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What are the South West Regional Accounts?

The South West Regional Accounts are an integrated economic information system for the South West. The Accounts have been compiled as part of the Business & Economy Module of the South West Regional Observatory to bring together information on all aspects of the region’s economy in a single, consistent, and integrated resource. The South West Regional Accounts are sponsored by the South West Regional Development Agency. The Accounts were constructed by Economic Systems Consultancy and Research.

The Regional Accounts include two elements. The first is a structural map of the economy which forms the basis for an economic model that enables the impact of changes in demand for South West goods and services (e.g. an increase in tourism) to be assessed on variables such as Gross Value Added and Full-Time Equivalent work. The map currently relates to the year 2004. The second element of the South West Regional Accounts is a time series of GVA, FTE work and numbers of business units. On this website, the time series is provided for 26 standard industry classifications and the SWRDA Priority Sectors. Data are provided for the SW region and the Unitary/County areas. The information can be benchmarked against Great Britain. The database currently runs from 1998-2005.

Classification of Industries

The SIC groups of the 26 industries are shown in the first column of each table.

SWERDA Priority Sectors are a composite of SIC groups. Not all Priority Sectors map easily onto the Regional Accounts. Some Priority Sectors, such as the Creative Industries for example, have part of a Regional Accounts sector within their composition. The fraction of the Regional Accounts sector that should be allocated to the Priority Sector differs according to the variable that is being measured. This following table gives a mapping of Regional Accounts groups to the Priority Sectors. Where no direct mapping exists, the fraction of GVA and FTE work that makes up the Priority Sector is shown.

Data Sources & Methods

Gross Value Added

A common measure of the economic value of output is Gross Value Added. For a given industry it is its gross output at basic prices less purchases of goods and services, less net spending taxes.

It includes compensation of employees which is the total benefit employees receive from employers. It includes wages and salaries, overtime payments, bonuses, pension costs, employers' NICs, redundancy payments, travel expenses and other benefits in kind. It includes self employment income, which is the income from labour and profits of households that operate as sole proprietorships and partnerships without independent legal status. It also includes gross operating profits of companies, capital consumption, trading surpluses of public corporations and rents.

Industry GVA on this website appears net of Financial Services Measured. Financial services indirectly measured or FSIM are the earnings of the financial sector from paying and charging different interest rates to depositors and borrowers. It is necessary to deduct this from the value added of industries charged for the use of services. FSIM has been allocated to industries on the basis of its intermediate purchase from the banking sector. This treatment is different to that in ONS regional accounts where FSIM is deducted at an aggregate industry level.

The total value of FSIM is also calculated differently to ONS. ONS currently allocate UK FSIM to regions on the basis of the location of the Financial Service industry. However, since FSIM are generated from the wider economy (e.g. from bank deposits held by companies) this methodology is likely to result in a bias. The SWRA methodology allocates FSIM to regions on the basis of each region’s use of Financial Services (as implied by the UK supply and use balances). This results in a transfer of around £12bn GVA from the provinces to London, increasing the productivity gap between London and most other regions.

A further difference in the measurement of GVA between ONS Regional Accounts relates to the treatment of the GVA of the Oil and Gas extraction industry. In ONS accounts the GVA of this industry is largely classed as ‘extra-regio’ and is not included in regional GVA estimates. The SW Regional Accounts maintain the allocations of GVA that appear in the ABI/2. The result is that productivity in the SW is generally lower than in ONS accounts, with the exception of Dorset which has some significant activity in this industry.

Data sources

For most industries data on GVA and its components are estimated from the ABI/2. For industries not covered or adequately measured by ABI/2 (e.g. primary industries, financial services, hotels and catering and public, health, social and education services) GVA is estimated from ONS regional accounts (except 2005), UK input-output tables, ABI/1 employment data and LFS self-employment data. GVA in ownership/letting of dwellings is estimated from data on the composition of the housing stock and average rents in each different sector (private, local authority housing etc). For 2005, GVA in those sectors normally covered by ONS are estimated from a number of alternative sources including the Farm Business Survey, CIPFA data and the ABI/2. For financial services estimates of GVA for 2005 are essentially a time-series forecast. Compensation of employees is estimated from total employment costs in ABI/2 and UK input-output accounts. Self employment income is estimated from data on self-employment, ONS household accounts and the earnings of employees in each industry. Net production taxes are estimated from UK input-output tables. FSIM are estimated from ONS regional accounts and distributed to industries using UK input-output relationships.

Sub-regional estimates should be treated with a greater element of caution because the underlying data sources are less reliable for smaller geographies.

Full-Time Equivalent workers & Business Numbers

FTE work includes employees in employment and the self-employed. One full-time worker is counted as working a 37 hour week. Business numbers are based around the definition used in the Annual Business Inquiry but also include each self-employed person as a ‘unit’. This probably overestimates the true number of businesses since some self-employed people will have employees and be included in the ABI/1 count.

Data sources

Data is derived from ABI/1; self employment data from ABI/2 and the LFS. The agricultural census and Defence Statistics are used to estimate the workforce/numbers of business units in agriculture and HM Services. The hours worked by part-time/casual workers in each industry is estimated from the LFS.

Using What if?

ECON|i incorporates a regional economic model based upon the regional accounts. This model can be used to generate simple economic impact analyses.

Two basic types of analysis are available, industry analysis and demand analysis.

Industry Analysis

The industry analysis allows you to specify changes in output or FTE workers for SW industries. For example, what is the effect on the SW economy of a new office machinery manufacturer employing 100 people?

The industry what if screen allows you to specify changes for the 26 SIC groups.

The user can specify £m changes in gross output at basic prices in the year of the accounting base or numbers of FTE workers, or a % change in gross output at basic prices in the year of the accounting base.

Note that value input figures must to be in the price base of the year to which the accounts relate if the employment estimates are to be consistent with the relationships in the accounts. So, for example, if using the 2004 accounts in 2007, £100m increase in output in 2008 must first be deflated to 2004 prices before inputting into the impact routine, otherwise the employment impact estimates will be overestimated. An alternative approach is to input the figure using the price base of the year of impact and then deflate the employment impact estimates accordingly.

On pressing ‘calculate’, the results are displayed in columns to the right. Effects are shown on SW GVA and FTE workers in each industry. The ‘initial’ effect is the direct impact upon the industry(s) that have been changed. The total effect adds to these all ‘knock on’ effects, including the effect of changes in household income and expenditure. These are calculated from an industry by industry Leontief input-output model with compensation of employees and gross mixed income endogenous.

Demand Analysis

The demand analysis allows the user to specify changes for the components of aggregate demand (households, exports, investment etc). For example, what if exports to the EU fall by 5% - what is the impact on workers in each SW industry?

The selection screen asks the user to specify variables to make changes to along with either £m or a % change. Inputting % changes will produce financial impacts in the prices of the base year of the accounts. If current prices are required, these values will need to be inflated. Inputs made in £m must to be in the price base of the year to which the accounts relate if the employment estimates are to be consistent with the relationships in the accounts. So, for example, if using the 2004 accounts in 2008, £100m increase in exports in 2008 must first be deflated to 2004 prices before inputting into the impact routine, otherwise the employment impact estimates will be overestimated. An alternative approach is to input the figure using the price base of the year of impact and then deflate the employment impact estimates accordingly.

On pressing ‘calculate’, the results are displayed in columns to the right. Effects are shown on SW GVA and FTE workers in each industry. The ‘initial’ effect is the direct impact upon the industry(s) that have been changed. The total effect adds to these all ‘knock on’ effects, including the effect of changes in household income and expenditure. These are calculated from an industry by industry Leontief input-output model with compensation of employees and gross mixed income endogenous.

Important Notes on Using What if

Whilst the what if routine is designed to make economic impact analysis accessible to a wider audience, a technical knowledge is still required to prepare the inputs to the analysis correctly. If you are in doubt about what you are doing you should seek technical advice.

If you use the results of an impact analysis in a report you write you must make it clear that the results of the analysis depend upon the assumptions you have made regarding the model inputs. You must not cite ECON|i or the regional accounts as a guarantee of the accuracy of assumptions that you have made.

By using the site, you implicitly accept the parties involved in the production of the regional accounts and the ECON|i software cannot be held responsible for any loss or damage resulting from the use of ECON|i or the regional accounts.

The What if? Impact Tool and the Sub-regions

The What if? tool calculates impacts on the SW regional economy and not its sub-regions. Unfortunately there is no way of modifying these impacts for sub-regional analysis with any degree of accuracy.

Impacts generated through ‘demand analyses’ cannot be modified at all since the composition of demand will be very different in each sub-region.

For industry impacts where a £m figure has been entered, it is not too unreasonable to assume that the initial effect on monetary variables such as GVA will be the same for the SW and the sub-region. The assumption being made is that the proportion of GVA in Gross output is the same in the SW industry and the sub-regional industry. In order to calculate the initial impact on sub-regional FTE work in this case, the implied % initial change in GVA in the sub-regional industry can be applied to the sub-regional industry’s number of FTE workers. For example, suppose a £10m impact is calculated to create £5m GVA initially; suppose the sub-regional industry has GVA of £50m. The initial % change in GVA is 10% (5/50). One can assume that the number of FTE in the sub-region will increase by 10% also.

For industry impacts where a number of FTE workers has been entered, the initial impact on sub-regional FTE work is this number. The initial impact on GVA can be calculated by taking the ratio of GVA/FTE in the relevant sub-regional industry and multiplying this by the initial FTE impact.

For % changes, the initial impact on GVA and FTE can be taken as the % of the relevant sub-regional industry’s GVA and FTE.

Knock-on or multiplier impacts on the sub-region are problematic to estimate. In general, because sub-regions are more open economies (i.e. they have greater import leakage), sub-regional multipliers will tend to be lower than SW regional multipliers. The multipliers for the SW are, on average around 1.6, e.g. knock-on effects are 60% of the initial impact. It is difficult to say what the average multiplier for a sub-region would be but, for a Unitary Authority such as Plymouth 1.25 would not seem unreasonable, whilst for a larger county 1.4 might be expected.

There is considerable variation in the multiplier between industries. There is some justification in thinking that the pattern of variation observed between SW industries might be reflected at the sub-regional level. Hence it might be reasonable to scale the SW industry multiplier effects (that is, the total effect minus the initial effect) by the ratio

[assumed sub-regional multiplier -1 ] / 0.6

For example, suppose we have a SW GVA total impact of 250m, of which 100m is the initial impact; £150m is therefore the multiplier effect, implying a regional industry multiplier of 2.5. If we are calculating the impact on Plymouth with an assumed average multiplier of 1.25, the sub-regional multiplied effect would therefore be [1.25-1]/0.6 * £150m = £62.5m and the total impact on Plymouth would be £162.5m. FTEs for the multiplied effect can be worked out by calculating the number of FTE per £m GVA in Plymouth as a whole and multiplying this by £62.5m.

These calculations are clearly very approximate.