ECON|i & the Regional Accounts

Economic Systems Consultancy & Research

ECON|i and the Regional Accounts

• Regional Accounts Data

• Regional Accounts Software

• Impact Analysis Using Regional Accounts

What are the Regional Accounts?

• The Regional Accounts comprise of two main elements:• Firstly

• A Detailed Structural Map of the Economy at a point in time which, in the main part, shows • the linkages between SW industries; • how SW industries link into external markets such as UK

regional and international export markets;• the connections between the SW industries, the labour market,

and SW household expenditure• This map facilitates an economic impact tool (input-output model)• Currently 2008 map, updated annually

What are the Regional Accounts?

• Secondly• A Time Series of Key Economic Variables

• GVA, FTE workers, Numbers of businesses, international export of products

• 111 industries defined by SIC• Bespoke SWRDA Priority Sectors• Geographies: SW; London; Other GB industries; GB; the 15

UA/County sub-regions of the SW (though not for exports)• Spanning 1998-2009

• Compared to ONS Regional Accounts - SWRA more detailed by industry, and importantly, provides comparable estimates of related variables e.g. FTE, not just GVA on its own.

Examples of statistics you can derive from the accounts

• Industrial structure• Intensities of GVA or labour by industry/Priority Sector, relative to GB

(the ‘location quotient’), regional and sub-regional over time• Measures of productivity

• GVA per FTE worker or per hour• Compare by detailed industry/Priority Sector, region, sub-region and

over time• Capital expenditure

• By industry, per FTE with regional comparisons• Orientation & Nature of Sales & Purchases

• International exports as per FTE• Purchases of goods & services from the SW as a % of total purchases

by industry• Input structure of an industry e.g. expenditure on R&D

Where Data Comes from: Major Sources

• Principal source for industry financial data is the ABI/2 (regional & sub-regional)

• ONS Regional Accounts GVA• ONS household accounts• ABI/1 labour market & industry data from NOMIS• Several variables derived from LFS returns (e.g. self-employment, hours

worked, occupation and qualification data)• Family Expenditure Survey• HMCE data on international exports by region• REWARD project data for environmental emissions and waste management• Miscellaneous sources such as agricultural census, defence agency statistics,

pensioners’ income series, UK supply-use tables.

• Data sources and estimation methods are set out in the help file of the software that runs the accounts (ECON|i).

What are the Benefits of theRegional Accounts?

• Accounts bring together disparate sources of regional data within a meaningful economic framework• provides consistency between data sets enabling greater

‘interactivity’ between data;• structure facilitates analysis e.g. enabling economic impact model

• Accounts thereby deliver• greater use & scope to existing data, expanding the evidence-base• a superior quality of evidence-base

to• a wider audience (users who would otherwise find such analyses

prohibitively technical or costly to undertake)• at a lower cost (lower user search costs, no duplication of effort,

economies of scale)

Availability of the Regional Accounts

• The Regional Accounts are available• through a piece of stand-alone software called ECON|i which

facilitates data inquiry and analysis (including economic impact)• FREE of charge to anybody• through the ECON|i website which provides a ‘slimmed down’

version of the stand-alone version• Users include

• RDA staff• Private consultants (both in the SW and elsewhere in GB)• Private companies working on in-house research• Academics• Students

Data are organised by broad themes

Data are selected through hierarchical trees

Different statistics can be derived from any given data selection, e.g. from GVA data, we can get a relative productivity measure (GVA/FTE GB=100)

The online accounts work in broadly the same way

The focus of the data however is upon the time series element. A lower level of industry detail is provided (26 SIC and SWRDA sectors) but geographical detail is maintained.

Online version also includes the economic impact tool for the 26 SICs and key variables of interest.

Economic Impact Analysis Using the Regional Accounts

• The Structural Map of the Regional Accounts can be interpreted as an ‘input-output’ model.

• In ECON|i this is referred to as the ‘What if?’ tool• This tool allows us to make changes to the demand for SW products

and calculate the implications for variables such as SW employment and GVA in each industry using the pattern of supply and demand we observe in the Accounts.

Strengths of What if?

• The tool is most effective at answering questions relating to changes in demand such as:

• If exports to the USA increase by 1%, which industries in the SW might benefit and by how much?

• If a plant employing 100 people in the dairy industry closes, what are the potential implications for other SW industries?

• What is the contribution of tourism to the economy and which industries constitute the ‘tourist industry’?

• What will be the impact of £100m construction project?

Limitations of What If?

• It is more difficult to answer questions relating to changes in supply such as:• If we improve broadband access to businesses, how will the SW

benefit?• If transport infrastructure in the region is improved, how will this

benefit the economy?You’d need to think through the demand implications of the supply–side change – which can be rather difficult and messy.

• The tool is focussed on the region rather than the sub-region.• The tool is ‘long-run’ with no specific allocation/distribution of effects

over time.• Assumes supply can always meet demand

• Not so much of a weakness as may first appear - results can help us identify/think about potential supply constraints

Limitations of What If?

• The quality of any impact analysis fundamentally depends upon asking the ‘right’ questions

• Ask the wrong questions and, irrespective of the quality of the impact tool, the answers will be misleading

• The most challenging part of economic impact analysis is constructing a sensible impact scenario – credible assumptions which lead to sensible model inputs.

• Whilst the data within the RAs can help to form sensible assumptions, economic impact analysis remains largely an exercise requiring considerable experience and technical expertise.

Some Thoughts, Tips etc on using the What if function

• The direct impacts are usually relatively important to get right. Multiplier effects usually smaller, more subjective. Devote resources to measuring direct accurately.

• ‘What if’ measures the ‘downstream’ effects of an impact. –Those directly affected– Immediate suppliers of those directly affected (‘first round’)–Supplier of suppliers (‘indirect’)–Household expenditure effects (‘induced)

• An impact study may involve several impacts e.g. new tourist facility – construction phase of impact; direct impact of facility’s operation; impact of new tourists – each needs to be assessed as a ‘what if’.

• Remember the ‘what if’ tool expects financial figures in the price base year of the RAs (currently 2008). Impacts in £ 2011 should be deflated before inputting OR the non-financial variables e.g. FTEs should be deflated post-what if.

• Consider building displacement effects in your assumptions – fairly subjective area.

• Given the subjectivity, it is prudent to build in a range of possible scenarios to your evaluation, e.g. based upon relatively optimistic/pessimistic modelling assumptions.

• Transitory impacts yield temporary impacts e.g. construction expenditure phase eventually ends and workers move on. FTEs should be interpreted as representing ‘person years of employment’

• Be careful when dealing with retail, wholesale or certain financial/professional companies who act as retail agents. These companies typically use their turnover as a measure of their size etc. However, the accounts require that you value output net of goods that are resold without processing e.g. retail stock. Can make a big difference.

• The accounts represent average relationships for an industry. Typically the purchasing data is pretty poor quality.

• If you have the information on the purchasing pattern of a specific industry, the incomes paid to staff, it may be worthwhile modifying the standard ‘what if’ analysis somehow. There are a number of ways you can do this – typically they require a bit of technical knowledge – so best to take advice.