In Quarter 1 (Jan to Mar) 2020, output per hour, the UK's headline measure of labour productivity, fell by 0.6% compared with the same quarter a year ago, while output per worker fell by 3.1% over the same period; this reflects the impact of "furlough" schemes, which reduced hours worked but preserved workers' employment statuses.
Multi-factor productivity (MFP) in Quarter 1 2020 is estimated to have decreased by 2.6% compared with the same quarter a year ago; this is the lowest growth rate since Quarter 3 (July to Sept) 2009.
Public service productivity decreased by 4.8% in Quarter 1 2020 compared with the same quarter a year ago; this fall was driven by an increase in input of 3.2% and a fall in output of 1.6%.
Healthcare was the main driver of the overall inputs growth, while the output fall was mostly because of health care and education.
Unit labour costs (ULCs) increased by 6.2% compared with the same quarter a year ago, the largest increase since Quarter 4 (Oct to Dec) 2006.
|Series||Status||Quarter on same|
quarter a year ago
|Quarter on previous|
|• Output per hour||National|
|• Output per worker||National |
|• Output per job||National|
|Public service productivity |
|Unit labour costs||National |
Download this table Table 1: UK Productivity Statistics for Quarter 1 (Jan to Mar) 2020.xls .csv
Productivity is a main driver of economic growth and is an important indicator of the economic health of a nation. It helps define both the scope for raising living standards and the competitiveness of an economy and is increasingly used to inform government policy.
This article provides the first insights on the impact of the coronavirus (COVID-19) on productivity in the UK in Quarter 1 (Jan to Mar) 2020. On 23 March 2020, the UK entered a period of "lockdown" imposed by the government to combat the coronavirus pandemic. Therefore, this article only captures a short period of the impact of the lockdown on productivity. A fuller view of the impact will be contained in the next productivity article, which will cover Quarter 2 (Apr to June) 2020 and will be published on 7 October 2020.
Productivity is a measure of the relationship between inputs and outputs in the economy; the fewer inputs needed to produce the same output, the more productive the economy is. Labour productivity measures the volume of gross value added (GVA) produced per unit of labour input, with hours worked as the preferred labour input.
Figure 1 shows how the 2008 economic downturn served as a break in the labour productivity series between the historical long-term average growth rates of 2.0% and the weak productivity growth that has followed it. Low labour productivity growth looks set to continue into the new decade as the UK economy faces further disruption. This sustained period of weak growth has been labelled the UK's "productivity puzzle" and is arguably the defining economic question of our times. The Royal Statistical Society acknowledged this challenge in December 2019 by awarding the UK Statistic of the Decade accolade to the Office for National Statistics' (ONS') labour productivity series. The series shows an estimated average annual growth of 0.3% in the decade or so since the 2008 economic downturn.
The coronavirus pandemic has forced employers and employees to adjust to new working schedules and arrangements, such as working from home, which may have either positive or negative impacts on the productivity of different parts of the economy. For example, the short period of lockdown observed in Quarter 1 2020 resulted in a fall in hours worked (1.2%) that was smaller than the fall in GVA (1.7%), which has helped output per hour worked to weaken. However, the government's "furlough" schemes have resulted in a disparity between output per hour and output per worker, which typically are closely aligned because the scheme has caused employment to stay in line with pre-pandemic levels, whereas hours worked has fallen.
Output per worker therefore fell by 3.1% as GVA fell by 1.7% and workers rose by 1.4%, when compared with the same quarter a year ago.
When looking at which parts of the economy were most affected, output per hour for most non-financial services sections fell in Quarter 1 2020, most notably in real estate activities which fell by 10.5% compared with the same quarter a year ago. However, output per hour for scientific, professional and technical services rose by 2.0%. Outside of services, output per hour fell by a smaller amount in manufacturing (down by 1.4% compared with the same quarter a year ago). Output per hour rose somewhat in non-manufacturing production (1.2%) and more in construction (5.0%).
As drivers of the whole economy fall in output per hour, non-financial services had the largest impact and accounted for 0.9 percentage points of the overall decline. Manufacturing accounted for 0.1 percentage points. Financial services and non-manufacturing production had relatively little impact. Construction slightly offset the trend and pulled up overall output per hour by 0.3 percentage points.
Whole economy output per hour was also pulled up by 0.2 percentage points because of a positive allocation effect. This shows a relative shift in the economy from lower to higher productivity industries, either because more productive firms are expanding or because lower productivity firms are reducing activity. This shift may in part be a result of the furlough schemes, which have particularly affected services sectors such as food and accommodation. These sectors tend to have relatively low output per hour, so if hours worked in these sectors falls disproportionately because of furlough schemes, on average output per hour for the UK is pulled up.
Changes to the allocation effect in Figure 2 can have several drivers. Over time, it is reasonable to assume that productive companies and sectors of an economy are likely to grow faster than their less productive counterparts. This will result in a shift of resources, including workers, to those more productive areas of the economy, increasing productivity over time.
Furthermore, less productive firms may go out of business. If this happens, then their more productive counterparts that are still operating will bring up average productivity in the economy. This effect will also be shown in the allocation part of Figure 2.
Data published alongside this article include a new compendium dataset that collates annual time series related to labour productivity at a more granular industry level than what is available in quarterly labour productivity datasets.
Users are invited to guide improvements to labour productivity datasets by commenting on a proposal to show growth rates as percentage log changes rather than the percentage change growth rates that are currently published in labour productivity datasets.Nôl i'r tabl cynnwys
Estimates of multi-factor productivity (MFP) provide a different view of productivity to our labour productivity estimates. MFP attempts to control for the changes in the various inputs used to create economic output and how these inputs are combined to deliver output. These inputs include changes to capital services (such as machinery and software), changes to the composition of the labour market (for example, the number of workers with university degrees) and changes to labour input in terms of hours. This is explained in our simple guide to MFP. MFP only covers the market sector and excludes the public sector and other similar parts of the economy.
MFP in the market sector in Quarter 1 (Jan to Mar) 2020 decreased by 2.6% compared with the same quarter a year ago. This is the lowest rate of MFP growth since 2009.
This fall coincides with the largest decrease in market sector gross value added (GVA) over the same period, decreasing by 2.2%. Figure 3 shows this fall in GVA and how changes to labour productivity are decomposed across labour and capital inputs.
The market sector saw a 1.2% decrease in hours along with the fall in GVA, although labour composition, which reflects labour capability, rose by 1.2%. Capital services, the level of productive capital used in the economy, increased by the same amount. This directly impacts the level of capital deepening, which is the amount of capital workers can utilise per hour worked.
Despite the positive effects of the growth in capital and labour composition, productivity in the market sector fell by 1%. This directly impacts MFP, which is the residual after accounting for changes to labour productivity after the impacts of labour composition and capital deepening. These effects can be seen in Figure 4.
Changes in the composition of labour have helped stabilise output per hour in recent periods. These changes include an increase in the proportion of hours worked by better-qualified and higher-paid workers in the labour force.
This is particularly true in the most recent quarter. In the last week of the quarter, workers were furloughed as companies took advantage of the government scheme that secures employment and wages for their workers. However, workers with less qualifications were disproportionately affected by these changes. Hours for those with no qualifications fell by 5.8%, while hours for the most qualified grew by more than 2.3%.
Younger workers saw a decrease of 5% in hours worked, whereas those aged over 50 years increased their hours by 1%. Younger workers tend to be on lower wages, and wages are used as a quality of labour weight in labour composition measures. As such, older workers boosted the labour composition further.Nôl i'r tabl cynnwys
Alongside our other measures of productivity, we also publish quarterly experimental measures of total public service productivity, covering both the public sector and private sector delivery. The Office for National Statistics (ONS) also publishes an annual estimate of total public service productivity, which is badged as a National Statistic. The quarterly series offers a timelier measure, as the annual series has a significant time lag but holds quality adjustments constant as these are updated annually.
Compared with the same quarter in the previous year, productivity of total public services fell by 4.8% in Quarter 1 (Jan to Mar) 2020 as over this period, inputs increased by 3.2% while output fell by 1.6%.
To show this more clearly, as inputs growth has a negative effect on productivity growth, Figure 5 inverts the growth rates of inputs. As such, the sum of the stacked bars (inverted inputs and output) is equal to productivity growth.
An increase in government healthcare expenditure was the main source of total inputs growth, whereas a fall in healthcare and education output were the main causes of the fall in total output.
Our output measures are noticeably impacted by the coronavirus (COVID-19) pandemic. In particular, the impact of the coronavirus on healthcare outputs is large and complicated. In our health measures, we have to consider the reductions in GP appointment services and attendance at accident and emergency alongside the scaling back of non-emergency surgery ("elective surgery"), the cancellation and postponement of outpatient activity and dental and ophthalmic services, and the increase in critical care activity. In addition, an adjustment to our education measurement methodology was introduced to take into consideration the widespread school closures during March 2020 and a shift to "remote learning".
It is important to note that our quarterly productivity statistics do not adjust for the quality of services delivered. Output estimates use data on changes in the quantity of various services delivered but do not include data on changes in the relative quality of these services. Data including quality adjustment for 2020 will be published in two years' time, as many of these quality factors reflect long-term outcomes where data are collected with a lag.
Placing these movements in the context of a longer time series, Figure 6 shows total public service productivity fell by 0.1% in 2019, the first fall in annual productivity since 2010. Inputs were estimated to have grown by 3.6%; this is greater than the estimated growth in output of 3.5%. This estimate should be treated with caution until the annual estimate for 2019 is available, as these data do not currently include adjustments for changes in the quality of services delivered.
Please note that the quarterly estimate in Quarter 1 2020 does not affect the experimental annualised productivity estimate in 2019.
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Unit labour costs (ULCs) capture the full costs of labour incurred in the production of a unit of economic output; they reflect the relationship between the cost of labour and the value of the corresponding output. If increases in labour costs are not reflected in the volume of output, this can put upward pressure on the prices of goods and services. Hence, ULCs are a closely watched indicator of domestically generated inflationary pressure in the economy. They are usually expressed as a ratio of the total labour compensation per hour worked, to the output per hour worked.
In Quarter 1 (Jan to Mar) 2020, ULCs increased by 6.2% compared with the same quarter in the previous year. This is the greatest change in ULCs since Quarter 4 (Oct to Dec) 2006. The increase was driven by a fall in gross value added (GVA) over the quarter. During the period of the lockdown covered by this release, government programmes for furloughed workers have helped keep labour costs elevated despite the fall in production activities. This has also had a notable effect on ULCs this period.
This latest change follows a period of fairly stable ULCs growth, which has occurred since Quarter 2 (Apr to May) 2016. Prior to this, ULCs growth had been volatile.
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The measure of labour productivity output used in these statistics is the chained volume (real) measure of gross value added (GVA) at basic prices.
Multi-factor productivity (MFP) estimates are compiled using the growth accounting framework, which decomposes changes in economic output, in this case GVA of the UK market sector, into contributions from changes in measured inputs: labour, capital and a residual element known as MFP. For more information, see our simple guide to MFP and our MFP QMI.
Additionally, we have previously published details on how labour productivity and MFP measures differ.Nôl i'r tabl cynnwys
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