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

Outline

2

1. Some background

2. Productivity – data, methods and analysis

3. GVCs – data, methods and analysis

4. Conclusions

– 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

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

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

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

… enabling the 2017 OECD Compendium of Productivity Indicators

7

www.oecd.org/std/productivity-stats

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

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

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.

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

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

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

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

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 Gurríaand Hungarian Minister of National Economy, MihályVarga

• Themes to include productivity benefits from openness and GVCs; MNEs, knowledge spillovers and upgrading; digital transformation, GVCs and productivity…

http://oe.cd/GFP2017.

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

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

- 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

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

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

Global Value Chains: of growing interest

2005 2007 2008

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

OECD-WTO TiVA database and GVC synthesis for Ministers

24

Then expansion

25

January 2013

40 countries18 industries3 years

May 2013

57 countries18 industries5 years

October 2015

61 countries34 industries7 years

December 2016

63 countries34 industries17 years

Underlying ICIO tables:

6.9 million cells per year

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

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%

TW

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SG

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KO

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MY

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ITA

TU

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DE

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FR

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PH

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CA

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GB

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HK

G

CH

L

NL

D

ZA

F

NO

R

NZ

L

US

A

JP

N

AU

S

AR

G

RU

S

IDN

BR

A

CO

L

BR

N

SA

U

2011 2009 2008

0%

20%

40%

60%

80%

100%

SA

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BR

N

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IDN

CH

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CH

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FR

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GB

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SG

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HK

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Domestic VA content Foreign VA content SNA service export share

0%

10%

20%

30%

40%

50%

60%

Ag

ric

ulture

Min

ing

Food products

Textiles &

appa

rel

Wood &

paper

Coke &

petrole

um

Chem

icals

Rubber &

pla

stics

Non-m

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min

erals

Ba

sic

m

etals

Fabric

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Machin

ery

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Moto

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Whole

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Transp

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tele

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Fin

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Bu

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FVA share of gross exports, 2011 FVA share of gross exports, 1995

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 … )

So much data to process

Trade in services

Trade in goods

ICIOBTDIxE

UN ComtradeOECD ITCS

EBTSI

eBOPSTiS

nationalSUTs/IOTs

SNA by activitySTAN, UNSD, Eurostat,

SNA main aggregatesOECD, UNSD, National

harmonised

SUTs/ IOTs

TiVA

IND34VA/PROD

IND34FD

CO2 Jobs/GVCs

HH Cons - COICOP

TourismSatellite

Non-Res direct

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 …

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

Gt

CO

2

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

ICIO Extensions – Jobs Origin of demand for manufacturing jobs in OECD, 1995-2011

-7

-5

-3

-1

1

3EU28 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

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 infrastructure33

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

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

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.)

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