Daniel Devine

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Did Brexit increase hate crimes? The answer is still yes.

So, hate crimes are in the news again after the Home Office’s release of the new data on October 17th. Thus began an avalanche of news stories about the alleged increase and its relationship with Brexit: Business Insider, the BBC, Al Jazeera, The Independent. And, along with it, all the debate that proceeded last year’s release as well. This primarily revolved around two controversies: whether it actually did happen; and, if it did, whether this represented an increase in reporting or actual crimes. I wrote on this exactly a year to the day, and argued that Brexit almost certainly increased hate crimes. It was obvious descriptively, but a couple of rough statistical tests showed it to be beyond any reasonable doubt. I did this on daily and monthly data. Brexit had a huge impact on the number of hate crimes.

The new release gives us another shot at the same question, with a few more months — up until August 2017, a full year after the referendum. So, here’s how it looks descriptively.

Once again, it is obvious that hate crimes increased after Brexit. However, as I suspected a year ago, this was a flash in the pan and didn’t sustain — it dropped to around the average of the last few years. However, it increased again, spiking around (and presumably including) the attack on Finsbury Park mosque, to highs that exceeded even the post-Brexit spike.

It is redundant, in light of the graph and the results of the last blog I wrote on this, to run more tests, but I repeated the same ones I did last year. They once again show that Brexit increased hate crimes. Actually, with the additional months, it is responsible for an increase of 1454 crimes rather than the 1603 using last year’s data. However, the plot following a regression discontinuity test is much more stark. Basic conclusion: Brexit increased hate crimes, probably less than I suggested last year, but with much more certainty.

Whether this represents a ‘real’ increase — as in, actual crimes — rather than just reporting is impossible to tell from this data. Perhaps convictions would be a better indication, but I have a hunch that some would find a way to discredit even those.

Stella Creasy, a Labour MP, said of the new stats: “While some of this rise may be attributable to improved reporting methods, there can be no doubt the Brexit vote has had an impact.” That, to me, is the fairest and only conclusion possible.

What should be more concerning is the steady increase over the years. The high of 2013 was the same as the low of 2017, and not much higher than the low of 2016.

I ended the last blog by saying “the referendum has shown that it does not necessarily take much to spark an increase in hate crimes. Other catalysts are possible. And it’s important that, when the next one comes, it is much harder to translate these beliefs into actions.” Unfortunately, media and governmental rhetoric didn’t ease off; polarisation didn’t reduce. The terror attacks of Manchester and Finsbury Park were those catalysts again.

Critical Review of Guy Verhofstadt’s ‘Europe’s Last Chance’: the Issue of Identity and Democracy

Guy Verhofstadt’s book occupies a unique genre. On the one hand, it is unapologetically, aggressively pro-Federal Europe. On the other, it provides a critique of the current incarnation of the European Union that would make even Nigel Farage blush. Of course, the difference lies in their answer to the problems of European integration: for Verhofstadt, it is federal Europe; for Farage, and other Eurosceptics and nationalists, it is a return to national democracy of old.

Verhofstadt embeds his argument in a highly rationalist framework. He argues that Europe must unite to compete on the global stage (Chapters 4–5), to deal more effectively with situations like the immigration crisis, rule of law crisis in Hungary, or economic crises (Chapters 8–9, 16–18); and addresses particular areas in which a federal Europe could perform better (Chapters 10–15). He then finishes with a ‘rebirth’ section with chapter headings that would make Brexiters shudder: ‘A government for the Euro’, ‘A European Army’, and ‘The United States of Europe’.

It is not this rational approach from Verhofstadt I will take issue with here, but rather two points which underpin much of his argument but are not addressed as fully as the economic or political arguments. The first is about identity. The second is about democracy. For the first I claim that he is a hypocrite and naïve; the second I claim that he is simply a hypocrite.

Identity

Verhofstadt devotes a chapter to ‘The Chronic Condition of Nationalism’, but moves easily between using ‘nationalism’ and ‘identity’. To him, ‘the delusional spirit of nationalism still haunts the continent’. He completely rejects identity. He argues that ‘a person is a unique personality […] there is no such thing as a clear identity’. Identity is ‘a narrow-mindedness that ignores that each persona has a whole range of identities and characteristics’.

This is an odd position to take for someone who has used the Twitter hashtag #IAmEuropean. Throughout the book, he makes claims that depend on his own European identity. He argues that Europe ‘stands in the middle of a clash of civilisations’. He argues that ‘we must concentrate once again on that which binds us, on the challenges we face jointly’. He even says ‘we Europeans’. In his critique of identity, he says that identity is used to decide on ‘who does and does not belong to a community’; later, he says ‘Russia is part of Europe. A European continent, and certainly a European civilisation, is unimaginable without Russia’. If that is not deciding on who does belong to a community, what is?

The point here is not to defend identity politics (and I wouldn’t want to). But rather point out that, in many ways, the defence of a federal Europe hinges on his own European identity. You can replace any of the defences he makes of Europe with ‘English’ or ‘England’ — or any other nation state in Europe — and it would not sound odd. He is quite correct that identity decides which belongs to a community. But rather than rejecting identity, he instead adopts a European identity, pitting Europe against the rest of the world (‘clash of civilisations’, also Chapters 4–5), and arguing for a shared, European identity against the ‘inward-looking’ national identities.

But there is another issue. Let’s assume identity matters, as it clearly does to Verhofstadt. And let’s assume identity matters for further integration: after all, he cites Eurobarometer data in support of his argument at the end of his book (p.271). Then comes the question on what this identity looks like across Europe. It’s possible to look at this using the same data the book uses.

The graph below shows that very few people feel European only, or European before their nationality. It is up to debate about whether nationality first and European second is a positive category for his argument. But about a third of all those polled across Europe see themselves as their nationality only — about 55% are both, with their nationality first. It is a classic question of whether European integration can continue without a ‘European demos’, and it is one that the book does not address.

Source: own calculations, data: EB86.2

 

Given the focus on European identity throughout the book, it is impossible to completely ignore identity politics. However, looking at identity more broadly is troubling for Verhofstadt’s overall goal of European federalism. Most people do not feel European. Most people still have deep-rooted, palpable attachments to their nationality. To ignore these is naïve. To ignore them and indulge a European identity is hypocritical.

Democracy

This leads to the second point. Throughout, the book refers to the European values of democracy, rule of law, and so on, that are embedded more formally in Article 2 of the Treaty of the European Union. He is clearly a democrat. However, he also says that European politicians must ‘fly in the face of public opinion where necessary’ in order to move European integration forward (p.101). This would not be a problem if the public wanted further European integration, of course. And we can answer that question too.

The graph below shows whether people believe the EU has gone too far (0) or not far enough (10) in its integration. Ultimately, most people are largely ambivalent. But we can also see that very few people want the EU to go further — fewer than think it has gone far enough.

Source: own calculations, data: ESS2014

And there is a huge amount of variation across Europe. There is always some bunching around the middle, except in some very Eurosceptic countries (Austria and the UK). No country, with the possible exception of the Netherlands and to a lesser extent Poland, is wildly keen on more integration (Germany perhaps, but that seems polarised).

Source: own calculations, data: ESS2014

 

Verhofstadt’s focus on democracy then seems misplaced. After all — he is advocating a solution no one wants. And he is doing that because of the rationalist perspective the book takes. It might be the case a United Europe would be more efficient, more powerful on the world stage. But you cannot root that argument in democracy.

Conclusion

Verhoftstadt’s Europe’s Last Chance is worth reading. It is both a critique of modern-day Europe and a rare, provocative argument for a Federal Europe. The rationalist argument is good and solid. Where the book falls is on the more intractable problems like identity and democracy. At the same time as appealing to a united European identity around shared values of democracy, it rubbishes any claim to national identity and advocates going against public opinion. These two positions cannot be held simultaneously — at least, not without problems. If the ideal of a Federal Europe is to be achieved, Verhofstadt would need to address both of these issues.

Best supported clubs by population

A while ago, I posted a short thread on Twitter looking at English football club attendances, given the population of the city they’re located in. Of course, this was entirely motivated by my desire to see either my poorly-supported club in a small town (Colchester), or my well-supported club in a relatively large city (Portsmouth), do well. Unfortunately, neither of these things happened. On the plus side, it was pretty good practice with visualising data in R, and it bizarrely got covered by the Yeovil local paper, Somerset Live.

To do so, I firstly included all clubs (including London clubs), and simply looked at their populations and average attendances in the 15/16 season. This lead to some weird numbers, given that the London ward West Ham is in (well, was, before moving stadium this season) is just around 1500 people. It seemed too much work to account for this, so I just left them out. But for posterity, here it is (the outlier to the left is Arsenal):

With London

Excluding London made more sense. Clearly, the most supported clubs are those in the Premiership and Championship, mostly in large cities (the Manchesters and Birmingham clubs). Despite being renowned for their support, Leeds actually do worse than you’d expect considering that the city is so large. But this is just accounting for home fans – and clearly Leeds’ support around the country boost their away following.

Without London

However, making attendance as a percentage of the population makes the picture look a lot different. Here it is ordered by league. By far and away the biggest supported club is West Brom, followed by Burnley. These, of course, are perhaps misleading: West Brom and Burnley draw their support from more than their core cities. However, it’s still an interesting way to think about club attendances, given that large city clubs are always going to have a structural advantage. This also makes sense for smaller clubs in smaller towns, like Fleetwood and Yeovil who are unlikely to draw support from much further afield.

By League

It’s also a good indication of those clubs who really should be doing better than they are, given their population. Nonetheless, hats off to the fans of Yeovil and Fleetwood – the best supported clubs in Leagues 1 and 2 (technically).

(Portsmouth are the second in League 2, and let’s not talk about Colchester).

Did Brexit increase hate crimes? Probably, yes.*

Tl;DR: Brexit probably caused an increase in hate crimes. I provide descriptive and statistical (linear regression and regression discontinuity) evidence for this claim, but the claim that there was a rise in reporting rather than hate crimes per sé is also plausible. It’s also positive to see that this is not a lasting effect (at least in the data).

In the wake of Brexit – when the UK voted to leave the European Union – there was a flurry of activity in newspapers and across the internet reporting a rise in racial tensions and hate crimes. In the following weeks and months, this was widely reported in the Guardian (a lot), the BBC, Human Rights Watch, Sky NewsThe Telegraph, and I’m sure some others that I’ve missed. Nevertheless, some individuals and outlets (such as Spiked and ConservativeHome) remain extremely sceptical of the claim that the vote to leave the EU was behind a rise in hate crime – and indeed, call into question the validity of the numbers at all.

As many outlets have picked up in the last week, the government have recently released the full figures of hate crime that cover the referendum and post-referendum months and days. This allows us a much closer look at what exactly was going on around that time (and gives me a chance to try out some new ideas at visualising data). Here, I take a look at these numbers, put them through some rough-and-ready statistical tests, and look at some other explanations of the findings. In general, though, the evidence is overwhelming that Brexit did cause a rise in hate crime. Nevertheless, it is encouraging that (at least according to the data) this does not seem to be a ‘lasting effect’, as The Independent reports.

What is hate crime?

Many of the biggest critiques of the data concern what is meant by ‘hate crime’. Hate crimes in general are defined as  ‘any criminal offence which is perceived, by the victim or any other person, to be motivated by hostility or prejudice towards someone based on a personal characteristic’. However, the data I use here is focused specifically on racially or religiously aggravated offences (from now, I will just call these hate crimes). This includes crimes such as: assault with or without injury, criminal damage, public fear or distress, and harassment. This also includes graffiti of a racist nature (presumably under the latter two categories), and attacks on asylum seekers or refugees (regardless of their race).

This does mean that essentially, anyone can report something as a hate crime if they perceive it as such. In addition, it’s true that a majority of these cases go unsolved – about a quarter of offences are taken to court. I don’t want to get into the territory of disagreeing with the very definition of hate crimes (or how they’re reported) – but it’s worth being open about what is behind the analysis.

An increase in hate crime is descriptively clear

At first glance, it is clear that there was a rise in hate crime surrounding the Brexit referendum. The first graph below shows hate crimes by month since 2013. Although there is always a seasonal effect – hate crimes increase over summer – the sharp rise in June and July 2016 is startling, and the drop off in August is not particularly drastic (or at least as drastic as we would hope). From this longer-term perspective, the summer months of 2016 are outliers in the recent history of hate crime.

monthly-crime

It’s also possible, with the Home Office data, to go more fine-grained. The graph below presents daily data for the months of May, June, July and August. Once again, the dashed horizontal line indicates when the referendum took place. The interesting part of this is the sudden increase the day after the referendum, which persists for several days, peaking approximately a week after (more on this later).  There is, as in the monthly data, a slow decline to pre-referendum levels.

daily-crime

From both of these graphs, it is clear that there was a peak in hate crime surrounding the referendum. But there is also a lot of variability, and some claim that this is not necessarily down to the referendum. In lieu of suitable data to test the competing claims, I wanted to look at this statistically as best I could.

And the differences are statistically significant

To do this, I took two approaches. I make no claim that these are conclusive. They are relatively back-of-the-envelope tests, but I think they are nonetheless strong evidence for the impact of Brexit on hate crimes. Firstly, I ran a basic regression on both the daily and monthly data. This uses the referendum to ‘predict’ the variation in hate crimes after the referendum (for those interested, there are more details at the end). The results of this are in the table at the end of this post. What the results indicate, however, is that Brexit increased hate crimes by about 31 a day (if we use the daily data), or by 1600 a month (if we use the monthly data). Due to the few months following the referendum, I would say the daily data is more accurate. Importantly, the results indicate that Brexit explains about 35% of the crimes in the days following Brexit.

But regressions are flawed for a range of reasons, especially when done like this. As is clear from above, there is a decreasing effect of Brexit (hate crimes tend towards the pre-Brexit level). In other words, June and July are huge outliers. So, as another check I carried out a regression discontinuity test. This narrows the focus to the days surrounding the referendum, and essentially treats the referendum as an experiment: the day of the referendum and afterwards are those ‘treated’ with the experiment, whilst those before are the control group. In other words, there should be no real difference between June 21st and June 24th other than the referendum.

The results are the same. It is statistically significant. Moreover, in the ‘RD Plot’ at the end of the post, you can see how this relationship changes dramatically. Put another way: the days either side of the referendum are fundamentally different, and the only plausible explanation is the referendum. Indeed, this is what the regression discontinuity provides extremely strong evidence for.

But was there really an increase in hate crime?

The evidence in the data is extremely strong. However, there can be a few objections which are more theoretical. The first, and most important, is that the difference might be due to an increased awareness and therefore increased reporting (this is what the police claimed at the time). In other words, hate crimes did not increase, but the reporting of them did. This is certainly plausible.

On the one hand, in the days following the referendum, I find this hard to believe. Why would people be more likely to report hate crimes following a referendum? This did not happen after the Charlie Hebdo attacks, or Paris attacks, or other elections, or the Palestine-Israel conflict. It only increased slightly after the Lee Rigby murder. The reverse is much more plausible: that hate crimes (remember, this includes damage to property and graffiti) ensued after the referendum. However, the peak of hate crimes occurred a week after the referendum. This is surely likely to be influenced by media coverage of the previous rises. Again, I think it is likely that there was indeed increased reporting of hate crimes, in response to national media coverage and the existence of more hate crime in general. In other words, I think it was a bit of both, with more hate crimes leading to coverage and more reporting (we must also remember that hate crimes are still hugely under-reported).

Other claims I find less appealing. One might just say it is a coincidence. The statistical weight of evidence is, for me, far too strong for that. It is far less than a 1% chance that this was just a random increase which happened to occur at the exact time of the referendum. Other claims might argue about the definition of hate crime, how they are accounted for, and how few are brought to court. These are not the focus of this post – not because they’re not important, but because they can’t be drawn from the evidence here.

Brexit, hate crime and the future

A lot of coverage has argued that the atmosphere in the UK is increasingly toxic and intolerant. The data released only extends a few months after the referendum, so we cannot be sure of what’s actually happening. But from the existing data, I would conclude that the actual impact of Brexit on hate crimes was a short-lived one, and that the effect will decrease over time.

However, I would also suggest, on a more negative note, that all Brexit did was mobilise latent attitudes into behaviour. In other words, I do not think it changed attitudes that much, but acted as a catalyst to change those attitudes into actual actions – and hate crimes. For what it’s worth, going forward, the media and politicians need to be extremely careful not to stoke the flames of these attitudes. The referendum has shown that it does not necessarily take much to spark an increase in hate crimes. Other catalysts are possible. And it’s important that, when the next one comes, it is much harder to translate these beliefs into actions.

*Probably = almost certainly

Statistical/methodological notes:

Graphics and tests were produced in the software package R, using data from the Home Office. The background design for the graphs was taken from code by Max Woolf.

Summary statistics for the two data sets used (monthly and daily data):

The regressions were run using the variable ‘brexit’ as a binary predictor for the dependent variable ‘hate.crime’. Clearly for the monthly data, this is hugely unbalanced, so should be treated with a bucket load of caution. The daily data is more stable. A better analysis would have used time series and lagged values.

hate-crime-regs

The regression discontinuity used the day after the referendum as the cut off. This is because the referendum really would not have had an effect until the result. Nevertheless, it is centred around 0, the day of the referendum. It would be good to do display this in the main text, but I couldn’t figure out a nice way to do it. The exception is this, but my R is too rusty for that.

rdplot

The R code used is as follows. You will need the theme function downloadable from here. If you’d like the data, please contact me.

setwd(“”) # set your working directory

hate <- read.csv(“day.hate.csv”) # read in the data
hate2 <- read.csv(“month.crimes.total.csv”)

install.packages(“rdrobust”) #install packages
library(“rdrobust”)
install.packages(“ggplot2”, dependencies = TRUE)
library(“ggplot2”)
library(“stargazer”)
library(“lubridate”)
library(“tseries”)
library(“scales”)
library(“grid”)
library(“RColorBrewer”)
install.packages(“extrafont”)
library(“extrafont”)
loadfonts()
pdf(“plot_garamond.pdf”, family=”Garamond”, width=4, height=4.5)

rdrobust(hate$hate.crime, hate$since.ref, c = 1 ) # regression discontinuity
rdd_est <- rdrobust(hate$hate.crime, hate$since.ref, c = 1 )
rdplot(hate$hate.crime, hate$since.ref, c = 1)

stargazer(hate, type=”html”,
title = “Summary Statistics for Daily Data”)
stargazer(hate2, type=”html”,
title = “Summary Statistics for Monthly Data”) # summary statistics, output in HTML

linear.day <- lm(hate$hate.crime ~ hate$brexit) # regular regression on day
linear.month <- lm(hate2$hate.crime ~ hate2$brexit) #… and months
stargazer(linear.day, linear.month, type=”html”,
title = “The Effect of Brexit on Hate Crimes”,
column.labels = c(“Daily Crime”, “Monthly Crime”),
coviariate.labels=”Brexit”) # table of the regression

month.crime.plot <- ggplot(data=hate2, aes(x=id, y=hate.crime)) +
fte_theme() +
geom_line(color=”#c0392b”, size=1.45, alpha=0.75) +
geom_vline(xintercept=42, linetype = “longdash”, color = “gray47″, alpha = 0.7) +
geom_text(aes(x=42, label=”Referendum”, y=2300), colour=”gray36″, size=8, family=”Garamond”)+
ggtitle(“Hate Crimes in England and Wales, 2013-2016”) +
scale_x_continuous(breaks=c(6,12,18,24,30,36,42),
labels=c(“June 2013”, “Dec 2013”, “June 2014”, “Dec 2014”, “June 2015”, “Dec 2015”, “June 2016”)) +
labs(y= “# Hate Crimes”, x=”Date”) +
theme(plot.title = element_text(family=”Garamond”, face=”bold”, hjust=0, size = 25, margin=margin(0,0,20,0))) +
theme(axis.title.x = element_text(family=”Garamond”, face=”bold”, size = 20, margin=margin(20,0,0,0))) +
theme(axis.title.y = element_text(family=”Garamond”, face=”bold”, size = 20, margin=margin(0,20,0,0))) +
geom_hline(yintercept=2000, size=0.4, color=”black”) # monthly graph
day.crime.plot <- ggplot(data=hate, aes(x=id, y=hate.crime)) +
fte_theme() +
geom_line(color=”#c0392b”, size=1.45, alpha=0.75) +
geom_vline(xintercept=54, linetype = “longdash”, color = “gray47″, alpha = 0.7) +
geom_text(aes(x=54, label=”Referendum”, y=85), colour=”gray36″, size=8, family=”Garamond”) +
ggtitle(“Hate Crimes in England and Wales, May-August 2016”) +
scale_y_continuous(limits=c(75,220)) +
scale_x_continuous(breaks=seq(14,123, by=14),
labels=c(“14 May”, “28 May”, “11 June”, “25 June”, “9 July”, “23 July”, “6 August”, “20 August”)) +
labs(y= “# Hate Crimes”, x=”Date”) +
theme(plot.title = element_text(family=”Garamond”, face=”bold”, hjust=0, size = 25, margin=margin(0,0,20,0))) +
theme(axis.title.x = element_text(family=”Garamond”, face=”bold”, size = 20, margin=margin(20,0,0,0))) +
theme(axis.title.y = element_text(family=”Garamond”, face=”bold”, size = 20, margin=margin(0,20,0,0))) +
geom_hline(yintercept=75, size=0.4, color=”black”) # daily graph

 

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