Transcript Slide 1

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 6th Framework Programme,
Priority 8, "Policy Support and Anticipating Scientific and
Technological Needs".
Main aspects
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EU KLEMS project is 3-year statistical and analytical research
project funded by 6th 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, LT, 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 2nd phase conduct a number of analytical research projects
Setup of project: Workpackages
Research
papers
WP2
Labour
accounts
Research
papers
WP3
Capital flow
accounts
Research
papers
WP4
Relative
price levels
Research
papers
WP7: Analysis of LP, TFP, prices and structure
WP1
Inter-industry
accounts
WP5: Data base development
WP 11: Communication and Dissemination
WP8
Labour Markets
and
Skill Formation
WP9
Technological
Progress and
Innovation
WP10
Linkages
with FirmLevel Data-Bases
WP6: Statistical Roadmap and Statistical Implementation Plan
in consultation with Eurostat and National Statistical Institutes
Progress June 04 – June 05
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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
• 1st 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
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NSI’s have shown major interest in project
Three status positions:
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Subcontracting: Statistics Finland, ISTAT, Statistics Netherlands
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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:
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New member countries covered by project: Czech Republic,
Slovenia
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Contacts to be developed: Greece, Portugal, Lithuania, Latvia,
Estonia, Cyprus, Malta
Also contacts with:
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USA (Harvard University, BEA, BLS),Japan (RIETI, Hitotsubashi),
Canada (Statistics Canada)
Main Issues on WP1-WP4
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WP1:
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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 WP1-WP4
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WP2:
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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
WP3:
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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 WP1-WP4
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WP4:
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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
EU KLEMS
Consortium
Partner
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B. Readable
format (incl.
meta-data)
A. Basic
data
National
Statistical
Office
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C. Input
KLEMS
data
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D. Output
KLEMS
data
E1. EU
KLEMS
Public
Output
Analytical
module
… but can be mirrored
by individual
consortium partners
or NSI’s
What is a Relational Database?
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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
SAS
EU KLEMS
Consortium
Partner
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B. Readable
format (incl.
meta-data)
A. Basic
data
National
Statistical
Office
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C. Input
KLEMS
data
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D. Output
KLEMS
data
E1. EU
KLEMS
Public
Output
Analytical
module
Productivity and other computations
are done in ProdSys©
SAS
ProdSys
EU KLEMS
Consortium
Partner
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B. Readable
format (incl.
meta-data)
A. Basic
data
National
Statistical
Office
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4
C. Input
KLEMS
data
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D. Output
KLEMS
data
E1. EU
KLEMS
Public
Output
Analytical
module
What is ProdSys© and what can it do?
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ProdSys 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
ProdSys will be ‘open source’:
• Users can make modifications
• EU KLEMS will maintain an ‘official’ EU KLEMS production
version of ProdSys
The Analytical Module will be
complemented with a Statistical Module
SAS
ProdSys
EU KLEMS
Consortium
Partner
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B. Readable
format (incl.
meta-data)
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C. Input
KLEMS
data
5
D. Output
KLEMS
data
A. Basic
data
National
Statistical
Office
NSO-approved input & output data
E1. EU
KLEMS
Public
Output
Analytical
module
E2. Public
Output
Statistical
module
Statistical vs. analytical modules of database
Analytical module of the database
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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:
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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
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Access to unpublished data and sharing between consortium
partners requires specific arrangements with NSI’s
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Assistance and advice in using greater (unpublished) detail from
Supply & Use tables as well as historical (pre-revision) SUTs.
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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
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Dilemma of not using “not so reliable” data on industry-by-asset
tables or using estimation methods
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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
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Statistical roadmap, including data base management system
(draft version available, final version after summer 05)
Preliminary test version of EU KLEMS database in 1st quarter of
06
First public version of EU KLEMS dataset with EU KLEMS
Manual in 4th quarter of 06
Statistical implementation plan (producer guide) by 3rd quarter
07
Statistical progress report (every 6 months)
Next steps
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3rd and 4th quarter 2005
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Feedback from NSIs on statistical Roadmap
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Possibility to plan additional meetings for exchanging information on
methods, data, etc.
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EU KLEMS participation in OECD workshop on productivity measurement
(Madrid) (17-19 October Madrid)
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November: expert workshop on WP2 (labour accounts) (London)
15/16 September: expert workshop on WP1 (inter-industry accounts)
(Groningen)
1st quarter 2006:
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Release of preliminary version of EU KLEMS database
Early 2006: special meeting for NSI’s and research from new member
states
Next steps
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2nd & 3rd quarter 2006:
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Feedback from NSI’s on preliminary version of EU KLEMS database
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Additional data inquiries and collection
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Start on discussion of statistical implementation plan
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Session on productivity measurement at IARIW meeting (August 2006,
Joensuu, Finland)
4th quarter 2006:
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Release first public version of EU KLEMS database
Contact Details
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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: [email protected]
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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: [email protected]
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E-mail:
Website:
[email protected]
http://www.euklems.net