This release contains data on economic output and labour productivity for each English local enterprise partnership (LEP). Economic output is expressed as nominal gross value added (GVA). Productivity is measured as GVA per hour worked and GVA per filled job.
Over the period 2008 to 2015, which covers the economic downturn and subsequent recovery, Oxfordshire LEP (3.9%) and London LEP (3.8%) had the highest average annual growth rates for nominal GVA. The lowest average annual growth over this period was Humber LEP (1.0%).
In 2015, the London LEP had the highest productivity in terms of GVA per hour worked (31% above the UK average). The 6 LEPs with the highest GVA per hour worked were all located within the regions of the Greater South East. The lowest productivity was in Stoke-on-Trent and Staffordshire LEP at 20% below the UK average.Back to table of contents
Local enterprise partnerships (LEPs) are partnerships in England between local authorities and businesses. They were created in 2011 and their role is to help shape local economic priorities and undertake activities to encourage local economic growth and the creation of jobs. There are 39 LEPs. Every local authority in England belongs to at least 1 LEP. However, some local authorities belong to more than 1 LEP. Details on the LEPs geography are reported in the quality and methodology section.
This release provides data on economic output and labour productivity for each LEP. The measures included are explained in this section in some detail.
Economic output is measured by nominal gross value added (GVA) income approach (I). GVA (I) data by industry (11 industrial sectors) and GVA (I) per head are also included. Note that GVA data are based on a nominal measure in current prices and have not been adjusted to account for the impacts of inflation.
GVA (I) data for LEPs have been produced to be consistent with our existing regional GVA (I) data that are published annually in December for the Nomenclature of Territorial Units for Statistics (NUTS) geographies. As such, these LEP GVA data carry the National Statistics designation. More detail on the approach adopted to produce GVA (I) for LEPs is available in the methodology section.
The latest data available for all measures are for calendar year 2015. A time series with annual data back to 1997 is provided in the accompanying datasets. These data on economic output for LEPs complement our December 2016 regional GVA (I) publication and update our February 2016 GVA for LEPs release.
Labour productivity for LEPs is measured by GVA per hour worked and GVA per filled job. GVA per hour worked divides GVA (I) by the total hours worked by the workforce in the LEP. GVA per filled job divides GVA (I) by the number of jobs. The preferred measure of labour productivity is GVA per hour worked as it takes into account different working patterns. The section on interpreting the data provides more information to explain why.
The LEPs productivity data in this article are compiled to be consistent with the regional productivity data for NUTS1 regions as published in the quarterly Labour productivity statistical bulletin. The LEPs productivity data are Experimental Statistics. For more information about Experimental Statistics, see the guide on our website.
Annual data for GVA per hour cover the period 2004 to 2015. Data for GVA per job are available from 2002 to 2015. All data are provided in the datasets accompanying this publication. These data on labour productivity for LEPs complement our January 2017 release of regional and sub-regional productivity in the UK.Back to table of contents
To monitor relative economic performance in an area we suggest using the Total gross value added (GVA) measure when examining growth in overall output and the GVA per hour worked measure when assessing productivity. By contrast, we recommend that care is taken when using the GVA per head measure. While it can be an alternative proxy for economic performance in some cases, it can also be a misleading indicator on occasions, particularly when used for areas with high net commuting flows.
Total GVA growth rates can be used as an indicator for a region’s annual economic performance. They show whether or not a local enterprise partnership (LEP) has grown and how fast compared with others in that year. Areas with the highest Total GVA growth rates over time will see their share of UK economic output increase.
GVA per head is calculated as economic activity in a region divided by the number of people living there. Note, however, there are some limitations to its use as a measure of economic performance. In particular:
- GVA per head divides a workplace-based numerator (GVA) by a residence-based denominator (residential population), so this measure does not account for people commuting into and out of a region; as a result, for a region with very high net in-commuting flows, such as Inner London, the level of GVA per head would be extremely high, but this would be almost entirely due to the commuting flows and as such it would not be a suitable proxy for productivity or economic performance
- by including all the residential population and not just those who are in employment, the denominator includes residents who are not directly contributing to GVA; GVA per head is therefore impacted by the share of children, pensioners and others not economically active within a subregion
For these reasons, GVA per hour worked and GVA per filled job are the most appropriate measures of regional and subregional productivity. GVA per hour is the economic activity in a region divided by the number of labour hours of workers in that region. GVA per filled job is the ratio of economic activity in a region divided by the number of jobs worked in that region. These measures only count those directly employed in the production process, rather than the whole population as in GVA per head. Additionally, they use a workplace-based denominator, thus fully accounting for commuting impacts.
On productivity measures, the differences between GVA per filled job and GVA per hour worked are that GVA per filled job does not consider regional labour market structures or different working patterns, such as the mix of part-time and full-time workers, and job shares. For example, a region with higher GVA per filled job than GVA per hour may have a large proportion of full-time workers. For this reason, GVA per hour worked is a more comprehensive indicator of labour productivity and the preferred measure at subnational level.
For additional information on comparing the productivity data over a period of time, the choice of smoothed or unsmoothed data and interpreting data in index form, please see Section 7 of the January 2017 release of regional and sub-regional productivity in the UK.Back to table of contents
GVA for LEPS results
Table 1 shows the 5 fastest and 5 slowest growing local enterprise partnerships (LEPs) in England between 2014 and 2015, in terms of gross value added (GVA). Oxfordshire was the fastest growing at 5.3% in nominal terms, just ahead of Swindon and Wiltshire. Northamptonshire was the lowest ranked with zero growth during the year.
Table 1: Local enterprise partnerships with the highest and lowest gross value added growth rates, 2014 to 2015, England
|Local Enterprise Partnership||%|
|Swindon and Wiltshire||5.2|
|Greater Birmingham and Solihull||4.7|
|Thames Valley Berkshire||4.2|
|Cornwall and Isles of Scilly||4.1|
|Coventry and Warwickshire||0.4|
|Stoke-on-Trent and Staffordshire||0.3|
|Source: Office for National Statistics|
Download this table Table 1: Local enterprise partnerships with the highest and lowest gross value added growth rates, 2014 to 2015, England.xls (17.9 kB)
Oxfordshire’s growth was mainly driven by professional, scientific and technical activities and administration activities. Swindon and Wiltshire grew particularly strongly in the industries of wholesale and retail, transport, and accommodation and food services. Construction, and finance and insurance activities were the engines of growth in Greater Birmingham and Solihull. In contrast, growth was lower than average for public administration, education and health in Northamptonshire, and Stoke-on-Trent and Staffordshire.
The picture of growth changes strongly over longer time horizons. Table 2 shows the 5 fastest and 5 slowest growing LEPs in England between 2008 and 2015. That covers the period of the economic downturn and subsequent recovery up until the latest data. Table 3 shows the same information for the longer time period of 1997 to 2015.
Table 2: Local enterprise partnerships with the highest and lowest gross value added growth rates, 2008 to 2015, England
|Local Enterprise Partnership||Annual average growth rate, %|
|Coventry and Warwickshire||3.4|
|Cornwall and Isles of Scilly||1.6|
|York, North Yorkshire and East Riding||1.5|
|Stoke-on-Trent and Staffordshire||1.1|
|Source: Office for National Statistics|
Download this table Table 2: Local enterprise partnerships with the highest and lowest gross value added growth rates, 2008 to 2015, England.xls (17.9 kB)
Table 3: Local enterprise partnerships with the highest and lowest gross value added growth rates, 1997 to 2015, England
|Local Enterprise Partnership||Annual average growth rate, %|
|Cheshire and Warrington||4.2|
|West of England||4.2|
|Greater Cambridge and Greater Peterborough||4.1|
|Stoke-on-Trent and Staffordshire||2.8|
|Source: Office for National Statistics|
Download this table Table 3: Local enterprise partnerships with the highest and lowest gross value added growth rates, 1997 to 2015, England.xls (17.9 kB)
Tables 2 and 3 show that Oxfordshire and London were the fastest growing LEPs over the period 2008 to 2015 and also the longer period from 1997 to 2015. The lowest growth rates were in Humber for the period since 2008 and Black Country for the period since 1997 while Stoke-on-Trent and Staffordshire also had low growth rates through both periods.
Examining the data by industry, the strong growth in Oxfordshire and London has been due to above average growth in information and communication technology (ICT) (Oxfordshire) and finance and insurance, and real estate (London). Meanwhile, Humber, and Stoke-on-Trent and Staffordshire have had relatively low overall growth rates through the period due to below average growth in several large sectors including ICT, finance and insurance, and real estate.
When assessing these longer-term trends by area, it is useful to note that across England overall the sectors that have had the highest performance since 2008 are not always the same as those that performed strongest prior to 2008. In particular, finance and insurance grew very strongly between 1997 and 2008 but less well since 2008, while the opposite is true for the manufacturing sector. Meanwhile, the professional, scientific and technical activities, and administrative and support service activities sectors grew strongly in both periods.
Data for each of the 39 LEPs can be found in the dataset published with this output. These tables provide data for each LEP for total GVA, GVA per head and GVA split into 11 industrial sectors.
Productivity for LEPs results
Figure 1 shows the highest and lowest productivity levels for LEPs based on nominal gross value added (GVA) per hour worked for 2015.
In 2015, London was the LEP with the highest productivity, 31% above the UK average. The London LEP was followed by Thames Valley Berkshire, with a slightly lower productivity level of about 27% above national average. Thames Valley Berkshire has a specialism in the "Information and Communication" sector of the UK economy and this is likely to be a factor behind its strong productivity performance.
It is notable that the 6 top performing LEPs shown in Figure 1 were located within the regions of the Greater South East (East of England, South East, and London). In total, there were 10 LEPs with GVA per hour worked above the UK average.
All 6 LEPs with the lowest GVA per hour worked shown in Figure 1 had GVA per hour worked at least 15% below the UK average. Stoke-on-Trent and Staffordshire LEP had the lowest productivity, ranking 20% below UK average. This was followed by Cornwall and Isles of Scilly, and Lancashire.
Data for each of the 39 LEPs are included in the dataset published with this output. These tables provide data for each LEP for GVA per hour worked and filled jobs.Back to table of contents
The GVA (I) data in this release provide regional nominal gross value added (GVA) data that are consistent with the data published in the December 2016 release of Regional GVA (Income Approach). GVA data for 32 out of the 39 local enterprise partnerships (LEPs) have been created from simple additions of currently published NUTS3 regions. The remaining 7 LEPs, which have boundaries that divide NUTS3 regions, have been calculated using methodology consistent with that used to implement NUTS boundary changes in estimates of regional GVA (I).
- For a detailed discussion of the methodology used to calculate GVA (I), you can consult the Quality and Methodology Information (QMI) report for Regional GVA.
The QMI contains important information on:
- the strengths and limitations of the data
- the quality of the output: including the accuracy of the data and how it compares with related data
- uses and users
- how the output was created
GVA estimates are presented in current basic prices. They do not allow for different regional price levels or changes in prices over time (inflation). The income approach to calculating GVA produces only current price estimates because some income components cannot easily be converted into prices and volume (for example, gross operating surplus). Consequently, LEPs productivity measures are also on a nominal basis only. In other words, there is no separation of volume and price in the final output. As such, different levels of nominal productivity across different subregions will be impacted by any difference in prices between these subregions, in addition to differences in production volumes per input.
As with the national accounts, regional, sub-regional and local GVA estimates (including LEP GVA estimates) are calculated as reliably as possible. There is no easy way to measure the reliability of the estimates but we carry out consistency checks on data inputs, apply methods consistently and make use of local knowledge through consultation with important users. The estimates are partly based on sample surveys and the quality of the results therefore varies according to sample size. This means that the results for smaller regions are subject to a greater degree of uncertainty than those for larger regions.
Table B1 in the GVA (I) dataset accompanying this publication shows the LEPs boundaries used to compile the data in this report. In each case, the LEP boundaries used have been an amalgamation of one or more local authority. In other words, for each local authority associated with a LEP, data covering the whole of that local authority are included within the LEP data.
There are 2 cases, however, where the working boundaries of a LEP cut through existing local authority boundaries. These are Enterprise M3 and Solent LEPs where parts of the local authorities of New Forest, Test Valley, Winchester and East Hampshire are in the Enterprise M3 LEP while parts are in the Solent LEP. As with the February 2016 release of GVA for LEPs and other recent publications, it has been decided that the whole of these affected local authorities should be allocated to the Enterprise M3 LEP, and to not include them in the estimates for the Solent LEP.
Note that the Northamptonshire and South East Midlands LEPs will merge by the end of March 2017 to form a single integrated LEP. However, this publication uses the current boundaries at the time of publication. Data for the new geography will be available in due course.
The dataset in this release is based on regional GVA data and subject to revisions.
The regional GVA statistics have been subject to several revisions in their December 2016 release. Changes to the UK National Accounts measure of GVA impacted upon the regional GVA estimates in the form of different national totals for the various components of income. Of these, a change to the treatment of owner-occupied imputed rental has resulted in the greatest impact on the national figures. A change in the house prices used to calculate the regional allocation of imputed rental of owner-occupied dwellings was implemented in 2015 to regions and countries in Great Britain.
There has also been a change in the measure of regional GVA for the manufacture of coke and refined petroleum industry (SIC Sub-section CD). Moreover, noticeable changes have occurred in industry BDE regarding Dorset and C regarding Cumbria. For more details on the changes in regional GVA statistics, please see the section on Methodological Changes of the GVA publication.
Subregional productivity jobs and hours data have also been revised in comparison with the March 2016 release on LEPs productivity. This follows from a number of factors including the annual reweighting of the Labour Force Survey to match with the latest population data.Back to table of contents
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