Measuring the economic impact of an intervention or investment Paper Two: Existing sources and methods December 2010
Executive summary Under the terms of the Service Level Agreement between the nine English RDAs and the Office for National Statistics (ONS), the ONS Regional Statisticians provide independent advice to regional users on the use of ONS and Government Statistical Service (GSS) statistics, including on technical issues, such as the use of statistics in monitoring performance against targets. This series of papers aims to complement IEF+ (and other guidance 1 ) by examining the sources, existing methods and concepts which surround the measurement of an IOI consistent with those used to produce official GVA estimates. This is the second and final paper of the series investigating the feasibility of estimating the economic impact of an Investment or Intervention (IOI), and investigates existing data sources and methods for estimating GVA. This paper was drafted prior to recent announcements from the coalition government about plans for abolishing Regional Development Agencies (RDAs) and changes to the approach to setting targets and monitoring progress. GVA is a key economic measure which is likely to be used in some way to assess interventions at a range of geographical scales and the authors feel the papers will remain relevant with the move to increasingly local decision making. However, readers should consider this context when reviewing the paper. It should be borne in mind when reading this paper that there is currently no requirement on ONS to produce statistics which enable the evaluation of the impact of IOIs. 1 Other guidance includes HMT s The Green Book: Appraisal and Evaluation in Central Government; OGC s Gateway Review for Programmes & Projects; Scottish Executive s Additionality & Economic Impact Assessment Guidance Note; BIS Guidance for Using Additionality Benchmarks in Appraisal; Research to Improve the Assessment of Additionality, and Self assessment as a tool to measure the economic impact of BERR policies - a best practice guide. i
Historically a number of methods have been used, taking a variety of approaches and making comparisons between IOIs problematic. These approaches (and to a large extent Impact Evaluation Framework plus (IEF+)) have, in the main, used the best methods and data publicly available. IEF+ itself has proved a significant advance to promoting greater consistency in the methods applied in the evaluation of an IOI, a consistency which is extremely important when evaluating IOIs. Investigations have pointed to beneficiary surveys as a fit-for-purpose method of assessing IOI impact. However, IEF+ could be strengthened further through improvements to the methods for estimating IOI Value Added. Current estimates of IOI Value Added do not align with National Accounts concepts. As a result they can not be compared to official Regional Accounts estimates produced by ONS Regional Accounts, which are used to monitor PSA7. If it is not considered necessary to create an IOI Value Added estimate consistent with National Accounts concepts, then such estimates of economic impact should not be labelled as GVA. Suggestions to improve estimates of IOI Value Added consistent with National Accounts concepts include: Use of multipliers and factors which better reflect the geographical and industry of the IOI through the use of ONS survey, administrative microdata and National and Regional Accounts products; Aligning primary research questions with the wording of ONS surveys and applying existing techniques to provide a IOI Value Added estimate consistent with National Accounts concepts; Due to the nature of some of the estimates of IOI Value Added derived through the use of all region, all industry, factors it is questionable whether they add anything more than the evaluation of the drivers of GVA, such as skills, jobs and productivity. ii
A holistic approach of measuring IOI impact could be through a scorecard approach which included the drivers of GVA. Using a scorecard approach would remove the requirements of creating an IOI Value Added estimate, and is likely to produce an estimate as accurate as a GVA. Further suggestions for improving IOI Value Added estimates or for using existing ONS data, and or surveys, would be welcomed. iii
Contents Executive summary...i Contents...iv Authors...vi 1 Introduction... 1 1.1 Background... 1 1.2 The two paper approach... 2 2 Aims... 3 2.1 Aims of the two paper series... 3 2.2 Aims of paper two... 4 3 Concepts & frameworks (legal or otherwise)... 5 3.1 Structure of Businesses... 5 3.2 Small and Medium Enterprises... 6 3.3 Inter Departmental Business Register (IDBR)... 6 3.4 IDBR versus Survey data... 9 3.5 Business Register and Employment Survey (BRES)... 10 3.6 Publication of employment estimates by ONS... 11 3.7 Annual Business Survey (ABS)... 12 3.8 Other ONS business surveys... 13 3.9 GVA: ESA, National and Regional Accounts... 14 3.10 Section Summary... 16 4 Input-Output framework and analyses... 18 4.1 Description... 18 4.2 Supply and Use Tables (SUTs)... 20 4.3 Analytical Tables (Symmetric Input-Output Tables)... 20 4.4 Section Summary... 22 5 Company accounts... 23 5.1 Company Accounts: Legal requirements on companies, SMEs... 23 5.2 Differences between national accounts and company accounts: difficulties of estimating GVA... 24 5.3 Section Summary... 25 6 What RDAs require for evaluation... 26 6.1 Targets & monitoring... 26 6.2 Delivering the PSAs... 27 6.3 Delivering the strategies... 30 6.4 Delivering national programmes: Business Link... 31 6.5 Determining economic impact... 32 6.6 Previous RDA evaluations: Inconsistent GVA estimates... 33 6.7 Improved practical guidance: BIS Impact Evaluation Framework plus... 35 6.8 Section Summary... 38 iv
7 Obtaining data on IOIs... 39 7.1 Legislation & Disclosure... 40 7.2 Microdata... 41 7.3 Classifications: Industry & geographical... 42 7.4 Section Summary... 43 8 Moving away from direct measures of GVA... 44 8.1 Using ONS Skills data to measure the economic impact of an investment or intervention... 44 8.2 Data limitations... 45 8.3 Possibilities for improving data... 47 8.4 Section Summary... 48 9 Summary... 48 Annex 1: GVA Definitions... 53 Annex 2: Company accounts... 55 Annex 3: Differences between national and company accounts... 57 Annex 4: Example of Business Register and Employment Survey questionnaire... 58 Annex 5: Annual Business Survey Questions... 65 Annex 6: Classification of industries... 68 Annex 7: Input-Output Tables and Multipliers... 70 Annex 8: Alternative Approaches to Assessment... 76 Annex 9: LFS/APS Skills Variables... 80 Glossary... 81 References... 84 v
Acknowledgements The authors would like to thank all who have helped in the production of this paper. We are grateful to our colleagues in the Office for National Statistics and the following academics, departments, devolved administrations and organisations: Andrew Hunt (Durham University); Steven Brand (University of Plymouth); Department for Business, Innovation & Skills; Department for Communities and Local Government; Department for Environment Food and Rural Affairs; The Scottish Government; Department of Finance and Personnel, Northern Ireland; Welsh Assembly Government; Regional Development Agencies of England; Regional Observatories of England. Authors Gary Wainman North West Regional Statistician Tel: 01925 400 310 Mobile: 07788 436441 Email: gary.wainman@ons.gsi.gov.uk Ian Gouldson North East Regional Analyst Tel: 0191 229 6435 Mobile: 07788 412474 Email: ian.gouldson@ons.gsi.gov.uk Neil Park South East Regional Analyst Tel: 0121 202 3256 Mobile: 07788 418840 Email: neil.park@ons.gsi.gov.uk vi
1 Introduction The need to deliver value for money when delivering an Intervention or Investment 2 (IOI) has created demand from regional and sub-regional decision makers for a consistent and robust method of determining the economic impact of an IOI. The devolution of economic development powers to regional and sub-regional organisations 3, and the framing of Public Service Agreements 4 (PSA) targets in terms of the Office for National Statistics (ONS) Regional Accounts Gross Value Added 5 (GVA) estimates, has brought the quality and appropriateness of methodologies that produce IOI Value Added (VA) estimates sharply into focus. 1.1 Background The number and the pragmatic nature of methods used to estimate GVA for a range of IOIs 6 has resulted in estimates of the impacts of IOI that are often inconsistent and not directly comparable, making prioritisation and decisionmaking based on these estimates problematic 7, highlighting the need for authoritative guidance on calculation of GVA estimates for IOIs balanced with a requirement that any impact analysis should be cost-effective, straightforward and not onerous. The area of estimating the impacts of IOI has grown in importance and has led to the development of guidance on how to estimate this impact by government departments responsible for administering the significant funds 2 An IOI was defined in section 3 of paper one as: an activity which has the potential to impact on the economy of a locality over a finite period. This definition has been chosen to encompass the widest possible number of interventions and recognises that many evaluations are undertaken over a finite period. 3 Key legislation surrounding the devolution of power are the Regional Development Agencies Act 1998 and the Local Democracy, Economic Development and Construction Bill. 4 Regional Economic Performance (REP) Public Service Agreement (PSA) are used to assess Regional Development Agencies, see section 6.1 for more detail. 5 An explanation of Gross Value Added is contained in section 4.3.1 of paper one. 6 Examples of evaluations which have estimated GVA include: Inner City Solutions (2008); PriceWaterhouseCoopers (2008, 2009a, 2009b); Regeneris Consulting (2008a, b). 7 The Department for Business, Innovation and Skills have produced practical guidance (Impact Evaluation Framework Document) to improve the process of evaluating interventions made by Regional Development Agencies. 1
used for many of the IOIs. This importance is likely to continue under the new coalition government due to their desire to take decision making to a lower geographical level, making the geographical scale of the IOI even more relevant. The Department for Business, Innovation & Skills (BIS) issued guidance to Regional Development Agencies (RDAs) on how to measure the economic impact of their projects, in the form of IEF+ in late 2009. This series of papers aims to complement IEF+ (and other guidance 8 ) by examining the sources, existing methods and concepts which surround the measurement of an IOI consistent with those used to produce official GVA estimates. The next sections will briefly review the rationale for the papers before introducing the second paper. 1.2 The two paper approach The production of guidance was via a phased approach comprising two papers, delivered between 2009 and 2010. This approach allowed issues to be examined systematically and in some detail to produce a set of guidance which adequately covered the subject. It had the advantage of allowing a large range of stakeholders to comment and feedback on drafts of the papers during their development, ensuring their views were considered. The first paper in this series, released in November 2009, discussed in greater depth how and why the requirement arose to estimate interventions by government and other public bodies, who invest directly and undertake other forms of intervention in the public realm 9, transport infrastructure, and the 8 Other guidance includes HMT s The Green Book: Appraisal and Evaluation in Central Government; OGC s Gateway Review for Programmes & Projects; Scottish Executive s Additionality & Economic Impact Assessment Guidance Note; BIS Guidance for Using Additionality Benchmarks in Appraisal; Research to Improve the Assessment of Additionality, and Self assessment as a tool to measure the economic impact of BERR policies - a best practice guide. 9 Public realm has been defined in this instance as the space between and within buildings that are publicly accessible, including streets, squares, forecourts, parks, public art and open spaces. 2
wider economy. To ensure the appropriateness of these IOIs, public organisations require robust and appropriate quantitative data on which to base their decisions. This is the second and final paper in the series investigating the feasibility of estimating the economic impact of an IOI, with a particular focus on Gross Value Added (GVA). 2 Aims This section will briefly discuss the aims of the two papers, before examining the aims of the second paper in more detail. 2.1 Aims of the two paper series The papers will assume a robust justification for the IOI has already been made and will concentrate on developing a framework for measuring the economic impact of an IOI. The papers will not consider other important impacts of an IOI, such as its strategic, environmental or social impacts or its achievability 10. Limiting the scope of the papers in this series allows the production, of a set of papers that can describe what is required to produce estimates of economic impacts of an IOI; an in-depth and timely investigation would be difficult should the scope be widened to encompass every conceivable impact of an IOI. However, it is feasible that other impacts of an IOI, for example social impacts, could be examined in future papers, or by other authors. 10 It is widely recognised that economic indicators are imperfect measures of progress and well-being, and work is ongoing on the development of complementary indicators. See Allin (2007) and ONS working paper: Measuring Societal Wellbeing in the UK. The impact of UK economic activity on the environment is currently measured through the ONS Environmental Accounts. 3
The series will comprise two papers, with the broad aims of: 1. introducing and defining the topic (Paper 1). 2. describing key metrics for measuring economic activity (Paper 1) 3. analysing methods for measuring the economic impact of an IOI (Paper 2) The papers are primarily focused on the application of official statistics, where the authors can add insight and value through their unique position as ONS regional staff based in RDAs. It is not concerned with locally collected information, surveys, reports, or consultations. 2.2 Aims of paper two The aims for the second paper in the series are to: Outline the concepts used to estimate GVA by ONS and how these could be applied when evaluating an IOI. Examine ONS statistics to determine their utility for evaluating an IOI, and the limitations of their use. Review a selection of methods used to evaluate IOIs to explain the benefits and limitations of the methodology when evaluating an IOI in terms of GVA consistent with ONS produced estimates. Begin to discuss a range of outcomes which affect GVA such as employment creation, productivity enhancement, and improvement in skills which impact directly on GVA. It should be borne in mind when reading this paper that there is currently no requirement on ONS to collect data or produce statistics at a level, or in a form which enables the evaluation of the impact of individual IOIs to be assessed. 4
3 Concepts & frameworks (legal or otherwise) This section shows how ONS holds information on businesses, collects data on their economic activity and produces estimates of GVA using internationally agreed concepts and methods. 3.1 Structure of Businesses Businesses can be classified in several ways; sole proprietor, partnership, public or private corporation or non-profit body. Local Government and Central Government bodies may also engage in business activities. The legal statuses of business units held on the IDBR are not the same as the institutional sectors used within the National Accounts, for example when certain banks moved from private to the public sector. This is a legitimate difference that affects comparisons between IDBR statuses and National Accounts sectors. Incorporated companies are listed with Companies House. Lists of companies are also collected and held in various commercial databases such as Global 11 (Dun & Bradstreet), OneSource 12 (InfoGroup) and Fame 13 (Bureau van Dijk). These databases can also contain data collected from company accounts. The level at which the businesses are listed and the data from company accounts may not be consistent with that contained in the ONS Inter Departmental Business Register (IDBR) and business surveys, as discussed later in this paper. Businesses commonly include a head office plus various management and operational arms that may be located anywhere in the world. 11 Dunn & Bradstreet Global Reference Solution https://solutions.dnb.com/ 12 InfoGroup s OneSource database http://www.onesource.com/ 13 Bureau van Dijk s FAME databse http://eps.bvdep.com/en/fame.html 5
3.2 Small and Medium Enterprises Small and Medium Enterprises (SMEs) are defined by the European Commission as companies with less than 250 employees with an annual turnover of 50 million or a balance sheet total of no more than 43 million 14. The definition is used to ensure consistency in targeting policies to assist SMEs and grant them certain advantages, for example, tax relief on research and development and capital expenditure. However, even within the UK there is no single definition of an SME. For example, the definition given in the Companies Act 2006 and that used by BIS differ in the treatment of turnover and balance sheet totals. Estimates of modelled SME numbers, employment and turnover are published by BIS (based on a range of assumptions), using ONS IDBR data plus information from the ONS Labour Force Survey (LFS) and HM Revenue & Customs (HMRC) Survey of Personal Incomes 15. 3.3 Inter Departmental Business Register (IDBR) The IDBR complies with European regulations governing the structure and uses of business registers for statistical purposes. It is a detailed but not exhaustive list of UK businesses, providing a sampling frame for surveys of businesses carried out by the ONS and by other government departments. It is a key data source for analyses of business activity and is the main source of data on business counts. The main sources for updating the IDBR are Value Added Tax (VAT) trader and Pay As You Earn (PAYE) employer data from HM Revenue & Customs 14 More information on the European Commission s definition of small and medium sized enterprises can be found at http://ec.europa.eu/enterprise/policies/sme/facts-figuresanalysis/sme-definition/index_en.htm. 15 More information on BIS small business statistics can be found at http://stats.berr.gov.uk/ed/sme/. 6
and details of incorporated businesses from Companies House. This is supplemented by ONS survey data and survey information from the Department of Enterprise, Trade and Investment Northern Ireland (DETINI) and the Department for Environment, Food and Rural Affairs (DEFRA) farms register. The IDBR combines the information from administrative sources with survey data to form a statistical register comprising over two million enterprises. The IDBR does not include some very small businesses without VAT or PAYE schemes (self employed and those with low turnover and without employees) and some non-profit making organisations. However, many small businesses register for VAT exemption purposes and should be contained on the IDBR. Information on turnover and employment are estimated in their first year of business. Initial classification to industry is based on business description and self-classification by the business as supplied to HMRC. The IDBR holds a variety of information on businesses and business structures, including name and legal status; Box 1 provides more details. The information is updated frequently using data from HMRC and ONS surveys, for example from the Annual Business Survey (ABS). Published information from the IDBR includes a snapshot taken in March each year for the UK Business: Activity, Size and Location publication 16, and Business Demography 17, which looks at business births and deaths over the year. The IDBR holds business structures in terms of local units, enterprises and enterprise groups. An enterprise is the smallest combination of legal units (generally based on VAT or PAYE) that has a certain degree of autonomy within an enterprise group. The enterprise address is generally the head office. Local units, for example a retail outlet or factory, are where the enterprise operates. 16 The current and historical editions of UK Business: Activity, Size and Location can be found at http://www.statistics.gov.uk/statbase/product.asp?vlnk=933. 17 The current and historical editions of Business Demography can be found at http://www.statistics.gov.uk/statbase/product.asp?vlnk=15186. 7
Variable Employment* Employees* Turnover* Employment in region size band Employees in region size band Standard Industrial Classification (SIC) 2003 SIC 2007 Legal status Foreign ownership Business birth date Number of local units Notes Employment = employees + business proprietors. Standard bands are defined (such as 20-49 for employees/ment and 500K- 999K for turnover) but ONS can specify bespoke bands e.g. 37-92 employment. Regional employment only for 2007 onwards. Regional employees only for 2007 onwards. SIC 2007 is only available for 2009 onwards. Non profit institutions, Central Government, Local Government, Limited Company, Sole proprietorships, Partnerships, Public Corporations & nationalised bodies Country e.g. UK, USA etc Month and year Enterprise Unit analysis only. * Stock of enterprise data have employment, employees and turnover for the whole enterprise in the UK; Local Unit (LU) extracts have employment and employees in the LU, turnover data is available for enterprises only. Box 1: Variables included on the IDBR ONS business surveys are sent to the reporting unit which is normally the enterprise, however, some complex businesses reporting units may cover all or some of their enterprises and local units. For example in Figure 1 there could be 3 reporting units: Large Co. Group Headquarters which reports on the whole enterprise group; Big Shop Supermarkets Headquarters which reports on the retail part of the enterprise group and Bonus Financials Headquarters which reports on the financial side of the enterprise group. One of the uses to which the IDBR is put in addition to its primary role as a sampling frame, is the matching of lists of assisted businesses using company names, enabling comparison at an aggregate level (to prevent disclosure of 8
any individual business s details) against businesses that have not received assistance ( counterfactual analysis). Large Co. Group Headquarters Location: London Site SIC2007: 70.10 Enterprise Group SIC2007: 47.11 Employment = 225 (10 onsite + Sum of Enterprise Units), Turnover = 150million (Sum of Enterprise Units) Big Shop Supermarkets Headquarters Location: Leeds LU SIC2007: 70.10 E SIC2007: 47.11 Employment = 130 (10 onsite + Local Units), Turnover = 50million; Bonus Financials Headquarters Location: Manchester LU SIC2007: 70.10 E SIC2007: 64.91 Employment = 85 (10 onsite + Local Units), Turnover = 100million Liverpool Employment: 45 LU SIC2007: 47.11 Warrington Employment: 40 LU SIC2007: 47.11 Manchester Employment: 35 LU SIC2007: 47.11 Preston Employment: 50 LU SIC2007: 64.91 Crewe Employment: 15 LU SIC2007: 64.91 Carlisle Employment: 10 LU SIC2007: 64.91 Key: Statistical Business Classification Enterprise Group (EG) = Enterprise Unit (E) = Local Unit (LU) = Standard Industrial Classification (SIC) 2007 47.71 Retail sale of clothing in specialised stores 64.91 Financial Leasing 70.10 Activities of head offices Note: SIC2007, Location, employment & turnover data are illustrative only and do not reflect the details of the businesses used in the example. Figure 1: Example of business structures on the IDBR 3.4 IDBR versus Survey data Survey data is subject to sampling error. For example, the estimate of UK employment in January to March 2010 from the LFS had a sampling variability of ±153 thousand on an estimate of 28.8 million. Surveys are based on a random sample of businesses weighted ( grossed up ) to produce estimates for the whole economy. At more detailed industry or geographical detail, levels of error typically become larger. For a change in a survey result to be statistically significantly different from zero, the change must be greater than 9
the levels of error associated with the change. Consequently, the larger the levels of error, the larger the change must be to be statistically significant and the more difficult it is to identify subtle changes. Both survey and IDBR data are subject to non-sampling errors such as errors of coverage, measurement, processing and non-response. Employment data on the IDBR and survey data may reflect different dates or time periods. For example, the Annual Business Inquiry Part 1 (ABI1) collected data on employment as at September each year (prior to 2006, reference date was December). This has now been replaced by the Business Register and Employment Survey (BRES), which also collects employment data as at September. Conceptually, if assisted businesses were somehow flagged on the IDBR they could be filtered to ensure selection within ONS survey samples. Although returns from such businesses may not be used in the weighting for final results they could potentially be used at aggregate level as a comparator of success of IOIs. However, this approach has not been explored or discussed within ONS. It could be unviable, would prove costly, may run foul of the Osmotherly guarantees and run counter to the ONS' aim to reduce the burden of data collection on businesses (although if the range of beneficiary and other business surveys used by RDAs could be reduced as a result then the overall net impact might be an overall reduction in the burden of reporting). 3.5 Business Register and Employment Survey (BRES) This survey has replaced the Annual Business Inquiry Part 1 (ABI1) and the Business Register Survey. In addition to employment data, BRES also collects turnover data for local units where available and produces modelbased estimates (see Annex 4 for an example of questions asked on a BRES survey). The turnover data will be used to improve the allocation of Annual Business Survey data to the sub-national level and employment estimates at regional and local level. The responses will also be used to improve the 10
quality of the IDBR. ABI1 (and in the future BRES) data are the primary source of employment data for detailed industry and geographical level. BRES is a sample survey, collecting data on employment and turnover for around 80 thousand reporting units and their local units. The BRES results may not be consistent with earlier data from the ABI1, and the ABI1 data has a discontinuity of around 400 thousand employees in a downward direction between 2005 and 2006. The discontinuity has resulted from a change to reference date from December to September, the inclusion of Business Register Survey results and changes to minimum domain methodology. Care should be taken, therefore, when comparing data from these sources between periods 18. Any discontinuities between the ABI1 and BRES will be fully analysed. ABI1 data are published at different levels of industry and geography through the NOMIS and Neighbourhood Statistics websites. 3.6 Publication of employment estimates by ONS The ONS publishes several different estimates of employment. The BRES estimates are collected from employers, based on a point in time. The Work Force Jobs (WFJ) estimates, available quarterly, provide data on employment obtained from Business Surveys, supplemented with information from the Labour Force Survey (LFS) and administrative data to give an estimate of number of people employed 19. So if a person has two jobs, they will appear twice in the BRES and WFJ results. LFS is a household survey, whereas BRES and WFJ (predominantly) go to employers. There is often a conflict between the industry in which people think they work (LFS) and the industry to which the business is classified (BRES 18 For more information on items to consider when using BRES data for timeseries analysis see http://www.nomisweb.co.uk/articles/news/files/abi2006discontinuities.doc 19 More information on the different sources of employment data and the sources which comprise the Work Force Jobs series can be found in Ganson (2002). 11
and WFJ), and the BRES results are considered to provide a more accurate portrayal of employment by industry. Other differences between the BRES and WFJ concern the definition of selfemployment and the inclusion of working proprietors, government supported trainees and HM Forces. 3.7 Annual Business Survey (ABS) The Annual Business Survey (ABS) used to be known as the Annual Business Inquiry Part 2 (ABI2). The survey collects financial variables from businesses allowing calculation of approximate total output, total intermediate consumption and approximate gross value added, based on National Accounts concepts but aligned with a realistic assessment of the kind of data that companies can actually supply, that is, as collected for Company Accounts. Coverage of the ABS excludes part of the Agriculture industry (SIC2007 groups 011 to 015), Financial and Insurance activities (Section K) and the public sector (Section O and public sector activity within Section P, Education, and Section Q, Health & Social Work) so the National Accounts use a range of additional sources to ensure coverage of the whole economy. Questionnaires are sent to around 65 thousand businesses using a random sample from the IDBR stratified according to business size in terms of employment, including all large businesses then a progressively reducing fraction of smaller businesses 20. The questionnaires ask for data for the calendar year but accept financial years ending between April 6 preceding the required calendar year and April 5 following it. Long form-types (see Annex 5 for an example of questions asked of units in the production industry) are sent to all businesses with an employment of 250 20 Post-stratification is carried out to allow for low-employment, high-turnover businesses. 12
or more and also to a proportion of selected businesses with lower employment. Short form-types are sent to the remaining selected businesses 21. Responses to short forms are expanded to cover all long formtype variables using the pattern of returned long form-type data within each industry and employment size-band this is referred to as imputation and has an impact on data quality 22. Returned data are then weighted ( grossed ) to UK level using ratio estimation. Results are published on the ONS website at the UK and regional level by industry. In addition to those standard tables, bespoke tables can be produced on request. 3.8 Other ONS business surveys A full list of surveys carried out by the ONS can be found in the ONS Simplification Plan 2009, which gives details of number of questionnaires, estimated compliance cost and a brief background for each survey. Other economic surveys conducted by the ONS include; Annual Survey of Hours and Earnings (ASHE) PRODCOM (Products of European Community) Inquiry of Activity for Construction and Allied Trades Monthly Production Survey (MPS) and Monthly Inquiry into the Distribution and Services Sector (MIDSS) monthly turnover and quarterly employment, now combined into the Monthly and Quarterly Business Surveys (MBS and QBS). Monthly Retail Trades Inquiry. After initial investigations these sources were not deemed suitable for measuring an IOI and were not explored further. 21 More background on the Annual Business Survey (formerly the ABI), including information on long and short forms can be found at http://www.statistics.gov.uk/abi/background_info.asp. 22 More information on the types and impact of imputation can be found at http://www2.napier.ac.uk/depts/fhls/peas/imputation.asp; http://www.missingdata.org.uk/ 13
3.9 GVA: ESA, National and Regional Accounts The European System of Accounts 1995 (ESA95 23 ) includes a requirement to maintain a business register and supply economic data under regulation to Eurostat, the statistical arm of the European Union. In order to produce monthly, quarterly and annual estimates to feed into the National Accounts, a wide range of surveys are conducted. Monthly surveys are used to estimate changes in turnover and current price output of industries (for example, as used to compile indices of production, construction, distribution and services 24 ) to inform early estimates of quarterly Gross Domestic Product (GDP). GDP is calculated at current price and chained volume price (stripping out the effect of price changes) 25. The first estimate of quarterly GDP, the preliminary estimate, is produced in the first month following the end of the quarter 26. The quarterly estimate is updated in the second month for the UK Output, Income and Expenditure release. Additional information from quarterly surveys inform the third month s update for the Quarterly National Accounts, allowing estimation of greater levels of detail by component and industry. The quarterly estimate may also be revised during the annual benchmarking process 27 over the following two years, provisional (for reference year T-1, where T is the year of publication) and final (T-2), for the UK National Accounts (Blue Book) using annual survey and administrative data that only becomes available some time after the reference year, including, for example, the results of the Annual Business Survey. 23 ESA95 is to be updated to a 2010 version, ESA 2010. 24 See ONS website; www.statistics.gov.uk/cci/nugget.asp?id=198; www.statistics.gov.uk/cci/nugget.asp?id=2570; www.statistics.gov.uk/cci/nugget.asp?id=558 25 More information on the approaches to calculating GDP can be found in Annex 1. 26 Brown et al (2009), Reed (2000) and Skipper (2005) provide more information on the early estimates of GDP. 27 UK Input-Output Analyses, 2006 Edition pages 214-216 14
There are a number of differences between survey results and National Accounts estimates. Survey results stand alone, whereas the National Accounts take on and balance a wide range of survey and administrative data. For example, GDP can be calculated using three approaches, production, income or expenditure (see Annex 1). Conceptually, all three approaches should give the same result. However, in the real world, sampling and reporting errors, lack of coverage and conceptual differences between data sources mean that adjustments must be made before a balance can be struck 28. The ONS does not produce regional short term indicators (RSTIs) for all regions. However, the Scottish Government and Northern Ireland produce their own versions and the ONS produces estimates for the Welsh Assembly Government. The RDAs funded the ONS to carry out a pilot exercise to produce RSTIs for each English region in November 2009. The RDAs are currently considering funding an update of the pilot, and ascertaining whether there is sufficient interest in moving to regular full scale production of RSTIs covering all English regions and devolved administrations. 29 The ONS publishes regional current price GVA in December each year (for reference year T-1, although industry and sub-regional estimates are only available for T-2) and plans to publish a prototype constant price GVA series compiled using the production approach (GVA(P)) in late 2010. However, the ONS has no plans to produce regular price indices at regional level which would allow estimates of regional inflation. Reducing the gap in GVA growth between regions is one of the Public Service Agreement (PSA) targets used to measure regional economic performance and assess the performance of the RDAs (see section 6 for more information on PSA targets and RDAs). 28 Penneck and Mahajan (1999) Annual Coherence Adjustments in the National Accounts 29 More information on the Regional Short term Indicators can be found at www.statistics.gov.uk/statbase/product.asp?vlnk=15353 15
3.10 Section Summary The type of business structure and its size (employment & turnover) affects the amount of data publicly available and available for use at the scale of the IOI. Individual firm level data is not available from ONS due to the issues of disclosure and the legislation within which it operates. Most returned survey data are collected from large businesses as defined by employment and turnover. The ONS uses imputation, grossing and other methods to produce UK and regional level estimates. ONS data which has potential for use in estimating IOI Value Added are derived from the IDBR (administrative data) or survey datasets, such as the ABI, BRES or ABS. Other ONS surveys are not deemed suitable for estimating IOI Value Added. IDBR The IDBR is a statistical register which is used as a sampling frame for business surveys. The IDBR contains extremely detailed information on business structures but the variables it holds are not fully aligned with National Accounts concepts, for example institutional sectors and turnover. IDBR covers the majority of businesses in the UK except very small businesses not registered for VAT and/or PAYE and some non-profit organisations. Turnover data from the IDBR is only available at the enterprise unit level, and not for local units, which may give a head office location bias and limit its usefulness for evaluating IOIs if turnover is used as a proxy for GVA. ONS surveys ABI1/BRES provides information on employment. 16
ABI2/ABS provides information on financial variables including turnover, purchase of goods and services, gross fixed capital formation and employment costs. ONS surveys are not designed to produce estimates at the firm level. The majority of ONS surveys are stratified to give accurate results at the national level, not regional or sub-regional. ONS survey responses are used to create estimates which are used in the estimation of UK and Regional GVA and therefore the questions asked of businesses are as consistent with National Accounts concepts as possible. This consistency could allow the wording from ONS survey questions to be used in beneficiary surveys to estimate IOI Value Added. When using ONS surveys, the greater the detail (by geography or industry) the greater the likelihood of suppression to avoid disclosure. This does not allow meaningful detailed analysis of IOI impact by detailed sector and geography; similarly, although detail may be available by sector or by geography, it may be suppressed if data are required by sector and by geography. Discontinuities resulting from changes in classification and methodology can make time series analysis difficult, although the ONS produces analyses of discontinuities to allow assessment of the scale of changes. Identifying real change from sampling variability is extremely difficult for detailed geography and sectors. ABS has the greatest potential for producing estimates of IOI Value Added consistent with UK & Regional GVA. GVA: ESA, National and regional accounts ONS surveys and other sources are used to help meet the requirement to produce GVA and GDP data. The survey results are only part of the production of an estimate of GDP as adjustments are made for conceptual, coverage and quality 17
reasons and to balance the different approaches (production and income), these adjustments can not be applied at the level of the IOI. The complexity of calculating GDP and regional GVA means that it takes around eighteen months to produce benchmarked national figures, and nearly two years to produce accurate regional figures. Short term indicators of output for different sectors, within each of the nine regions of England have been produced recently, however these are only indicators of change rather than levels of GVA and are not suitable for measuring IOI Value Added. The complex calculations and imputations used to produce GDP and regional GVA estimates can not be applied at the firm level to produce IOI Value Added. 4 Input-Output framework and analyses 4.1 Description The UK is an open economy with a clearly defined national boundary, across which pass exports and imports. If all economic activity in the UK was measured over a period of time, each transaction would have an equal and opposite counterpart (that is a buyer and seller); supply of goods and services would be balanced by equal value of uses of goods and services; and the output of each industry would be equivalent to the sum of the inputs used to produce the output. Part of the balancing of annual GDP through the Input-Output (I-O) framework involves the compilation of annual current price I-O Supply & Use Tables (SUTs), in which estimates of industry output, product supply, industry uses and product use are placed in a framework 30, showing how products are used in each industry to produce their outputs, allowing the identification of imbalances and the detailed allocation of balancing adjustments across 30 Input output supply & use tables contain 108 industries and 123 products. 18
industries, products and the components of production, income and expenditure. Other uses of I-O SUTs are to provide annual weights for the output and input indices of Production, Distribution, Construction and Services and for constant price GDP. The tables also provide a basis for the UK s Environmental Accounts 31. The GVA components by industry provide control totals for ONS Regional GVA estimates. Only UK level tables are produced by ONS, but other public and commercial organisations produce their own versions, including regional tables. Examples include Experian 32 and One North East 33,34. There are a number of difficulties to be overcome when compiling regional SUTs. For example, data on imports to and exports from the UK are collected using a mix of survey and administrative sources and, as most trade is through ports and airports, the data is comprehensive for the sample surveyed and accurate, given various non-sampling errors. Movement of goods and services across regional boundaries is not measured, so it is difficult to estimate the value of exports or imports from one region to another. The distribution of goods through wholesale and retail outlets provides an additional level of complexity when assessing trade between regions. 31 More information on Environmental Accounts can be accessed from http://www.statistics.gov.uk/statbase/product.asp?vlnk=3698 32 See http://economics.experian.co.uk/region%20and%20cities.aspx. 33 See http://www.nerip.com/download/344/ian%20stone%20econ%20model%20presentation%2020%20november%202 006.ppt.aspx 34 Eurostat are developing SUTs and Symmetric I-O Tables for the EU and Euro area, including tables for countries that do not produce their own. 19
4.2 Supply and Use Tables (SUTs) SUTs are compiled at current prices, showing supply and demand for each product at purchasers prices. SUTs are produced each year for reference year T-2 (where T is the year of publication). Summary tables are published in the UK National Accounts (Blue Book 35 ) and full tables are published in the Input-Output section of the ONS website 36. The process of compiling SUTs requires vast amounts of data, some of which are not available or are of lower quality than desired, even at the UK level. The ABS is the main source of estimates of total sales and purchases by industries. However, alternative sources are required to allocate total sales and purchases to products. For example, data on sales by product are available from PRODCOM for the manufacturing industries, but there are no equivalent sources for other UK industries (e.g. a SERVCOM for the service industries). Detailed data on UK purchases of goods and services by industry (which is an important indicator of supply chains and indirect impacts) are available from the ONS Purchases Inquiry prior to 2007. Data are not available for years after 2007. For more information see Annex 7. 4.3 Analytical Tables (Symmetric Input-Output Tables) I-O Analytical Tables (also known as Symmetric Input-Output Tables) are compiled at current basic prices and show imports separately. The transport and distribution margins on products are also treated separately, and are shown as a purchase of the transport and distribution products by industries and consumers. Taxes and subsidies on products are reallocated to move purchases from purchasers prices to basic prices. Applying various assumptions, the Supply Table is diagonalised and the resulting Use Table is converted to coefficient form and multipliers produced. For more information see Annex 7. 35 Current and historical versions of the Blue Book can be accessed from http://www.statistics.gov.uk/statbase/product.asp?vlnk=1143. 36 Input-Output tables and information can be found at www.statistics.gov.uk/inputoutput. 20
The tables can be used to estimate the direct, indirect and induced effects of increasing supply or demand for products, also known as impact or supply chain analysis. The tables show the goods and services used to produce a unit value of output for an industry. Increasing the output of an industry in response to increased demand for its product directly increases the amount of goods and services used to produce that additional output. Indirectly, each of the industries that produce those goods and services must increase their output to match the additional demand. Further iterations are required to supply the additional demands of those industries. As wages and salaries increase in line with increased output of industries, there may also be an induced effect leading to increased demand for goods and services by households. Type I multipliers reflect the direct and indirect impacts of a change in demand. Type II multipliers also include an estimate of the induced effects. Multipliers can be calculated for a range of variables, including output, employment, income and GVA (examples of employment cost and output multipliers can be found in Annex 7). A full analysis of the impact of a change requires the use of matrix algebra, but multipliers can be used to provide an approximate estimate. For example, if the output multiplier for the chemical industry is 1.45, then an increase in demand of 10.0 million will directly increase the output of the chemical industry by 10.0 million, but applying the multiplier gives us an estimate of the direct and indirect effect throughout the economy, 10.0 million x 1.45 = 14.5 million. As can be seen in Annex 7, there is a wide variation between industry multipliers, and accurate estimates can only be made using the most detailed versions (and there may be further variability included within even the most detailed published level) 37. 37 It should be noted that using multipliers will not give estimates of the impact of additionality, substitution, displacement, etc. See section 6 for a discussion of guidance from BIS on estimation of these factors and HMT s Green Book. 21
The ONS produces Analytical Tables for the UK roughly once every 5 years. However, the latest tables available are for 1995 (on a SIC(1992) basis) and were published in 2002. In 2006, to provide resources for the modernisation of National Accounts, plans to produce Annual Tables were suspended 38. The ONS plans to produce Analytical Tables for the reference year 2005 (on a SIC(2003) basis) to be published in 2011. 4.4 Section Summary The I-O framework shows detailed industry relationships and can be used to estimate direct and indirect impacts of changes to the economy but are based on national industry/supply chain structures. The UK tables allow a whole economy impact to be determined, with the impacts across different industries identifiable. However, this analysis would reflect the UK industry structure and their use to estimate regional impacts may underestimate or overstate the impact because of the different industry mix and supply chains across regions. Estimates of the impact of any IOI would be consistent with National Accounting concepts. Symmetric I-O Tables are produced infrequently, approximately every 5 years and therefore do not reflect any changes to the composition of the economy in the interim period, for example through increased fuel costs and technological advances, assuming zero elasticity. Intermediate consumption patterns in the UK SUTs are broadly fixed on 2004/5 structures. Regional I-O Tables are available from proprietary data houses but the data on which they are based are largely national. The lack of detailed regional data on sales and purchases by industry means that it is very difficult to produce tables without using UK level structures. Multipliers from ONS Symmetric I-O Tables are national, reflecting national rather than regional supply chains and industry compositions. 38 More information on modernising the National Accounts can be found in see papers by Beadle (2007), Clifton-Fearnside, Akers et al 22
5 Company accounts 5.1 Company Accounts: Legal requirements on companies, SMEs Businesses with annual turnover above 70 thousand, the current cut-off, must register with HMRC for VAT and businesses with employees must operate a PAYE system to collect national insurance and income tax. Although at first sight this appears to be a rich source of data, there are restrictions on the availability and use of administrative information for statistical purposes. The data may also be unsuitable because of coverage, classification, definitional and conceptual differences and issues of timeliness. There may also be issues with non-response or avoidance 39. Obtaining administrative data may also be subject to legal limitations and subject to confidentiality restrictions. The ONS already has access to some administrative data, such as the NHS local registers for patients transferring between regions and some variables for VAT/PAYE registrations from HMRC. Individual government departments produce their own aggregate statistical analyses from some administrative sources 40. The Statistics and Registration Service Act (SRSA) 2007 41 established a framework for sharing of administrative datasets between government departments, but this requires approval by Parliament and takes time to negotiate and set up; some data has already been shared, and work continues on other Data Sharing Orders. 39 Non-response and avoidance is less of an issue with administrative data than survey-based data. 40 ONS and other government departments must adhere to Protocol 3 of UK Statistics Authority Code of Practice. More information on the detail of Protocol 3 can be found at: http://www.statisticsauthority.gov.uk/assessment/code-of-practice/index.html 41 Statistics and Registration Service Act 2007 - http://www.opsi.gov.uk/acts/acts2007/ukpga_20070018_en_1 23