Jobs density


Jobs density figures for 2017 are available down to the local authority level. Jobs density is defined as the number of jobs in an area divided by the resident population aged 16-64 in that area. For example, a jobs density of 1.0 would mean that there is one job for every resident aged 16-64. It is apparent that not everybody in this age-group would be in employment or actively seeking work, therefore the UK average is well below a job density figure of 1.0. It is generally by comparison with the UK density that we can determine whether there are more workers resident in an area travelling outside the area to work than those travelling in, or vice versa, although it depends on the age structure and local demographics.

The total number of jobs is a workplace-based measure and comprises employee jobs, self-employed, government-supported trainees and HM Forces. The total jobs numbers are greater than the employment estimates derived from the business register employment survey, because they encompass a wider definition of the jobs market that includes the self-employed.

The results have been downloaded from the National Online Manpower Information Service website.

Definition of the Lancashire-14 area used in this report

The Lancashire-12 area is comprised of the 12 local authorities that fall within the Lancashire County Council administrative boundary. The Lancashire-14 area incorporates the two additional unitary authorities of Blackburn with Darwen and Blackpool and has the same geographic footprint as the Lancashire Local Enterprise Partnership (LEP) area.

Analysis of the Lancashire-14, North West and UK figures

The Instant Atlas report lists the job density rates for each of the 14 authorities within the broader Lancashire area, and also includes the UK, regional and county rates. We are discontinuing the use of Instant Atlas dashboards, but we have updated this one with 2017 data. Please note that we are now unable to change the appearance of the dashboard, so it still displays the year 2016, but is actually for 2017.

In 2017 the jobs density rate of 0.79 for both Lancashire-14 and Lancashire-12 was below both the UK average of 0.85 and the North West rate of 0.83.

Preston (1.06) had a jobs density rate which just fell outside the top 10% of the UK rankings of 391 local authority areas. Fylde (1.03) was ranked in 48th position. Ribble Valley and South Ribble were the other Lancashire-14 authority with job density rates in excess of the UK average, falling inside the top third of the rankings.

There are large British Aerospace sites in Fylde and Ribble Valley that underpin their relatively high rates. Preston has a diverse economy that includes significant levels of both public and private service sector employment. Along with South Ribble, Preston benefits from its strategic location in central Lancashire.

Rossendale (0.54), Chorley (0.64) and Wyre (0.65) recorded the lowest jobs density rates in the Lancashire-14 area, falling into the bottom 20% of the UK rankings. Many residents within these areas commute to jobs outside of their respective district boundaries. The average earnings results confirm that these three authorities, but particularly Rossendale and Wyre, have lower levels of workplace-based earnings, and better earnings by place of residence. These figures indicate that many residents commute outside their respective areas for better paid jobs.

Figure 1. Jobs density rates, ranks and total job numbers in Great Britain (Microsoft Power BI slide)


Unlike the results from previous years, the jobs densities in Lancashire-14 for 2017 were not as high as some of the neighbouring authorities. This can be seen in the national map which appears as a Microsoft Power BI slide, while we have also included an interactive PDF. This contains the number of jobs, jobs density and rank for all the authorities that appear within the map's extent.

The map shows authority areas nearby Lancashire-14 with higher job densities. These are Craven in North Yorkshire, Manchester and Warrington (all 1.14, rank 25). Trafford (1.13, rank 28) lies between Manchester and the Warrington unitary authority.

The Microsoft Power BI national map presents the results for all local authorities in Great Britain, and can be filtered by region. There are some very high density values in Inner London, but the City of London had a rate (125.12) that was far in excess of any other area. The small size and population of the authority, combined with the concentration of financial institutions and other organisations, resulted in a huge job to resident ratio. Westminster was in second place with 4.36, whilst the neighbouring borough of Camden had a rate of 2.22.

An analysis of all authorities across the country reveals a number of other London authorities, and other major urban localities, with high job density rates, whilst some sparsely populated localities had relatively low rates. This pattern however is not consistent across the country. For example, Lewisham (0.41) recorded the lowest rate in the UK, but its close proximity to central London means that its local job density must be placed within the context of a far wider area of influence.

The number of jobs, jobs density and rank of all UK authorities is also available as a Microsoft Excel download

Further mapping

 National map of job densities by local authority (PDF 749 KB)

(To access the statistics the PDF must be opened within Adobe Reader or Professional. If the image automatically appears within your browser window select the download option if it is available. If you see an 'open with' option choose Adobe Reader, or opt to save rather than opening immediately. When you have opened the PDF in Adobe Reader you can access the data by using the 'Model Tree' which is one of the icons in the left margin. Otherwise enabling the 'Object Data Tool' which may appear as a menu option from 'Analysis' under the 'Edit' tab. With this tool you can click on the area in question, but it may require numerous clicks. It is easier to select the authority from the list that appears in the Model Tree.)

Page updated January 2019