Over the years, OECD work on productivity and globalisation has closely mirrored the work of the GGDC on these issues, reflecting considerable cooperation over the past 25 years. Dirk Pilat, Deputy Director of the OECD Directorate for Science, Technology and Innovation, presented OECD work on productivity and Global value chains - an overview and cooperation with the GGDC.

1. OECD WORK ON PRODUCTIVITY
AND GLOBAL VALUE CHAINS –
LESSONS LEARNED AND NEW
DIRECTIONS
Dirk Pilat, Paul Schreyer, Colin Webb and Norihiko Yamano,
OECD
GGDC Anniversary Conference, Groningen, 28 June 2017

2. Outline
2
1. Some background
2. Productivity – data, methods and
analysis
3. GVCs – data, methods and analysis
4. Conclusions

3. – OECD – currently 35 member countries, but close
engagement with over 100 countries
– Productivity was already a key focus of the OECD’s
predecessor, the OEEC, e.g.:
• European Productivity Agency from 1953 to 1960
• Studies inspiring GGDC work, e.g. Paige and
Bombach (1959)
– Globalisation also a natural focus – GVCs only later
– Regular focus on both productivity and globalisation as
drivers of growth. Three aspects to the work:
1. Methodology
2. Data
3. Analysis and policy recommendations
1. Background – the OECD
3

4. Initially, little interaction between productivity analysis &
national accounts and large gaps in the national accounts
framework, e.g.:
– no recognition of capital services, and no breakdown
in the price and volume of capital services;
– the use of index number formulas with a fixed base
year
– an asset boundary largely confined to tangible or
physical capital.
2. Productivity - methodology
4

5. Convergence through:
1. SNA revisions, especially 1993 (e.g. index numbers,
software as intangible asset)
2. OECD Productivity Manual (2001)
3. Extensive debate on ICT and productivity and impacts
on measurement in 1990s (e.g. hedonic prices and
OECD Handbook by Jack Triplett)
4. Blueprint for US accounts (Jorgenson and Landefeld,
2005) and 2008 SNA revision (e.g. R&D)
5. EUKLEMS project – dialogue on measurement
6. OECD Manual on Capital Measurement and Handbook
on Capital Measures of IPR
7. Expert group on Supply-Use Tables
8. Natural resources and capital
2. Productivity - methodology
5

6. At first, mainly analysis at aggregate level:
– But inconsistencies in data and gaps, e.g. in hours
worked and capital
– OECD Productivity Database since 2003
STAN database developed as of 1990, first released in
1992
Also, growing number of policy indicators, e.g. product
market regulation, labour markets, trade, FDI, etc.
2. Productivity – data and the STAN
database, …
6

7. … enabling the 2017 OECD Compendium
of Productivity Indicators
7
www.oecd.org/std/productivity-stats

8. Beyond aggregates and sectoral data:
• Administrative data, such as patent data.
• Private sources of micro data, notably the ORBIS database
developed by Bureau Van Dijk, e.g. in Future of Productivity
(OECD, 2015a).
• Official micro data from statistical offices that are used in
OECD analysis through the use of software routines that are
applied by national statistical agencies to generate new and
policy-relevant micro-aggregated indicators, e.g. in MultiProd
project.
2. Productivity analysis – a growing
use of micro data
8

9. 2. Productivity – breaking down
growth differences
9
-5 0 5 10
TUR
IRL
KOR
POL
SWE
DEU
JPN
OECD
USA
CAN
GBR
AUS
EU28
FRA
BEL
NLD
FIN
ESP
ITA
2009-2015 2001-2007
Growth in GDP
per capita
-5 0 5 10
2009-2015 2001-2007
= Growth in GDP per hour
worked
-5 0 5 10
2009-2015 2001-2007
+ Growth in hours worked
per capita
Contributions to growth in GDP per capita (% change at annual rate)
OECD (2017), OECD Compendium of Productivity Indicators 2017, OECD Publishing, Paris.
http://dx.doi.org/10.1787/pdtvy-2017-en

10. 2. Productivity – looking beyond the
aggregate growth rate (with Orbis)
10
The productivity gap between the globally most productive firms and other firms has widened
Note: “Frontier firms” is the average labour productivity (value added per worker) of the 100 or 5% globally most productive firms in each
two-digit industry. “Non-frontier firms” is the average of all firms, except the 5% globally most productive firms.
Source: OECD preliminary results based on Andrews, D., C. Criscuolo and P. Gal (2016), “Mind the Gap: Productivity Divergence
between the Global Frontier and Laggard Firms”, OECD Productivity Working Papers, Orbis database of Bureau van Dijk.

11. In some sectors, the productivity divergence is
more marked
ICT services Non-ICT services
Note: Excluding the financial sector
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
Frontier firms
Laggards
Top 10%
Top 2%
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
Frontier firms
Laggards
Top 10%
Top 2%
Source: Andrews, D., Criscuolo C., and Gal P. N., “The Best versus the Rest: The Global Productivity Slowdown, Divergence
across Firms and the Role of Public Policy”, OECD Productivity Working Papers, 2016-05, OECD Publishing, Paris.
The divergence in multi-factor productivity growth

12. 2. But is the problem about succeeding at the top
or dragging at the bottom... or both?
Bottom decile 4th-6th decile Top decile
Source: OECD Multiprod project, preliminary results, May 2016, see: http://www.oecd.org/sti/ind/multiprod.htm
Canada manufacturing sector Canada non-financial business services
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
2000 2002 2004 2006 2008 2010 2012
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
2000 2002 2004 2006 2008 2010 2012
Denmark manufacturing sector Denmark non-financial business services
-0.4
-0.3
-0.2
-0.1
0
0.1
2000 2002 2004 2006 2008 2010 2012
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
2000 2002 2004 2006 2008 2010 2012

13. 13
Productivity Divergence is more marked at
the bottom of the distribution
Year fixed effects of a regression of dispersion in log(LP_VA) and in log(MFP_Wooldridge),
Within country-sector pairs
Source: OECD Multiprod project, preliminary results, October 2016, see: http://www.oecd.org/sti/ind/multiprod.htm

14. Compare year fixed effects for
divergence at:
• Top (90-50 wage ratio)
• Bottom (50-10 wage ratio)
of wage distribution.
Results:
– Divergence more pronounced
for the bottom half of the
wage distribution.
Wage dispersion also comes mostly from the
bottom of the distribution
Source: OECD Multiprod project, preliminary results, October 2016, see: http://www.oecd.org/sti/ind/multiprod.htm

15. 2. Productivity – the Global Forum on
Productivity
15
• 2017 Annual Conference of the
Global Forum on Productivity
(26-27 June), Budapest
– “Openness, global value chains,
and productivity-enhancing
policies”
• Opening speeches from OECD
Secretary General Angel Gurría
and Hungarian Minister of
National Economy, Mihály
Varga
• Themes to include productivity
benefits from openness and
GVCs; MNEs, knowledge
spillovers and upgrading; digital
transformation, GVCs and
productivity…
http://oe.cd/GFP2017.

16. 2. Productivity – the OECD’s work today
16
• Productivity has become a central part of the OECD’s agenda:
– Part of overall OECD narrative on inclusive and sustainable growth
– Focus on understanding and ultimately addressing the slowdown in
productivity growth
– Important links to other challenges, e.g. environmental
sustainability and inequality
• More demand-driven:
– Strong interest from governments
– Establishment of Global Forum on Productivity
• Stronger foundation in (cross-country) microdata, to complement
analysis based on aggregate and structural data – many new
insights emerging

17. Genesis of IO work at OECD
Early 1990s
Structural change and impact of embodied R&D on
productivity
Data Requirements:
- Business R&D expenditure by industry
- Output, value added and employment by industry
- Bilateral trade by industry
- Harmonised national Input-Output tables
Birth of the STAN family of databases …
3. The origins of GVC and IO analysis
17

18. - 10 countries
- 5 benchmark years from ≈ 1970 to 1990
- 36 industries – ISIC Rev.2 (SNA68)
- Current and constant prices
- Investment matrices.
- Data still available on request …
OECD’s first I-O publication - 1995
18

19. IO revisited
Early 2000s
- 24 countries
- benchmark year ≈ 1995
- 36 industries – ISIC Rev.3 (SNA93)
- Current prices
Ahmad, N. and A. Wyckoff (2003), "Carbon Dioxide Emissions
Embodied in International Trade of Goods", STI Working
Paper, No. 2003/15, DOI: http://dx.doi.org/10.1787/421482436815
Phase 2 Embodied CO2 - Part 1
19

20. consolidation of IO work
2006 - 2009
- 40+ countries (most OECD, G20)
- Years ≈ 1995, 2000 and 2005
- 48 industries – ISIC Rev.3 (SNA93)
- Current prices
Nakano, S., et al. (2009), "The Measurement of CO2
Embodiments in International Trade: Evidence from the
Harmonised Input-Output and Bilateral Trade
Database", OECD STI Working Papers, No. 2009/03,
DOI: http://dx.doi.org/10.1787/227026518048
Phase 2 Embodied CO2 - Part 2
20

21. Global Value Chains: of growing interest
2005 2007 2008

22. From harmonised IOTs to
Inter-Country Input Output (ICIO) system
2009 +++
- Financial Crisis 2008-09 … led to worldwide collapse in
international trade and … some head-scratching: why so
widespread ?
- Calls for new metrics to understand GVCs
- Strong advocacy from WTO and other international orgs
1st release of TiVA indicators 16th January 2013.
BIG LAUNCH – press conference (OECD SG / WTO DG etc).
40 countries, 18 aggregate industries; 3 years: 2005, 2008, 2009;
supporting documentation, dedicated website and A VIDEO
Phase 3 of the IO work: The TiVA explosion
22

23. 23
OECD-WTO TiVA database and GVC
synthesis for Ministers

24. 24

25. Then expansion
25
January 2013
40 countries
18 industries
3 years
May 2013
57 countries
18 industries
5 years
October 2015
61 countries
34 industries
7 years
December 2016
63 countries
34 industries
17 years
Underlying ICIO
tables:
6.9 million cells
per year

26. 63 Countries
Covering all 35 OECD countries, all EU28, all G20, most ASEAN
and APEC economies and selection of South American countries
(most recent additions: Colombia, Costa Rica, Croatia, Morocco,
Peru and Tunisia)
Firm heterogeneity within manufacturing industry :
China (exporters and non-exporters) and Mexico (global
manufacturing firms)
34 Industries:
from including 16 manufacturing sectors and 14 service sectors
17 years: 1995-2011
First set of “nowcasts” now available up to 2014
Latest set of indicators – TiVA 2016
26

27. Exports require imports
27
Services matter
New bilateral trade patterns emerge
Country / industry integration into GVCs
Some basic messages from the TIVA work
0%
5%
10%
15%
20%
25%
USA JPN DEU KOR IND GBR FRA CAN AUS RUS
Gross exports Domestic value added embodied in foreign final demand
0%
2%
4%
6%
8%
10%
12%
14%
JPN USA KOR DEU AUS TWN SAU RUS BRA HKG
Gross imports Foreign value added in domestic final demand
0%
10%
20%
30%
40%
50%
TWN
SGP
KOR
MYS
THA
KHM
VNM
FIN
TUN
POL
CHN
MEX
SWE
CRI
ESP
ITA
TUR
DEU
FRA
IND
PHL
CAN
GBR
CHE
HKG
CHL
NLD
ZAF
NOR
NZL
USA
JPN
AUS
ARG
RUS
IDN
BRA
COL
BRN
SAU
2011 2009 2008
0%
20%
40%
60%
80%
100%
SAU
BRN
COL
IDN
CHL
MEX
VNM
NOR
KOR
MYS
CHN
RUS
THA
ARG
ZAF
CAN
AUS
TWN
PHL
BRA
JPN
TUN
DEU
POL
TUR
FIN
ITA
KHM
USA
CRI
NZL
IND
ESP
SWE
CHE
FRA
GBR
SGP
NLD
HKG
Domestic VA content Foreign VA content SNA service export share
0%
10%
20%
30%
40%
50%
60%
Agriculture
Mining
Foodproducts
Textiles&apparel
Wood&paper
Coke&petroleum
Chemicals
Rubber&plastics
Non-metallic
minerals
Basicmetals
Fabricatedmetals
Machinery
ICT&electronics
Electricalmachinery
Motorvehicles
Othertransport
Othermanufactures
Wholesale,retail&
hotels
Transport&
telecoms
Finance&
insurance
Businessservices
Otherservices
Total
FVA share of gross exports, 2011 FVA share of gross exports, 1995

28. Challenges of constructing ICIO
DATA
- Compiling and validating maximum official statistics – from
various collections (SNA, international trade, industry stats, HH
consumption, TSA etc) from numerous sources: e.g. OECD,
UNSD, Eurostat and national statistics offices
- Filling gaps and dealing with inconsistencies in data: across sources
and both within and between countries.
- Balancing everything
TECHNICAL
- Since beginnings, always pushing the limits of IT environment (at
least at OECD … )

29. So much data to process
Trade in services
Trade in goods
ICIO
BTDIxE
UN Comtrade
OECD ITCS
EBTSI
eBOPS
TiS
national
SUTs/IOTs
SNA by activity
STAN, UNSD, Eurostat,
SNA main aggregates
OECD, UNSD, National
harmonised
SUTs/ IOTs
TiVA
IND34
VA/PROD
IND34
FD
CO2 Jobs/GVCs
HH Cons - COICOP
Tourism
Satellite
Non-Res
direct

30. Some particular features of ICIO
Accounting for firm heterogeneity in manufacturing:
Split tables for China (processors, other exporters and non-exporters)
and Mexico (“global manufacturers” versus other firms)
To measure Domestic VA in exports or final demand, ideally need to
isolate exporters from non-exporters in ICIO (different production
characteristics). OECD extended-SUTs initiative encouraging other
countries to attempt this. www.oecd.org/sti/ind/tiva/eSUTs_TOR.pdf
Separation of “direct purchases by non-residents” from cross-
border trade: has sparked interest from Tourism policy analysts
Allocation of domestic trade and transport margins from
manufacturing output to services: emphasises the service content
of manufactured exports
None of this is easy …

31. ICIO extensions – Embodied CO2 revisited
UNFCCC COP side events (2009, 2015)
OECD Green growth indicators
CO2 embodied in international trade: http://oe.cd/io-co2.
0
2
4
6
8
10
12
14
16
18
20
0
2
4
6
8
10
12
14
16
18
20
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
GtCO2
CO2 emissions from fuel combustion
Consumption-based (OECD)
Production-based (OECD)
Production-based (non-OECD)
Consumption-based (non-OECD)
Net-imports of embodied CO2
into OECD countries
Net-exports of embodied CO2
of non-OECD countries

32. ICIO Extensions – Jobs
Origin of demand for manufacturing jobs in OECD, 1995-2011
-7
-5
-3
-1
1
3
EU28 NAFTA Southeast and East Asia (Excl. China) Brazil China India Russia Rest of the World Total
Source: OECD (2015), OECD Science, Technology and Industry Scoreboard 2015: Innovation for Growth, OECD Publishing,
doi: http://dx.doi.org/10.1787/sti_scoreboard-2015-en.
Millions of persons, annual changes by region of demand

33. TiVA / ICIO: Next steps – from 2017
• Always demand for more countries (Africa?!) and more recent
years
• Recent regional TiVA meeting – March 2017
• New version being developed based on ISIC Rev.4 (NACE
Rev.2) and latest SNA 2008 / BPM6 inputs
• Nowcasting: for more timely information, improve methods for
extrapolating TiVA indicators to provide figures for more recent
years (t-1 rather than t-3).
• Better accounting for firm heterogeneity – beyond China and
Mexico Linking trade, SNA and business statistics? Fruits of
extended SUTs project
• Developing and extending the statistical infrastructure
33

34. 4. Conclusions - The OECD and GGDC
Useful and important cooperation in many ways
• Among the only organisations seeking to develop large
structural databases for policy research – a public good
• Friendly competition/cooperation useful to improve quality
Inspiration of academic research important for the OECD’s
work
- Pioneers in some areas, new research questions
- Active and early users of the data (e.g. STAN and ICIO
test-users)
Both seeking to fill gap between statistical concepts and
analytical needs
Common research interests, e.g. ICT and productivity, GVCs

35. Some differences
• OECD agenda, capacity building & priorities determined by:
- Numerous OECD Committees and their Working Parties. Many
meetings with many Delegates
- Key role in G20 and increasing engagement with non-Members at
a global scale (and with many seeking membership)
• Access to leaders (including via G20 / G7) - high visibility
• Links with regional/international orgs (UN, WTO, EU, APEC etc)
• Deep working level relations with policy analysts in Ministries –
relevancy, but also high level of scrutiny (e.g. TiVA results)
• Active engagement with statistical agencies – setting standards
(e.g. SNA)
• Challenges in managing high level expectations

36. Concluding remarks
 Research on productivity (including microdata) and IO-based
analysis of GVCs are now firmly established as major
contributors to economic, environmental and social policy
making – no longer niche areas. High visibility and interest from
policy makers
 Increasing numbers of young researchers attracted by the joys of
empirical work with large datasets, e.g. microdata and IO.
 National statistical offices motivated to improve underlying
statistics e.g. consistent bilateral trade, extended SUTs project
etc, and provide access to microdata
 Regional TiVA initiatives converging towards common
approaches to construct global IOTs (APEC-TiVA, EU Figaro,
NAFTA-TiVA etc.)

37. Thank you
Contacts:
dirk.pilat@oecd.org, paul.schreyer@oecd.org, colin.webb@oecd.org
and norihiko.yamano@oecd.org
Twitter:
@OECDinnovation and @OECD_Stat
Internet resources:
Productivity database: www.oecd.org/std/productivity-stats
STAN: www.oecd.org/sti/stan
TiVA: www.oe.cd/tiva
Global Forum on Productivity: www.oecd.org/global-forum-
productivity
Multiprod: www.oecd.org/sti/ind/multiprod.htm