Labour Market Snapshot

This page presents a summary of the latest labour market data for the UK. As well as the usual data such as total Employment or the Unemployment Rate, we additionally focus on inactivity, vacancies, labour market flows, and mobility and reallocation across industries and occupations.

The results are constructed from the UK Labour Force Survey (LFS) dataset, which is the nationally-representative survey used to construct the official unemployment statistics. We use the latest available quarterly release, so our data run up to 2022 Quarter 4 (Oct-Dec).

Here is a brief summary of the current state of the UK labour market:

• Total Employment remains around 250,000 workers below its pre-pandemic value, so the labour market is far from recovered despite the low Unemployment Rate. Employment is low because economic Inactivity is high. The recovery of employment seems to have stalled in the last quarter of data.
• Worker Job Finding Rates from unemployment, employment, and inactivity are all high and have recovered from the lows experienced during lockdown. However, there is evidence of slowing in the last quarters, due to the global energy crisis. For the job-to-job transition rate, this might mean that the so-called Great Resignation might finally be coming to an end.
• Aggregate Vacancies continue to fall and are 43% above their pre-pandemic level, slightly down from an all-time high a few quarters earlier. High vacancies are a source of the labour shortages plaguing the economy, and the Vacancy Filling Rate is now lower than it was before the pandemic. The economy is far off its usual Beveridge Curve, but is starting to return.
• The probability that an employed worker becomes unemployed is starting to rise, so the risk of losing your job shows slight signs of increasing.
• The rates at which workers transition from employment to another job, or to inactivity, are both elevated but starting to come down.
• Gross Mobility across Industries and Occupations remains depressed. This means that fewer workers are changing industry or occupation when they move jobs, and are preferring to stay in jobs similar to their last job rather than making career moves.
• Net Mobility across Industries and Occupations was high during the depths of the pandemic, but is now slowing down towards normal levels. If Net Mobility is high this means that some Industries/Occupations are growing by poaching workers from other Industries/Occupations which are shrinking.
• The economy is thus settling down at a new composition of Industries and Occupations, with many sectors still much smaller than they were before the pandemic. In particular, the Manufacturing, Retail, and Construction industries have shrunk while Public Administration and high skilled service industries grew. Skilled Trades and Managerial occupations have shrunk while Professional and Administrative occupations grew.
• Labour shortages continue to be a problem, both in the aggregate and for certain badly affected industries such as Manufacturing and Accommodation and Food. The worst hit industries are facing shortages not just due to high vacancies but also due workers not wanting to search for jobs in those industries.
• The misallocation between the industries where firms are hiring and where workers are willing to work is now the worst it has been since our data began. The economy could be creating 20% more jobs per quarter if workers were willing or able to change the sectors they were searching in.

Read on to view the latest data find out more.

This page is maintained by Alex Clymo, so please contact a.clymo@essex.ac.uk for any data queries. For any general enquiries please visit our Contact page.

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Employment, Unemployment, and Inactivity Since the Pandemic

The left graph below plots the change in the total number of people employed in the UK economy since 2019Q4. The right graph plots the Unemployment Rate and Inactivity Rate in 2019Q4 and in the latest available data:

Employment in 2022Q4 was 254,000 people lower than pre-pandemic, so the economy has ony recovered around 2/3 of the employment losses from the depths of the recession. The recovery is therefore still far from over. Surprisingly, the Unemployment Rate is not high, and is currently at 4%, slightly higher than it was just before the pandemic. The low Employment is instead because the Inactivity Rate has risen to 20.4%.

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Worker Job Finding Rates

The three graphs below plot the job finding rates of unemployed, employed, and inactive workers since 2019Q1. For unemployed workers this gives the fraction of unemployed workers who found a job and were employed in the next quarter, and similarly for Inactive workers. The Job To Job transition rate is the fraction of employed workers who moved to a new job in the next quarter. In each figure the blue line is the raw data, and the red line is the data smoothed with a 5 quarter moving average.

The figures show that the job finding rates dropped during the pandemic for all three groups and started recovering around early 2021 as the economic effects of the pandemic eased. Now the global slowdown associated with the energy crisis seems to be causing job finding rates to fall, and job finding rates from unemployment and inactivity have nearly fallen back down to their pre-pandemic levels.

The job to job rate is high, and continues to be so despite the current turmoil. This is part of the “Great Resignation” story, that workers are quitting their jobs at a high rate sine the pandemic. We discussed this in detail here. Looking at the last quarter of raw data, the job to job rate has dropped slightly from its peak of over 3% down to 3%, which could be a sign that the Great Resignation is slowing down as the global economy has started to slow down again.

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Vacancies and the Beveridge Curve

The left graph below plots the change in the total number of open vacancies for jobs in the UK economy since 2019Q4. The right graph plots the change in the Vacancy Filling Rate since its average value in 2019. The Vacancy Filling Rate is the probability that a firm manages to fill its vacancy with a hired worker in the next quarter.

Vacancies fell by nearly 60% during the pandemic, as firms massively cut back on hiring during lockdowns. Such a quick and deep fall in vacancies is unprecedented in the data. But as the economy opened back up again vacancies have soared back, up to 60% above their pre-pandemic level, an all-time high. This is the source of the labour shortages plaguing the economy. The Vacancy Filling Rate was high during the pandemic, meaning that firms were finding it easy to hire since so few firms were hiring, but it is now nearly 30% lower than it was before the pandemic.

Below we plot the Beveridge Curve, which is a classic relationship for analysing the labour market. Each dot represents one quarter of data, with blue dots representing data before the pandemic and red dots data since. The Beveridge Curve shows that at times when vacancies are high, unemployment tends to be low, because high vacancy posting naturally leads to workers being hired and pulled out of unemployment. However, the rapid changes in the pandemic pushed us off the previous Beveridge Curve:

The graph shows the Beveridge Curve from 2002Q1 to the latest data. Each datapoint refers to one quarter, with key quarters named on the graph. The horizontal axis gives the unemployment rate in that quarter, and the vertical axis gives the level of vacancies in that quarter. The level of vacancies is normalised to 1 in 2019Q4. Data are from the UK Labour Force Survey and ONS VACS02, and are seasonally adjusted.

During the pandemic vacancies collapsed while unemployed did not massively rise, most probably due to the furlough scheme protecting workers from being fired. Now, post pandemic, vacancies are high while unemployed is coincidentally near its level in 2019Q4. Whether the Beveridge Curve has permanently shifted out, or we will return to the old curve as vacancies start to fall, has important implications for the natural rate of unemployment and inflation. Indeed, in 2022Q4 we are starting to see tentative signs the Beveridge curve is shifting back down.

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Worker Separation Rates and Labour Market Churn

The three graphs below plot the separation rates of employed workers into unemployed, a new job, and inactivity since 2019Q1. For example, the Employment To Unemployment (E2U) rate is the fraction of employed workers who are unemployed in the next quarter, and similarly for inactivity (E2I). The Employment To Employment (E2E) rate is the same as the Job To Job transition rate shown earlier. The blue lines are raw data and the red lines are smoothed.

We see that during the pandemic the rate that workers lost or left their job and moved to unemployment or inactivity rose. This reflects increased rates of layoffs and retirements, among other factors. The rate at which employed workers moved to new jobs fell, as the economy slowed down. Since then, the Employment To Unemployment rate has been falling, and the E2E rate recovering, since the start of 2021, reflecting the economic recovery. The E2I rate was elevated, meaning that workers continue to leave the labour force, a cause of the labour shortages.

However, things are starting to change again. There is a small increase in the employment to unemployment rate over the last few quarters of data, suggesting that unemployment risk might be rising with the global energy crisis. Similarly, the employment to inactivity rate has been falling, so workers seem to be moving into inactivity less then at the worst of the labour shortages.

Many of the changes above highlight that we are currently seeing a high level of churn in the labour market. Churn is defined as the total number of worker job movements as a fraction of total employment (see the text under the picture below for a precise definition). As we can see in the picture below, churn has risen from around 10.5% to a maximum of 13% since the pandemic. The worker flows above show that churn is high because workers are i) making lots of job-to-job moves, ii) moving back and forth between employment and inactivity a lot, and iii) unemployed workers are finding jobs at a high rate. However, churn is now falling again in 2022.

The graph shows the level of labour market churn since 2019Q4. This is defined as the sum of all employment related transitions as a fraction of total employment. Specifically, this is ( U2E + E2U + I2E + E2I + 2*E2E ) / E, where E is the stock of employed workers at a given time, and X2Y is the flow of workers between states X and Y from that time to the next quarter. We count E2E transitions twice since each E2E move counts as both a hire and a quit. Data are from the UK Labour Force Survey, and are seasonally adjusted.

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Gross Mobility

A very important labour market indicator is the amount of Gross Mobility across industries and occupations. Workers move back and forth across jobs in different industries and occupations very often, reflecting moves in their personal career trajectories which may offer opportunities to move to jobs they are better suited to. To measure this idea, Gross Mobility across industries is defined as the fraction of all hires in the economy which involved a worker changing industry. This includes hires directly between jobs and where the worker spent time in non-employment, and the definition is the same for Gross Mobility across occupations. The two graphs below plot each idea, with the blue lines giving the raw data and the red line smoothed data.

We can see that Gross Mobility became depressed during the pandemic, and remains so up to the current data, despite a slight recovery. This provides an important counterpoint to the high degree of churn we saw in the last section: Yes, worker churn is high, but workers are churning more within their own industries and occupations, and the churn is not inducing lots of career changes.

Even worse, Gross Mobility appears to be falling again with the current energy crisis, at least for industries. Between COVID and the current crisis, we are now approaching three full years of low gross mobility and hence low reallocation of workers across jobs in the economy.

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Net Mobility and Industry and Occupational Changes

Net Mobility measures the “net” flow of workers between industries and occupations. For example, if 10,000 workers move from Retail to Education jobs and 8,000 workers move from Education jobs to Retail jobs, then we say that the net flow of workers from Retail to Education is 10,000 – 8,000 = 2,000. This means that the Education sector has grown by stealing workers from the Retail sector, in this hypothetical example. Net Mobility is an important concept because high Net Mobility means that the economy is changing, with some sectors shrinking workers flowing to growing sectors. We plot Net Mobility for industries and occupations since 2019Q1 in the figures below, with raw data in blue and smoothed data in red.

We see that net mobility across industries and occupations was high during the pandemic, which means that the economy was changing. Some industries and occupations shrank and others grew, with workers flowing to the growing sectors. This is a well known pattern of recessions. Net mobility has been falling since 2021, suggesting that the economy is starting to settle down to a potentially new structure. Although, net mobility is still higher than pre pandemic.

To see how the economy has changed, in the figures below we plot the change in employment since the pandemic in each industry and occupation:

We see that there have been massive changes in the shape of the economy since the pandemic, with some industries and occupations shrinking much more than others, and only a few sectors seeing any employment growth. Most sectors still have low employment, which reflects that aggregate employment has not fully recovered yet. In particular, the Manufacturing, Retail, and Construction industries have shrunk while Public Administration and high skilled service industries grew. Skilled Trades and Managerial occupations have shrunk while Professional and Administrative occupations grew. The post-pandemic economy is therefore very skewed, with only professional and administrative occupations growing while trades and manufacturing continue their long run decline.

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Industry-Specific Labour Market Tightness and Vacancies

Labour shortages are a big problem in the post-pandemic economy, which we have discussed in detail here. Aggregate vacancies are high while unemployment is low, so firms are short on unemployed workers to hire. In our work we have shown that the problem is even worse than this because certain industries are facing particularly severe shortages.

In the right figure below we plot the increase in vacancies in each industry since before the pandemic. We can see that vacancies are high in every industry of the economy, and have increased markedly in some key industries such as Manufacturing and Construction.

In the left hand figure we plot our estimate for labour market tightness in each industry. Tightness measures how hard it is to hire in each industry, by taking the ratio of vacancies to the number of workers searching for jobs in that sector, which we calculate using a novel method. This shows how the labour shortages really differ across industries. Manufacturing has seen an increase in tightness of over 350%, suggesting that it is more than 4 times harder to hire in this industries than before the pandemic. In our work we show that tightness is highest in the worst hit industries both because of the high number of vacancies in those industries, but also due workers not wanting to search for jobs in those industries any more.

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Wage Inequality and Compression

Are labour shortages helping to push up wages for lower paid workers? Yes, they are. In the figure below we plot real hourly wage growth since the pandemic for different levels of wages. Specifically, we plot the change in the wage from 2019Q4 to the current quarter [note: only updated to 2022Q2] for each percentile of the wage distribution. Workers in the lowest wage percentiles have seen their wages rise by around 2% per year since the pandemic, while workers with higher wages have seen their wages increase by 1% per year or even less. Overall, the post pandemic period has seen “wage compression” which has reduced income inequality.

Note that this does not control for composition effects, so does not reflect exactly the increase in pay that each employed worker sees. Some of the effect is driven by lower paid workers leaving their jobs, which raises the average wage for remaining employees.

The graph shows real hourly wage growth since the pandemic for different levels of wages. Specifically, we calculate the average wage in each wage percentile bin in each quarter. We then compute the change in the average wage for each percentile bin i between 2019Q4 and the most recent data as (wage(i,current quarter)-wage(i,2019Q4))/wage(i,2019Q4).

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Misallocation of Search Effort Across Industries

Is misallocation negatively affecting the labour market? We developed a novel measure of misallocation by measuring whether workers are looking for jobs in the same industries that jobs are actually available. If workers are looking for jobs where they are available then misallocation is low. If not, then misallocation is high. We measure misallocation as a percentage measure called the Match Efficiency Ratio (MER). If the MER is 100% than we have a perfect allocation. The lower the number the worse misallocation is, defined as the number of new jobs formed as a percentage of the number of jobs we would have created if there was no misallocation. This is shown in the figure below for the whole sample running up to the current data:

The graph shows the Match Efficiency Ratio, which is a concept we constructed in our paper here. This gives the total number of hires in the UK economy each quarter as a percentage of the theoretical maximum number of hires if there was no misallocation. No misallocation means that workers are searching for jobs in each industry in exactly the right proportions to maximise the number of new hires that quarter. A lower value in the graph means the labour market is less efficient. Data are from the UK Labour Force Survey and ONS VACS02 survey, and are seasonally adjusted.

We can see that misallocation is the worst it has ever been, with the Match Efficiency Ratio now down to only 80.5%. This means that we are creating 19.5% fewer new jobs per quarter than if workers were looking in jobs better aligned with the industries where firms are actually posting vacancies. Before the financial crisis efficiency was closer to 90%, and after hitting a high of 95% it has been on a downwards trend ever since. This is a fundamental problem for the UK economy: workers either do not want, or are not qualified or skilled enough to apply for, the jobs that firms are currently offering.