Transcript WIOD Database Construction Marcel Timmer

This project is funded by the European Commission, Research Directorate General as part
of the 7th Framework Programme, Theme 8: Socio-Economic Sciences and Humanities.
Grant Agreement no: 225 281
Socio-economic accounts
Abdul A. Erumban
Reitze Gouma
Marcel P. Timmer
Gaaitzen J. de Vries
Groningen Growth and Development Centre
University of Groningen
WIOD Conference, Sevilla May 2011
Outline
- What is included in the socio-economic accounts?
- Approach in WIOD for constructing labor by skill type
- Approach in GTAP for constructing labor by skill type
- Comparison of approaches: China
- Current status, World KLEMS initiative and ongoing work
Socio-economic accounts
Builds upon the detailed industry-level EU KLEMS
database, extension to other countries in WIOD:
• Gross output and value added (consistent with
National Accounts) in current, constant, and
international prices
• Capital formation
• Labor by skill types (education based)
• Low-skilled, Medium-skilled, High-skilled
WIOD approach labor by skill type
- Collection of country-specific data for non-EU countries (that is, those
not included in the EU KLEMS database)
- Internal, intertemporal, and international consistency
- Output and capital formation from National Accounts (NA)
- Labor input data from sources consistent to NAs
-
Economic censuses
Employment and labor force statistics
Households surveys
- PPPs based on input-output approach (Timmer and Inklaar, 2012)
GTAP approach labor by skill type
• Previous versions of GTAP were based on wage and employment data from 19701992 for 13 countries, with various cross-country assumptions (e.g. no ‘real’ data for
China)
GTAP version 8
[Weingarden and Tsigas, 2010]
• Mapping for 150 countries
• ILO Yearbook of Labor Statistics: employment by industry
and occupation (for a single year 2005/2006)
• ILO October Inquiry: wage by job
• National data for China and India
• Matching wage by job with occupations
Comparison example: China
GTAP (single year 2002)
• Employment by occupation for seven industries for 2002 from
China Labor Statistical Yearbook [CSLY] (2007)
• Distribution of education by sector and occupation by education
for 2006 from CLSY(2007)
• Disaggregate some occupations using ILO employment data
from 1982
• Wage by job from ILO October Inquiry
• Match jobs with occupations
Comparison example: China
WIOD (time series1995-2006)
• Joint work with: Harry Wu’s group (Hitotsubashi University & The
Conference Board) as well as NBS
• Employment from China Statistical Yearbook, additional detail from
sector-specific surveys. First China Economic Census 2004 allows us to
include self-employed by industry
• 2004 Distribution of educational attainment by detailed industry from
the First China Economic Census 2004
• Trend for other years from CLSY for 2002 onwards, and other sectorspecific surveys for earlier years
• Wage data from various rounds of the China Household Income Project
(microdata)
Socio-Economic Accounts - current status
EU 15
Y
K
L
L*
EU 12
Y
1
Austria
X
X
X
X
Bulgaria
X
2
Belgium
X
X
X
X
Cyprus
X
3
Denmark
X
X
X
X
Czech Rep
X
4
Finland
X
X
X
X
Estonia
X
5
France
X
X
X
X
Hungary
X
6
Germany
X
X
X
X
Latvia
X
7
Greece
X
X
X
X
Lithuania
8
Ireland
X
X
X
X
9
Italy
X
X
X
10 Luxembourg
X
X
11 Netherlands
X
12 Portugal
K
Non EU 13
Y
K
L
L*
X
Australia
X
X
X
X
X
Brazil
X
Canada
X
China
X
X
India
X
X
X
Indonesia
X
X
X
X
Japan
X
X
X
X
Malta
X
X
Korea
X
X
X
X
X
Poland
X
X
Mexico
X
X
X
X
Romania
X
X
Russia
X
X
X
X
X
Slovak Rep
X
X
X
Taiwan
X
X
X
X
X
X
Slovenia
X
X
X
Turkey
X
X
13 Spain
X
X
X
X
USA
X
14 Sweden
X
X
X
X
15 UK
X
X
X
X
X
L
X
L*
X
X
X
X
Y =output and value added, current and constant
K =Capital formation
L =Employment
L* =Employment by skill (low, medium, high)
X
X
X
X
X
X
X
X
X
WIOD – World KLEMS
D5.2 (month of delivery: 12): Preliminary KLEMS database for WIOD
countries not covered in EU KLEMS
 Delivered employment quanties for all WIOD countries
 Currently working and waiting on labor by skill type and capital
estimates for countries not yet covered in EU KLEMS database
 To this end we have set up the WORLD KLEMS consortium
 First conference August 2010 at Harvard, Cambridge included
national statisticians and researchers from many countries (90
participants).
 Work is currently under way by dedicated research groups in
cooperation with NSIs
World KLEMS (WIOD relevant)
US: Jorgenson and associates (Harvard) with BEA/BLS
Canada: Stats Can
Australia: Stats Australia
Japan: Fukao and associates (Hitotsubashi)
Korea: Pyo and associates (Seoul Nat Uni)
China: Harry Wu group (Conference Board, Hitotsubashi) + NSI
India: Das and associates (ICRIER, Delhi)
Brazil: Hofman and associates (ECLAC) with NSI and local groups
Mexico: Hofman and associates (ECLAC) with NSI
Russia: Groningen in cooperation with Rossstat
Indonesia/Taiwan: Groningen with Khuong Vu (Singapore Nat Uni)
Turkey: Groningen with Conference Board
Ongoing work
• China and India: good output and employment estimates,
testing and improving labor split by types
• Early stage: labor split by skill types for Eastern European
countries, and several large developing countries (e.g.
Brazil, Indonesia, Mexico, and Turkey)
• Updating output and employment for all countries to 2009
Thank you for your attention