Lukas Kikuchi, Ishan Khurana and Will Stronge

April 21 2020

The ‘Claimant Count’ is an administrative measure of the number of people claiming benefit principally for the reason of being unemployed, using individual records from the benefit system: it gives us a good indication of the numbers of unemployed up and down the country. During this developing COVID-19 Crisis, we should obviously pay attention to unemployment statistics in order to gauge the economic impact that lockdown and social distancing are having on our economic health.

 

However, today’s data release – pertaining to the period between 13 Feb and the 12 March – does not include the avalanche of unemployment claims that have recently been reported by the DWP. This avalanche of claimants has been reported as occurring between 16 March and 31 March – meaning that this spike will only be captured by the data released on 19 May.

 

In order to help make sense of today’s data we have first plotted the previous claimant count (from late Jan and early Feb) across the UK at the level of counties. We can use this as a ‘baseline’ to represent ‘normal’ (official) unemployment levels, and to compare all data from the COVID-19 period – including today’s ONS release.

 

We’ve also broken down the industrial composition of the UK, and considered recent business surveys to get an indication of which industries are seeing large-scale lay offs. This provides us with a platform from which to make tentative forecasts about unemployment and regional disparities relevant to this COVID-19 crisis period. Needless to say: this data analysis will need to be updated regularly.

Figure 1: What was the geographical spread of unemployment in the UK before COVID-19?


Figure 1 plots the rate of people claiming benefit principally for the reason of being unemployed between 9 January and 13 February per county. While absolute numbers of benefit claims per county are somewhat useful – they are limited insofar as these numbers only really mean anything if they are made relative to the population in that area. In short, we know if unemployment claims are particularly high in a certain area if the claimant count is high relative to the population more broadly.

 

The rate of claimants is therefore much more useful: it gives us the amount of benefit claimants – and therefore an indication of unemployment –  relative to the population in a particular area. The rate displayed in the above figure is the number of claimants for every 100 persons in that region.

 

As was known to many, headline claimant figures often obscure significant regional disparities across the UK: some places have a greater unemployment problem than others. Our ‘baseline’ graph above highlights this, with Surrey, Hampshire, Oxfordshire and York all having a claimant rate between 1.5 and 1.8, while places such as Bradford, Birmingham, Blackpool, Hull, and Blackburn all have a claimant rate of over 6 (with some reaching 9.3).

 

Figure 2: What was the geographical spread of unemployment as recorded between 13 Feb and 12 March 2020?


Figure 2 plots the rate of people claiming benefit principally for the reason of being unemployed between 13 February and 12 March per county. 

 

Compared to our baseline February data, there is little to no significant variation to be observed. The ONS remarks that ‘unemployment is largely unchanged compared with a year earlier and 0.1 percentage point higher than the previous quarter’. The shift in claimant counts between what this data reports and the previous data set is statistically insignificant (0.008%) on average.

 

But what informed predictions can we make, in lieu of the data to be released in May that would cover the high-claimant count at the onset of lockdown? First, let’s consider the industrial composition of industries across UK regions. Following that, we can look at which industries are reporting large-scale layoffs to get a broad picture of the likely spread of COVID-19 related unemployment.

Figure 3: What is the industrial make-up of UK regions?

Bokeh Plot

Figure 3 shows the industrial make up of each region: what is the distribution of industries in each region? How is the region’s workforce spread across industries?

 

You can toggle which region you want to look up and the bar chart will adapt accordingly – showing the percentage of the region’s workforce against each industry.

 

For instance, the South West region has a higher ratio of accommodation and food service activities than others: 9% of that region’s workforce is employed in that sector compared, for example, to just 5% of the workforce of the West Midlands.

Figure 4: Where are industrial sectors concentrated in the UK?



Figure 4 above shows where industries are concentrated across the country. It shows the proportion of the total workforce of that particular industry that works in each particular region.

 

You can toggle which industry you want to look up and the colour scale will adapt accordingly – from the lowest percentage of that industry’s total workforce working in that particular region, to the highest.

 

For example nearly 16% of the total construction industry workforce is located in the South East region (an even greater proportion than in the London area).

 

The information and communication industries are highly clustered in London and surrounding South East region: over 50% of the workforce in these industries perform their roles there. At the other end of the map, 51% of the workforce of the mining and quarrying industry are located in Scotland.

 

Figure 5: Which workers are being laid off during this crisis?

With the industrial composition of the UK – and its regions – in hand, we can consult what information we have concerning how businesses are responding to COVID-19. In particular, we can consult the BIC Survey data on which industries are reporting large scale lay offs in the short term.

 

Figure 5 above is a plot from the most recent Business Impact of Coronavirus (COVID-19) Survey (BICS). This qualitative, fortnightly survey covers business turnover, workforce, prices and trade. These data are currently unweighted and should be treated with a certain amount of caution regarding claims about the UK economy overall. Nevertheless, they have been developed to deliver timely indicators to help understand the impact of COVID-19 on industry and workers.

 

Figure 5 shows the % of businesses by Industry (SIC) that responded saying they are laying off workers in the short term. 

52% of businesses in accommodation & food services said they are laying people off

Average weekly pay in this industry is just £264 per week

According to the BICS, 52%  of businesses in accommodation and food services said they are laying people off. There are 2.5 million people employed in this industry in the UK overall and incomes tend to be low: average weekly pay is just £264/week. Alongside accommodation and food services, four other industries are reporting large-scale layoffs of staff in the short-term:

 

  • Administrative and Support Service Activities
  • Arts, Entertainment and Recreation
  • Construction
  • Transportation and Storage

 

See the drop down box below for more information as to what these industry titles cover.

Accommodation and Food Services:

 

This category includes youth hostels, restaurants, clubs, pubs, take-away food shops, hotels and cafes.

 

Administrative and Support Service Activities:

 

This industry category is vast, including everything from travel agents, private security firms, landscape services, call centres, business and industrial cleaning work, to temporary employment industries and extermination services.

 

Arts, Entertainment and Recreation:

 

This industry category includes the performing arts, library activities, fitness facilities, museum work and zoological gardens.

 

Construction:

 

This category includes demolition services, construction of domestic and commercial buildings, electrical installation, plastering, painting, roofing, joinery, scaffolding amongst and so on.

 

Transportation and Storage:

 

This category includes rail transport of various kinds, freight, water transportation, removal services, taxi operation amongst other kinds of activity.

Figure 6: Which regions have a high-concentration of 'High Layoff' industries?

Bokeh Plot

To give a picture of what that means for regions we have produced Figures 6 & 7.

 

Figure 6 once again plots the industrial composition of regions, but highlights in red those five industries within which at least 30% of firms are reporting that they are laying workers off in the short-term; those industries we’re calling ‘High Layoff’ industries.

 

Figure 7: The combined concentration of 'High Layoff' industries as a % of total industry across regions

Bokeh Plot

Finally, we can then map the combined concentration of those five ‘High Layoff’ industries (within which at least 30% of firms are reporting that they are laying workers off in the short-term).

 

Figure 7 lists each region by the proportion of overall industry that these five ‘High Layoff’ industries take up in combination.

 

Over 30% of all overall industry in the East of England, South West, South East and London respectively is made up of ‘High Layoff’ industries.

 

Needless to say, no precise numbers can be given at this point, and forecasts for long-term unemployment are even more uncertain, but we now have a picture of which industries, and which region will be hit by this crisis in the short-term most.

Some regions with existing high rates of unemployment, including the North East for example, will be take an even further hit by the COVID-19 virus

However, other regions that recorded low rates of unemployment before the crisis, including the South East and South West, will also feel the economic bite of the COVID-19 virus

Some regions with existing high rates of unemployment, including the North East for example, will be take a further hit by the COVID-19 virus: out of all industries active in that region, over a quarter (27%) are ‘High Layoff’ industries.

 

But other – perhaps more surprising – regions are set to suffer also. The South East, South West, London and East of England regions all comprise of many ‘High Layoff’ industries. These regions do not typically (pre-COVID-19) have high rates of unemployment but, we can predict, will be feeling the bite of unemployment in the months of lockdown and social distancing.

Note and data sources

With thanks to Rob Calvert Jump for his considerations on the topic.

 

The BICS survey was sent to around 17,800 UK businesses and covers the period between 9th of March and 2nd April. Results presented in this release are based on a limited number of responses – around 25.9% (4,598) of all businesses that were surveyed responded. Full Readme can be found here. The average wage by industry data is from EARN03 which can be found here.

 

Note: we have previously written on why the normal ‘official’ unemployment count is dubiously low, but in this time of crisis it is difficult to asses how far out the official ONS numbers are.

Regional industry composition:

 

https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/datasets/workforcejobsbyregionandindustryjobs05 

 

Geographical data:

 

https://opendata.arcgis.com/datasets/a917c123e49d436f90660ef6a9ceb5cc_0.geojson

 

Claimant count (monthly):

 

https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/methodologies/claimantcountqmi

 

Residence-based proportions between claimants and residents: This is the official measure below national/regional level. It is available for local authorities, constituencies, travel to work areas, regions and countries and it expresses the number of claimants as a percentage of the population aged 16-64, sourced from the mid-year population estimates. At national/regional level the official measure is the workplace-based rate, but use this measure when comparing national/regional areas with smaller areas (e.g. local authorities) to ensure you are comparing like with like.

 

BIC Survey:

https://www.ons.gov.uk/economy/economicoutputandproductivity/output/datasets/businessimpactofcovid19surveybics