EU KLEMS project on Productivity in the European

EU KLEMS project on Productivity in the European Union Presentation for Working Group on National Accounts Eurostat, Luxembourg, 27 June 2005 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 6 th Framework Programme, Priority 8, "Policy Support and Anticipating Scientific and Technological Needs".

Main aspects • • EU KLEMS project is 3 -year statistical and analytical research project funded by 6 th Framework Programme Purpose is to create a database on growth accounts by industry (NACE 60+) for EU member states with a breakdown into contributions from capital (K), labour (L), energy (E), materials (M) and service inputs (S) Full coverage of “old” EU-15 plus 5 new member states (PL, SK, HU, CZ and SI) Limited coverage of other 5 new member states (CY, MT, LV and EE) Also comparisons with U. S. , Canada and Japan 1970 -2005, with greatest detail for post-revision period 14 research institutes across Europe, led by GGDC and NIESR In 2 nd phase conduct a number of analytical research projects

Setup of project: Workpackages

Progress June 04 – June 05 • • • Consortium meetings (October 2004, London; June 2005, Helsinki) • Co-ordination of database construction and analytical work • Presentation of project results Data co-ordination group meetings (June 2004 & February 2005, A’dam) • Decisions about concepts • Identification of problem areas Data collection: • Data availability questionnaire in January/February • 1 st round of data collection focused on pre-revision data Data base management • Workshop Database Management (DM) group on 18 & 19 January • Acquisition and installation of SAS software & Prodsys Contacts & meetings with NSI’s • Visited most NSI’s three status positions • Data delivery schedules

• NSI’s have shown major interest in project Three status positions: Subcontracting: Statistics Finland, ISTAT, Statistics Netherlands • • Observer status: INSEE, Statistics Denmark, Statistisches Bundesamt, Institute of National Statistics (Belgium), Statistics Austria, Statistics Ireland, INE, Statistical Office Slovakia, Statistical Office Poland, CSO Hungary Participatory status: Statistics Sweden, STATEC (Luxembourg), ONS Contacts under development: New member countries covered by project: Czech Republic, Slovenia • • • Contacts to be developed: Greece, Portugal, Lithuania, Latvia, Estonia, Cyprus, Malta Also contacts with: • USA (Harvard University, BEA, BLS), Japan (RIETI, Hitotsubashi), Canada (Statistics Canada)

Main Issues on WP 1 -WP 4 • WP 1: • • • Output and intermediate inputs will be based on revised Supply and Use tables (with FISIM adjustment and chain link) Refinement to methodology to measure use table in basic prices (capture trade and transportation margins) Industry classification (EUK-72) close to NACE Rev. 1 with some refinements Consortium will integrate older pre-revision tables (where possible in co-operation with NSIs) Working agreement with OECD STI (Science, Technology and Industry) on SUT work (in consultation with Eurostat)

Main Issues on WP 1 -WP 4 • WP 2: • • Distinction between labour quantity (hours and employment) and labour quantity (age, gender, education level) Labour quantity uses integrated labour and national accounts as default; but alternative approaches are considered Labour quality will be dependent on country sources WP 3: • • • Point of departure are capital formation series Key issue is maximum breakdown of asset types (including ICT categories) … … and method of allocation of assets to individual industries

Main Issues on WP 1 -WP 4 • WP 4: • • PPPs are required on industry-by-industry basis Make partly use of Output PPPs based on unit value ratios (e. g. from Prodcom) … … partly of Expenditure PPPs, allocated to individual industries and adjusted for relative transport and trade margins and relative net taxes Multilateral weighting of industry PPPs on the basis of EKS weighting system

EU KLEMS Analytical Module is set up as a Relational Database Central datahub … but can be mirrored by individual consortium partners or NSI’s

What is a Relational Database? • • Separate data and meta-data Meta-data (concordances) has number of dimensions, e. g. • Year: 1970, 1971, …. . • Country: A, B, C, . . • Industry: 1, 2, 3, …. • Unit: nominal, real, deflator • Type: investment in building, machinery, …, If one wants to call up nominal investment in machinery in industry 3 in country A in 1970, dimensions are combined and link to a unique number Relational database is different from a hierarchical system and more flexible

Core of the Database is Programmed in SAS which exploits Advantages of Relational Database Structure

Productivity and other computations are done in Prod. Sys©

What is Prod. Sys© and what can it do? • • • Prod. Sys is software program on top of SAS designed for productivity measurement and growth accounting (ESI-VU/ Federal Reserve Board) Basic tools for EU KLEMS database: • Aggregation • Disaggregation • Balancing • Concording • Cross-classification Prod. Sys will be ‘open source’: • Users can make modifications • EU KLEMS will maintain an ‘official’ EU KLEMS production version of Prod. Sys

The Analytical Module will be complemented with a Statistical Module

Statistical vs. analytical modules of database Analytical module of the database • • • Core of the EU KLEMS database Uses “best practice” techniques in area of growth accounting Focuses on international consistency Aim is full coverage (country * industry * variable) for revision period Consider alternative or pioneering assumptions (for example, output and price measurement of ICT goods and non-market services, measurement of skill levels, construction of capital services, capitalization of intangible assets). Statistical module of the database: • • Developed parallel to the analytical module Data consistent with those published by NSIs Methods according to rules and conventions on national accounts, supply and use tables, commodity flow methods, etc. (SNA 1993, ESA 1995) or at least supported by NSI’s Statistical module meets statistical standards of NSI's and Eurostat and can eventually be incorporated in their present statistical practices.

Issues in co-operation with NSI’s requires continuous contacts on bilateral basis • Access to unpublished data and sharing between consortium partners requires specific arrangements with NSI’s • • In principle use integrated labour and national accounts for labour quantity data as default, but alternative sources (including micro data, where possible) are also important • Dilemma of not using “not so reliable” data on industry-by-asset tables or using estimation methods • • Assistance and advice in using greater (unpublished) detail from Supply & Use tables as well as historical (pre-revision) SUTs. Use of unpublished data for development of analytical and statistical modules of database needs to be carefully monitored EU KLEMS aims to organize working schedules around individual NSI’s programmes, but flexibility is needed to make it work

Deliverables related to NSI’s • • • Statistical roadmap, including data base management system (draft version available, final version after summer 05) Preliminary test version of EU KLEMS database in 1 st quarter of 06 First public version of EU KLEMS dataset with EU KLEMS Manual in 4 th quarter of 06 Statistical implementation plan (producer guide) by 3 rd quarter 07 Statistical progress report (every 6 months)

Next steps • 3 rd and 4 th quarter 2005 • • • Possibility to plan additional meetings for exchanging information on methods, data, etc. • EU KLEMS participation in OECD workshop on productivity measurement (Madrid) (17 -19 October Madrid) • • Feedback from NSIs on statistical Roadmap November: expert workshop on WP 2 (labour accounts) (London) 15/16 September: expert workshop on WP 1 (inter-industry accounts) (Groningen) 1 st quarter 2006: • • Release of preliminary version of EU KLEMS database Early 2006: special meeting for NSI’s and research from new member states

Next steps • 2 nd & 3 rd quarter 2006: • • Additional data inquiries and collection • Start on discussion of statistical implementation plan • • Feedback from NSI’s on preliminary version of EU KLEMS database Session on productivity measurement at IARIW meeting (August 2006, Joensuu, Finland) 4 th quarter 2006: • Release first public version of EU KLEMS database

Contact Details • Bart van Ark (project director) Groningen Growth and Development Centre, University of Groningen PO Box 800, 9700 AV Groningen Telephone: +31 50 363 3674 E-mail: h. h. van. ark@rug. nl • Gerard Ypma (project administrator) Groningen Growth and Development Centre, University of Groningen PO Box 800, 9700 AV Groningen Telephone: +31 50 363 3707 E-mail: g. ypma@rug. nl • • E-mail: Website: euklems@eco. rug. nl http: //www. euklems. net