This article provides experimental statistics covering sub-regional productivity measures
In January 2009, the National Statistician produced an article examining the measurement of regional economic performance. The article discussed the limitations of GVA per head as a measurement of the economic performance of a region and the income of its residents. The article instead proposed that to understand regional economic performance a suite of indicators should be used. These include the productivity measures GVA per filled job and GVA per hour.
The themes of the National Statistician's article also apply to the analysis of sub-regional economic performance. At the sub-regional level it is therefore recommended that GVA per head is not used as a proxy for measuring sub-regional economic performance but rather that a suite of indicators should be used including measures of productivity.
In practice, however, while the Office for National Statistics (ONS) does publish an annual series of regional productivity measures, it has to date not published sub-regional productivity data. This article fills this gap by producing experimental sub-regional productivity data; namely GVA per filled job and GVA per hour worked.
Regional productivity data is published by ONS in the ‘Productivity Measures by Region’ table which is updated annually in the Labour Productivity Statistical Bulletin (Q3). This regional table includes two productivity measures; GVA per filled job and GVA per hour worked.
The sub-regional productivity data has been compiled to be consistent with the data in this regional table. This requires ensuring that the sub-regional measures of GVA, jobs and hours are all consistent with the regional totals. This has been carried out as follows:
Regional GVA data is published by ONS as either smoothed (Headline) GVA or unsmoothed GVA. Regional productivity calculations use the unsmoothed workplace based GVA at current basic prices series (Table 1.7 in the regional GVA document included in the useful links – see Note 3).
Therefore, to calculate sub-regional productivity, GVA at NUTS 2 and NUTS 3 geographies has been calculated to be constrained to this unsmoothed NUTS 1 GVA data series.
This means that the sub-regional GVA data being used in these sub-regional productivity calculations differs slightly from the GVA data series currently published by ONS for NUTS 2 and NUTS 3 sub-regions. This is because the published sub-regional GVA data are all constrained to the Headline NUTS 1 GVA series, whereas the data being used in these productivity calculations is constrained to the unsmoothed NUTS 1 GVA series.
At the regional level, GVA per filled job is calculated using a ‘Productivity Jobs’ series as the denominator. This is compiled from four components; employee jobs, self employed jobs, government supported trainees (GST) & HM Forces. The employee, self employed and GST totals are those published by the ONS as Total Civilian Workforce Jobs. To this is added data on HM Forces employment. With the exception of HM Forces employment, this data is all on a quarterly basis. Therefore to produce an annual total for ‘productivity jobs’ an average of the four quarters in the year are taken.
The Civilian Workforce Jobs data series is not calculated for sub-regional geographies. Therefore for sub-regional productivity calculations we use the ‘Total Jobs’ data series that is an alternative workplace based measure of jobs that ONS produces principally for use in calculating job densities at regional and sub-regional level. Total jobs comprises employees (from the Annual Business Inquiry), self-employment jobs (from the Annual Population Survey), government-supported trainees (from DfES and DWP) and HM Forces (from MoD).
To ensure consistency with regional productivity data, the jobs series used in sub-regional productivity calculations is the ‘Total Jobs’ data for NUTS 2 and NUTS 3 sub-regions constrained regionally to the NUTS 1 ‘Productivity Jobs’ data.
At the national and regional level, GVA per hour worked is calculated using a ‘Productivity Hours’ series as the denominator. This is calculated by multiplying the jobs series at industry level (which is based on Labour Force Survey (LFS) data allocated by industry) by the average actual hours worked for the industry, also derived from the LFS. Results are then scaled to ensure the whole economy productivity hours equal the appropriate LFS hours total. This data is calculated quarterly and an annual total is constructed as the average of the four quarters in the calendar year.
At sub-regional level, only annual productivity data is being produced. Therefore, the Annual Population Survey (APS) is used rather than the LFS as it has a larger sample size. The process involves calculating total hours for each sub-region as the sum of employee hours, self employment hours, hours worked in government training schemes and hours worked by HM Armed Forces.
Employee hours are calculated by using the APS to estimate average hours worked per employee job for each sub-region. These totals are then multiplied by the level of employee jobs for each sub-region taken from the Annual Business Inquiry (ABI) to give a total employee hours total for each sub-region. Self employment hours are calculated from the APS.
For government training schemes and HM armed forces, the regional totals are allocated to sub-regions based on each sub-regions share of regional employee + self employment hours as calculated in the previous stage.
Adding together the sum of employee hours, self employment hours, hours worked in government training schemes and hours worked by HM Armed Forces provides a total hours estimate for each sub-region. Once calculated this NUTS 2 and NUTS 3 sub-regional data is then constrained regionally to the NUTS 1 ‘Productivity Hours’ data to ensure consistency with regional productivity data.
For 2005, it was not possible to use APS data, therefore LFS data was used – with the average taken of the four LFS surveys carried out in 2005.
Sub-Regional Geographies
Sub-regional productivity data is produced in this article for the NUTS 2 and NUTS 3 geographies. Nomenclature of Units for Territorial Statistics (NUTS) is a geography developed by the European Union to allow comparison of regional and sub-regional data across the EU-25 member states. A number of ONS regional and sub-regional outputs are produced based on the NUTS geography. These include regional and sub-regional GVA. This GVA data is an input in the calculation of sub-regional productivity. Each NUTS 3 sub-region covers the same area as either a single local authority or a combination of two or more adjacent local authorities.
Useful Links
Regional Productivity data is published in Table 9 of the Labour Productivity Statistical Bulletin. The latest issue.
The ONS productivity handbook.
Regional Gross Value Added - Latest Data (648.5 Kb Pdf) .
Methodology Guide for Regional GVA.
Inventory of Sources and Methods for Compilation of Regional GVA in the UK.
There is a strong correlation between the two measures of labour productivity being considered in this article, GVA per hour worked and GVA per filled job. For this reason, in this brief analysis of the results we focus on just one of the measures, GVA per hour worked.
Figure 1 shows the fifteen English NUTS 3 sub-regions with the highest GVA per hour worked in 2008. The highest productivity levels are found in Inner London with productivity in Inner London West 56 percent above the UK average and Inner London East 33 percent above the UK average.
Outside of London, productivity is highest in Berkshire whilst productivity is also over 15 percent above the UK average in Surrey and in Swindon.
It should be noted that one impact of the very high productivity levels in London is that relatively few sub-regions actually fall above the UK average. Just 23 out of the 93 English NUTS 3 sub-regions had a GVA per hour above the UK average in 2008. Furthermore, these sub-regions were predominantly found in the South of England with only 3 of these 23 sub-regions found in the North or Midlands (Solihull, Cheshire CC and Derby).
Given the skewed nature of the distribution it is worth considering the mid-ranking (median) sub-region (i.e. the sub-region that ranks 47th out of the 93 English sub-regions) and comparing its performance to the (mean) UK average. For 2008, the mid-ranking sub-region was Tyneside with a GVA per hour that is 91% of the UK average.
Figure 2 shows the fifteen English NUTS 3 sub-regions with the lowest GVA per hour worked. It shows three sub-regions with productivity over 25 percent below the UK average and a further five sub-regions with a productivity over 20 percent below the UK average.
The sub-regions included in Figure 2 are varied in location and type. A number are located towards the geographical periphery of England or are coastal resorts. Additionally, a number of largely rural sub-regions are included in the list such as Northumberland, Lincolnshire, Herefordshire and Shropshire. Equally, however, there are some mostly urban local authorities such as Blackburn with Darwen, Stoke-on-Trent, Wallsall & Wolverhampton, Sefton and Dudley and Sandwell.
Smoothed Data
Unsmoothed time series data at small geographies such as NUTS 2 and NUTS 3 tend to show volatility, created by sampling and non-sampling errors. Therefore, a five year weighted average has been used to remove this volatility and produce a smoothed time-series. The data presented in this article is this smoothed sub-regional productivity data series. It should be noted that when calculating the sub-regional productivity data, unsmoothed data has been used at all times. The smoothing process has only been applied to the final results. For any users who would like to be able to make use of the unsmoothed results, this data is included in the data section of this publication.
The latest sub-regional productivity data available is for 2008. The timeliness of the data is determined by the release calendar for sub-regional GVA data. Sub-regional GVA data for 2009 will be available in December 2011 and an update to this article will follow shortly afterwards. At the regional level, data is available a year ahead of sub-regional level data.
There is a strong correlation between the two measures of labour productivity being considered in this article, GVA per hour worked and GVA per filled job. For this reason, in this brief analysis of the results we focus on just one of the measures, GVA per hour worked. For Northern Ireland, GVA per hour worked data is unavailable for the NUTS 2 and NUTS 3 geographies. Therefore, for Northern Ireland, GVA per filled job data is shown instead.
Figure 3 shows GVA per hour worked data for all NUTS 3 sub-regions in Scotland. The data shows a number of sub-regions with high productivity performance. Both City of Edinburgh and Falkirk are ranked within the top ten UK sub-regions in terms of productivity performance whilst East Lothian and Midlothian and Aberdeen City and Aberdeenshire have productivity above the UK average.At the opposite end of the scale a number of Scottish sub-regions display relatively low levels of productivity, with productivity in seven sub-regions over twenty per cent below the UK average. These are predominantly the more rural and geographically peripheral sub-regions of Scotland.
Figure 4 displays productivity data for the NUTS 3 sub-regions of Wales. It shows that there is only one sub-region in Wales with productivity around the UK average. This is Cardiff and Vale of Glamorgan. It should be noted that due to the skewed distribution described earlier, this sub-regions actually ranks a relatively high 27th out of 130 sub-regions in Great Britain. A further three sub-regions in Wales are around the middle of the rankings, albeit their productivity is around 8-10 per cent lower than the overall UK average.
The majority of the sub-regions in Wales, however, are towards the lower end of the rankings with five sub-regions having productivity over 20 percent below the UK average. These sub-regions are generally the more rural sub-regions of Wales.
Figure 5 shows GVA per filled job productivity data for Northern Ireland. Productivity is highest in the sub-region of Belfast, albeit it is 6 per cent below the UK average. Productivity is lowest in the sub-regions covering the North, West and South of Northern Ireland where productivity is over 22 per cent below the UK average.
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As discussed in the introduction, in January 2009, the National Statistician produced an article examining the measurement of regional economic performance. This article discussed the limitations of GVA per head as a measurement of the economic performance of a region and the income of its residents.
So what is the problem with using GVA per head to measure sub-regional productivity? As productivity describes the ability to produce outputs, taking into consideration the amount of inputs used to produce them, then at first sight it may appear that GVA per head would make an appropriate indicator of productivity, as it is providing a measure for each sub-region that compares output (GVA) in the numerator with an input (population) in the denominator.
The problem, however, stems from the fact that the input measure used in GVA per head (residential population) is not a good measure of the actual labour input involved in the production of the sub-region's output (GVA).
There are a number of reasons for this. Firstly, 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.
A second key problem with GVA per head is that it is dividing a workplace-based numerator (workplace based GVA) by a residence-based denominator (residential population). This means it does not account for people commuting in and out of a sub-region.
For these reasons, GVA per hour worked or GVA per filled job are the most appropriate measures of sub-regional productivity. These measures only count the input of those who are directly employed in the production process (rather than the population as a whole) and additionally they provide a workplace based labour input denominator to match the workplace based GVA numerator, thus fully accounting for the impacts of commuting.
The differences in the results between measures of sub-regional productivity and GVA per head are not negligible. To illustrate this, Figure 6 shows GVA per head, GVA per filled job and GVA per hour worked for a small number of selected NUTS 3 sub-regions.
The major factor that tends to lead to GVA per head being higher than productivity for a sub-region is a high level of in-commuting. Therefore, urban centres often display this pattern. The examples of Nottingham and Glasgow are shown in Figure 6.
The opposite is also true. Therefore in Figure 6, GVA per head is much lower than productivity for Wirral and South-Nottinghamshire. These sub-regions both display significant out-commuting. This pattern is typical for many rural and suburban sub-regions.
Other factors that can influence the GVA per head measure include the employment rate in a sub-region and the share of population who are aged 16-64. However, the commuting effect tends to be the one that most dominates in diverging GVA per head from productivity across many UK sub-regions.
The net result is that, as described in the National Statistician's article, ONS recommends the use of GVA per filled job or GVA per hour worked as the appropriate measures of sub-regional productivity. These productivity measures can be included in a wider basket of indicators alongside income and labour market data to more fully describe sub-regional economic performance.
The difference between GVA per filled job and GVA per hour worked is that GVA per hour worked takes into consideration the hours worked per job. These may differ across sub-regions due to different industrial structures and different levels of part-time working. As such GVA per hour worked is considered the preferred measure.
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Richard Prothero, Regional Economic Analysis
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