With the Levelling Up White Paper now published, we’re busy working to map the resources that we have on using evidence and evaluation across the twelve missions. More on that in the next couple of weeks.
We’re also aiming to publish some blogs looking at what economic research has to say on some of the broader issues around levelling up. Let’s start with scale of the challenge. Just how big are the economic inequalities that policy needs to address?
It is often said that the UK is the most spatially unequal country in the developed world. This is repeated so often in the media and public discourse that it is widely accepted as fact. Some statistics that are false or misleading are repeated so often they are called ‘zombie statistics’—they just won’t die, no matter how often researchers point out the facts or the nuance. Are we looking at a zombie statistic here?
Comparing spatial disparities across countries is difficult, and commonly used measures are particularly problematic for the UK. The studies that find the largest spatial disparities in the UK, relative to other countries, compare differences in GDP per capita across small administrative areas – so-called territorial level 3 or TL3 regions. Countries are ranked by various ‘measures of dispersion’ of the TL3 regions, such as the difference between the TL3 regions with the highest and lowest GDP per capita.
There are two major problems with these comparisons:
They often compare apples and oranges.
The size and make-up of TL3 regions varies widely depending on how administrative boundaries are drawn. The UK has 179 TL3 regions. This is the second largest number of regions across all OECD countries, in contrast with France which has 96 TL3 regions and Spain which has 59. Most importantly, the UK is unique in that its most productive city, London, is split into 21 separate TL3 regions. This means that many of the top UK TL3 regions are often just different parts of London, whilst regions at the bottom consist solely of rural areas. In countries with fewer TL3 regions, cities are often grouped with their suburbs and surrounding rural areas, so differences between regions—or the urban-rural differences within regions–are muted.
GDP per capita is a flawed measure of productivity (let alone living standards).
GDP per capita divides the output produced in an area by the number of residents who live in the area. If lots of people commute into an area, it’s GDP per capita will look large, even if the people that live there are poor. This problem is particularly pronounced when looking at small areas, such as the separate TL3 regions in London. Camden & City of London – the highest-ranked TL3 region – has a population of around 260,000, yet some 800,000 people work there and contribute to its GDP. The use of GDP per capita, combined with the artificial division of London into 21 separate areas, vastly overstates the level of spatial disparities in the UK.
A paper by Phil McCann compares the UK and other OECD countries using several different spatial levels, including TL3. In the comparisons that use GDP per capita at the TL3 level, the UK consistently comes out top in terms of spatial disparities. In contrast, comparisons at the TL2 level – a larger level of aggregation where London is counted as a single region, comparable to Paris, Berlin or Tokyo – put the UK in the top quarter or top fifth of countries. Of course, the administrative boundaries of London still leave out large numbers of commuters from surrounding areas. Comparisons that use functional labour market areas – ‘metro urban regions’, similar to TTWAs – place the UK around the middle of the pack.
Taken together, the evidence suggests that spatial disparities in the UK are relatively high by international standards, but nowhere near as high as sensationalist headlines might have us believe.
The Levelling Up White Paper emphasises the need to address spatial disparities. It also emphasises the importance of high-quality evidence for local and central government to make decisions about what policies and interventions to support. We need to make sure we keep zombie statistics out of the mix.