Protectionism is bad when Trump does it – so why is it so often welcomed by British cities?

Protectionist in chief, Donald J. Trump. Image: Getty.

Do we stand on the verge of a new trade war? In light of competition from elsewhere, the drawbridge is being pulled up to shelter local industry from these malevolent foreign forces. And that, argue some policy makers, is going to help keep money in the economy and create jobs.

I’m not talking about Donald Trump, steel and whiskey. I’m talking instead about the idea of councils buying their goods and services locally, an idea that has been dubbed ‘Corbynomics’ and has Preston as its poster child. But the parallels are striking.

In recent years Preston City Council in particular has been active in increasing its spend on local businesses, giving them preference over suppliers from elsewhere. This has brought both curiosity from some policy makers and strong support from others, with John McDonnell describing this brand of ‘municipal socialism’ as the kind of radicalism needed across the country.

What is curious though is how differently policies promoting protectionism are viewed at the local and national level. The lines against international trade barriers are well rehearsed, and Donald Trump has been roundly criticised for his approach, with even his economic advisor quitting over it. And yet paradoxically protectionism is welcomed at the local level, somehow viewed as a defence for small businesses rather than the same politics of populism.


The same applies to the idea of local currencies. There are a number of local currencies in the UK, such as the Exeter and Bristol (tagline “Our city. Our money”) and pounds. The principle is that they support independent businesses by encouraging people to shop locally – in a war of David (local independents) versus Goliath (big national or multinational companies), it is argued that these policies help level the playing field. Of course, this is exactly the argument that Trump makes about US steel (David) and China (Goliath).

The struggles of the US steel industry are unlikely to be down to unfair trade practices, nor the deluge of cheap Chinese products. (Chinese steel accounts for just 2 per cent of all steel imports into the USA.) Similarly, the challenges that weaker city economies face have little to do with local authorities spending their budgets with companies outside their areas, nor people choosing to buy from Amazon rather than their local high street. Instead these struggles are caused by the ability of places to attract high-skilled investment into their economies, and the ability of these businesses to ‘export’ their wares to a regional, national or international market. This is caused by a number of issues, of which low skills of the workforce is chief amongst them.

So as US trade tariffs have been criticised by many, we must also view protectionist policies at the local level in light of the same criticism. Successful cities are ones that are open to business, irrespective of where these businesses are based. We should be encouraging them to increase trade, not shut it down.

Paul Swinney is head of policy & research at the Centre for Cities, on whose blog this article first appeared.

You can hear him discuss these issues on a recent episode of Skylines, the CityMetric podcast.

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Google knows you took the bus: on the creepy accuracy of Google Maps Timeline

You are here. And here. And here. And... Image: Google Maps.

Knowledge is power, they used to say. Nowadays, they say “data is power”, and they’re not wrong. Unlike many of the modern, high-value tradable goods in our society like oil or gold, data is a limitless resource that we’re constantly creating more of day after day.

What the actors who own this data choose to do with it can often be a point of vast contention: should I be happy for Google to reliably know where I am, where I’ve been, and most frighteningly, where I’m going? It’s not up for dispute that the scope of these tools can be immense – but how much of that scope should we take for granted?

Google Maps is a tool full of wonderful surprises. It can plan a journey for you, tell you what deals to get at the supermarket, and give you updates at the bus stop. Some of the things Maps can do, it does without us even asking; Google knows when we pop to the shops, or when we stand by a bus stop.

This concept is called “geofencing”: cross-referencing geolocation data with the services at that location, and issuing notifications to a device on that basis. Google knows I’m in the supermarket because my location matches up with the area the supermarket is known to occupy, and through a complex series of phone masts and wifi access points, it knows I’m between the vegetable aisles. Okay, maybe things aren’t quite that specific, but the detail is stellar – and often, slightly concerning.

A simple flick through the timeline feature of Google Maps reveals that Google can plot day by day where you were, when you went home, and, maddeningly, how you took that journey – or at least, it can make an educated guess. By applying geofencing programming, Google can calculate when we are near a bus stop, and cross-reference that data with bus routes and other bus stops to determine with a reasonable degree of certainty when its users are taking the bus. Google doesn’t go as far as to try and guess which bus, but it could make an educated guess.

The same is true of train stations; pause in one, follow the expected route of the railway line, and travel through additional train stations, and Google will have no trouble in informing you after the fact that you have travelled by train. A reminder that you don’t need to have planned a journey on Maps for Google to surmise this: it is all calculated based on shifting geolocation data, and nothing more.

Walking, cycling and driving are harder for Google to calculate, because there are no geofenced points of entry for these modes of transport. It is therefore likely that, once bus, train and metro have been eliminated from the mix, Google simply inspects the time taken between harvested geolocation data to calculate the transport mode used. But without geofencing, it’s harder to determine the exact route taken by a user: because they’re not following a prescribed route, and because geolocation data is much easier to take while stationary, routes on timeline taken independent of public transport can end up looking… messy.

Google fails to surmise that some of this journey was taken by train and presumes I took an unorthodox drive through Kent in the early hours. Image: Google Maps/CityMetric.

The system isn’t perfect. For one, it can’t account for anomalies. I took a rail replacement bus service recently, and Timeline was dumbstruck by how I’d managed to get home. But the ever-increasing availability of data surrounding transport timetables means that the assumptions Google can make about our transport choices are only bound to get more accurate. That’s important, because its information that few organisations beyond Google are likely to have real access to.

If we take London as an example, we know that Transport for London (TfL) can use data on traffic flows, ticket barriers, and incomes for bus routes to determine how people use a service. In fact, TfL has even used its own wifi services to calculate route maps on the Tube. However, without undergoing intricate surveys, they will struggle to plot exactly how journeys are taken beyond the Tube Map, especially with regards to buses, disparately owned NR services, and so on.


Google has exactly the information to remedy this – and it’s integrated into Timeline, simply because people consented to having their location data collected. If your local borough council asked to do the same, and the only provision it could grant was that you might get a better bus service, many people would probably opt-out. Part of the reason why we accommodate the location-harvesting of Google is because we consider Maps such a vital service, and its domain – at least in terms of its rights to record our geolocation – is hardly contested. Even those of us who use Citimapper regularly tend to have Maps downloaded on our phone.

Google Maps is in a unique position to mark the differences between journeys that are entirely spontaneous and journeys that are pre-planned, because it is measuring both. That information could be highly useful in designing timetables and shaping user-friendly services.

Moreover, as geolocation data grows more precise, it will be able to help us pin down the flows of pedestrians and cyclists in our cities. While it’s possible to gather this data in the public domain without geolocation, it’s economically prohibitive to do so in less densely populated areas. This data would help prioritise cycle-friendly and pedestrian friendly developments on the understanding of where demand is greatest.

This sort of data inevitably carries such a high risk factor, however – not only as far as personal privacy is concerned, but also surrounding efficacy. We presume that if we know every individual's travel patterns, we can design perfect travel services – but patterns change all the time. An algorithm can never incorporate the latest change before it is registered by the system. While data like that collected by Google Timeline could be put to better use by transport authorities, it shouldn't be abused, nor serve as a panacea for good design.

Worst of all, it’s hardly clear that this data is up for public consumption. The furore over data protection means it would be considered deeply unethical for Google to hand this location data over to anyone, let alone a local government body like TfL. It may be moot point; Google itself claims that Timeline is for our own amusement and little more.

But maybe we’d get better services if it wasn’t; after all, geolocation isn’t slowing down anytime soon.