Welcome to the first of our Data Dabbling series of 2019. The aim of these pieces is simply to throw out some data that we’ve been working on, which may or may not end up being a part of a solution we offer, but which will nonetheless surely provoke interest and discussion.
The interactive chart below shows data on worker inflows and outflows we’ve pulled together, down to the level of local authority.
Net Commuting Inflows and Outflows
Let’s begin with the X-axis. This shows the net commuting flow for each local authority, as a percentage of its working population, which is basically calculated as the number of employees working there, minus the number of employees living there. Local authorities on the right-hand side of the group have a net inflow of workers into their area every day, whereas those on the left-hand side of the chart have a net outflow.
So if you hover over the bubble furthest to the right, you’ll see that it is Westminster (this includes the City of London). As you can see, the net commuting inflow of workers into the area every day is huge, being in excess of 1.1 million people. We might describe such areas as “workshops”, since large numbers of people come there to work every day, before returning to their places of residence outside the area.
Hover over the bubble furthest to the left, and you will see that this is another London borough — Lewisham — which has an estimated net outflow of more than 102,000 workers every day. In contrast to workshop areas like Westminster, we might describe these places as “dormitories” — that is, places where people tend to commute out of in order to work.
Coming onto the Y-axis, this is an index of job similarity, measured at the 2-digit SOC occupation level — jobs are sorted in 25 categories and we’re measuring how similar the pattern is for those living compared to those working in each place. Those areas at the top of the chart (tending towards 1) generally have the same type of employees commuting in as they have commuting out, whereas those at the bottom (tending towards 0) generally have an incoming worker population that do quite different jobs than those who commute out of it to work (the horizontal line is median similarity).
Those local authorities at the top, such as Bridgend with a similarity index of 0.95, are therefore relatively self-contained, in that overall there’s a small net flow, but the workers demanded are broadly similar to the workers supplied. Whereas those at the bottom, such as Harborough with a similarity index of 0.76, are far more of a revolving door, where those entering the area to work tend to be employed in occupations that are very different than those who are commuting out of it to work every day, even though the number broadly balance out.
What the chart shows is the ways that labour markets can be very different at the local level. Some areas are clearly net importers of workers; others are net exporters. In some areas the types of jobs done by workers coming into the area is broadly similar to the types of jobs being done by the workers commuting out of the area each day; in other areas, there is a more marked difference in the jobs done by incoming and outgoing workers. Although this insight only scratches the surface, it is nevertheless a good conversation starter, particularly for economic developers in terms of how they think about retaining talent in their area and attracting talent to their area.