Published on 26 November 2021
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New insights into the UK’s productivity performance

How do we measure productivity? Dr Jen-Chung Mei and Adam Muhtar delve into some recent statistics shedding new light on the UK’s “productivity puzzle”.

Economists have long noted the central role that productivity – the value of output produced per unit of resources put in – plays in determining the trajectory of an economy and consequently how well off a society is. Productivity is linked to higher profits, rising wages, larger tax revenues, and stronger public finances, to name a few. As Andrew Haldane, the former Chief Economist of the Bank of England, in a formal speech in 2018 mentioned: “Productivity is what pays for pay rises. And productivity is what puts the life into living standards.” Yet for such an important metric of our economic success, measuring productivity is not as straightforward as it might seem. 

A key practical issue in understanding productivity is the need to ensure the comparability of the measure of output over time: statistical detail is important. Since inflation causes the prices of goods and services sold in economy as a whole to change, simply taking headline figures such as annual profits in pounds (a part of Gross Value Added (GVA) in the national accounts statistics) glosses over the effects of these price changes. Measurement of output therefore needs to be adjusted by taking out the effects of inflation to make meaningful comparisons of productivity dynamics across time periods. These price deflators are applied to nominal measures to obtain the output in ‘real’ terms. 

However, obtaining appropriate price deflators can be challenging; there are different sets of price changes for different industries and at different stages of the production cycle. For instance, the price changes for cars set by car manufacturers may be different to the price fluctuations for its production input costs, such as steel, rubber, and electronic components. To further complicate matters, the input and output price fluctuations are different for different industries – inputs of a restaurant differ from the inputs used by car manufacturers. The complex compilation of input and output price indices entails intensive data gathering exercises.

Prior to 2021, the UK’s Office for National Statistics’ (ONS) method of estimating comparable output measurements was the ‘single extrapolation approach’. This approach essentially sidesteps these price variation issues by extrapolating the Gross Value Added (GVA) for a selected base year in line with the growth rate of output volume over time. By assuming that output in volume terms increases in a constant ratio to GVA in pounds, this method is prone to inaccuracies – particularly in the face of supply side shocks where the price of specific products are impacted (for example, an oil price shock or price pressures due to supply chain bottlenecks).

However, the latest improvement in productivity statistics from the ONS takes into account the impact of input price changes such as these through the application of the ‘double deflation’ method. Essentially, for every industry, the current price figure for its output is deflated by a price index specific to that output and, separately, the current price estimate of its inputs is also deflated by an appropriate input price index. This double deflation method is widely recognised as the best approach.

These adjustments have shed new light on productivity dynamics in the UK over the past few decades. An ongoing concern among economists is the “UK’s productivity puzzle”, a reference to the fact that the UK’s productivity appears to have stagnated since around the time of the 2008 Global Financial Crisis.

Table 1: Average annual growth rate of UK GVA using the new and old methods

Annual GVA growth rate





Decline 2008-2019
to 1997-2007


New double inflation method 2.57% 1.05% -1.52%
Old single extrapolation method 2.85% 0.02% -2.83%

Notes: GVA here is expressed using chained volume measurements in basic prices. Estimates using the double deflation method are based on the ONS’s October 2021 Blue Book update, while the estimates using the single extrapolation method are based on the ONS’s July 2021 Blue Book update. Source: ONS and authors’ calculation.

Figure 1: Revision to average annual productivity growth rates

Revision to average annual productivity growth rates

Source: ONS and authors’ calculation based on 2021 November Blue Book revision and 2020 November Blue Book update.

The new measurements using the double deflation method from the ONS may indicate that this problem is somewhat less severe than previously thought. Table 1 shows the Impact of introducing double deflation to GVA, the output measure used in productivity calculations. The growth rate of GVA has been revised up from 2008 onwards, compared with the previous statistics.

Figure 2: Revisions to annual labour productivity growth rates by sector 1998-2019

Revisions to annual labour productivity growth rates by sector 1998-2019

Notes: The top panel represents the productivity growth gap between 1998-2007 and 2008-2019 (i.e., subtracting average growth rate of 1998-2007 from 2008-2019) in percentage change points. The bottom panel represents the differences in productivity growth rates between 2021 November Blue Book revision and 2020 November Blue Book update (average 1998-2019), distinguished between manufacturing and other sectors. 
Source: ONS and authors’ calculation based on 2021 November Bule Book revision and 2020 November Blue Book update.

Figure 1 shows that consequently the growth rate of productivity (measured as output per hour worked) has been revised up after 2008. Productivity growth was 1.2%-1.3% in 2016-2017 (blue dash) compared with just below 1% in the previous data (orange line).

In Figure 2, we also look at the comparison of productivity in different sectors of the economy between the new and old data. There are upward revisions broadly across UK industries’ productivity (top panel). The bottom panel further shows that the three largest upward revisions are the manufacturing of computers, electronics, wood and paper products, and textiles, wearing apparel. They have now an average annual growth rate in labour productivity of 9.7%, 5.4%, and 5.3% between 1997 and 2019 compared with 3.7%, 1.4%, and 1.3% previously. These adjustments are partly due to the changes in prices of inputs and output with the improved deflators.

What is notable is that the biggest upward revisions occur in manufacturing industries (bottom panel), although there have also been upward revisions for the IT, energy, agriculture, transport equipment, and recreation and culture sectors. At the same time there have been downward revisions to the productivity of many service sectors of the economy (shown in the lower panel of Figure 2) – which were already in some cases among the biggest contributors to the productivity gap comparing 1998-2007 to 2008-2019 (the upper panel of Figure 2). The main driver of the changes has been the impact of double deflation on the price deflator for telecommunications services  (ONS Productivity Measure Section 5). Thanks to work co-authored by the Bennett Institute’s Professor Diane Coyle, its real output and productivity have been significantly revised up, but as it is a key input into many services such as business services and finance, their real GVA and productivity have been revised down.

Figure 3 Revision to annual productivity level and growth through manufacturing and service sectors 1998-2019

Revision to annual productivity level and growth through manufacturing and service sectors 1998-2019

Notes: The Figure represents the productivity level based on the index 2016 = 100, for all manufacturing and service sectors, respectively. Manufacturing sectors include Food products and Beverages; Textiles, Apparel, Leather; Wood, Paper products; Coke, Refined Petroleum; Chemical, Pharmaceutical; Rubber, Plastics, Basic metals, Metal product; Computer, Electronic; Other Machinery and Equipment; and Transport Equipment. Service sectors include Whole Sale and Retail; Transport and Storage; Hotels and Catering; Finance and Insurance; Real Estate; Business Services; Admin Services; Public Services; Recreation and Culture; and Other Services. 
Source: ONS and authors’ calculation based on 2021 November Bule Book revision and 2020 November Blue Book update.

The latest insights from ONS paint a subtly but significantly different picture of the narrative commonly told about the UK economy’s transition from one driven by manufacturing to one whose dynamic sectors are services such as finance and professional services. Figure 3 shows the old (dashed) and new (solid) level of labour productivity in manufacturing and services as a whole (in both cases rebased to 100 in 2016). It is immediately evident that manufacturing productivity has grown faster than previously shown, according to the latest set of statistics. While the shift in the share of total output accounted for by services remains the overarching story, manufacturing productivity performance has been better than we thought.

While the double deflation method is still in its early phases of development and application, the richer economic picture brought about by these new estimates underlines the importance of getting the data right—a central component of sound evidence-based research and policies. Understanding the UK’s productivity puzzle requires a deeper understanding of the intricacies of measurement and the evolution of prices and output in different parts of the economy.

The Bennett Institute’s Research on Sectoral Productivity is funded by the Gatsby Foundation.


The views and opinions expressed in this post are those of the author(s).


Adam Muhtar

Affiliated Researcher

Adam Muhtar is a Data Scientist at the Bank of England, working on projects that aim to generate actionable insights from high-dimensional unstructured data using natural language processing, network science,...

Dr Jen-Chung Mei

Dr Jen-Chung Mei is a Lecturer in Economics at Westminster Business School, and a member of the Productivity Institute. He was a Postdoc Research Associate at the Bennett Institute for Public...

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