Measures of output (GVA) and measures of the labour market (hours, workers, and jobs) are both subject to rapid and substantive change: where productivity is a ratio of these two measures this means this measure can exhibit unusual but short-term patterns.
Users are advised to apply caution in using these data: We recommend comparing productivity measures with the previous year to capture the medium-term structural nature of productivity change and reduce the impact of short-term volatility.
Labour productivity for Quarter 2 (Apr to June) 2020, as measured by output per hour, fell by 1.8% when compared with the same quarter in the previous year.
In Quarter 2 2020, output per worker fell by 21.1% compared with the same quarter in the previous year; this is the steepest fall on record and is larger than that observed for output per hour because of the impact of the furlough scheme that retains employees as workers even though they work zero hours.
When compared with the previous quarter (Quarter 1 2020), output per hour fell by 2% while output per worker fell by 19%, again reflecting the impact of the furlough scheme.
These statistics are published in line with updated and reweighted labour market data.
Our headline measure of productivity is output per hour growth compared with the same quarter in the previous year. We normally use “quarter-on-year” comparisons as they give a better indicator of longer-term productivity trends.
The coronavirus pandemic, and the government response to it began to affect the UK economy at the end of Quarter 1 (Jan to Mar) 2020. Quarter 2 (Apr to June) 2020 is the first quarter that has been affected from start to finish.
Output per hour fell by 1.8% in Quarter 2 2020, the largest fall since Quarter 2 2009. This was driven by GVA falling faster than hours worked. Compared with the previous year, GVA fell by 21.5% and hours worked fell by 20%. GVA is a measure of the production of goods and services in the economy and is closely aligned to gross domestic product (GDP).
Labour productivity, as measured by output per worker, decreased by 21.1% in Quarter 2 2020 compared with the same quarter in the previous year. Historically, output per hour and output per worker have been much closer aligned, but the Coronavirus Job Retention Scheme (CJRS) has resulted in a large disparity between the two measures.
The CJRS allows companies to furlough workers, keeping them employed and allowing them to work zero hours, as described in Coronavirus and the effects on UK GDP. The total number of workers fell by 0.4% on the previous year, which is a much smaller movement than would be expected in response to a 21.5% fall in GVA.
This is the largest output per worker fall on record, but the furlough scheme, by design, makes this an extremely difficult period to compare with the historical data, and strengthens our argument that output per hour should be considered the headline measure.
|Quarter on same quarter in previous year||Quarter on previous quarter|
|Output per hour||Output per worker||Output per hour||Output per worker|
|(growth %)||(growth %)||(growth %)||(growth %)|
Download this table Table 1: Headline labour productivity indicators for the UK.xls .csv
Output per hour fell by 2% during Quarter 2 2020 compared with the previous quarter. This is the largest fall since Quarter 1 1974. During the same period, output per worker fell by 19%.
Since the 2008 to 2009 economic downturn, both employment and total hours have demonstrated growth, which over the period has broadly kept pace with the growth in GVA causing productivity to grow slowly by historical standards.
The consequences, such as government interventions, of the coronavirus pandemic have resulted in a fall in economic activity. Figure 2 highlights how GVA and hours worked have fallen at historic rates. The government furlough scheme has resulted in total employment broadly staying in line with pre-lockdown levels.
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We have compiled Experimental Statistics to demonstrate the effect of the government’s furlough schemes on labour productivity. Accurately capturing data for furloughed workers has been a challenge in the lockdown period, as details on the government’s furlough schemes were not required questions for long-established surveys. For example, this is the case for the Labour Force Survey (LFS), a main source of hours data for labour productivity estimates.
In the absence of direct furloughed questions on the LFS, extra guidance was given to interviewers on how to classify those mentioning furlough as a reason for doing fewer hours than usual in the reference week. The guidance states that furlough responses should be directed toward the “laid off/short time/work interrupted by economic or other causes” response category of the “Yless20” variable. Respondents choosing this response category, or one of five other response options, then get asked if their reason for working fewer hours than usual was because of the coronavirus (COVID-19).
Based on the absence of other furlough questions for the April to June 2020 period, we think that those employees answering “laid off/short time/work interrupted by economic or other causes”, “Other personal/family reasons” or “Other reasons” to “Yless20” and “Yes” to the reason being because of the coronavirus is the best possible estimate we have for furloughed employees on the LFS.
It is possible that this method may include people that are not on furlough but are away for other reasons related to the coronavirus, but will also fail to include those on furlough that do not consider it their main reason for doing fewer hours.
Despite these filters, there is a notable difference in the furlough estimates from LFS responses and experimental data published by Her Majesty’s Revenue and Customs department (HMRC). There could be several reasons for this, including those noted above. It is also important to note the HMRC data count “employments”, which are equivalent to jobs, whereas the LFS figures count “workers” and any worker could have more than one job.
In order to demonstrate the possible effects of the furlough schemes, Figure 3 shows output per job figures including and excluding furloughed jobs. These data are distinct and should not be confused with the output per hour and output per worker statistics quoted elsewhere in this release.
While the output per job series are National Statistics, the data excluding furloughed jobs are experimental. The experimental series uses HMRC data averaged across the quarter to determine the effect to which jobs have been affected and takes this from the total jobs figures.
The overall effect of excluding furloughed workers, as demonstrated in Figure 3, is an increase in output per job. This is because the output in the quarters affected by the lockdown are shared across fewer jobs. The effect is large enough to change the direction of output per job and to bring it above 2018 productivity levels on this metric.
The data presented in Figure 3 should be used cautiously. Our preferred measure of labour productivity is output per hour because hours worked data takes account of different working patterns among workers. Jobs data fail to do this in a meaningful way – there is no indication from jobs data how much time a worker spends at a job. If part-time jobs are disproportionately affected by the lockdown then it is sensible to assume that hours data would fall to a lesser degree than jobs, resulting in a less significant shift in the output per hour data for the period.Back to table of contents
This estimate of UK productivity uses revised data for the Labour Force Survey (LFS) for the first half (January to June) of 2020. We will release full labour productivity and multi-factor productivity statistics soon.
The measure of labour productivity output used in these statistics is the chained volume (real) measure of gross value added (GVA) at basic prices.
All data in this release were collected during the lockdown that was imposed because of the coronavirus (COVID-19). During this period there have been additional challenges to collecting labour market data and estimating gross domestic product (GDP). As a result, the estimates are subject to increased uncertainty and there is an increased likelihood of larger revisions than usual in future releases of these measures.Back to table of contents
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