UK labour productivity, as measured by output per hour, is estimated to have grown by 0.7% from Quarter 3 (July to Sept) 2017 to Quarter 4 (Oct to Dec) 2017; this is the second quarter in a row that output per hour grew, after falling in the first half of 2017.
By contrast, output per worker and output per job both grew by 0.1% between the third and fourth quarter; the difference between these two measures and output per hour reflects a fall in average hours per job and per worker.
In output per hour terms labour productivity grew in both services and manufacturing industries; services productivity grew by 0.3% on the previous quarter and manufacturing productivity grew by 2.6%.
Earnings and other labour costs growth outpaced productivity growth, resulting in unit labour cost (ULC) growth of 2.1% in the year to Quarter 4 2017, up from the 1.4% growth in the year to Quarter 3 2017.
This release reports labour productivity estimates for Quarter 4 (Oct to Dec) 2017 for the whole economy and a range of industries, together with estimates of unit labour costs. Productivity is important as it is considered to be a driver of long-run changes in average living standards.
This edition forms part of our quarterly productivity bulletin, which also includes an overarching commentary, quarterly estimates of public service productivity and articles on productivity-related topics and data.
Labour productivity is calculated by dividing output by labour input. Output refers to gross value added (GVA), which is an estimate of the volume of goods and services produced by an industry, and in aggregate for the UK as a whole. Labour inputs in this release are measured in terms of workers, jobs (“productivity jobs”) and hours worked (“productivity hours”).
This release also reports estimates of unit labour costs (ULCs), which capture the full labour costs – including social security and employers’ pension contributions – incurred in the production of a unit of economic output. Labour costs make up around two-thirds of the overall cost of production of UK economic output. Changes in labour costs are therefore a large factor in overall changes in the cost of production. 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, therefore this is a closely watched indicator of inflationary pressure in the economy.
The equations for labour productivity and ULCs can be found in the Quality and methodology section of this release.
The output statistics in this release are consistent with the latest Quarterly national accounts published on 29 March 2018. Note that productivity in this release does not refer to gross domestic product (GDP) per person, which is a measure that includes people who are not in employment.
The labour input measures used in this release are consistent with the latest labour market statistics as described further in the Quality and methodology section of this bulletin. Data in this release reflect revisions to GVA and income data incorporated in the latest Quarterly national accounts.
Unless otherwise stated all figures are seasonally adjusted.
The next labour productivity bulletin (released 6 July 2018) will include some analysis of a number of methodological changes, previously consulted upon and agreed at user group meetings held last year and earlier this year. This will precede the adoption of these methods changes in the following release in October 2018. More information on these will be included alongside the next bulletin.Nôl i'r tabl cynnwys
Labour productivity on an output per hour basis – our headline measure – grew by 0.7% in Quarter 4 (Oct to Dec) 2017. This was the second quarterly increase in a row and left productivity 1.8% above its peak in Quarter 4 2007 prior to the economic downturn. Productivity for Quarter 4 2017 was 1.0% above the post-downturn peak that occurred in Quarter 4 2016. By contrast, output per worker and output per job both grew by 0.1% between the third and fourth quarter; the difference between these two measures and output per hour reflects a fall in average hours per job and per worker.
An increase of 0.7% is slightly higher than the average quarterly rate of productivity growth in the decade prior to the 2008 economic downturn, since when UK productivity growth has been subdued. This sustained stagnation, often referred to as the “productivity puzzle”, contrasts with patterns following previous UK economic downturns when productivity initially fell, but subsequently recovered to the previous trend rate of growth. There is wide and varied economic debate regarding the causes of this puzzle and further analysis of recent UK productivity trends can be found in the January 2016, May 2016 and June 2016 Economic Reviews, as well as in several standalone articles including: What is the productivity puzzle?, The productivity conundrum, explanations and preliminary analysis and The productivity conundrum, interpreting the recent behaviour of the economy.
This puzzle is shown in Figure 1, which presents two alternative measures of productivity – output per hour and output per worker – alongside their projected 1994 to 2007 trends. Following years of steady growth, each measure peaked prior to and fell during the economic downturn. However, due to a strong labour market performance accompanying a relatively weak recovery in output growth, productivity has not returned to its pre-downturn trend. Productivity in Quarter 4 2017, as measured by output per hour, was 16.4% below its pre-downturn trend – or, equivalently, productivity would have been 19.6% higher had it followed this pre-downturn trend1.
Figure 2 breaks down the growth in productivity between Quarter 1 (Jan to Mar) 2008 and Quarter 4 2017 into contributions from different industry groupings and an “allocation effect” due to changes in the share of output and labour in each grouping. All else being equal, stronger (weaker) productivity growth in any given industry, or a movement of output and labour towards (away from) higher productivity industries will tend to increase (reduce) aggregate productivity growth.
Non-financial services were the main positive contributor to productivity growth over this period, partly offset by negative contributions from non-manufacturing production and finance. The negative allocation effect – suggesting that output and labour have been moving away from higher to lower productivity industries in recent years – partly captures the falling share of output in mining and quarrying, which has among the highest levels of productivity of UK industry; partially a result of the falling reserves of oil and gas in the North Sea. Although negative for the period as a whole, the allocation effect was initially positive following the downturn, but turned negative in recent years.
Notes for: Labour productivity up for second quarter in a row
- Differences between these two measures are due to differences in the denominator used in the calculation. Using the actual output per hour series as the denominator, rather than the trend series, results in a higher percentage gap. This is due to the actual series being lower than the trend series post-downturn.
Services output per hour grew by 0.3% in Quarter 4 (Oct to Dec) 2017, with output growing faster than hours worked over the period. In manufacturing, labour productivity grew by 2.6%, with output growth combining with a fall in hours worked over the quarter.
Figure 3 examines longer-term trends, showing output per hour and its components since Quarter 1 (Jan to Mar) 2008. Services are represented in the first panel, while manufacturing is represented in the second. Manufacturing output per hour has been more volatile than services in recent years. This reflects a degree of divergence in manufacturing between gross value added (GVA) and hours, most noticeable in 2009 and 2011 to 2012, whereas in services, GVA and hours follow fairly similar trends.
Nôl i'r tabl cynnwys
Unit labour costs (ULCs) reflect the full labour costs, including social security and employers’ pension contributions, incurred in the production of a unit of economic output. Changes in labour costs are a large factor in overall changes in the cost of production. If increased costs are not reflected in increased output, for instance, this can put upward pressure on the prices of goods and services – sometimes referred to as “inflationary pressure”. ULCs grew by 2.1% in the year to Quarter 4 (Oct to Dec) 2017, reflecting a larger percentage increase in labour costs per hour than output per hour. This was the largest increase in ULCs since Quarter 1 (Jan to Mar) 2017.
Figure 4 shows changes in ULCs since Quarter 1 2008 on a quarter on same quarter a year earlier basis. The bars represent the contribution to changes in ULCs from changes in labour costs per hour and changes in output per hour. Holding other factors constant, increasing output per hour reduces ULCs – as total labour costs remain constant while output rises. As a result, output per hour has its sign reversed in Figure 4. In this presentation, positive (negative) output per hour growth has a negative (positive) effect on ULC growth.
While growth in ULCs has been broadly positive since the onset of the economic downturn, averaging around 1.6% since Quarter 1 2008, there has been substantial variation during this period. During the recent economic downturn, ULCs began to grow at a relatively high rate, reaching a peak of 6.0% by the end of the downturn in Quarter 2 (Apr to June) 2009 and remaining elevated until Quarter 1 2010. Figure 4 shows that the initial increase in ULC growth during the downturn was driven by falling output per hour, but from Quarter 2 2009 onwards, increasing labour costs per hour were the driving factor. Following the downturn, growth in ULCs began to slow, eventually becoming negative in Quarter 4 2010.
Following a period of low or negative growth, ULC growth has been around 2% for the past two years. This increase broadly reflects higher hourly labour cost growth, with relatively little offsetting output per hour growth.
Nôl i'r tabl cynnwys
This release reflects revisions to gross value added and income data resulting from quarterly national accounts, affecting quarters in 2017. Very small revisions to jobs and hours data since 2011 reflect improved estimates of the distribution of jobs across industries, concentrated in agriculture. Revisions resulting from seasonal adjustment affect all periods, where seasonal adjustment is applied.
Methodological changes which had previously been scheduled for introduction in the current release have been postponed until later in the year, to allow more time for quality assurance.Nôl i'r tabl cynnwys
The measure of output used in these statistics is the chained volume (real) measure of gross value added (GVA) at basic prices, with the exception of the regional analysis in Table 9, where the output measure is nominal GVA (NGVA), using the income approach. These measures differ because NGVA is not adjusted to account for price changes; this means that if prices were to rise more quickly in one region than the others, then the measures of productivity for that region could show relative growth in productivity compared with other regions purely as a result of the price changes.
Labour input measures used in this bulletin are known as “productivity jobs” and “productivity hours”. Productivity jobs differ from the workforce jobs (WFJ) estimates, published in Table 6 of our Labour market statistical bulletin, in three ways:
to achieve consistency with the measurement of GVA, the employee component of productivity jobs is derived on a reporting unit (RU) basis, whereas the employee component of the WFJ estimates is on a local unit (LU) basis
productivity jobs are scaled so industries sum to total Labour Force Survey (LFS) jobs – note that this constraint is applied in non-seasonally adjusted terms; the nature of the seasonal adjustment process means that the sum of seasonally adjusted productivity jobs and hours by industry can differ slightly from the seasonally adjusted LFS totals
productivity jobs are calendar quarter average estimates, whereas WFJ estimates are provided for the last month of each quarter
Productivity hours are derived by multiplying employee and self-employed jobs at an industry level (before seasonal adjustment) by average actual hours worked from the LFS at an industry level. Results are scaled so industries sum to total unadjusted LFS hours and then seasonally adjusted. Labour productivity is then derived using growth rates for GVA and labour inputs in line with the following equation:
Industry estimates of average hours derived in this process differ from published estimates (found in Table HOUR03 in the Labour market statistics release), as the HOUR03 estimates are calculated by allocating all hours worked to the industry of main employment, whereas the productivity hours system takes account of hours worked in first and second jobs by industry.
Whole-economy unit labour costs (ULCs) are calculated as the ratio of total labour costs (that is, the product of labour input and costs per unit of labour) to GVA. Further detail on the methodology can be found in Revised methodology for unit wage costs and unit labour costs: explanation and impact.
The equation for growth of ULCs can be calculated as:
Manufacturing unit wage costs are calculated as the ratio of manufacturing average weekly earnings to manufacturing output per filled job. On 28 November 2012 we published Productivity measures: sectional unit labour costs, describing new measures of ULCs below the whole-economy level and proposing to replace the currently published series for manufacturing unit wage costs with a broader and more consistent measure of ULCs.
A research note, Sources of revisions to labour productivity estimates, is available, and further commentary on the nature and sources of the revisions introduced in this quarter is available in the UK productivity bulletin – introduction.
The Labour productivity Quality and Methodology Information report contains important information on:
- the strengths and limitations of the data and how it compares with related data
- uses and users of the data
- how the output was created
- the quality of the output including accuracy of the data
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