EU KLEMS project on Productivity in the European Union

1. EU KLEMS project on Productivity in the European Union Presentation at EPROS meeting, Luxembourg, 8-9 November 2004, Luxembourg Bart van Ark (Groningen Growth and Development Centre, University of Groningen) This project is funded by the European Commission, Research Directorate General as part of the 6th Framework Programme, Priority 8, "Policy Support and Anticipating Scientific and Technological Needs".

2. Main aspects • EU KLEMS project is 3-year statistical and analytical research project funded by 6th Framework Programme • Purpose is to create a database on productivity by industry for EU member states with a breakdown into contributions from capital (K), labour (L), energy (E), materials (M) and service inputs (S) • Conduct out a number of analytical research projects in areas of: • analysis of productivity, prices, industry structures, technology and innovation indicators • labour markets and skills • technological progress and innovation • link to productivity research using firm level databases • 14 research institutes across Europe, led by GGDC and NIESR

3. Background for EU KLEMS project (I) • Policy interests: • monitoring and evaluating the Lisbon and Barcelona agendas, complementary to existing indicators (e.g. Eurostat structural indicators) • Divergence between EU and US productivity performance • Impact of new entry of 10 member states on EU economic performance • Developments in academic world: • Growth regression literature is running out of steam • Growth accounting methodologies have become more sophisticated • Need for better data to test hypotheses on, e.g., skill-biased technological change and role of non-technological innovations

4. Background for EU KLEMS project (II) • Statistical developments in productivity measurement and national accounts • Publication of Eurostat Handbooks on Price and Volume Measures and Input-Output Manual • Publication of OECD Productivity and Capital Measurement Manuals • Developments in light of implementation of present SNA and steps towards next SNA version (e.g. role for intangibles - Canberra II group) • Increased availability of firm level databases for productivity measurement

5. Productivity is the Key Variable of Economic Performance

6. Setup of project: Workpackages

7. WP1: Interindustry Accounts (I) • Measures: • Gross output (basic prices) and intermediate inputs (purchaser prices) at industry level from which to obtain value added • Intermediate inputs (purchase prices) by origin of supply broken down into energy inputs, material inputs and service inputs • Measures of prices for output and intermediate inputs to deflate value series • Industry level: before 1995 ±A31; after 1995 ±A60 • Sources: • Input-Output Tables and National Accounts from individual countries, Eurostat and OECD • Extended to obtain greater industry detail on the basis of census/industry survey information

8. WP1: Interindustry Accounts (II) • Methodological and data research: • Availability of annual IO-tables (ind x ind)] • Construct on basis use/supply tables • Intrapolation in between benchmarks • Inconsistency between GVO and GVA measures from IO-tables and NA • Solve breaks in series due to ESA 95 & SNA 93 • industry classification • treatment of financial intermediation services • Software expenditure Measurement of output in services (market services and public services) • Measurement of quality change in price indices • Use of hedonic prices for ICT output

9. WP2: Labour Accounts (I) • Measures: • Measures of total number of persons engaged (including full-time and part-time distinction) and average and total number of actual hours worked. • Breakdown of labour quantity into gender, age (3-4 categories), and level of educational attainment (3 or more categories). • Obtain measures of total labour compensation • Sources: • National Accounts from individual countries, Eurostat and OECD • Extended to obtain greater industry detail on the basis of labour force statistics • Alternative sources: social security statistics, household surveys

10. WP2: Labour Accounts (II) • Methodological and data research: • Consistency of employment from enterprise/ establishment based surveys, household surveys and national accounts • Small samples can lead to volatile series - can introduce errors • Analysis of average working hours (e.g., with time use surveys) • Detailed comparison of categories of educational attainment: • High, Medium, Low • Country specific divisions • Occupational classifications, e.g., for IT workers • Labour costs – must include non-wage labour costs • Self-employed – wage imputation • Temporary workers (employment exchanges) – where they are allocated?

11. WP3: Capital Accounts (I) • Measures: • Investment in seven asset categories (IT equipment, communication equipment, other machinery, transport equipment, software, non-res. structures, dwellings) • Estimation of capital stocks and rental prices. • Price indices for investment and user cost to obtain capital services. • Measures of total capital compensation • Sources: • National Accounts from individual countries, Eurostat and OECD • Extended to obtain greater industry detail on the basis of commodity flow tables, production and trade statistics

12. WP3: Capital Accounts (II) • Methodological and data research: • Specific capital assets: • Measurement of software • Treatment of owner occupied housing • Land, inventories and infrastructure • Leased assets • Hedonic price measures for ICT capital inputs • Age of physical capital stock: harmonised or national? • Age-efficiency profiles: harmonised or national? • Role of taxation differences • Rate of return – internal or external, aggregate or industry specific

13. Statistical vs. analytical modules of database • Statistical module of the database: • Data consistent with those published by NSIs • According to rules and conventions on national accounts, supply and use tables, commodity flow methods, etc. (SNA 1993, ESA 1995) • Data meet statistical standards of NSI's and Eurostat and can eventually be incorporated in their present statistical practices. • Analytical module of the database • Developed parallel to the Statistical module • Produces additional data and fills gaps using alternative techniques (e.g. growth accounting) which presently will go beyond the ESA95 and SNA93 or do not (yet) meet statistical standards • Consider alternative or pioneering assumptions regarding statistical conventions on, for example, the output and price measurement of ICT goods and non-market services, measurement of skill levels, construction of capital stock and capital services, or capitalization of intangible assets.

14. Deliverables related to NSI’s • Statistical roadmap (month 9): • methods and procedures guide for consortium • already available in mini-format • EU KLEMS Manual (month 24): user guide • Statistical implementation plan (month 35): producer guide • Statistical progress report (every 6 months)

15. Involvement of NSI’s (I) • Discuss with (national) consortium members possibilities to match data availability at NSI’s and data requirements by consortium • Advice on methodologies • Co-operate in areas of specific interest of NSI’s • Advice on quality of results • Discuss possibilities to implement productivity dataset at NSI’s • Participate in consortium workshops • Invite consortium members for participation in NSI projects or events as well as ESTAT NAWG or EPROS

16. Involvement of National Statistical Agencies (II) • Subcontracting: Statistics Finland, ISTAT, possibly ONS • Participatory status: Statistics Netherlands • Observer status: … • Contacts: Statistics Austria, INSEE, INE, Statistisches Bundesamt, Statistics Denmark, Statistics Sweden, Institute of National Statistics (Belgium), ... • Other EU-15 partners: Greece, Ireland, Luxembourg, Portugal • New member countries covered by project: Czech Republic, Hungary, Poland • Other new member countries may contribute

17. Next steps • October 04-February 05: contacts with NSIs to investigate possibilities for co-operation and advice on development of statistical roadmap • March-November 05: possibility to plan additional meetings for exchanging information on methods, data, etc. • January 06-October 06: first round of feedback from NSI’s on results for statistical and analytical module • As of beginning 06: discussion of statistical implementation plan • Throughout project: invitation to participate in Consortium activities and regular reporting to NAWG