.uk
Appendix: Omitted table.