We have so many aspirations for big data and evidence based policy, but apparently a fatally limited capacity to see the obvious: voters were furious about immigration and the EU. Techniques exist to build better empirical evidence regarding issues that matter to citizens; we should use them or risk a repeat of the referendum.   

Commentators from all over the spectrum believe that the leave vote represents not (only) a desire to leave the EU, but also the release of a tidal wave of pent up anger. That anger is often presumed to be partly explained by stagnating living standards for large parts of the population. As the first audience question on the BBC’s Question Time program asked the panel “Project Fear has failed, the peasants have revolted, after decades of ignoring the working class how does it feel to be punch in the nose?”. The Daily Mail’s victorious front page said the “Quiet people of Britain rose up against an arrogant, out-of-touch, political class”. The message is not subtle.

Amazingly, until the vote, no one seemed to have known anything: markets and betting odds all suggested remain would win. Politicians, even those on the side of Leave, thought Brexit was unlikely. The man bankrolling the Brexit campaign lost a fortune betting that it wouldn’t actually happen (the only good news I’ve seen in days). Niall Ferguson was allegedly paid $500,000 to predict that the UK would remain.

This state of ignorance contrasts radically with what we do know about the country. We know, in finicky detail, the income of every person and company. We measure changes in price levels, productivity, house prices, interest rates, and employment. Detailed demographic and health data are available – we have a good idea of what people eat, how long they sleep for, where they shop, we even have detailed evidence about people’s sex lives.

Yet, there seems to be have been very little awareness of (or weight attached to) what the UK population itself was openly saying in large numbers.

Part of the reason must be that the government didn’t want to hear. Post crisis everything was refracted through the prism of TINA – There Is No Alternative. There was no money for anything, so why even think about it? Well, now we have an alternative.

The traditional method for registering frustration is obviously to vote – a channel which was jammed in the last election. Millions of people voted UKIP, or for the Green Party, and got one MP a piece: no influence for either point of view.  A more proportional voting system is one well known idea, and I think an excellent one, but there are lots of other possibilities too.

What if there was a more structured way to report on citizen’s frustrations on a rolling basis? An Office of Budgetary Responsibility, but for national sentiment – preparing both statistical and qualitative reports that act as a radar for public anger. It would have to go beyond the existing ‘issue tracking’ polling to provide something more comprehensive and persuasive. Perhaps the data could be publicly announced with the same fanfare as quarterly GDP.

Consultative processes at the local level are much more advanced than at the national level. Here is some of the current thinking on the best ways to build a national ‘anger radar’, drawing on methods widely used at the local level.

Any such process faces the problem of  ‘strategic behaviour’. If someone asks you your opinion on immigration, you might be tempted to pretend you are absolute furious about it, even if you are are only mildly piqued by the topic. Giving extreme answers might seem like the best way to advocate for the change you want to see. Such extreme responses could mask authentically important signals. Asking respondents to rank responses in order or assign monetary values to outcomes are classic ways to help mitigate strategic behaviour.

Strategic behaviour can also be avoided by looking at actions that are hard to fake. Economists refer to these as ‘revealed’ preferences – often revealed by the act of spending money on buying something. It’s awful to think about, but house prices might encode public opinions on immigration. If house prices are lower in areas of high immigration, it might reveal to us the extent to which citizen truly find it to be an issue. Any such analysis would have to use well established techniques for removing confounding factors, for example accounting for the fact the immigration might disproportionately be to areas with lower house prices anyway. This approach might not be relevant for the issues in EU referendum, but might be important for other national policies. Do people pay more for a house which falls in the catchment of an academy school, for example. (More technical detail on all these approaches).

Social media is another source of data. Is the public discourse, as measured on Twitter or Facebook (if they allowed access to the data) increasingly mentioning immigration? What is the sentiment expressed in those discussions? Certainly a crude measure, but perhaps part of a wider analysis – and ultimately no cruder than the methods used to estimate inflation.

All these approaches are valuable because they tell us about ‘raw’ sentiment – what people believe before they are given a space to reflectively consider. ‘Raw’ views are important since they are the ones that determine how people will act, for example at a referendum.

But that is not enough on it’s own. As discussed in a previous post, good policy will also be informed by a knowledge of what people want when they have thought more deeply and have information that allows them to act in their own best interests. These kinds of views could be elicited using using processes such as the RSA’s recently announced Citizen’s Economics Council, where 50-60 (presumably representative) citizens will be given time and resources to help them think deeply about economic issues of the day, and subsequently give their views to policy makers.

Delib, a company that provides digital democracy software, offers a budget simulator which achieves a similar goal. The affordances of the interface mean that uses have to allocate a fixed budget between different options using sliders. In the processes of providing a view, users intrinsically become aware of the various compromises that must be made, and deliver a more informed decision.

We live in a society where more data is available about citizen’s behaviour then ever before. As is widely discussed, that represents a privacy challenge that is still being understood. The same data represents an opportunity for governments to be responsive in new ways. Did the intelligence services know which way the vote would go using their clandestine monitoring of our private communications? Who knows.

We cannot predict everything, famously a single Moroccan street vendor’s protest set off the whole of the Arab Spring. But we can see the contexts that makes that kind of volatility possible, and I believe the anti immigration context could easily have been detected in the run up to the referendum.

There is no longer any reason for a referendum about the EU to become a channel for anger about tangentially related issues. The political class would not have been ‘punched on the nose’ if they were a little better a listening.

Hat tip: Thanks to the Delib Twitter account, which has been keeping track of the conversation about new kinds of democracy post Brexit, which I’ve used in this post.

One thought on “Building an ‘anger radar’ – ideas for better democracy post Brexit

  1. Pingback: Ruminating over Brexit isn’t helping, changing the press might | Jimmy Tidey's Blog

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