- This article covers the period until the end of 2019, so precedes the coronavirus (COVID-19) pandemic.
- UK total public service productivity fell by 0.2% in 2019, the first time it has fallen in eight years.
- Total inputs grew by 2.6%, mostly driven by healthcare and an increase in expenditure for “other” government services.
- Total quality-adjusted output grew by 2.4%, because of the contribution of healthcare, education, adult social care, and children’s social care.
- For healthcare, the largest service area by expenditure, quality adjusted productivity fell by 1.5%.
This article includes updated measures of non-quality-adjusted (NQA) and quality-adjusted (QA) output, inputs, and productivity of nine public service areas, in the UK between 1997 and 2019. All these statistics are based on a calendar year.
Our datasets linked to this publication provide more comprehensive detail on inputs, output and productivity, the estimates of quality adjustment, expenditure and revisions.
We recommend referring to the Improved methods for total public service productivity: total, UK, 2019 methodology, which provides commentary on the methodological changes that affect this article. Because of changes in data sources and methods, estimates for some public service areas are not directly comparable with previous annual estimates.
In addition, detailed information of the main concepts, output and inputs measures by service area are provided in the Sources and methods for public service productivity estimates.
Figures in this article cover up to the end of 2019, so do not include the months affected by the coronavirus (COVID-19) pandemic. However, some forward-facing data used in these statistics may be affected by the early part of the coronavirus pandemic.Back to table of contents
In 2019, public service inputs and output grew compared with the previous year. Since inputs grew faster than output (2.6% and 2.4% respectively), productivity fell by 0.2%. This is the first annual fall in public service productivity since 2010.
However, productivity growth over the last decade remained positive, averaging 0.4% per annum between 2009 and 2019. By comparison, total public service productivity declined between 1998 and 2008.
Total public service output and inputs are calculated by aggregating output and inputs of nine service areas based on their share of expenditure, as explained in our Sources and methods for public service productivity estimates methodology. A larger expenditure share means the service area has a larger contribution to the overall productivity statistic. Healthcare had the largest expenditure share (37.9%), followed by education (17.6%) and then “other” government services (17.1%). These include a variety of smaller activities such as general government services, economic affairs, environmental protection, housing, recreation, and other public order and safety.
The contributions to growth in Figure 4 reflect the productivity growth for the service areas measured directly, weighted by their expenditure share each year. In 2019, healthcare had the largest negative contribution to total public service productivity.
Police, defence, and “other” government services are not included in Figure 4, since they are measured using the “output-equals-inputs” convention and, consequently, they have no impact on estimates of total public service productivity growth.
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Healthcare represents the largest service area included in public service productivity.
Public service healthcare productivity fell by 1.5% in 2019, following near zero growth in the previous year. The fall observed in 2019 (the biggest since 2009) was driven by 2.7% growth of inputs and 1.1% growth of output.
While the figures in Figure 5 are calculated on a calendar-year basis, most of the data used in healthcare productivity is produced using financial year data. As a result, falls in output in the financial year ending 2020 may have some effect on the 2019 figures. This may have been partly because of the early part of the coronavirus (COVID-19) pandemic.
Please note that new healthcare output data has been used to measure hospital and community healthcare services (HCHS) output for 2019.Back to table of contents
Education is the second largest service area in public service productivity by expenditure share.
Productivity of UK education services continues its positive trend of the last five years, increasing by 0.9% in 2019. This was caused by output growth of 0.9%. Inputs growth was close to 0%.
Both quality-adjusted and non-quality-adjusted output of education have historically grown over time, with a few exceptions.
The methodology of quality adjustment for education productivity has been recently updated.Back to table of contents
Public order and safety (POS) include a range of services. You can find out more in our Sources and methods for public service productivity estimates methodology. Where applicable, output is also adjusted for quality.
Productivity for POS increased by 4.2% in 2019, which represents the highest output growth on record. Quality adjusted output fell by 2.2%, while inputs fell by 6.1%.
Quality measures have had a negligible impact on output growth. Prison safety statistics remained stable, and courts timeliness data slightly improved. Data on reoffending were not incorporated on account of comparability issues caused by the coronavirus (COVID-19) pandemic.
Data on proven reoffending from the Ministry of Justice has historically been used, alongside other measures, to quality adjust output in the criminal justice system. However, data on reoffending for the last quarter of 2018 and all of 2019 have been affected by the coronavirus pandemic, as it looks at proven reoffending that occurs within the following year. Levels of reoffending for the 2019 cohort have fallen significantly, because of the impact of lockdowns and a slowdown in the rate at which offenses are proven. It is therefore more difficult to compare 2019 reoffending rates with earlier data. The Office for National Statistics (ONS) has therefore made a small adjustment to reoffending data in Quarter 4 (Oct to Dec) 2018 to account for this by holding reoffending rates constant for the 2019 period. This is on the basis that it cannot be used as a comparable quality measure during the coronavirus period.
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Police, defence, and other government services are service areas in which all output is indirectly measured. In 2019, police inputs growth fell by 0.8%, making this the fifth consecutive year of negative growth. Defence inputs grew by 6.4% in 2019, recovering from a fall of 0.8% in 2018.
In 2019, other government services saw the biggest change of the three indirectly measured services, increasing by 7.0%.
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Public service productivity estimates: education
Dataset | Released 22 February 2022
Inputs, output and productivity indices and growth rates for education service. Includes estimates of quality adjustment, sub-service expenditure and revisions.
Public service productivity estimates: total public service
Dataset | Released 22 February 2022
Inputs, output and productivity indices and growth rates for total public services. Includes estimates of quality adjustment, service expenditure and revisions.
Services delivered by or paid for by the government (central or local). If paid for by the government, they may be delivered by a private body. For example, the provision of nursery places by the private sector, where these places were funded by the government.
Direct output measurement
Using a cost-weighted activity index to estimate the non-quality-adjusted of a service provided. For example, the number of students in state schools, adjusted for attendance to produce an estimate of total hours of schooling delivered each year. Differs from indirect output measurement, where output is assumed equal to inputs.
A statistical estimate of the change in the quality of a public service, using an appropriate metric. For example, safety in prisons as part of the public order and safety adjustment.
The Classification of the Functions of Government (COFOG) is the structure used to classify government activities. It is defined by the United Nations Statistics Division.
The way we refer to the breakdown of public services into nine areas, closely following COFOG.
Also referred to as “goods and services”, or “intermediate consumption” (the UK National Accounts term). Intermediate inputs include goods and services used up in the provision of a public service, such as utilities, energy, professional services and medical supplies.
A price index used to remove inflation effects from current price estimates of expenditure to provide a volume estimate.Back to table of contents
Productivity is the measure of how many units of output are produced from one unit of inputs. It is calculated by dividing total output by total inputs. Details of inputs and output can be found in the Sources and methods for public service productivity estimates methodology.
Growth rates of output and inputs for individual service areas are aggregated by their relative share of total government expenditure (expenditure weight) to produce estimates of total public service output, inputs and productivity. Service areas are defined by Classification of the Functions of Government (COFOG) rather than administrative departments or devolved administrations. As a result, estimates presented cannot be taken as direct estimates of departmental productivity. Lastly, it should be noted that these estimates do not measure, for example, the value for money in public services, or the true effectiveness of the services (quality adjustment includes some measurement of this, but coverage is limited).
Estimates of public service productivity are published each year, and on a calendar-year basis for consistency with the UK National Accounts. There is a two-year time lag associated with the estimates, because of the timeliness of our data, which come from administrative sources. This means that they meet certain quality criteria, listed in the Code of Practice from the UK Statistics Authority.Back to table of contents
The authors of this publication are Sanjana Arora, Jon Gardner, Richard McFerran, Meera Parmar, Dominic Thomas and Sara Zella. We are grateful to colleagues in various government departments for making their data available for the compilation of these statistics, and providing helpful comments.Back to table of contents
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