Connecting the Levelling Up Agenda to the Labour Market

The Levelling Up agenda is, at heart, about tackling economic and social inequalities, and the White Paper has identified the importance of detailed local data in successfully achieving these goals. To start thinking about the connection between the agenda and the labour market, we’ve produced an interactive chart below, which uses data to help us understand the relationship between the share of high skilled jobs and high skilled workforce across the country.

The chart plots Travel to Work Areas (TTWA) in terms of their share of jobs considered high skilled (defined as 1-3 digit Standard Occupation Classifications) on the Y-axis, and the share of their workforce which is considered high skilled (those with a qualification at Level 4 or above) on the X-axis, and we’ve done this for 2010 and 2020 in order to see how this has changed over that decade. The yellow horizontal and vertical dotted lines represent the average, dividing the chart into the following quadrants based on their concentration of high skilled jobs and high skilled workforce:

• Areas in the top right-hand corner have a high skill equilibrium
• Areas in the bottom left-hand corner have a low skill equilibrium
• Areas in the bottom right-hand corner have a skills surplus
• Areas in the top left-hand corner have a skills gap

(Note: you can see the change from 2010 to 2020 by pressing the play button at the top, and you can get insights on individual areas by using the dropdown, and by hovering your cursor over a circle to get a breakdown of the data):

The first and most obvious takeaway is that there is broad alignment in most areas between high skilled jobs and high skilled people, which we can see by the general diagonal trend from the bottom left to the top right of the chart. Secondly, most of the areas with an equilibrium between high skilled jobs and a high skilled workforce are in the South East. For example, the big circle on the top right is London, and some of the areas close to it include Reading, Cambridge, Oxford, Brighton, and Heathrow. Thirdly, there are very few areas with a skills gap between jobs and workforce (top left-hand quadrant). Whitehaven in Cumbria (next door to the Sellafield nuclear power plant) is the most prominent example, with 48.4% of its jobs in 2010 being high skilled, yet with just 21.4% of its workforce having Level 4 and above qualifications. Fourthly, there are many more areas with a skills surplus than a skills gap, and these areas are much more scattered around the country than the high skills equilibrium areas. For example, areas such as Dartmouth, Kendal, Buxton, Andover and Gillingham all feature in that bottom-right quadrant.

But the most interesting feature of the chart is when we look at the change from 2010 to 2020. What we see is a sizeable shift to the right in most areas, but this has not been accompanied by an upwards shift. In other words, whilst most areas now have a much bigger share of their populations with higher skill qualifications than back in 2010, this has not been matched by the creation of a similar level of high skilled jobs. Although this phenomenon can be largely attributed to the fact that many of those who have retired during the last ten years did not go to university, the bottom line is that we can see quite clearly that churning out a workforce with higher level qualifications has not been matched by a similar demand for high skilled jobs. For a more in-depth analysis of this chart, you can watch our recent webinar here, with the discussion on this data taking place from 25:15 to 36:10.

We are about to embark on a free webinar series over the next few months, where we’ll be looking at the role data can play in tackling certain elements of the Levelling Up agenda, particularly in terms of its relevance to Place, Skills, Local Partnerships, and Reducing Disparities. You can register for any or all of these webinars here.

Emsi Burning Glass is the world’s leading authority on the labour market and is active in more than 30 countries.