©2012 Asian Productivity Organization©2012 Asian Productivity Organization

Contents1

1.1 Databook 20121

1.2 List of Contributors

2

2 Overview

5

3 Production-Side GDP

15

3.1 Economic Scale and Growth16

3.2 Catching Up in Per Capita GDP

25

3.3 Sources of Per Capita GDP Gap

32

4 Expenditure-Side GDP

41

4.1 Composition of Final Demand41

4.2 Demand-Side Growth Decomposition

53

5 Productivity

61

5.1 Per Worker Measure of Labor Productivity

62

5.2 Per Hour Measure of Labor Productivity

68

5.3 Total Factor Productivity

75

5.4 Enhancement of Labor Productivity

85

6 Industry Perspective93

6.1 Output and Employment

93

6.2 Industry Growth101

6.3 Labor Productivity by Industry

112

7 Real Income

117

7.1 Real Income and Terms of Trade117

7.2 Terms of Trade and Productivity Growth126

Appendix127

A.1 GDP Adjustments

127

A.2 Capital Stock130

A.3 Rate of Return and Capital Services

131

A.4 Data Sources

133

A.5 Industry Classification

134

References

135

iii

©2012 Asian Productivity Organization

1 Introduction

Contents

Box
Box 1

Compilation of National Accounts in Asian Countries

20

Box 2

Populations of Asian Countries

35

Box 3

The System of National Accounts 2008

38

Box 4

Quarterly Economic Growth

51

Box 5

The Middle-Income Trap and Implications for China

64

Box 6

Measuring Hours Worked

69

Box 7

Sensitivity of TFP Estimates

92

Table 1

Cross-Country Comparison of GDP Using Exchange Rates, 1970, 1990, 2000, and 2008–201016

Table 2

Cross-Country Comparison of GDP Using PPP, 1970, 1990, 2000, and 2008–201018

Table 3

GDP Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2010

22

Table 4

Cross-Country Comparison of Per Capita GDP Using Exchange Rate, 1970, 1990, 2000,©2012 Asian Productivity Organization

Table

and 2008–2010

26

Table 5Per Capita GDP, 1970, 1990, 2000, and 2008–201030

Table 6Country Groups Based on the Initial Economic Level and the Pace of Catch-Up

31

Table 7

Final Demand Shares in GDP, 1970, 1980, 1990, 2000, and 201041

Table 8Per Worker Labor Productivity Levels, 1970, 1990, 2000, and 2008–2010

63

Table 9Labor Productivity Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2010

66

Table 10Per Hour Labor Productivity Levels, 1970, 1990, 2000, and 2008–2010

71

Table 11

Labor Productivity Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–201073

Table 12Output Growth and Contributions of Labor, Capital, and TFP

82

Table 13

Role of TFP and Capital Deepening in Labor Productivity Growth, 1970–2010

91

Table 14

Country Groups Based on the Current Economic Level and the Pace of Catch-Up

94

Table 15

Output Growth by Industry, 2000–2009

106

Table 16

Labor Productivity Growth by Industry, 2000–2009

113

Table 17

Real Income and Terms of Trade, 1970–2010, 1995–2000, 2000–2005, and 2005–2010

118

Table A1

Parameters in Hyperbolic Function

130

iv

FigureFigure 1

GDP Growth of Asia, the EU, Japan, and the US, 1970–2010

15

Figure 2

Share of Asia in World GDP in 2010 and Projection for 2016

15

Figure 3

Relative Prices of GDP, 2005

17

Figure 4

Regional GDP of Asia and EU Relative to the US, 1970–2010

19

Figure 5

GDP of China, India, and Japan, 1970–2010

19

Figure 6

Regional GDP of South Asia, ASEAN, and GCC, 1970–201021

Figure 7

Country Contributions to Regional GDP Growth, 1970–1990 and 1990–201023

Figure 8

Correlation of GDP Growth in the 1990s

24

Figure 9

Correlation of GDP Growth in the 2000s

25

Figure 10

Share of Asian Population in the World in 2010

25

Figure 11

Cross-Country Comparison of Per Capita GDP Using Exchange Rate of Japan and Australia Relative to the US, 1970–2010

27

Cross-Country Comparison of Per Capita GDP Using Exchange Rate of Asian Tigers
Relative to the US, 1970–201027

Figure 13

Per Capita GDP of Japan, the EU, and Australia Relative to the US, 1970–2010

28

Figure 14

Per Capita GDP of Asian Tigers Relative to the US, 1970–2010

28

Figure 15

Per Capita GDP of China, India, and ASEAN Relative to the US, 1970–2010

29

Figure 16

Per Capita Non-Mining GDP in Oil-Rich Countries, 200929

Figure 17

Initial Level and Growth of Per Capita GDP, 1970–201031

Figure 18

Labor Productivity and Employment Rate Gap Relative to the US, 1995 and 201033

Figure 19

Sources of Per Capita GDP Growth, 1995–2000 and 2000–201034

Figure 20

Share of Female Employment

34

Figure 21

Employment Rates, 1970, 1990, and 2010

35

Figure 22

Final Demand Shares in GDP of China, 1952–201043

Figure 23

Final Demand Shares in GDP of the US, 1929–201043

Figure 24

Final Demand Shares in GDP, 1995 and 2010

44

Figure 25

Ratio of Dependent Population and Consumption Share in GDP at Current Prices, 2010

45

Figure 26

Export and Import Shares in GDP, 1995 and 201046

Figure 27

Long-Term Trend of Household Consumption Share in GDP, 1970–201047

Figure 28

Ratio of Dependent Population, 201048

Figure 29

Household Consumption by Purpose, 200948

Figure 30

Long-Term Trend of Investment Share in GDP, 1970–201049

Figure 31

Investment by Type of Asset, 1970 and 201050

Figure 32

Long-Term Trend of Net Export Share in GDP, 1970–2010

53

Figure 33

Final Demand Contributions to Economic Growth, 1995–2000 and 2000–2010

54

Figure 34

Final Demand Contribution Shares to Economic Growth of the Asian Tigers, 2000–2010

55

Figure 35

Impacts of Global Financial Crisis and Recoveries, 2007–2010

56

Figure 36

Impacts of Asian Financial Crisis, 1997–1998

57

Figure 37

Final Demand Decomposition of Real GDP Growth, 1970–2010

58

Figure 38

Labor Productivity Level by Per Worker GDP, 2010

62

Figure 39

Labor Productivity Trends of China and India, 1970–2010

65

Figure 40

Labor Productivity Level Relative to the US, 1970–2010

67

Figure 41

Labor Productivity Gap by Per Worker and Per Hour GDP Relative to the US, 201070

Figure 42

Labor Productivity Trends in Japan and the Four Asian Tigers, 1970–2010

71v©2012 Asian Productivity Organization

Figure 12©2012 Asian Productivity Organization

Contents

Figure 43

Labor Productivity Growth, 1970–2010, 1970–1990, and 1990–201072

Figure 44

Labor Input Growth, 1970–2010, 1970–1990, and 1990–201072

Figure 45

Labor Productivity Trends of Japan over Century and Levels of Asian Countries in 2010

74

Figure 46

Time Durations Taken to Improve Labor Productivity by Japan and the Asian Tigers

74

Figure 47

TFP Growth, 1970–2010, 1970–1990, and 1990–201076

Figure 48

Sources of Economic Growth, 1970–2010

77

Figure 49

Contribution Shares of Economic Growth, 1970–2010

77

Figure 50

Sources of Economic Growth, 1970–1985, 1985–2000, and 2000–2010

78

Figure 51

Contribution Shares of Economic Growth, 1970–1985, 1985–2000, and 2000–2010

79

Figure 52

Comparison of Sources of Economic Growth with OECD Countries, 2000–2010

80

Figure 53

Individual Countries’ Growth Accounting Decomposition, 1970–2010

81

Figure 54

IT Capital Contribution to Capital Input Growth of Japan and the US, 1970–2010

84

Figure 55

IT Capital Contribution to Capital Input Growth of Asian Tigers, China, and India, 1970–2010

85

Figure 56

Capital Deepening, 1970–2010, 1970–1990, and 1990–2010

86

Figure 57

Capital Productivity Growth, 1970–2010, 1970–1990, and 1990–201087

Figure 58

Capital Productivity Trends in Japan and the Four Asian Tigers, 1970–201087

Figure 59

Capital Productivity Trends in China and India, 1970–201087

Figure 60

Sources of Labor Productivity Growth, 1970–201088

Figure 61

Contribution Shares of Labor Productivity Growth, 1970–201088

Figure 62

Sources of Labor Productivity Growth, 1970–1985, 1985–2000, and 2000–201088

Figure 63

Contribution Shares of Labor Productivity Growth, 1970–1985, 1985–2000, and 2000–201089

Figure 64

Decomposition of Labor Productivity Growth, 1970–2010

90

Figure 65

Industry Shares of Value Added, 200995

Figure 66

Industry Shares of Value Added in Manufacturing, 200996

Figure 67

Industry Shares of Value Added and Employment by Country Group, 1980, 1990, 2000,
and 2009

96

Figure 68

Long-Term Trends of Value Added Share in the Agriculture Sector, 1970–200998

Figure 69

Industry Shares of Employment, 200999

Figure 70

Long-Term Trends of Employment Share in the Agriculture Sector, 1970–2009

100

Figure 71

Job Creation in Manufacturing, 1970–2009

101

Figure 72

Industry Origins of Economic Growth, 1985–1990, 1990–1995, 1995–2000, and 2000–2009

102

Figure 73

Contribution of Manufacturing to Economic Growth, 1995–2000

103

Figure 74

Contribution of Manufacturing to Economic Growth, 2000–2009

103

Figure 75

Contribution of Service Sector to Economic Growth, 1995–2000

104

Figure 76

Contribution of Service Sector to Economic Growth, 2000–2009

104

Figure 77

Contribution of Wholesale and Retail to Economic Growth, 1995–2000

105

Figure 78

Contribution of Wholesale and Retail to Economic Growth, 2000–2009

105

Figure 79

Industry Origins of Output Growth in Manufacturing, 1995–2000 and 2000–2009

107

Figure 80

Industry Origins of Regional Economic Growth, 1995–2000 and 2000–2009

108

Figure 81

Industry Origins of Asian Economic Growth, 2000–2009

109

Figure 82

Industry Origins of Economic Growth, 1970–2009

110

Figure 83

Industry Origins of Labor Productivity Growth, 1985–1990, 1990–1995, 1995–2000,
and 2000–2009

114

Figure 84

Contribution of Manufacturing to Labor Productivity Growth, 1995–2000

115

Figure 85

Contribution of Manufacturing to Labor Productivity Growth, 2000–2009

115

vi

Contribution of Service Sector to Labor Productivity Growth, 1995–2000

116

Figure 87

Contribution of Service Sector to Labor Productivity Growth, 2000–2009

116

Figure 88

Contribution of Wholesale and Retail Sector to Labor Productivity Growth, 1995–2000

116

Figure 89Contribution of Wholesale and Retail Sector to Labor Productivity Growth, 2000–2009

116

Figure 90

Effect of Net Income Transfer on GDP, 1970–2010

119

Figure 91

Real Income and Real GDP Growth, 1970–2010

120

Figure 92

Trading Gain Effect, 2005–2010

121

Figure 93

Price of Crude Oil, 1986–2012

122

Figure 94

Decomposition of Real Income Growth, 1970–2010 and 2000–2010

122

Figure 95

Decomposition of Real Income Growth, 1973–1979 and 1996–1998

123

Figure 96

Sources of Real Income Growth, 1970–2010

124

Figure 97

Terms-of-Trade Effect and Labor Productivity Growth, 1970–2010

126

Figure A1

Adjustment of FISIM

127

Figure A2

FISIM Share in GDP in the 2000s

127

Figure A3

Software Investment Ratio and GFCF Ratio to GDP, 2005

128

Figure A4

Capital-Output Ratio, 1980 and 2010

131

Figure A5

Ex Post Real Rate of Return in Asia, 1970–2010132

Figure B1

Implementation of the 1968 and 1993 SNA and Plan for the 2008 SNA

20

Figure B2.1

Distribution of the World’s Population in Different Regions, 1950–2100

36

Figure B2.2

Asian Countries’ Population Size and Projection, 1970, 2010, and 2050

36

Figure B2.3

Population Proportion of the Dependent Population, 201037

Figure B2.4

Demographic Dividend, 1950–2100

37

Figure B4.1

Views of Quarterly Economic Growth in Asian Countries by the AQGM

51

Figure B4.2

Quarterly Economic Growth in Asian Countries, 2009Q4 – 2011Q4

52

Figure B5

China’s GDP Forecast Relative to the US, 2010–2020

64

Figure B6

Average Annual Hours Worked Per Worker Relative to the US, 2000–201069

Figure B7.1

Labor Income Share for Employees, 2010

92

Figure B7.2

Sensitivity of TFP Estimates by the Change of Income Share, 1970–2010

92

vii

©2012 Asian Productivity Organization

Figure 86

Abbreviations
ADB
AEP
AMA
APO
APO20

AQGM		ASEAN
Asia23
Asia29CPI
EU
EU15©2012 Asian Productivity Organization

EU27
FISIM
GCC
GDP
GFCF
GFS
GNI
ICP
IMF
ISIC
IT
KEO		
Lao PDR		
LCU		
NDP		
NPISHs
NPO
NSO
OECD
PPI
PPP
QNA
ROC
SEEA
SNA
TFP
UAE
UN
UNSD
US

viii

Asian Development Bankage-efficiency profile
Analysis of Main Aggregate (UNSD database)
Asian Productivity Organization
20 member economies of the Asian Productivity Organization: Bangladesh,
Cambodia, the Republic of China, Fiji, Hong Kong, India, Indonesia, Islamic Republic of Iran, Japan, the Republic of Korea, the Lao PDR, Malaysia, Mongolia,
Nepal, Pakistan, the Philippines, Singapore, Sri Lanka, Thailand, and Vietnam
Asian quarterly growth map
Association of Southeast Asian Nations: Brunei, Cambodia, Indonesia, the Lao
PDR, Malaysia, Myanmar, the Philippines, Singapore, Thailand, and Vietnam
APO20 plus the People’s Republic of China, Brunei, and Myanmar
Asia23 plus GCC countries
consumer price index
European Union
15 member economies of the European Union prior to enlargement: Austria,
Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain, Sweden, and the United Kingdom
European Union: EU15 plus Bulgaria, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovak Republic, and Slovenia
financial intermediation services indirectly measured
Gulf Cooperation Council: Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the UAE
gross domestic productgross fixed capital formation
Government Finance Statistics
gross national income
International Comparisons Program
International Monetary FundInternational Standard Industry Classification
information technology
Keio Economic Observatory, Keio University
Lao People’s Democratic Republic
local currency unit
net domestic productnon-profit institutions serving households
national productivity organization
national statistical office
Organisation for Economic Co-operation and Development
producer price index
purchasing power parity
quarterly national accounts
Republic of China
System of Integrated Environmental and Economic Accounting
System of National Accounts
total factor productivity
United Arab Emirates
United Nations
United Nations Statistics Division
United States

Foreword
The Asian Productivity Organization (APO) has contributed to the sustainablesocioeconomic development of the Asia-Pacific by supporting productivity
enhancements in its member economies since 1961. In April 2011, the APO
marked its golden jubilee. For the past 50 years, it has undertaken numerous projects to promote and disseminate productivity tools, and witnessed
the region’s tremendous economic progress. Although the global economy isembroiled in financial turmoil that started in 2007, most APO members have
weathered the crisis well and are striving to continue on their paths of growth
despite the setbacks.
While recognizing the region’s economic achievements over the past five dec­ades, APO member countries have reached a juncture and are ready to adopt
a new paradigm in the productivity movement. The APO stands ready to caterto emerging demands for productivity in the interlinked global economy. The
APO holds firm to its organizational vision of being the leading internationalorganization on productivity enhancement, thereby enabling its members to
be more productive and competitive by 2020. Three strategic directions guidethe APO: strengthen NPOs and promote the development of small and medium
enterprises and communities; catalyze innovation-led productivity growth; andpromote Green Productivity.
There is growing interest in internationally comparable data on productivity
growth. In response, we initiated a research project in 2007 to annually publish
the APO Productivity Databook series, alongside the development of the APO
Productivity Database. This publication is the fruit of the APO Productivity Databook Project, implemented by the Research and Planning Department of the
APO Secretariat in collaboration with Keio Economic Observatory (KEO), Keio
University in Tokyo.
The work includes research efforts to improve the measurement of productivity growth in a way that allows international comparisons as well as to enhance
the understanding of sources of economic and productivity growth. I take great
pleasure in the release of this edition, and my profound gratitude goes to theresearch team led by Professor Koji Nomura at the KEO, which has invested
great effort in meticulous research. I also wish to thank all the national experts
for providing their national economic data to the APO.
I hope that readers will appreciate this publication as a reference and find practical uses for it in their endeavors.

Secretary-General
Asian Productivity Organization
Tokyo, July 2012ix

©2012 Asian Productivity Organization

Ryuichiro Yamazaki1.1 Databook 2012

1 Introduction
1

1.1 Databook 2012
This is the fifth edition in the APO Productivity Databook series. The publication aims to provide a longterm cross-country comparison of economic growth and productivity levels of Asian economies inrelation to global and regional economies. Baseline indicators are calculated for 29 Asian economies,
representing the 20 Asian Productivity Organization (APO) member economies (referred to as the
APO20) – Bangladesh, Cambodia, the Republic of China (hereafter ROC), Fiji, Hong Kong, India, Indonesia, the Islamic Republic of Iran (hereafter Iran), Japan, the Republic of Korea (hereafter Korea), theLao People’s Democratic Republic (hereafter Lao PDR), Malaysia, Mongolia, Nepal, Pakistan, the Philippines, Singapore, Sri Lanka, Thailand, and Vietnam, and nine non-member economies in Asia – thePeople’s Republic of China (hereafter China), Brunei, Myanmar, and the Gulf Cooperation Council(hereafter GCC) that consists of Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates (hereafter UAE). In addition, as reference economies, the United States (US), the European Union(EU), and Australia are included. This edition covers the period 1970–2010.
The productivity measures in this report are based on the estimates developed for the APO Productivity Database project conducted since September 2007 as a joint research effort between the APO andthe Keio Economic Observatory (KEO), Keio University. The concepts of the estimates in this edition
are mainly based on the System of National Accounts in 1993 (1993 SNA). In this edition, some significant revisions on the national accounts were incorporated. Observing new developments for upgrading of statistics systems in APO member economies, in December 2011, Thailand newly published its
national accounts based on the 1993 SNA, and Japan published its national accounts with the new
benchmark year 2005, which has considerable impacts on its gross domestic product (GDP). In August
2011, the Philippines published its new national accounts based on the 1993 SNA and partly on the2008 SNA. While there are movements toward upgrading the SNA, some countries, such as Cambodia
and Indonesia, still have not fully introduced the 1993 SNA. The variations of data definitions andcoverage occur due to these different statuses of SNA adaptions among the member economies, calling for data harmonization for performing comparative productivity analyses. This Databook projecttries to reconcile the national accounts variations that are based on the different concepts and definitions to provide harmonized estimates for international comparison.

Another new feature of this edition is that it includes data up to 2010. This was done in response toreaders’ requests to obtain the latest data and information, wherever possible. By contrast, last year’s
edition used only 2008 data for comparison purposes. The new achievement to present 2010 data
estimates where available was realized by pushing back the publication month of the Databook series
from March/April to June/July, so as to await the release of some countries’ annual national accounts
and thus obtain estimates from the latest year. As such, the latest year’s data can principally be basedon the annual national accounts rather than the quarterly accounts. This edition reflects the revisions
in the official national accounts and other data that were published as of March 2012.

1©2012 Asian Productivity Organization

To analyze the overall productivity improvement as well as partial productivity improvement (i.e., labor productivity and capital productivity), the Databook project constructs the estimates of capital
services appropriate to the concept of capital input introduced in the 2008 SNA. Based on our estimates of capital services, the sources of economic growth in each economy are decomposed to factor
inputs of labor and capital and total factor productivity (TFP) for 15 Asian economies – China, the ROC,
Fiji, Hong Kong, India, Indonesia, Iran, Japan, Korea, Malaysia, Mongolia, the Philippines, Singapore,
Thailand, and Vietnam – along with the US as a reference economy. In addition, TFP estimates for India
and Iran are newly presented in this edition.

1 Introduction

This project is managed by Koji Nomura (KEO, Keio University), with coordination by Yasuko Asano(Research and Planning Department, APO). The source of the data is the respective national accounts
and some national statistics on labor and production in each economy. The project has collected raw
data and metadata information at KEO and also through the APO Productivity Databook Questionnaires from respective national experts in the APO member economies. These experts are listed in
Section 1.2. The submitted data were examined and processed by the research team led by Koji
Nomura, who in collaboration with senior researcher Eunice Lau, as well as research assistants Kyoko
Ishikawa, Shinyoung Oh, Hiroshi Shirane, and Keiko Inoue, prepared the text, tables, and figures presented in this report.

1.2 List of Contributors
Authors of This Report
Dr. Koji Nomura
APO Productivity Database Project Manager,
Associate Professor, KEO, Keio University,
2-15-45 Mita, Minato-ku, Tokyo 108-8345, Japan

Ms. Eunice Ya Ming Lau
Researcher, KEO, Keio University

Research Assistants at KEO, Keio University
Ms. Kyoko Ishikawa
Ms. Shinyoung Oh
Mr. Hiroshi Shirane
Ms. Keiko Inoue
APO Officer
Ms. Yasuko Asano
Program Officer, Research and Planning
Department, Asian Productivity Organization,
1-2-10 Hirakawa-cho, Chiyoda-ku, Tokyo
102-0093, Japan

National Experts©2012 Asian Productivity Organization

Bangladesh
Mr. Mohammad Ballal Hossain
Joint Director, Statistics Department,
Bangladesh Bank, Head Office,Motijheel C/A, Dhaka 1000

2

Cambodia
Mr. Chettra Keo
Director, National Accounts Department,
National Institute of Statistics, Ministry ofPlanning, #84, St. 130, Don Penh, Phnom Penh

Republic of China
Ms. Jia-yuan Mei
Chief, National Accounts Section,
Bureau of Statistics, Directorate-General of
Budget, Accounting, and Statistics, Executive Yuan,
6F, No. 2, Guangjhou Street, Taipei 10065

Fiji
Ms. Navilini Singh
Statistician, National Accounts, Economics
Statistics Division, Fiji Islands Bureau of Statistics,
P.O. Box 2048, Government Buildings, Suva

India
Dr. Shailja Sharma
Deputy Director General, National Accounts
Division, Central Statistics Office, Ministry of
Statistics and Programme Implementation,
Sardar Patel Bhavan, Parliament Street, New Delhi

Indonesia
Ms. Wachyu Winarsih
Leader of Social Analysis, Directorate of Statistical
Analysis and Development, Statistics Indonesia(Badan Pusat Statistik Republik Indonesia),
Jl. Dr. Sutomo No. 6–8, Jakarta 10710

1.2 List of Contributors

Head, Faculty of Management and Business, andHead, Entrepreneurship Center, Tarbiat Modares
University, Jalal-e Ale Ahmad Highway, Tehran

Japan
Mr. Mantaro Matsuya
Director, National Wealth Division,
National Accounts Department, Economic andSocial Research Institute, Cabinet Office,
Government of Japan, 3-1-1 Kasumigaseki,
Chiyoda-ku, Tokyo 100-8970

Republic of Korea
Dr. Geonwoo Lee
Research Fellow, Korea Institute for Industrial
Economics and Trade, 206-9 Cheongryangri-dong,
Dongdaemun-ku, Seoul 130-742

Lao PDR
Mr. Phousavanh Chanthasombath
Economist, Lao Department of Statistics,
Ministry of Planning and Investment,
Ban Sithanneau, Souphanouvong Road, Vientiane

Malaysia
Mr. Razaman Bin Ridzuan
Statistician, National Accounts Statistics Division,
Department of Statistics, Malaysia,
Level 3, Unit 01-05, Wisma Minlon, 12th Miles,
Sungei Besi Highway, 43300 Seri Kembangan,
Selangor Darul Ehsan

Mongolia
Ms. Bayarmaa Baatarsuren
Statistician, Macroeconomic Statistics Department,
National Statistical Office of Mongolia,
Government Building III, Bagatoiruu 44,
Ulaanbaatar 11

Nepal
Mr. Rajesh Dhital

1

Statistical Officer, Central Bureau of Statistics,
Ramshapath, Thapathali, Kathmandu

Pakistan
Mr. Shahid Mahmood Butt
Director, National Accounts, Statistics Division,Federal Bureau of Statistics, SLIC Building No. 5,
14th Floor, F-6/4, Blue Area, Islamabad

Philippines
Ms. Estela T. De Guzman
Director, Industry and Trade Statistics Department,
National Statistics Office, Ground Floor,
Solicarel Building II, Ramon Magsaysay Blvd.,
Sta. Mesa, Manila

Sri Lanka
Mr. Weerasinghe Wasala Mudiyanselage Ananda
Sarath Premakumara
Director Statistics, Department of Census andStatistics, Ministry of Finance and Planning,
Sample Surveys Division, Unity Plaza Building,Bambalapitiya, Colombo 04

Thailand
Ms. Wannapa Khlaisuan
Policy and Plan Analyst, Professional,
National Accounts Office, National Economic andSocial Development Board, 962 Krung Kasem Road,
Pomprab, Bangkok 10100

VietnamMs. Thi Viet Hong Nguyen
Head of Statistics and Informatics Section,
Institute of Statistical Science, General Statistics
Office, 54 Nguyen Chi Thanh Street,
Dong Da District, Hanoi

3©2012 Asian Productivity Organization

Islamic Republic of Iran
Dr. Sayed Hamid Khodadad Hosseini©2012 Asian Productivity Organization

APO member economies
Non-member Asian economies included in Databook 2012

1 Introduction

4

Overview

2 Overview
The year 2010 proved to be a false dawn and the world economy has taken a turn for the worse.
Global activity weakened significantly through 2011 from its strong rebound the previous year, andprospects for 2012 do not look promising. World output grew slower at 3.8 per cent in 2011, compared
to 5.2 per cent in 2010. Even weaker growth of 3.3 per cent is forecast for 2012, assuming no unexpected events, but risks are clearly to the downside (IMF 2012).

2

2011 was a turbulent year plagued by a series of unforeseen, extraordinary events and developments.
In the absence of these adverse events, global activity had already been anticipated to slow, as the
temporary output boost in 2010 due to the inventory cycle and fiscal stimulation in most major economies started to phase out. Further slowdown can be explained by the unexpected shocks that hit theinternational economy, from the Great East Japan Earthquake and tsunami to the spreading unrest in
the Middle East and North Africa, causing disruptions to supply chains and the oil supply, and oil pricehikes. The International Monetary Fund (2011) estimates that the combined effects of these one-time
events may have lowered output in advanced economies by 0.5 percentage points, mostly in the second quarter of 2011, but these effects have started to unwind. What proves to be more menacing andworrying over the immediate horizon are two unforeseen adverse developments that have come tothe fore in the second half of 2011: a much slower and weaker recovery than anticipated in crisis-hit
advanced economies, and a large increase in fiscal and financial uncertainty in the US and in the eurozone. The world economic outlook will depend on how these events pan out individually and interact
with one another. Given the intensity of the euro crisis, IMF projections for 2012 have been revised
downward to 3.3 per cent, with world economic growth forecasts becoming more uneven. While advanced economies are expected to manage lackluster growth of 1.2 per cent, emerging economies
are forecasted to sustain growth of 5.4 per cent, albeit representing a significant slowdown from theirrecent performance of 6.2 per cent in 2011 and 7.3 per cent in 2010. Developing Asia remains theworld’s fastest growing region at 7.3 per cent in the coming year, compared with 1.8 per cent in theUS, and −0.5 per cent in the euro zone. With divergent growth paths, the shifting of economic balance
to the East is set to continue. The risk is that the world economy may underperform these forecasts if
the euro sovereign debt crisis is not effectively managed and contained.

The weak recovery has aggravated the unresolved structural fragilities in advanced economies andexposed the painful political and economic reality that the scope for macroeconomic policies to cushion economies against further adverse shocks is much reduced since the crisis of 2007–2008. In theUS, political gridlock over fiscal consolidation plans has increased policy uncertainty and underminedthe effectiveness and stability of the policymaking environment. The political brinkmanship to thepoint of compromising US creditworthiness has greatly tarnished the country’s long-standing

5©2012 Asian Productivity Organization

Disappointingly, the rebound in 2010 failed to materialize into a strong, balanced, and sustained recovery in the advanced economies due to the stalling of two rebalancing acts. First, domestic demandhas not made the successful shift from fiscal stimulus to private demand. Business and consumer
sentiment and order books dropped sharply from summer 2011 in most countries (except Japan),dampening private demand (OECD 2011). The reasons vary across countries, but lower equity prices
and persistent housing market weakness imply deteriorating household balance sheets. First, together with unrelenting job uncertainty, households are cautious and business confidence is not revived.
With fiscal consolidation well under way in most advanced countries (except Japan), private demandhas not managed to pick up the slack. Second, global current account rebalancing is needed to compensate weak domestic demand in advanced economies with current account deficits, most notably the US, through an increase in foreign demand. This implies a symmetric shift to take place incountries with current account surpluses, most notably China. Although global current account imbalances shrank temporarily during the crisis in 2008–2009, the required underlying structural adjustments for the trend to sustain have not taken place. Global imbalances look set to widen.

2 Overview

reputation for responsible and credible management of its finances, culminating in the decision byStandard & Poor’s (S&P) to downgrade the US long-term sovereign credit rating from AAA to AA+ on
5 August 2011. Meanwhile, the deepening of the sovereign debt crisis in the euro zone threatens fiscal
and financial contagion. On 13 January 2012, S&P downgraded the credit ratings of nine euro-zone
countries, including France, Italy, and Spain. The debts of Portugal and Cyprus are now classed as junk,
as is Greece’s. For a long time, responsive policy measures have been enough only to buy time. Financial contagion is a real threat to the ailing global economy, and its successful containment is paramount in the euro rescue package. It is vital to the world economy that decisive measures are taken toconvince investors and restore financial stability.
Developments in the US and the euro zone have highlighted the extent to which political paralysis
can exacerbate uncertainty and make the markets jitter, rapidly dissipating any room for policy maneuver to support growth. Fiscal austerity and growth in a weak economy are two contradictory policy goals. Nervous investors, by demanding high bond yields, can exert tremendous pressure on
troubled governments, tilting the balance toward fiscal consolidation to restore credibility at the expense of growth. Falling bond prices also lead to tightening of credit as weakened banks deleverage
and recapitalize, putting further brakes on growth. Low growth makes debt sustainability more difficult to achieve, entrapping countries in vicious feedback loops. For the US, the task on hand is to agree
on credible back-loaded, medium-term fiscal consolidation plans, which will calm the market on the
one hand and not jeopardize the unsteady recovery on the other. The programmed fiscal tighteningby 2 per cent and 3 per cent of GDP in 2012 and 2013, respectively, is judged excessive given the relatively weak economic outlook. Japan, with a national debt well over 200 per cent of GDP, also needs
to clarify its plans to reduce debts and deficits in the years ahead.

©2012 Asian Productivity Organization

However, the epicenter of downside risks to the world economy is the euro zone. Like all major countries, government budgets of euro zone member states were put under strain during the global financial crisis. Investors had been treating all sovereign bonds within the euro zone the same until Germany
signaled that defaults could happen. As a response, markets started to differentiate among the eurozone members, and spreads on bond yields began to widen. First, the bond yields of Greece, which
was insolvent, skyrocketed. It required funding to avoid defaults, but the policy response of the European Union (EU) was indecisive and hesitant, unnerving investors. Significant contagion then spreadto other fiscally vulnerable, but not insolvent, euro zone members, escalating the crisis and bringing
bank solvency into question as well. With the deepening of the crisis, the size of a credible policy commitment snowballs and this has been testing the political resolve of the currency union. Looking
ahead, a disorderly default or a euro exit would result in massive wealth destruction, bankruptcies,
and a collapse in confidence in European integration and cooperation, with dire consequences firstfor Europe, followed by the rest of the world. According to a simulation by the OECD (2011), Europe islikely to experience a prolonged and deep recession, while Japan and the US are likely to face a marked
decline in activity, and the emerging economies will likely face a 9.5 per cent reduction in world tradeover a period of two years and high volatility of capital flows. This worst-case scenario must be avoided through apt policies and commitment. Even still, the troubled euro economies still face a long roadto economic health. Fiscal consolidation aside, growth is the more palatable route to debt sustainability if available, and the best recipe for growth is to raise productivity through structural reforms,
which is easier said than done.
In contrast, emerging and developing economies are facing challenges quite different from those ofadvanced economies. Signs of overheating and financial vulnerabilities related to strong credit expansion have prompted policy rate hikes or other measures to reduce credit growth. Headline andcore inflation have been on the rise in many parts of the world until recently. Inflationary pressures
have stemmed from rising commodity prices, oil prices, and food prices (which affect all economies),6

Overview

as well as domestic capacity constraints in economies such as China, India, and Brazil. Although thesepressures started to moderate in 2011 as demand softened and growth slowed, oil prices have held
up in recent months in response to supply developments and rising geopolitical risks. In 2011, consumer prices went up by 5.6 per cent and 9.0 per cent in China and India, respectively.1 Inflation is
projected to decelerate in the emerging and developing economies as a whole to around 6.25 percent in 2012, down from over 7.25 per cent in 2011, with inflation being persistent in some regions(IMF 2012). Continued high inflation could risk pushing up long-term inflation expectations, and monetary authorities should remain vigilant.

2

Meanwhile, a number of major emerging and developing economies continue to experience buoyant
credit and asset price growth, increasing their vulnerability to losses in confidence and a paring backof expectations at home or by falling demand from abroad. These economies are therefore susceptible to the possibility of a hard landing. China has been tightening its monetary conditions over the
past year – real credit growth has receded, to about 10 per cent at an annual rate. Housing market
transactions and prices have fallen from exceptionally high levels, although construction is still goingstrong. The risk now is that activity could slow more than projected with net trade likely to be a dragon growth, reflecting both strong import growth and, in the near term, soft external demand. Growthis projected to slow from 9.2 per cent in 2011 to 8.2 per cent in 2012 (IMF 2012).

Just as one can make much faster progress by following a well-trodden path than being a trailblazer,
it seems highly likely that growth will ebb once the easier part of the catching up has been exhausted,even though the precise turning point may vary widely from country to country. At that point, “youreconomy comes to depend more on innovation and on learning from your own mistakes than on
improving on the success of others.”2 An economy that fails to move beyond the brute force of industrialization will struggle to make the jump from middle-income to upper-income status. The researchshows that countries with high old-age dependency ratios, low consumption shares of GDP, high andvolatile inflation, and undervalued exchange rates make growth slowdowns more likely. These findings highlight China’s challenges ahead in avoiding the middle-income trap, and, in turn, social unrest. Korea, having reached an income on par with Europe, by being expert at applying and improving
existing technology with a highly skilled and hardworking workforce, may also have come to a point
when it needs to reinvent itself beyond its world-class manufacturing, to develop its third-world

1: The Economist poll and Economist Intelligence Unit estimate/forecast, 28 January 2012.
2: The Economist Briefing: South Korea’s economy, 12 November 2011.

7©2012 Asian Productivity Organization

Over the medium term, the challenge faced by the fast-growing emerging Asian economies is how tobridge the middle-income trap. After two decades of breakneck growth, emerging Asia, especiallyChina and India, is catching up with the advanced economies (see Figure 5). The scant growth of theheavily debt-laden rich countries since the financial crisis is hastening the pace of convergence. As
growth in the rich world is faltering, the emerging world has accounted for the majority of growth in
the world economy in recent years and the economic balance has been shifting. At the current juncture, it may appear unthinkable that these economies will one day slow, but past experience has suggested that they will and that day may be more imminent than we think. International data hint that
rapidly growing economies slow significantly (defined as a downshift in the growth rate by at least 2
percentage points) when their per capita incomes reach around US$17,000 in 2005 prices, a level that
China should achieve by or soon after 2015. Other thresholds are per capita income reaching 58 percent of that in the leading country, or the share of employment in manufacturing hitting 23 per cent.
This slowdown is predominantly explained by a drop-off in total factor productivity (TFP) growth(Eichengreen, Park, and Shin 2011).

2 Overview

services and encourage entrepreneurship. India, which is less well-off than China, should have greaterroom to catch up. However, it is failing badly in delivering much needed infrastructure to support
economic growth at a double-digit pace. Power is its biggest bottleneck. The economy is prone tooverheating and runs a current account deficit and sizeable fiscal deficit.
In this report, the impact of the global financial crisis has made its way into our annual data. The inclusion of 2010 data noticeably pulls down the averages for the 2000s as a whole. Productivity analysis
will help cast valuable insight into how the long-term growth potential of an economy has been affected. As it stands, prospects for the West look less promising than for the East as far as future capability for productivity growth is concerned. With a focus on long-term analysis, the APO Productivity
Databook not only looks at a country’s productivity performance but also its economic compositionand sources of growth in order to provide readers with more comprehensive descriptions and comparisons of a country’s economic structure and characteristics. Furthermore, we have been able toexpand the number of countries covered in our TFP analysis to 15 Asian countries.
International comparisons of economic performance are never a precise science; instead, they
are fraught with measurement and data comparability issues. Despite our best efforts in aligning
the data, some data uncertainty remains. As we operate in a reality of incomplete information,some adjustments made are necessarily conjectural, while others are based on assumptions. In addressing this shortcoming, conclusions drawn are cross-referenced against other similar studies.
However, the magnitude of economic indicators and differences could be subject to a higher degreeof data uncertainty.
Bearing in mind these caveats, the main findings from our analysis are as follows.
Economic scale and growthu In terms of exchange-rate-based GDP, China has overtaken Japan since 2010 as the largest econo-

my in Asia and the second largest economy in the world after the US. On this measure, Asia29 was
28 per cent and 33 per cent larger than the US and EU15 in 2010, respectively (Table 1).
u Based on GDP adjusted for purchasing power parity (PPP), the weight of the world economy iseven more tilted toward Asia, with Asia29 being 91 per cent and 105 per cent larger than the US
and EU15 in 2010, respectively. China has overtaken Japan as the largest Asian economy since2001, and its size was 70 per cent relative to that of the US in 2010 (Figure 5). India was a close thirdin 2010 with its GDP using PPP very nearly catching up with that of Japan (Table 2).
u Over the past two decades, Asia29 grew at 5.3 per cent on average per annum, compared with 2.4

per cent and 1.8 per cent in the US and EU15, respectively. Japan was the slowest growing economy
among Asia29 at 0.9 per cent, compared with the fastest growth of 9.9 per cent achieved by China.

©2012 Asian Productivity Organization

u The divergence of growth performance between Asian countries on the one hand and the US and

EU15 on the other was even more pronounced if we look at the 2000s alone (Table 3). For the past
two decades, China and India have emerged as the driving force propelling Asia forward, accounting for 46 per cent and 15 per cent of regional growth, respectively (Figure 7).
u The global financial crisis slowed Asia29 growth significantly from a recent peak of 8.1 per cent in

2007, to 4.7 per cent in 2008 and further to 3.7 per cent in 2009, before rebounding strongly to 9.8
per cent in 2010. This is in comparison to the deep recession of −2.7 per cent and −4.5 per centexperienced by the US and EU15, respectively, in 2009.

8

Overviewu While correlation of economic growth in China on the one hand and the US and EU 15 on theother has grown weaker in recent years, the correlation of other East Asian countries with the US
and EU15 has grown stronger (Figures 8 and 9).

2

Catching up in per capita GDP
u Our results show the outcome of the dramatic development effort of the four Asian Tigers.3 Singa-pore and Hong Kong have managed to close a per capita GDP gap with the US of around 65 percent in just under four decades. Singapore has even surpassed the US since 2004, and in 2010 its
per capita GDP was 23 per cent higher. In contrast, veteran Japan has fallen behind and its gap with
the US has widened to around 30 per cent. In 2010, the ROC’s and Korea’s per capita GDP was 76
per cent and 64 per cent of the US level, respectively (Figure 14).
u Despite their rapid growth, per capita GDP of China and India was 16 per cent and 7 per cent thatof the US in 2010, respectively, due to their population size. Even so, it represents a sevenfold increase in China’s relative per capita GDP over the last four decades (Table 15). The level achieved by
Asia29 was 16 per cent that of the US, indicating that there is ample room for catch-up.
u Asia’s huge per capita GDP gap with the US is predominantly explained by its labor productivity

gap. With the exception of the four Asian Tigers, Japan, and Iran, all Asian countries have a laborproductivity gap of 50 per cent or higher (Figure 18). However, the change in employment rates
also played a significant role in some countries (Figure 19).
u Asia’s employment rates relative to the US are generally high, with the leading countries being

10–15 percentage points above that of the US. However, the prevalent surge seen in recent years
is also due to weakness in US employment (Figure 21).
The demand-side storyu With a few exceptions, household consumption is the biggest component of final demand. In re-cent years, Asia29’s consumption ratio has dropped below 50 per cent of GDP, largely reflecting thetrend in China. This compares with 70.5 per cent in the US, 58.3 per cent in EU15, and 54.5 per centin Australia (Table 7).
u The share of household consumption in GDP tends to be more volatile and falling in countries thatare undergoing rapid development. As countries get richer, the household consumption sharetends to rise. At the other end of the spectrum, countries with low income and a high dependency
ratio also sustain a high consumption ratio to GDP (Figures 24 and 25).
u China faces huge imbalances in its economy with the investment share of GDP (at 47.8 per cent) asu Overall, Asia invests more than the US/EU15 as a share of its GDP. Lately this wedge has been wid-

ening. Historically, Australia’s investment share has been sandwiched between that of Asia and the3: Refers to Hong Kong, the Republic of Korea, Singapore, and the Republic of China.

9©2012 Asian Productivity Organization

the biggest component in final demand and the household consumption share plummeting to34.9 per cent in 2010. In contrast, the weight of net exports has been rising in the past decade.
Despite softening in recent years due to weak foreign demand, it still accounts for 3.9 per cent of
final demand in 2010.

2 Overview

US/EU15. In 2010, Asia29 invested 35.1 per cent of its GDP, compared with 15.8 per cent for the US,
18.6 per cent for EU15, and 25.9 per cent for Australia (Table 7 and Figure 30).
u If history is any guide, an investment share of 40 per cent or above is unsustainable in the longterm. This implies that the investment share of 47.8 per cent in China is expected to fall eventually(Figure 30).
u GCC economies are unusually skewed toward net exports because of their oil. Net exports ac-

counted for 18.2 per cent of final demand in 2010, compared with Asia29’s 2.7 per cent and China’s
3.9 per cent. Given that its share was as high as one-third in 1970, this represents a reduced dependence on net exports in GCC countries over time.
u Only the US and South Asia run trade deficits of a more persistent nature, which accounted for −3.6

per cent and −4.0 per cent of final demand, respectively, in 2010.
u Basic necessities account for a high proportion of household consumption in lower-income coun-tries – the cross-country version of Angel’s Law (Figure 29). Korea and Indonesia spent over 7.5 percent of their household consumption on education, while the US spent almost one-fifth on health,unmatched in other countries.
u During the Asian financial crisis, when investment took a battering in many countries, household

consumption was the main driver of growth. However, in some countries, such as Hong Kong and
Malaysia, net exports accounted for most of the economic growth (Figure 33).
u In the 2000s, investment recovered in the Asian economies and drove growth. For Singapore, Hong

Kong, and the ROC, however, the strength of net exports was still the dominant force behind theireconomic growth. In the 2000s, growth slowed in the US and EU15, and the contributions of government consumption to growth nearly tripled as contributions from investment took a plunge(Figure 33).
u Most Asian countries were adversely impacted by the global financial crisis in 2008 and 2009. While

Japan’s recession was particularly deep (contracting by 5.6 per cent in 2009), other Asian countries
experienced a slowdown in growth or mild recession. Even so, relative to their customary rapid
growth in recent years, the magnitude of the impact was still substantial (Figure 37).
u Asian countries experienced a sharp fall in investment or net exports, or both. In contrast, the US

and EU15 suffered from sizable contraction in investment and household consumption, whichpulled down growth (Figure 37).
u Japan was the only Asian country where the global financial storm of 2007–2008 caused a deeper©2012 Asian Productivity Organization

retrenchment in the economy than the Asian financial crisis of 1997–1998. The latter marked an
exceptional time for many Asian economies, causing investment to nose-dive in 1998 and consumption to fall, albeit to a lesser extent. Net export growth, on the other hand, was exceptionallystrong in some of these countries (Figure 37).
Economy-wide productivity – The supply-side story
GDP per worker
u For most Asian countries, their per capita GDP gap with the US is largely explained by their laborproductivity shortfalls of 80 per cent or more against the US level. Only Singapore and Hong Kong

10

Overview

have effectively closed that gap. The relative labor productivity of Asia23 was 15 per cent that of
the US in 2010 (Figure 38 and Table 8).

2

u Growth of per-worker GDP in Asia has outstripped that in the US, allowing catch-up. In particular,

the low-income countries appeared to experience a labor productivity growth spurt in the 2000s.
China achieved the fastest labor productivity growth of 10.2 per cent on average per year in 2005–
2010, followed by India’s of 7.3 per cent. This compares with that of the US of 1.3 per cent. Singapore’s 0.4 per cent growth over the same period was the weakest performance among the AsianTigers and Japan (Table 9).
u Countries that are catching up fast with the US in per capita GDP are also fast catching up in laborproductivity. Similarly, countries with deteriorating relative per capita GDP are found to also be
deteriorating or changing little compared to the US in labor productivity (Figure 40).
GDP per houru The productivity gap based on GDP per hour is generally wider between Asian countries and theUS. While the adjustments are negligible for most Asian countries, the productivity gap significantly widened by 15–25 percentage points for the Asian Tigers, suggesting that people work
much longer hours than in the US (Figure 41).
u Most Asian countries experience faster growth in GDP per hour than the US. Among them, China’s

performance is the most outstanding, with average annual productivity growth doubling from 4.3
per cent to 9.1 per cent between 1970–1990 and 1990–2010, compared to that of the US at 1.5 percent and 1.9 per cent over the same periods (Figure 43).
u Mapped onto Japan’s historical trajectory of GDP per hour, most Asian countries cluster aroundthe level that Japan achieved in the 1950s and 1960s, with the Asian Tigers being the clear frontrunners away from the pack. This indicates that most Asian countries are still half a century away
in catching up with Japan (Figure 45).
Total factor productivity
u Half of the Asian countries compared experienced faster TFP growth than the US over the period
1970–2010, with China being a league of its own. Its TFP growth was at 3.2 per cent on average ayear, compared with that of Thailand at 1.8 per cent in second place and that of the US at 0.9 per
cent. With TFP growing at 0.5 per cent on average per year, Singapore’s productivity performancehas been weak relative to its economic counterparts (Figure 47).
u Over the past four decades, economic growth in Asia has been predominantly explained by thecontribution of capital input, but the role of TFP growth should not be underestimated. Its contribution accounted for over 20 per cent of economic growth in half of the Asian countries compared,
with it being most prominent in China (37 per cent), Thailand (31 per cent), and Hong Kong (29 percent) (Figure 49).

that the contribution of capital input is getting progressively smaller in Asia, falling to a share of
below 50 per cent on average, while the contribution of TFP is getting progressively more significant, rising to a share of above 40 per cent on average in the 2000s (Figure 51).
u The evident rise in the contribution of IT capital is noteworthy. By the 2000s, it had risen to above

5 per cent in most Asian countries compared while accounting for over one-third of economic

11©2012 Asian Productivity Organization

u The composition of economic growth is shifting over time. In the past two decades, we observe

2 Overview

growth in Japan. This compares with 30 per cent in the US (Figure 51). The allocation shift toward
IT capital started two decades earlier in the US than in any Asian country (Figure 54).
u Widening our perspective to include other OECD countries shows that Asia’s vibrant economic

growth and TFP performance in the 2000s was unmatched by any other country, except Ireland(Figure 52).
u Over the past decades, we observe that economic growth has decelerated in the early starters (i.e.,

Japan and the Asian Tigers). Their experience lends support to the likelihood of an eventual slowdown in China; the question is more likely to be when than if. TFP growth slowed from its former
peaks achieved in the late 1970s or early 1980s until recent years when countries experienced TFP
resurgence (Figure 53).
Enhancement of labor productivity growthu Although capital deepening is the prime cause of labor productivity growth, TFP growth can makea significant difference in determining a country’s relative labor productivity performance (Figures
60 and 61).
u Capital deepening appears to be an accompanying process of rapid economic development. The

early starters (i.e., Japan and the Asian Tigers) underwent more rapid capital deepening in the initial period whereas the reverse is true for the currently emerging Asian economies. For example,
the rise in capital–labor ratio decelerated from 10.4 per cent on average a year to 7.4 per cent in
Korea between 1970–1990 and 1990–2010, whereas it doubled in China from 5.2 per cent to 10.4
per cent (Figure 56).
u Capital deepening tends to go hand in hand with deterioration in capital productivity. China’s perfor-

mance is particularly impressive as its acceleration in capital deepening in the past two decades did
not compromise its capital productivity as much as the early starters in the early period (Figure 57).
u China achieved the fastest labor productivity of 6.7 per cent on average a year in the period 1970–

2010, while it was only third in its pace of capital deepening. This was because its productivity
performance was bolstered by the fastest TFP growth of 3.2 per cent achieved over the same period (Figures 60 and 61). The roles of TFP growth and IT capital deepening have also been expanding over the years in other countries (Figures 62 and 63).
u Over a long period stretching four decades, we can discern a downward trend in labor productivity

growth among the early starters, but a step up in China and India. Singapore’s productivity performance, albeit robust compared with other mature economies like the US, has been very modest
against its Asian counterparts (Figure 64).

©2012 Asian Productivity Organization

Industry perspective
Industry structureu Evidence supports the view that a country’s industry structure transforms with its economic development. There is a broad negative correlation between the share of agriculture in total GDP and
per capita GDP. Finance, real estate, and business activities increase in weight as countries move up
income levels, whereas mining is the sector that defines the oil-exporting countries (Figure 65).
u Manufacturing is a significant sector, accounting for over 20 per cent of total value added in mostAsian economies. It is particularly prominent in China, Thailand, Korea, Malaysia, and the ROC.

12

Overview

Asian manufacturing is dominated by machinery and equipment in the richer Asian economies
while their poorer counterparts concentrate on light manufacturing such as textiles and the foodindustry (Figure 66).

2

u While Asian countries are diversifying away from agriculture, the sector still dominates employ-ment, accounting for 41 per cent of total employment in 2009 for Asia29, down from 62 per cent in
1980. Its share in total value added rose from 6 per cent to 10 per cent over the same period, implying more labor efficiency (Figure 67). However, it is still the only sector that consistently has a disproportionately higher employment share than justified by its value-added share. Shifting out ofagriculture into more efficient sectors will boost economy-wide productivity (Figure 71).
Industry origins of economic growthu Our results support the observation that China and India have taken different development paths,
with the former relying more on the traditional growth engine of manufacturing and the latteron services.
u In the past two-and-a-half decades China has been undergoing a slight transition, with its growthshifting from being manufacturing-driven to more services-driven. In the period 2000–2009,
the contributions to economic growth by manufacturing and services were 35 per cent and 45
per cent, respectively, compared with 47 per cent and 30 per cent in the first half of the 1990s(Figure 72).
u In contrast, growth in India has always been more driven by services, the contribution of whichrose from 51 per cent in the late 1980s to 64 per cent in the 2000s, while manufacturing usuallycontributes one-fifth or less (Figure 72).
u A total of 28 per cent of Asia29’s regional growth originated from the expansion of manufacturingin the 2000s, two-thirds of which was accounted for by China. In other words, China’s manufacturing alone contributed 18 per cent to regional growth (Figure 81).
Industry origins of labor productivity growthu Our results show that services are no longer a drag on a country’s productivity performance, but
are as capable as manufacturing in generating labor productivity growth.
u In the 2000s, transport, storage, and communications achieved the fastest labor productivity

growth in Asia23 (at 4.7 per cent on average a year), followed by agriculture (4.1 per cent), utilities(3.3 per cent), and manufacturing (3.1 per cent) (Table 16).
u While the importance of manufacturing as a contributor to overall labor productivity growth has

Real income and terms of tradeu Real GDP could systematically underestimate (overestimate) growth in real income when termsof trade improve (deteriorate). Positive net primary income from abroad also bolsters a country’s
real income.

13©2012 Asian Productivity Organization

never waned in some countries (Korea, the ROC, China, and Thailand), services were contributing
at least one-third or more in most Asian countries compared with the 2000s. Manufacturing has
never been a major contributor in India in its recent development process, or in Hong Kong and Sri
Lanka in the 2000s (Figures 84 and 87).

2 Overview

u It is generally observed that the trading gain effect is more significant in the short term thanin the long term. Our findings confirm this observation, with the exceptions being for some oilexporting countries such as Kuwait and Brunei, where trading gain has always been positive andsignificant (Table 17).
u Net primary income from abroad tends to oscillate within a tight range of ±1.5 per cent of GDP for

more mature and large economies, and within a wider range of ±10 per cent for small and less welloff economies. However, Japan and the Philippines have been breaking through their respective
margins of fluctuations in recent years with net primary income from abroad reaching 3.3 per centin 2008 and 33.3 per cent in 2010, respectively. Singapore’s historical margin fluctuates within alarge range when compared with other rich economies, from +1.9 per cent in 1997 to −7.1 per centin 2004 (Figure 90).
u Our results show that for most countries studied, the difference between growth of real GDP andreal income (reflecting the combined effect of trading gain and net primary income from abroad)was within the margin of ±20 per cent over the long period 1970–2010; Kuwait and Brunei appear
to be the outliers (Figure 91).
u Our results also reflect Australia’s recent fortune found in trading gain as the prices of their com-modity exports rise and their import prices fall in the past decade or so (Table 17 and Figure 96).
u The five countries that have been enjoying a trading gain over 1.0 per cent per annum are all oil-exporting countries. Among them, only Iran managed to achieve a positive growth in labor productivity. In contrast, export-oriented, high productivity Asian countries have been facing adeteriorating trading gain position as a price for their own success (Figure 97).

©2012 Asian Productivity Organization

Asia is a diverse regional economy within which countries have embarked on their own journeys of
economic development at different times and different paces. As shown by our analysis, nearly all
countries are making concerted efforts to move away from agriculture and accumulate capital in order to improve their growth potential and catch up with the West. Their efforts are yielding results
beyond just impressive growth rates. Our evidence confirms that countries’ capital accumulation isaccompanied by strong productivity improvements. Through the statistics and data presented in thisreport, we manage to catch a glimpse of the current unparalleled economic dynamics inherent in theregion. China, in particular, has been rising in world economic rankings, having overtaken Germany as
the largest exporter in 2009 and Japan as the second-largest economy in 2010. Growth in India has
also received a sudden spur in recent years. As the rich economies are heavily laden with debt (to thepoint of crisis in some) and associated difficulties, this may well prove to be an opportunity for theregion to consolidate its development achievements further.

143.1 Economic Scale and Growth

3 Production-Side GDP
In the past two decades, a wedge in growth performance between Asia and the West has opened.
With the exception of the years adversely affected by the Asian financial crisis (i.e., 1997–1999), Asia29
has been growing faster than the US and EU15 by more than 3 and 4 percentage points on average ayear, respectively (Figure 1). Furthermore, this wedge has been widening in recent years; at the heightof the global financial storm (i.e., 2009), the growth differentials were 7.2 and 8.1 percentage points
against the US and EU15, respectively. The subsequent rebound in 2010 was also a lot stronger in Asia
than in the West. It is therefore no surprise that the center of gravity in the global economy is gradually shifting toward Asia. In 2010,
the Asian economy contributed%
10
two-fifths of world output (36 per
8cent for Asia29), compared with the6
US and EU27, each accounting for a4
one-fifth share (Figure 2). The IMF
2(2011) projects that the Asian share0
in world output will continue to rise,
−2
Japan
US
reaching 45 per cent (42 per cent for−4
Asia29EU15
Asia29) by 2016. In contrast, the US
−6
1970
1975
1980
1985
1990
1995
2000
2005
2010
and EU27 will shrink by a similar extent to around 18 per cent (15 per
Figure 1 GDP Growth of Asia, the EU, Japan, and the US,
cent for EU15).
1970–2010___Annual growth rate of GDP at constant market prices

Sources: Official national accounts in each country, including author adjustments.

2010

2016

APO20
21 %

Others
20 %

Asia
40 %

Others20 %Asia29
36 %
EU27
20 %

EU15
18 %
US
20 %

Other Asia
3%

EU15
15 %
EU27
18 %

APO20
22 %

Asia
45 %

Asia2942 %US18 % Other Asia
3%

Figure 2 Share of Asia in World GDP in 2010 and Projection for 2016___Share of GDP using constant PPPs

Source: IMF, World Economic Outlook Database, September 2011.

4: The database used in the Databook series includes author adjustments made to harmonize GDP coverage better across countries.
When compared with last year’s edition, GDP reported in this edition includes the final consumption of FISIM (financial intermediation services indirectly measured), and thus GDP is larger by 0.5–2.0 per cent than that in last year’s edition. Although thisedition mainly follows the 1993 SNA, the current decision to exclude investment of valuables and to include software investment
and final consumption of FISIM is detailed in Appendix A.1. The Databook 2012 reflects some large revisions published by national
statistical offices in 2011 and in the first quarter of 2012. More specifically, at the end of 2011, Thailand officially switched to the1993 SNA, and its national accounts compatible with the 1993 framework became available for the first time. To construct thelong time-series data in this report, back data based on the 1968 SNA have been adjusted to be consistent with the new series.
(For example, government consumption in the new series includes consumption of fixed capital (CFC) owned by the government
since 1990. We estimate government capital stock and its CFC for the period 1970–1989 and adjust the past estimates of government consumption and GDP accordingly.) There are also some revisions to the data, largely results of national accounts revisions
including backward amendment and/or benchmark revisions.
5: Appendix A.1 discusses the extent to which countries’ GDP data are comparable.

15©2012 Asian Productivity Organization

As the advanced economies havebeen much weakened following therecent financial crisis, the fortune of
the world economy is increasingly
tied with that of Asia. To better understand the dynamics of the longterm economic growth within theregion, the remainder of the chapter looks into the details of countries’ diverse development efforts
and achievements since the 1970s,
through cross-country level comparisons of GDP and other related
performance indicators.4 Underlying
international level comparisons areharmonized GDP data of individual
countries5 and a set of conversion

3

3 Production-Side GDP

rates between the individual national currencies and a common currency unit (customarily the US
dollar). The choices for conversion rates are exchange rates and purchasing power parities (PPP). (Fortheir strengths and weaknesses, see Appendix 1.)

3.1 Economic Scale and Growth
Table 1 provides snapshot-level comparisons of Asian countries, based on GDP at current market
prices using exchange rates,6 for the six separate years of 1970, 1990, 2000, and 2008–2010. By thisTable 1 Cross-Country Comparison of GDP Using Exchange Rates, 1970, 1990, 2000, and 2008–2010___GDP at current market prices, using annual average exchange rate
1970
Japan
China
India
Pakistan
IranIndonesia
Bangladesh
Korea
Philippines
ThailandROC
Saudi Arabia
Malaysia
Hong Kong
KuwaitMyanmar
Sri Lanka
Singapore
Vietnam
UAE
Nepal
Cambodia
Qatar
BahrainOman
Fiji
BruneiMongolia(regrouped)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

360
454
464
319
89
35
11

172.4
217.6
222.7
152.8
42.7
16.9
5.1

©2012 Asian Productivity Organization

Australia

1,038 497.9
1,197 573.8
45

21.6

2000

(%)

2008

(%)

2010

(%)

Japan
4,741 100.0
China
1,198 25.3
Korea
533 11.3
India
479 10.1
ROC
326 6.9
Saudi Arabia 190 4.0
Hong Kong
169 3.6
Indonesia
168 3.5
Thailand126 2.7
Iran
110 2.3
UAE
105 2.2
Singapore
94 2.0
Malaysia
94 2.0Philippines
81 1.7
Pakistan
72 1.5
Bangladesh
46 1.0
Kuwait38 0.8Vietnam
31 0.7
Oman
20 0.4Qatar
18 0.4
Sri Lanka
17 0.4Bahrain
8 0.2
Myanmar
7 0.2
Nepal
6 0.1
Brunei
6 0.1
Cambodia
4 0.1
Fiji
2 0.0
Lao PDR
2 0.0
Mongolia
1 0.0

Japan
4,859 100.0
China
4,519 93.0
India
1,269 26.1
Korea
931 19.2
Indonesia
518 10.7
Saudi Arabia 480 9.9
ROC
400 8.2
Iran
387 8.0
UAE
321 6.6
Thailand290 6.0
Malaysia
223 4.6
Hong Kong
215 4.4
Singapore
190 3.9
Philippines
174 3.6
Kuwait150 3.1
Pakistan
148 3.0
Qatar
117 2.4
Vietnam
92 1.9Bangladesh
80 1.6Oman
61 1.3
Sri Lanka
41 0.8Bahrain
23 0.5
Myanmar18 0.4
Brunei14 0.3Nepal
14 0.3
Cambodia
10 0.2
Mongolia
6 0.1
Lao PDR
5 0.1
Fiji
4 0.1

Japan
5,047 100.0
China
4,990 98.9
India
1,333 26.4
Korea
834 16.5
Indonesia
547 10.8
Iran
400 7.9
Saudi Arabia 380 7.5
ROC
378 7.5
Thailand279 5.5
UAE
276 5.5
Hong Kong
209 4.1
Malaysia
193 3.8
Singapore186 3.7
Philippines
168 3.3
Pakistan
158 3.1
Kuwait108 2.1
Qatar
99 2.0Vietnam
98 1.9Bangladesh
90 1.8Oman
49 1.0
Sri Lanka
42 0.8Bahrain
20 0.4Myanmar
20 0.4Nepal
15 0.3
Brunei11 0.2
Cambodia
11 0.2
Lao PDR
6 0.1
Mongolia
5 0.1
Fiji
3 0.1

China
Japan
India
Korea
Indonesia
Iran
Saudi Arabia
ROC
Thailand
UAE
Malaysia
Singapore
Hong Kong
Philippines
Pakistan
Qatar
KuwaitVietnamBangladesh
Oman
Sri Lanka
MyanmarBahrain
Nepal
Brunei
Cambodia
Lao PDR
MongoliaFiji(regrouped)(regrouped)(regrouped)(regrouped)(regrouped)

APO20
9,857 202.9
Asia23
14,409 296.5
Asia2915,562 320.2
East Asia 10,931 225.0
South Asia 1,552 31.9
ASEAN
1,535 31.6
GCC
1,152 23.7

APO20
9,999 198.1
Asia2315,021 297.6
Asia2915,954 316.1
East Asia 11,462 227.1
South Asia 1,638 32.5
ASEAN
1,518 30.1
GCC
933 18.5

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

(reference)(reference)(reference)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

4,493
4,891
5,103
4,006
422
367
211

144.8
157.6
164.5
129.1
13.6
11.8
6.8

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

7,102
8,314
8,693
6,969
620
613
380

149.8
175.4
183.4
147.0
13.1
12.9
8.0

(reference)

US
EU15

5,801 186.9
6,179 199.1

Australia

323

10.4

US
EU15
EU27
Australia

9,952 209.9
9,544 201.3
10,584 223.3
407 8.6

US
EU15
EU27
Australia

14,292 294.1
13,999 288.1
15,968 328.6
1,039 21.4

Unit: Billions of US dollars.
Sources: Official national accounts in each country, including author adjustments.
Note: See Appendix A.1 for the adjustments made to harmonize GDP coverage across countries.

16

2009

(%)

Japan
3,103 100.0
China
390 12.6
India
332 10.7
Korea
270 8.7
ROC
165 5.3
Indonesia
127 4.1
Saudi Arabia 118 3.8Iran
94 3.0Thailand
88 2.8Hong Kong77 2.5UAE
51 1.6
Philippines
49 1.6
Pakistan
48 1.5
Malaysia
46 1.5Singapore
39 1.3
Bangladesh
29 0.9Kuwait
19 0.6Oman
12 0.4
Sri Lanka
8 0.3
Qatar
7 0.2
Vietnam
7 0.2
Myanmar
5 0.2
Bahrain
4 0.1
Nepal
4 0.1
Brunei
3 0.1
Cambodia
2 0.1
Fiji
1 0.0
Mongolia
1 0.0
Lao PDR
1 0.0(reference)(reference)

US
EU15

1990

(%)

209 100.0
92 43.963 30.4
12 5.8
11 5.1
10 4.8
10 4.7
9 4.3
7 3.5
7 3.5
6 2.8
5 2.6
4 1.9
4 1.8
3 1.4
3 1.3
3 1.2
2 0.9
1 0.6
1 0.5
1 0.5
1 0.4
1 0.3
0 0.2
0 0.1
0 0.1
0 0.1
0 0.1

US
EU15
EU27
Australia

13,939 276.2
13,639 270.3
15,604 309.2
998 19.8

US
EU15
EU27
Australia(%)

5,926 100.0
5,501 92.8
1,692 28.6
1,015 17.1
717 12.1
467 7.9455 7.7
430 7.3
341 5.8
304 5.1
238 4.0
227 3.8
224 3.8
199 3.4
176 3.0
129 2.2
127 2.1
105 1.8
100 1.7
60 1.050 0.823 0.423 0.419 0.3
14 0.2
11 0.2
7 0.1
6 0.1
3 0.1
11,53017,493
18,59013,102
2,037
1,883
1,098

194.6
295.2
313.7
221.1
34.4
31.8
18.5

14,527 245.1
13,942 235.3
15,934 268.9
1,271 21.4

3.1 Economic Scale and Growthmeasure, Japan had been the largest economy in Asia until 2010 when China finally overtook Japan’s
position to become the second-largest economy in the world after the US. Japan clearly surged aheadstrongly between the 1970 and 1990 comparisons, dwarfing the relative size of all other Asian economies and reducing the US lead from five times to less than two times its economy. The turn of Japan’s
fortune came in 1990, when the country’s bubble years of the late 1980s ended and its descent began.
Thereafter, stagnation in Japan combined with vibrant growth in developing Asia has resulted in the
rapid erosion of Japan’s prominence in the regional economy. On this measure, Asia29 was 28 per centand 33 per cent larger than the US and EU15 in 2010, respectively.

3

Comparisons based on exchange rates could appear arbitrary, as movements in exchange rates canbe volatile, subject to short-term, at times substantial, fluctuations of speculative capital flows andgovernment intervention. Furthermore, comparisons based on exchange rates typically underestimate the size of a developing economy and in turn the perceived welfare of its residents. The rankingsof scale of economy change dramatically when international price differences are properly accountedfor. This is because exchange rates embody the trade sector bias (i.e., more influence by the prices oftraded than non-traded goods and services)and thus do not necessarily succeed in correcting the price differentials among countries. As
18 Japandeveloping economies tend to have relatively
Australia
6
Fiji
−15
lower wages and in turn lower prices for nonKorea
−23
Qatar
−25
traded goods and services, a unit of local curKuwait−27
rency has greater purchasing power in the local
Hong Kong
−27
UAE
−34
economy than reflected in its exchange rate.
Bahrain−34
Singapore
Saudi Arabia
Oman
ROC
BruneiMalaysia
China
Indonesia
ThailandPhilippines
Bangladesh
Sri Lanka
Mongolia
India
Pakistan
Nepal
Cambodia
Iran
VietnamLao PDR
Myanmar

−35
−36
−40
−40
−46
−54
−58
−59
−60
−61
−65
−65
−65
−67
−68
−68
−69
−70
−70
−72
−76

−80

−60

−40

−20

0

20 %

Figure 3 Relative Prices of GDP, 2005___Ratio of PPP to exchange rate (reference country=US)
Sources: AMA rates by UNSD and PPP by World Bank.

6: The exchange rates used in this Databook are the adjusted rates, which are called the AMA (Analysis of Main Aggregate) rates in
the UN Statistics Division’s National Accounts Main Aggregate Database. The AMA rates coincide with the IMF rates (which aremostly the annual average of market or official exchange rates) except for some periods in countries with official fixed exchange
rates and high inflation, when there could be a serious disparity between real GDP growth and growth converted to US dollars
based on IMF rates. In such cases, the AMA adjusts the IMF-based rates by multiplying the growth rate of the GDP deflator relative
to that of the US.
7: It is therefore important to note that any international GDP comparisons are sensitive not only to revisions in national accounts
but also to revisions in multilateral PPPs. Results presented in this edition are based on the PPP estimates of the 2005 International
Comparisons Program benchmarking round.

17©2012 Asian Productivity Organization

Figure 3 shows the extent to which the exchange rates have failed to reflect countries’
price differentials properly relative to the US.
With the exception of Japan and Australia, exchange rates systematically under-represent
the relative purchasing power for all the countries covered in this report. The underestimation is substantial for some, ranging from 15
per cent for Fiji to 76 per cent for Myanmar.
Thus, the exchange-rate-based GDP considerably underestimates the economic scales
in real terms for those countries. By taking
into account the international price differentials, purchasing power parity (PPP) rectifies
the trade sector bias, and in turn the relative
size of economies can be more adequately
measured.7

3 Production-Side GDP

Table 2 repeats the same snapshot-level comparisons of Asian countries as in Table 1 but based on
GDP at constant market prices using constant PPPs for Asian countries. By correcting for international
price differentials, Asia29 has been expanding rapidly, and was 91 per cent, instead of 28 per cent,larger than the US economy in 2010, having overtaken it in 1988 (Figure 4). East Asia (China, the ROC,
Hong Kong, Japan, Korea, and Mongolia) caught up with the US in 2008 from a low base of 42 per centin 1970. In contrast, EU15 has been experiencing a relative decline in economic size, from 116 per centof the US economy in 1970 to a low of 93 per cent in 2010. Based on GDP using constant PPPs, therefore, the weight of the world economy is even more tilted toward Asia than portrayed by GDP using
exchange rates. This reflects the fact that nearly all Asian countries increase in relative size after international price differentials have been properly accounted for. The relative size of China’s economy in
Table 2 Cross-Country Comparison of GDP Using PPP, 1970, 1990, 2000, and 2008–2010___GDP at constant market prices, using 2005 PPPs, reference year 2010
1970

2000

(%)

2008

(%)

Japan
3,644 100.0
China
1,387 38.1
India
1,159 31.8
Korea
519 14.2
Indonesia
415 11.4
Iran
388 10.6
Saudi Arabia 347 9.5
ROC
308 8.5
Thailand260 7.1
Pakistan
203 5.6
Philippines
173 4.8
Hong Kong
150 4.1
UAE
143 3.9
Malaysia
134 3.7
Bangladesh
88 2.4Singapore85 2.3
Vietnam
67 1.8
Kuwait50 1.4
Sri Lanka
38 1.0Oman
32 0.9Qatar
23 0.6
Nepal
17 0.5
Myanmar
15 0.4
Brunei13 0.4Bahrain
11 0.3
Cambodia
7 0.2
Mongolia
5 0.1
Lao PDR
4 0.1
Fiji
3 0.1

Japan
4,076 100.0
China
3,738 91.7
India
1,972 48.4
Korea
977 24.0
Indonesia
631 15.5
Iran
573 14.1
ROC
565 13.9
Saudi Arabia 455 11.2
Thailand405 9.9
Pakistan299 7.3
Malaysia
266 6.5
UAE
235 5.8
Philippines
231 5.7
Hong Kong
220 5.4
Singapore
170 4.2
Bangladesh
140 3.4
Vietnam
139 3.4
Kuwait87 2.1
Sri Lanka
64 1.6
Oman
49 1.2
Qatar
44 1.1
Myanmar30 0.7Nepal
28 0.7Bahrain
17 0.4
Brunei17 0.4
Cambodia
14 0.4
Lao PDR
8 0.2
Mongolia
6 0.1
Fiji
4 0.1

China
Japan
India
Korea
Indonesia
Iran
ROC
Saudi Arabia
Thailand
Pakistan
Malaysia
UAE
Philippines
Hong Kong
Singapore
VietnamBangladesh
KuwaitQatar
Sri Lanka
Myanmar
Oman
Nepal
Cambodia
BahrainBruneiLao PDR
MongoliaFiji(regrouped)(regrouped)(regrouped)(regrouped)

APO20
10,788 264.7
Asia23
14,573 357.5
Asia2915,461 379.3
East Asia
9,582 235.1
South Asia 2,503 61.4
ASEAN
1,911 46.9
GCC
888 21.8

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

(reference)(reference)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

2,870
3,198
3,447
1,994
644
344
249

191.2
213.0
229.6
132.8
42.9
22.9
16.6

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

7,668
9,083
9,688
6,014
1,504
1,174
605

210.4
249.3
265.9
165.0
41.3
32.2
16.6

(reference)(reference)©2012 Asian Productivity Organization

1990

(%)

Japan
1,501 100.0
India
502 33.4
China
312 20.8
Iran
215 14.3
Saudi Arabia 140 9.3
Indonesia
100 6.7
Korea
87 5.8
Philippines
83 5.5
Kuwait
81 5.4
Pakistan
70 4.6
Thailand
64 4.3ROC
58 3.9Bangladesh
57 3.8
Malaysia
34 2.3
HongKong
33 2.2
Vietnam
30 2.0Singapore
17 1.1
Sri Lanka
15 1.0Qatar
12 0.8Myanmar
9 0.6
UAE
7 0.5
Brunei
7 0.5
Oman
5 0.3
Bahrain
4 0.3
Mongolia
2 0.1
Fiji
1 0.1

US
EU15

4,735 315.4
5,487 365.5

Australia

260

17.3

US
EU15

8,909 244.5
9,531 261.6

Australia

469

12.9

US
EU15
EU27
Australia

12,449 305.4
11,956 293.3
13,413 329.1
666 16.3

US
EU15
EU27
Australia

China
Japan
India
Korea
Indonesia
Iran
ROC
Saudi Arabia
Thailand
Pakistan
Malaysia
UAE
Philippines
Hong Kong
VietnamSingapore
Bangladesh
KuwaitQatar
Sri Lanka
MyanmarOman
Nepal
BahrainCambodia
BruneiLao PDR
Mongolia
Fiji

177.9
279.0
294.8
182.3
50.7
34.8
15.7

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC
US
EU15
EU27
Australia

(%)

China
10,125 100.0Japan
4,389 43.3
India
4,064 40.1
Korea
1,468 14.5
Indonesia
1,048 10.4
Iran1,047 10.3
ROC
824 8.1
Thailand632 6.2
Saudi Arabia 628 6.2
Pakistan
471 4.6
Malaysia
417 4.1
Philippines
368 3.6
UAE
361 3.6
Hong Kong
327 3.2
Singapore294 2.9
Vietnam
281 2.8
Bangladesh
247 2.4
Qatar
156 1.5
Kuwait135 1.3
Sri Lanka
106 1.0
Myanmar
93 0.9Oman
80 0.8Nepal
40 0.4
Cambodia
31 0.3Bahrain
31 0.3
Brunei19 0.2
Lao PDR
16 0.2
Mongolia
11 0.1Fiji
4 0.0(regrouped)

15,081
24,35525,683
15,816
4,581
2,973
1,328

164.4
265.6
280.0
172.5
49.9
32.4
14.5

(reference)

14,608 173.9
13,871 165.2
15,717 187.1
859 10.2

2010

(%)

9,171 100.0
4,203 45.8
3,757 41.0
1,381 15.1
988 10.8
982 10.7
745 8.1
603 6.6
588 6.4
453 4.9
389 4.2
356 3.9342 3.7
306 3.3
263 2.9
256 2.8233 2.5
133 1.4
130 1.4
98 1.185 0.976 0.839 0.430 0.329 0.319 0.2
15 0.2
10 0.1
4 0.0(regrouped)

14,93823,43224,75515,307
4,260
2,920
1,323

Unit: Billions of US dollars (as of 2010).
Sources: Official national accounts in each country, including author adjustments.
Note: See Appendix A.1 for the adjustments made to harmonize GDP coverage across countries.

18

2009

(%)

8,398 100.0
4,449 53.0
3,470 41.3
1,377 16.4
945 11.2
941 11.2
758 9.0603 7.2
594 7.1
438 5.2
396 4.7
360 4.3
338 4.0314 3.7
259 3.1
249 3.0
221 2.6
141 1.7
116 1.4
95 1.177 0.973 0.937 0.429 0.429 0.319 0.2
14 0.2
11 0.1
4 0.0

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

16,08626,32427,715
17,145
4,928
3,200
1,391

158.9
260.0
273.7
169.3
48.7
31.6
13.7

(reference)

14,099 153.7
13,267 144.7
15,042 164.0
880 9.6

US
EU15
EU27
Australia

14,526 143.5
13,531 133.6
15,324 151.4
897 8.9

3.1 Economic Scale and Growth2010 more than doubled to 231
per cent that of Japan, comparedwith 108 per cent when exchange
rates are used in Table 1. Similarly,
its size increased from 41 per centto 70 per cent relative to the US
economy in 2010. On this measure, China has overtaken Japan
since 2002 to become the leading
economy in Asia (Figure 5). This
represents remarkable growth,
considering that the Chinese
economy was only 21 per centthat of Japan and 62 per cent thatof India in 1970. India has alsonearly caught up with Japan, with
its relative size having increased
from 33 per cent in 1970 to 93 percent in 2010. If India and Japan
were to grow at the same pace as
they have been on average during 2000–2010, (i.e., at 7.2 percent and 0.7 per cent a year, respectively), India is projected toovertake Japan and become thesecond-largest economy in Asiaand the third-largest economy
in the world by 2013. Assumingthat China and the US also growat the same pace as they havebeen during the same period, thetotal GDP of the three largest
Asian countries alone will be
about 50 per cent larger than the
US economy.

US=100

200
180

3

160
140
EU15

120

US

100

Asia29

80
60

APO20

East Asia

40
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 4 Regional GDP of Asia and EU Relative to the US,
1970–2010___Indices of GDP at constant market prices, using 2005 PPPs

Sources: Official national accounts in each country, including author adjustments.

US=100

80
70
60

China

50
40
30

Japan

20
India
10
0
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 5 GDP of China, India, and Japan, 1970–2010___Indices of GDP at constant market prices, using 2005 PPPs

Sources: Official national accounts in each country, including author adjustments.

8: ASEAN (Association of Southeast Asian Nations) consists of Brunei, Cambodia, Indonesia, Lao PDR, Malaysia, Myanmar, the Philippines, Singapore, Thailand, and Vietnam.
9: GCC (Gulf Cooperation Council) consists of Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates (UAE). These
GCC countries display economic characteristics very different from those of other Asian economies due to their preponderant reliance on the oil and energy sector. Together, these countries account for about 45 per cent of the world’s proven oil reserves and25 per cent of crude oil exports, and possess at least 17 per cent of the proven global natural gas reserves.

19©2012 Asian Productivity Organization

Figure 6 shows the rapid expansion of the relative size of theSouth Asia economy (consistingof Bangladesh, India, Nepal, Pakistan, and Sri Lanka), 83 per cent of which was accounted for by India
in 2010. The catch-up effort of ASEAN8 has also been vigorous, but the setback caused by the Asianfinancial crisis of 1997–1998 is clearly visible. This partly explains why the ASEAN economy has fallen
behind the regional economy of South Asia. In contrast, the progress of GCC9 countries sagged for3 Production-Side GDP

Box 1

Compilation of National Accounts in Asian Countries

Understanding data comparability is essential for the construction of an international database, and it requires significant effort and expert knowledge. Between May and August 2010, metadata surveys on thenational accounts and other statistical data required for international comparisons of productivity wereconducted among the APO member economies. The aim of these surveys was to gather the metadata of
the input data series required to populate the APO Productivity Database.
Broadly speaking, cross-country data inconsistency can arise from variations in one or more of the three
aspects of a statistic: definitions, coverage, and methodology. The international definitions and guidelines
work to standardize countries’ measurement efforts, but country data can deviate from the international
best practice and vary in terms of omissions and coverage achieved. Last but not least, countries can also
vary in their estimation methodology and assumptions, which may account for part of the differences weobserve in the data and interfere with comparisons of countries’ underlying economic performance.
Most of the economic performance indicators in this report are GDP-related. The surveys therefore put a lotof emphasis on discerning countries’ GDP compilation practices. For GDP, we take the System of National
Accounts 1993 (1993 SNA) as the standard, and note how countries’ practices deviate from it. Since there
are differences between the 1993 SNA and its predecessor (1968 SNA) in some concepts and coverage, it isimportant to know in which year in the data series definitions and classification started to switch over, so
as to identify breaks in the time series. Figure B1 presents the current situation in compilations and data
availability of the backward estimates based on the 1968 and 1993 SNAs and the future plan for introducing

1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015
Bangladesh
Cambodia
ROC
Fiji
India
Indonesia
Iran
Japan
Korea
Lao PDR
Malaysia
Mongolia
Nepal
Pakistan
Philippines
Sri Lanka
Thailand
Vietnam

68
93
68
93
68
93
08
68
93
08
68
93
08
68
93
08
68
93
08
68
93
08
68
93
08
68
93
08
68
93
08
68
93
08
68
93
08
68
93
08
68
93
08
68
93
68
93
68
93
08

1973
1979
1951
1951

1988

1968

1974

1950

2005
1995

1978
1960

2012

2003
2005 2008
1999

2004

2007

2010

1970

N.A.(Some definitions of 1993 SNA are introduced. It will be fully implemented in 2013.)
1959

1981

1955
1970
1970

2013

1991 1993

2013

1978
1980

(2008 SNA will be implemented progressively)

2000
1986

1997

1960
1975
(mixture of 1953 SNA until 1968)
1980

2015
2007

2012

1995

1975

2014
2000

1981

2014

2002
2000

N.A.(Before 1993 SNA is introduced, Material Product System was used.)

1946

2015
2004

1990

1988

2000

1985

1998
1998

1975

2006
2004

2015
2012
2011
2011

1998 2001

1972 1975
1986

Introduction year

©2012 Asian Productivity Organization

2000

1993

N.A.(Some definitions of 1993 SNA are introduced. The main framework is still based on 1968 SNA.)

1990
1989

Backward estimates and implementation

2012
1993

2015

Plan making backward estimates

Figure B1 Implementation of the 1968 and 1993 SNA and Plan for the 2008 SNA
Source: APO Metadata Survey 2011.
continued on next page >20

3.1 Economic Scale and Growth> continued from previous pagethe 2008 SNA. For example, Japan started to publish national accounts based on the 1993 SNA in 2000
(backward estimates based on the 1993 SNA are available from 1980 at present) and will introduce the2008 SNA progressively and switch to it in 2015–2016.
As Figure B1 suggests, countries differ in their year of introduction, the extent of implementation, andbackward estimates available. According to our survey response, most APO countries are currently 1993
SNA compliant (partly or fully), although for some countries the switchover was only a recent affair; and forIndonesia and Thailand, the 1993 SNA is planned to be fully introduced in the near future. The starting yearof the official 1993 SNA-compliant time series therefore varies a great deal across countries, reflecting thedifferences in the availability of backward estimates. Countries may have adopted the 1993 SNA as theframework for their national accounts, but the extent of compliance in terms of coverage may still vary. Our
survey findings highlight two areas that require alignments to improve comparability: the treatment of
FISIM (financial intermediation services indirectly measured) and the capitalization of software.

3

FISIM is an indirect measure of the value of financial intermediation services provided, but for which financial institutions do not charge explicitly (United Nations, 1993: para. 6.124). It represents a significant partof the income of the finance sector. The 1993 SNA recommends that FISIM should be allocated to users (toindividual industries and final demands). This is in contrast to the 1968 SNA, where the imputed banking
services were allocated exclusively to the business sector. The common practice was to create a notional
industry that buys the entire service as an intermediate expense and generates an equivalent negativevalue added. As such, the imputed banking services have no impact on GDP. Therefore, the 1993 SNA recommendation, if fully implemented, will impact on industry GDP and the overall GDP for the total economy (by the part of FISIM allocated to final demands). Among the 20 APO member economies, 12 countries
have incorporated FISIM in their official national accounts. Due to the lack of information to adjust the data
properly, our current decision is to harmonize the data by excluding FISIM from GDP for all countries in the
APO Productivity Database.
The 1993 SNA also recommends the capitalization of intangible assets, which changes not only the size ofGDP but also the size of capital input. One intangible asset is computer software, which includes prepackaged software, custom software, and own-account software. Among the APO member economies,
only nine have capitalized all three types of software. Another three countries exclude own-account software in their capitalization, in one country only pre-packaged software is capitalized, and in one country
only custom software is capitalized. For the APO Productivity Database, tentative adjustments have been
made to harmonize data to include all software. See Appendix A.1 for details of the adjustments.

over two decades; only in the past
five years has it picked up slightly
and brought the relative size ofthe country group back to its previous peak of the early 1980s.10

US=100

35
30
25
20

ASEAN

South Asia

15
10

GCC

5
0
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 6 Regional GDP of South Asia, ASEAN, and GCC,
1970–2010___Indices of GDP at constant market prices, using 2005 PPPs

Sources: Official national accounts in each country, including author adjustments.

21©2012 Asian Productivity Organization

Countries’ relative performance isalso reshuffled when economic
growth is used as the yardstick.
Table 3 presents cross-country
comparisons of real GDP growthin Asia, covering the 1990s and2000s.11 The rankings vary fromperiod to period and are no long­er dominated by the economic giants. In fact, small developing
Asian countries, like Qatar, Cambodia, Vietnam, and Mongolia,
are equally capable of striking up
exuberant growth. In contrast,

3 Production-Side GDP

Table 3 GDP Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2010___ Average annual growth rate of GDP at constant market prices
1990–1995
China
KuwaitMalaysia
Singapore
Thailand
Vietnam
Korea
Indonesia
ROC
Cambodia
Lao PDR
Oman
MyanmarBahrain
Sri Lanka
Hong Kong
India
Nepal
Pakistan
Bangladesh
Iran
UAE
Brunei
Saudi Arabia
Fiji
Qatar
Philippines
Japan
Mongolia

1995–2000

11.6
9.2
9.1
8.2
8.2
7.9
7.6
7.6
7.0
6.6
6.2
5.7
5.7
5.5
5.3
5.1
5.0
4.9
4.6
4.3
3.7
3.6
3.1
2.8
2.7
2.3
2.2
1.4
−1.8

(regrouped)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

Qatar
China
MyanmarCambodia
VietnamUAE
Lao PDR
India
Singapore
ROC
Bangladesh
Korea
Sri Lanka
Nepal
Malaysia
Bahrain
Iran
Mongolia
Philippines
Pakistan
Oman
Hong Kong
Saudi Arabia
KuwaitFiji
BruneiJapan
Indonesia
Thailand

2000–2005
10.6
8.3
8.0
7.0
6.7
6.3
5.9
5.7
5.6
5.1
5.1
5.1
4.9
4.8
4.7
4.4
4.1
3.6
3.5
3.2
3.2
2.6
2.6
2.1
2.0
1.4
0.8
0.8
0.7

(regrouped)

3.9
5.3
5.2
5.1
4.9
7.2
3.8

(reference)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

2.5
1.6

Australia

3.2

US
EU15
EU27
Australia

2005–2010
12.1
9.3
9.0
8.1
7.2
7.2
6.8
6.8
6.3
6.1
6.1
5.4
5.3
5.3
4.9
4.7
4.6
4.6
4.5
4.4
4.1
4.0
3.8
3.5
3.1
3.1
2.1
2.0
1.2

(regrouped)

2.9
4.1
4.1
4.2
5.3
2.6
3.9

(reference)

US
EU15

Myanmar
China
Cambodia
Qatar
Vietnam
Kuwait
Iran
India
Mongolia
Lao PDR
Bahrain
UAE
ThailandBangladesh
Pakistan
Singapore
Malaysia
Indonesia
Philippines
Korea
Hong Kong
Sri Lanka
Saudi Arabia
ROC
Nepal
Oman
Brunei
Fiji
Japan
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC
US
EU15
EU27
Australia

1990–2010
17.1
10.7
10.6
7.9
7.7
6.8
6.7
6.5
6.3
6.3
6.2
6.0
5.6
5.5
5.2
4.8
4.4
4.3
4.2
4.0
3.9
3.7
3.6
3.2
2.7
1.6
0.7
0.3
0.1

(regrouped)

3.9
5.5
5.4
5.2
6.4
5.1
4.8

(reference)

4.2
2.9
2.8
3.8

Qatar
MyanmarChina
Lao PDR
India
Vietnam
Oman
Cambodia
Mongolia
Singapore
Sri Lanka
Bangladesh
BahrainIndonesia
Iran
Philippines
Malaysia
Nepal
Pakistan
ROC
Hong Kong
Korea
Thailand
UAE
Saudi Arabia
KuwaitBrunei
Japan
Fiji
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC
US
EU15
EU27
Australia

2000–2010
9.9
9.5
9.1
7.3
7.2
6.6
6.3
6.2
5.7
5.4
5.2
5.2
5.1
5.0
5.0
4.9
4.7
4.6
4.6
4.4
4.3
4.2
3.9
3.8
3.6
3.0
1.8
1.7
0.9

(regrouped)

4.0
6.3
6.2
6.4
7.2
5.2
4.2

(reference)

2.4
1.8
1.8
3.4

China
Qatar
MyanmarCambodia
VietnamLao PDR
India
Singapore
Malaysia
Bahrain
Korea
Bangladesh
Sri Lanka
Kuwait
Iran
ROC
Oman
Indonesia
UAE
Thailand
Nepal
Pakistan
Hong Kong
Philippines
Mongolia
Saudi Arabia
Brunei
Fiji
Japan
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC
US
EU15
EU27
Australia

12.6
11.4
10.0
7.8
7.2
7.0
7.0
6.3
6.0
5.8
5.7
5.5
5.1
5.1
4.9
4.7
4.5
4.5
4.4
4.4
4.3
4.1
4.0
3.8
3.7
3.2
1.4
1.1
0.7

(regrouped)

3.7
5.3
5.3
5.2
5.9
5.0
4.2

(reference)

0.7
0.7
0.9
2.6

Qatar
Myanmar
China
Cambodia
India
VietnamLao PDR
Mongolia
Iran
Bahrain
Bangladesh
Singapore
Sri Lanka
Indonesia
Oman
Philippines
Pakistan
Malaysia
Thailand
Kuwait
UAE
Korea
Hong Kong
ROC
Nepal
Saudi Arabia
Brunei
Fiji
Japan
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

4.0
5.9
5.8
5.8
6.8
5.2
4.5

(reference)

2.4
1.8
1.8
3.2

US
EU15
EU27
Australia

1.5
1.2
1.3
3.0

©2012 Asian Productivity Organization

Unit: Percentage.
Sources: Official national accounts in each country, including author adjustments.
Note: See Appendix A.1 for the adjustments made to harmonize GDP coverage across countries.

10: In interpreting the results in this report, we must bear in mind that conventional GDP tends to overstate the income of these oilexporting countries since it does not account for the depletion of natural resource stock, and in turn a large part of their GDP may
not be sustainable. Besides, GDP growth can underestimate the growth of real income available to the country brought about by
a favorable change in terms of trade, and vice versa. For an oil-exporting country, the growth wedge of the two measures could
be significant in the face of volatile oil prices. For example, Saudi Arabia’s real GDP growth underestimated its real income growthby 24 per cent between 1970 and 2010 (see Chapter 7).
11: Annual data maximize the use of available information and data, and are normally published two to three years in arrears. For
more timely analysis, quarterly economic data are used as they are normally published within a month of the reference period
and are subsequently revised as more data become available. That is, there is a trade-off between data timeliness and precision.
See Box 4 for more details.

223.1 Economic Scale and Growth

Japan has been consistently struggling at the bottom over the past two decades, with average growthof 0.9 per cent per year, compared with Asia29’s 5.3 per cent and the fastest growth of 9.9 per centachieved by China. During this period, only three Asian countries – Brunei, Fiji, and Japan – grew
slower than the US (2.4 per cent), and only Japan grew slower than EU15 (1.8 per cent). The divergenceof growth performance between the Asian countries on the one hand and the US and EU15 on theother was even more pronounced if we look at the 2000s alone (i.e., Asia29’s 5.8 per cent comparedwith the US at 1.5 per cent and EU15 at 1.2 per cent). The change of guards in Asia can be clearly seenin Figure 7. While Japan was the story of yesteryears, China and India have emerged as the driving
force propelling Asia forward over the past two decades, accounting for 46 per cent and 15 per centof regional growth, respectively. Although Japan has been the slowest growing economy in Asia, it
remained the fourth-largest contributor to regional growth in 1990–2010 due to its size.

3

Looking at the four sub-periods (in Table 3), growth in the reference countries, namely the US, EU15,
and Australia, revived between 1990–1995 and 1995–2000, before it began to deteriorate in the subsequent two periods in the 2000s. Both the US and EU15 went through deep recession in 2009, following the global financial storm. Consequently, for the second half of 2000s, they managed a growth of
only 0.7 per cent. In contrast, growth in Asia has gone from strength to strength with a blip in thesecond half of the 1990s due to the Asian financial crisis. Fastest acceleration has been achieved bySouth Asia, from an annual average growth rate of 4.9 per cent in 1990–1995 to 7.2 per cent in 2005–
2010, compared with 5.1 per cent and 6.4 per cent for East Asia, respectively. In contrast, ASEAN,
which was most impacted by the Asian financial crisis among all country groups, has not yet fully recovered its pre-crisis growth vitality with the average growth rate in the second half of the 2000s,
being 2 percentage points lower than that achieved in the first half of the 1990s.

It has been a subject of much debate if the Asian economy has

1970–1990
Japan
China
India
Korea
Indonesia
Saudi Arabia
ROC
Iran
Thailand
UAE
Pakistan
Hong Kong
Philippines
Malaysia
Singapore
VietnamOman
Sri Lanka
Bangladesh
Qatar
Brunei
MyanmarBahrain
Nepal
MongoliaFiji
Lao PDR
Cambodia
Kuwait −0.5
−10

1990–2010
34.6

16.1
9.8
6.6
5.0
4.4
3.9
3.7
2.9
2.7
2.0
1.9
1.7
1.6
1.1
0.6
0.4
0.4
0.4
0.2
0.2
0.1
0.1
0.1
0.1
0.0
0.0
0.0

0

10

20

30

40 %

China
India
Korea
Japan
Indonesia
Iran
ROC
Thailand
Malaysia
Saudi Arabia
Pakistan
UAE
VietnamSingapore
Hong Kong
Philippines
Bangladesh
Qatar
KuwaitMyanmar
Sri Lanka
Oman
Nepal
Cambodia
Bahrain
Lao PDR
BruneiMongolia
Fiji

46.4
15.5
5.9
5.1
3.7
3.7
3.1
2.3
1.7
1.7
1.5
1.3
1.2
1.2
1.1
1.0
0.9
0.6
0.5
0.4
0.4
0.3
0.1
0.1
0.1
0.1
0.0
0.0
0.0

0

10

20

30

40

50 %

Figure 7 Country Contributions to Regional GDP Growth,
1970–1990 and 1990–2010___Contribution share to the growth of gross regional products (growthrate of Asia29=100)
Sources: Official national accounts in each country, including author adjustments.

23©2012 Asian Productivity Organization

Based on Table 3, it is easy to assume that Asia was not evenslightly affected by the global financial crisis, as Asia29’s growthrate accelerated from 5.4 per centto 6.3 per cent between 2000–
2005 and 2005–2010. But, in fact,
Asia29’s growth slowed significantly from a recent peak of 7.9
per cent in 2007, to 4.6 per cent in2008 and further to 3.7 per cent in2009, before rebounding strongly
to 7.6 per cent in 2010, partly reflecting their crisis response in
the form of fiscal stimulation. Outof the 29 countries, eight Asian
economies experienced negative
growth in 2009, with the deepest
contraction of 5.7 per cent taking
place in Japan. Of the four AsianTigers, only Korea managed a narrow escape from a recession with
0.3 per cent growth in 2009.

3 Production-Side GDP

US

EU15

AUS

UAE

Group 5
SAU

QAT

OMN

KWT

BHR

THA

VIE

SIN

Group 4
PHL

MYA

MAL

LAO

IDN

FIJ

CAM

BRN

SRI

Group 3
PAK

NEP

IRN

IND

BAN

ROC

Group 2
MGL

KOR

JPN

HKG

CHN

Group 1China (CHN)
1.0
Hong Kong (HKG) 0.4 1.0
Japan (JPN)
0.0 0.7 1.0
Korea (KOR)
0.2 0.8 0.7 1.0
Mongolia (MGL) −0.5 −0.5 −0.3 −0.2 1.0
ROC (ROC)
0.6 0.8 0.5 0.7 −0.7 1.0
Bangladesh (BAN) −0.2 −0.1 −0.3 −0.3 0.4 −0.6 1.0
India (IND)
0.1 −0.4 −0.4 −0.1 0.6 −0.3 0.3 1.0
Iran (IRN)
0.0 0.2 0.2 −0.1 −0.4 −0.0 0.0−0.1 1.0
Nepal (NEP)
0.1 0.1 −0.2 0.1 −0.2 −0.1 0.1 0.2 0.4 1.0
Pakistan (PAK)
0.3 0.3 0.4 0.3 −0.4 0.5 −0.2 0.1 0.4 −0.2 1.0
Sri Lanka (SRI)
0.3 0.3 −0.0 0.1 −0.1 0.1 0.2−0.3 −0.3 0.2−0.6 1.0
Brunei (BRN)
0.3 0.4 0.4 0.6 −0.2 0.6 −0.2 0.2 0.3 0.0 0.9 −0.5 1.0
Cambodia (CAM) −0.3 0.2 0.1 0.5 0.3 0.3 −0.0 0.1 −0.2 −0.1 0.3 −0.3 0.5 1.0
0.3 −0.1 −0.4 0.1 0.1 0.1 −0.1 0.8 −0.0 0.2 0.3 −0.5 0.5 0.4 1.0
Fiji (FIJ)
0.5 0.9 0.8 0.9 −0.4 0.8 −0.3−0.2 0.1 0.0 0.4 0.2 0.5 0.1−0.0 1.0
Indonesia (IDN)
0.4 0.5 0.1 0.6 0.3 0.3 0.1 0.6 −0.3 −0.1 0.2 0.0 0.4 0.4 0.6 0.5 1.0
Lao PDR (LAO)
0.5 0.9 0.8 0.9 −0.4 0.8 −0.3−0.1 0.1 0.1 0.3 0.2 0.5 0.2 0.1 1.0 0.6 1.0
Malaysia (MAL)
0.0 0.2 −0.2 0.2 0.3 −0.1 0.7 0.5 0.1 0.2 0.1 0.0 0.3 0.4 0.4 0.0 0.5 0.1 1.0
Myanmar (MYA)
Philippines (PHL) 0.0 0.4 0.3 0.4 0.5 −0.1 0.3 0.4 −0.1 0.2−0.3 0.3 −0.0 0.1 0.1 0.4 0.7 0.5 0.4 1.0
0.6 0.9 0.5 0.8 −0.3 0.7 −0.1−0.1 −0.0 0.2 0.0 0.5 0.2 0.1 0.0 0.9 0.6 0.9 0.2 0.6 1.0
Singapore (SIN)
0.6 0.7 0.5 0.8 −0.6 0.9 −0.5−0.0 0.2 0.3 0.6 −0.0 0.8 0.2 0.3 0.8 0.4 0.8 0.1 0.1 0.7 1.0
Thailand (THA)
0.7 0.3 0.3 0.2 −0.0 0.3 0.0 0.3 0.0 −0.1 0.2 0.2 0.2 −0.4 0.1 0.5 0.5 0.5 0.0 0.5 0.5 0.4 1.0
Vietnam (VIE)
0.3 0.2 −0.2 −0.1 −0.6 0.1 0.2−0.2 0.4 0.7−0.1 0.3 −0.1 −0.5−0.0 0.1 −0.3 0.1 0.1 −0.2 0.2 0.2−0.1 1.0
Bahrain (BHR)
0.6 0.1 −0.4 −0.2 −0.1 0.0 0.5 0.4 0.1 0.1 0.2 0.1 0.1 −0.2 0.5 −0.0 0.4 0.0 0.6 0.1 0.2 0.1 0.4 0.4 1.0
Kuwait (KWT)
0.6 0.4 0.3 0.0 −0.7 0.5 −0.0−0.5 0.0 −0.2 0.2 0.4 0.0 −0.5−0.4 0.4 −0.1 0.3 −0.2 −0.2 0.3 0.3 0.5 0.4 0.3 1.0
Oman (OMN)−0.2 −0.1 −0.1 −0.3 0.4 −0.5 0.6−0.0 −0.4 −0.6−0.3 0.2 −0.5 −0.2−0.3 −0.3 0.1 −0.3 0.2 0.1 −0.2 −0.7 0.0 −0.2 0.2 0.2 1.0
Qatar (QAT)
Saudi Arabia (SAU) −0.2 0.2 0.5 −0.0 −0.5 0.2 −0.2−0.8 0.4 −0.4 0.4 −0.2 0.1 −0.1−0.6 0.1 −0.6 0.0 −0.4 −0.5 −0.2 0.0−0.2 0.0 −0.4 0.4 0.0 1.0−0.2 0.3 0.3 0.3 0.6 −0.1 0.5 0.3 −0.1 −0.3−0.0 0.2 0.1 0.4−0.1 0.2 0.5 0.2 0.6 0.7 0.3 −0.1 0.3 −0.6 0.0 −0.1 0.4 −0.2 1.0
UAE (UAE)
0.1 −0.5 −0.7 −0.5 0.6 −0.5 0.4 0.7 −0.4 −0.0−0.3 0.0 −0.4 −0.3 0.5 −0.5 0.3 −0.4 0.3 0.3 −0.3 −0.5 0.3 −0.1 0.6 −0.2 0.4 −0.7 0.1 1.0
Australia (AUS)−0.7 −0.2 0.0 −0.0 0.7 −0.4 0.4 0.1 −0.2 −0.4−0.1 −0.1 0.0 0.6−0.2 −0.3 0.0 −0.3 0.3 0.2 −0.3 −0.4−0.4 −0.7 −0.4 −0.5 0.3 0.1 0.7 −0.1 1.0
EU15−0.2 −0.2 −0.5 −0.3 0.7 −0.6 0.7 0.6 −0.2 −0.0−0.3 0.0 −0.3 0.2 0.4 −0.4 0.4 −0.3 0.7 0.4 −0.1−0.5 0.0 −0.2 0.5 −0.4 0.5 −0.6 0.5 0.7 0.4 1.0
US
If greater than 0.55

If less than −0.55

Figure 8 Correlation of GDP Growth in the 1990s___Correlation of GDP growths at constant prices

Sources: Official national accounts in each country, including author adjustments.

©2012 Asian Productivity Organization

decoupled from the business cycle in the US and EU15. If it has, the world economy will be less volatile. Park and Shin (2009) provide evidence that East Asia has seen a marked increase in intra-regional
trade, and, at the same time, diversified its exports markets to other parts of the world, such thatits output movement has become more idiosyncratic than before, and in turn, less dependent onthat of the US. In particular, the importance of the US market as an outlet of China’s final goods exports has weakened recently. In contrast, the impact of Asia’s extra-regional integration with the global financial markets on business cycle synchronicity is less clear-cut. While deep financial markets
allow more risk diversification and the smoothing out of consumption, closer integration also provides the conduit for financial contagion, and East Asia still suffers from the flight for quality whena crisis strikes. As the impact of the global financial crisis was filtering through, Asia seemed to be
immune from the adverse impact initially. However, when the global investors began to retreat fromthe region and the financial menace began to transmit through the real economy, Asia too started toslow significantly.
Figures 8 and 9 compare the correlation coefficients of growth rates among countries in the 1990s
and the 2000s, respectively. Countries are grouped by region. Overall, the correlation coefficients between China and other Asian economies strengthened between the two decades, suggesting that
China has become more integrated within the Asian economy. It is interesting to note that the correlation coefficient between China and Japan moved from 0.0 to 0.6, and China’s correlation with the US
and EU15 is weaker than with other Asian countries. Correlation among the East Asian countries has

24

3.2 Catching Up in Per Capita GDP

China (CHN)
1.0
Hong Kong (HKG) 0.6 1.0
Japan (JP N)
0.6 0.8 1.0
Korea (KOR)
0.4 0.6 0.8 1.0
Mongolia (MGL) 0.4 0.8 0.7 0.4 1.0
ROC (ROC)
0.8 0.8 0.8 0.7 0.6 1.0
Bangladesh (BAN) 0.6 0.6 0.2 −0.1 0.5 0.3 1.0
India (IND)
0.6 0.4 0.2 −0.2 0.2 0.3 0.7 1.0
Iran (IRN)−0.1 0.4 0.4 0.5 0.4 0.3 −0.3−0.0 1.0
Nepal (NEP )0.3 0.1 −0.1 −0.1 0.3 0.3 0.3 0.4 −0.0 1.0
P akistan (P AK)
0.3 0.7 0.4 0.2 0.5 0.5 0.5 0.7 0.5 0.3 1.0
Sri Lanka (SRI)
0.7 0.7 0.4 0.2 0.6 0.7 0.6 0.5 −0.0 0.7 0.5 1.0
Brunei (BRN)
0.2 0.3 0.6 0.7 0.1 0.4 −0.3−0.1 0.6 −0.4 0.1 −0.0 1.0
Cambodia (CAM) 0.2 0.8 0.7 0.5 0.8 0.4 0.3 0.2 0.7 −0.1 0.6 0.2 0.4 1.0
Fiji (FIJ)−0.3 0.2 0.3 0.4 0.3 0.2 −0.2−0.5 0.4 −0.3 0.0 −0.2 0.4 0.2 1.0
Indonesia (IDN)
0.8 0.6 0.4 0.2 0.6 0.6 0.7 0.5 −0.2 0.6 0.3 0.8 −0.3 0.3−0.4 1.0
Lao P DR (LAO)
0.6 0.3 0.0 −0.1 0.3 0.3 0.9 0.6 −0.4 0.4 0.2 0.7 −0.2 −0.1−0.3 0.7 1.0
Malaysia (MAL)
0.6 0.9 0.9 0.7 0.9 0.9 0.3 0.2 0.4 0.3 0.5 0.7 0.3 0.6 0.3 0.6 0.2 1.0
Myanmar (MYA) −0.1 0.5 0.4 0.2 0.5 0.3 0.0 0.3 0.8 0.0 0.8 0.2 0.4 0.7 0.3 −0.1 −0.3 0.4 1.0
P hilippines (P HL) 0.8 0.9 0.9 0.6 0.8 0.9 0.5 0.4 0.2 0.2 0.5 0.7 0.3 0.6 0.2 0.7 0.3 0.9 0.3 1.0
Singapore (SIN)
0.8 0.9 0.8 0.6 0.6 1.0 0.5 0.5 0.2 0.3 0.6 0.8 0.3 0.5 0.1 0.7 0.4 0.8 0.3 0.9 1.0
Thailand (THA)
0.5 0.7 0.9 0.8 0.6 0.8 −0.1 0.1 0.6 0.0 0.4 0.4 0.7 0.6 0.4 0.2 −0.2 0.8 0.5 0.8 0.7 1.0
Vietnam (VIE)
0.4 0.8 0.7 0.6 0.7 0.6 0.3 0.4 0.8 0.1 0.8 0.4 0.4 0.9 0.1 0.3 0.1 0.7 0.8 0.6 0.6 0.6 1.0
Bahrain (BHR)
0.3 0.7 0.5 0.3 0.8 0.4 0.4 0.3 0.6 0.4 0.7 0.5 0.1 0.8−0.1 0.5 0.1 0.7 0.7 0.5 0.4 0.4 0.9 1.0
Kuwait (KWT)−0.0 0.5 0.5 0.1 0.6 0.3 −0.0 0.1 0.5 0.1 0.4 0.4 0.4 0.6 0.3 0.1 −0.2 0.6 0.8 0.4 0.3 0.6 0.5 0.7 1.0
Oman (OMN)
0.1 0.2 0.1 −0.0 0.4 −0.1 0.5−0.3 −0.3 −0.0−0.3 0.1 −0.4 0.2−0.0 0.5 0.4 0.2 −0.4 0.2 −0.0 −0.2 0.1 0.2 −0.1 1.0
Qatar (QAT)
0.6 0.5 0.2 0.2 0.5 0.4 0.8 0.4 −0.2 0.3 0.3 0.6 −0.1 0.1 0.1 0.6 0.9 0.4 −0.1 0.5 0.6 0.0 0.2 0.1 −0.2 0.4 1.0
Saudi Arabia (SAU) 0.2 0.6 0.5 −0.1 0.6 0.4 0.3 0.4 0.2 0.2 0.5 0.5 0.0 0.5 0.1 0.4 0.1 0.6 0.6 0.6 0.5 0.5 0.4 0.6 0.9 −0.0 0.0
UAE (UAE)
0.0 0.6 0.5 0.2 0.7 0.4 0.3 0.3 0.6 0.1 0.6 0.4 0.4 0.7 0.5 0.1 0.1 0.6 0.8 0.5 0.4 0.5 0.7 0.7 0.8 −0.1 0.3
Australia (AUS) −0.2 0.1 0.2 0.2 0.1 −0.0 −0.3 0.1 0.8 −0.1 0.3 −0.3 0.6 0.5 0.1 −0.4 −0.4 0.1 0.7 0.0 −0.1 0.4 0.6 0.4 0.3 −0.4 −0.4
EU15
0.4 0.8 0.9 0.7 0.8 0.6 0.2 0.0 0.7 −0.2 0.4 0.2 0.6 0.9 0.4 0.3 0.0 0.7 0.5 0.7 0.6 0.8 0.9 0.6 0.5 0.3 0.2
US
0.4 0.9 0.9 0.7 0.7 0.8 0.1 0.2 0.6 −0.1 0.6 0.4 0.6 0.8 0.4 0.3 −0.1 0.8 0.7 0.8 0.8 0.9 0.8 0.6 0.7 −0.1 0.1
If greater than 0.55

US

EU15

AUS

UAE

Group 5
SAU

QAT

OMN

KWT

BHR

THA

VIE

SIN

Group 4
PHL

MYA

MAL

IDN

LAO

FIJ

CAM

BRN

SRI

Group 3
PAK

NEP

IRN

IND

BAN

ROC

Group 2
MGL

KOR

JPN

HKG

CHN

Group 13

1.0
0.7 1.0
0.0 0.4 1.0
0.3 0.6 0.4 1.0
0.6 0.7 0.4 0.9 1.0

If less than −0.55

Figure 9 Correlation of GDP Growth in the 2000s___Correlation of GDP growths at constant prices

Sources: Official national accounts in each country, including author adjustments.

strengthened over time, and, with the exception of China, so has their correlation with the US and
EU15. The correlation among countries in Group 3 and their correlation with the US and EU15, has also
grown stronger. Within Group 3, we see that the ties of Vietnam and the Philippines with East Asia
have become much closer.

3.2 Catching Up in Per Capita GDP

Others
27 %

EU27
7%

APO20
35 %

Asia
61 %

EU15
Asia296%56 %US
5 % Other Asia
4%

Figure 10 Share of Asian Population in the Worldin 2010Source: IMF, World Economic Outlook Database, September 2011.

25©2012 Asian Productivity Organization

Performance comparisons based on wholeeconomy GDP do not take into account the
population size and can in turn exaggerate
the well-being of countries with large populations. Asia is the world’s most populous
region. In 2010, it accounted for 61 per centof the world’s population (56 per cent for
Asia29), and China and India alone accountfor more than one-third (Figure 10). Basedon per capita GDP, which adjusts for differences in population size (but not income
distribution), Asia’s rising economic giants2010

3 Production-Side GDP(i.e., China and India) are still very much less well-off compared with the US standard, whereas the
Asian Tigers fare exceptionally well.12
Table 4 presents cross-country comparisons of per capita current-price GDP, using exchange rates as
the conversion rates. However, given the volatile nature of exchange rates, snapshot comparisons likethose presented in Table 4 can appear arbitrary. Rather, long-term trends of nominal per capita GDP
provide a better guide of relative movements. Based on this measure, Japan closed up on the US levelin the late 1980s and peaked in 1995, reflecting the strong yen (Figure 11). Figure 12 shows comparisons among the four Asian Tigers (Singapore, Hong Kong, the ROC, and Korea). Singapore and Hong
Table 4 Cross-Country Comparisons of Per Capita GDP Using Exchange Rate, 1970, 1990, 2000,
and 2008–2010___GDP at current market prices per person, using annual average exchange rate
1970

2000

(%)

2008

(%)

2009

(%)

2010

(%)

(%)

2.01 100.0
0.96 47.9
0.93 46.0
0.43 21.2
0.39 19.3
0.37 18.6
0.37 18.4
0.28 13.8
0.21 10.6
0.21 10.4
0.20 10.0
0.20 9.9
0.14 7.1
0.12 5.9
0.12 5.9
0.11 5.5
0.11 5.2
0.10 4.9
0.09 4.4
0.09 4.2
0.03 1.4

Japan
Hong Kong
Singapore
ROC
Korea
MalaysiaFiji
IranThailandPhilippines
Indonesia
Mongolia
Sri Lanka
Pakistan
India
China
Bangladesh
Nepal
Lao PDR
Cambodia
MyanmarVietnam

25.10 100.0
13.48 53.7
12.75 50.8
8.08 32.2
6.31 25.1
2.57 10.2
1.85 7.4
1.71 6.8
1.62 6.4
0.80 3.2
0.71 2.8
0.58 2.3
0.49 1.9
0.43 1.7
0.40 1.6
0.34 1.4
0.27 1.1
0.24 1.0
0.21 0.8
0.19 0.8
0.13 0.5
0.10 0.4

Japan
Hong Kong
Singapore
ROC
Korea
Malaysia
Fiji
ThailandIranPhilippines
China
Sri Lanka
Indonesia
Pakistan
Mongolia
India
VietnamBangladesh
Lao PDR
Cambodia
Nepal
Myanmar37.35 100.0
25.38 67.9
23.41 62.7
14.64 39.2
11.35 30.4
4.00 10.7
2.11 5.6
2.08 5.6
1.71 4.6
1.06 2.8
0.95 2.5
0.89 2.4
0.81 2.2
0.52 1.4
0.48 1.3
0.47 1.3
0.41 1.1
0.37 1.0
0.32 0.8
0.31 0.8
0.28 0.7
0.16 0.4

SingaporeJapan
Hong Kong
Korea
ROC
Malaysia
Iran
ThailandFiji
China
Indonesia
Mongolia
Sri Lanka
Philippines
India
VietnamLao PDR
Pakistan
Cambodia
Bangladesh
Nepal
Myanmar39.26 100.0
38.06 96.9
30.86 78.6
19.16 48.8
17.37 44.2
8.10 20.6
5.35 13.6
4.43 11.3
4.31 11.0
3.40 8.7
2.24 5.7
2.11 5.4
2.02 5.1
1.93 4.9
1.11 2.8
1.08 2.8
0.89 2.3
0.89 2.3
0.78 2.0
0.58 1.5
0.53 1.4
0.36 0.9

Japan
Singapore
Hong Kong
Korea
ROC
Malaysia
Iran
ThailandChina
Fiji
Indonesia
Sri Lanka
Philippines
Mongolia
India
Vietnam
Pakistan
Lao PDR
Cambodia
Bangladesh
Nepal
Myanmar39.58 100.0
37.22 94.0
29.88 75.5
17.11 43.2
16.33 41.3
6.93 17.5
5.45 13.8
4.24 10.7
3.74 9.4
3.43 8.7
2.33 5.9
2.07 5.2
1.83 4.6
1.69 4.3
1.15 2.9
1.14 2.9
0.93 2.3
0.93 2.3
0.78 2.0
0.64 1.6
0.56 1.4
0.39 1.0

SingaporeJapan
Hong Kong
Korea
ROC
Malaysia
Iran
ThailandChina
Fiji
Indonesia
Sri Lanka
Mongolia
Philippines
India
VietnamLao PDR
Pakistan
Cambodia
Bangladesh
Nepal
Myanmar44.79 100.0
42.95 95.9
31.72 70.8
20.77 46.4
18.57 41.5
8.44 18.8
6.29 14.0
5.17 11.6
4.42 9.9
3.77 8.4
3.02 6.7
2.41 5.4
2.24 5.0
2.13 4.7
1.44 3.2
1.21 2.7
1.12 2.5
1.02 2.3
0.83 1.90.70 1.6
0.66 1.5
0.46 1.0

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei1.82 90.3
3.95 196.7
0.38 19.1
5.01 249.4
0.93 46.4
4.46 221.8
1.50 74.4

Bahrain9.16 36.5
Kuwait8.95 35.7
Oman
6.53 26.0
Qatar
15.73 62.7
Saudi Arabia 7.29 29.0
UAE
28.86 115.0
Brunei12.70 50.6

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei

13.12
17.94
8.18
30.37
9.49
35.20
17.34

35.1
48.0
21.9
81.3
25.4
94.2
46.4

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei20.94 53.4
54.37 138.5
21.41 54.5
83.64 213.1
18.35 46.7
51.67 131.6
36.83 93.8

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei17.37 43.9
37.66 95.2
15.42 39.0
62.12 156.9
14.18 35.8
39.80 100.6
27.86 70.4

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei18.47 41.2
42.77 95.5
21.66 48.4
73.37 163.8
16.57 37.0
40.45 90.3
33.91 75.7

(regrouped)(regrouped)

3.46
2.47
2.56
4.73
0.47
1.20
13.19

9.3
6.6
6.9
12.7
1.3
3.2
35.3

35.27
25.25
21.92
21.26

94.4
67.6
58.7
56.9

(regrouped)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

0.32
0.23
0.23
0.32
0.13
0.13
1.36

15.8
11.4
11.6
16.1
6.4
6.3
67.9

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

2.59
1.68
1.73
2.99
0.39
0.84
9.28

10.3
6.7
6.9
11.9
1.5
3.4
37.0

(reference)(reference)©2012 Asian Productivity Organization

1990

(%)

Japan
Hong Kong
Singapore
Fiji
ROC
Iran
Malaysia
Korea
ThailandSri Lanka
Pakistan
Philippines
Bangladesh
Cambodia
India
China
Mongolia
Myanmar
Nepal
Indonesia
Vietnam

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

(regrouped)(reference)

US
EU15

5.06 251.9
3.50 174.1

US
EU15

23.24
16.88

92.6
67.3

Australia

3.56 177.1

Australia

18.92

75.4

US
EU15
EU27
Australia

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

(regrouped)

4.28
3.91
4.18
7.11
1.04
2.67
28.45

10.9
10.0
10.7
18.1
2.6
6.8
72.5

(reference)

US
EU15
EU27
Australia(regrouped)

4.28
4.04
4.24
7.43
1.08
2.61
21.92

10.8
10.2
10.7
18.8
2.7
6.6
55.4

(reference)

46.95 119.6
35.41 90.2
32.09 81.7
48.31 123.1

Unit: Thousands of US dollars.
Sources: Official national accounts in each country, including author adjustments.
Note: See Appendix A.1 for the adjustments made to harmonize GDP coverage across countries.

26

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC
US
EU15
EU27
Australia

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

4.88
4.66
4.89
8.45
1.32
3.20
25.12

10.9
10.4
10.9
18.9
3.0
7.1
56.1

(reference)

45.40 114.7
34.36 86.8
31.23 78.9
45.41 114.7

US
EU15
EU27
Australia

46.96 104.8
34.99 78.1
31.80 71.0
56.87 127.0

3.2 Catching Up in Per Capita GDP

In terms of per capita GDP at constant prices using PPPs, Japan was
the first country in Asia to start
catching up with the US (Figure13). By 1970, its per capita GDP
was 63 per cent that of the US,
quite a distance ahead of other
Asian countries. It had been closing the gap with the US up to1991 (86 per cent), but the gap
widened again when the impactof the long recession of the 1990s
started to manifest itself.13 In recent years, Japan’s level has stabilized to around 70 per cent that of
the US.
Japan’s per capita GDP was the
top among Asian countries until it
was overtaken by Singapore14 in
1993. The result highlights theoutcome of the dramatic development effort made by the four
Asian Tigers, as shown in Figure 14.

US=100 in each year

160
140
120
100

3

Japan
US

80
60

Austraria

40
20
0
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 11 Cross-Country Comparison of Per Capita GDP
Using Exchange Rate of Japan and Australia Relative to theUS, 1970–2010___GDP at current market prices per person, using annual averageexchange rates, relative to the US
Sources: Official national accounts in each country, including author adjustments.

US=100 in each year

100

Singapore
80

60

Hong Kong

40

Korea

ROC

20

0
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 12 Cross-Country Comparison of Per Capita GDP
Using Exchange Rate of Asian Tigers Relative to the US,
1970–2010___GDP at current market prices per person, using annual averageexchange rates, relative to the US
Sources: Official national accounts in each country, including author adjustments.

12: Even so, it is not without its shortcomings as a welfare measure. A rise in the per capita GDP data does not always directly translate into an improvement in the welfare of the people concerned. In fact, as an average measure, per capita GDP can bear little
relevance to individuals’ personal experience if, for example, the distribution of economic gain is highly skewed or economic
advancement has been achieved at high environmental and health costs, which are not accounted for in the statistics. There are a
lot more attributes to individuals’ welfare than captured in one simple measure called per capita GDP. Supplementary statistics are
therefore necessary to build a fuller picture of progress made in individual well-being.
13: Jorgenson and Nomura (2007) indicated that the manufacturing sector was the main contributor to the catching-up processof the Japanese economy in the 1960s, and that the US–Japan TFP gap for the manufacturing sector had almost disappearedby 1990.

27©2012 Asian Productivity Organization

Kong have been moving closelywith one another for three and ahalf decades until the mid-2000s,
when Singapore spurred strongly
ahead of Hong Kong. The ROC
and Korea move roughly together
but at a lower level than Singapore and Hong Kong. In Asia, Japan and Singapore are the twocountries that have income levels
almost equivalent to those of the
US and Australia. However, thisview is considerably revised when
we focus on production or real income per capita (i.e., using PPPs
as the conversion rates) (Table 5).

3 Production-Side GDP

Not only were they edging to
the top, they were constantly
closing the gap with the US. Starting from a level of 36 per cent thatof the US in 1970, Singapore surpassed the US in 2004.15 In 2010,
Singapore had a per capita GDP
which was 23 per cent above thatof the US, and it has been therichest economy in Asia. This represented a remarkable achievement. Hong Kong occupies thesecond place, with a per capita
GDP similar to that of the US.
Japan’s per capita GDP, at 73 percent of the US or around 60 per
cent of the group leader (Singapore), is similar to that of EU15.
The ROC and Korea trail closly at
76 per cent and 64 per cent of theUS, respectively.

US=100 in each year

100

90

Austraria

80
EU15
70
Japan

60

50
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 13 Per Capita GDP of Japan, the EU, and Australia
Relative to the US, 1970–2010___GDP at current market prices per person, using 2005 PPPs, relative
to the US

Sources: Official national accounts in each country, including author adjustments.
US=100 in each year

120

Singapore100

US©2012 Asian Productivity Organization

The relative performance of China
80
and India, the two most populous
Hong Kongcountries in the world, is pulled
60
down on this measure due totheir population size, with their40
ROC
per capita GDP at 16.1 per centand 7.4 per cent that of the US20
Korea
in 2010, respectively (Figure 15).
Even so, this should not tarnish
0
1970
1975
1980
1985
1990
1995
2000
2005
2010
their remarkable progress madeover the past decades, especially
Figure 14 Per Capita GDP of Asian Tigers Relative to the US,
that of China, whose per capita
1970–2010
GDP was less than 2 per cent that___Ratio of per capita GDP at constant market prices, using 2005 PPPs,
of the US in 1970; China’s relative
relative to the US
per capita GDP has increased sevSources: Official national accounts in each country, including author adjustments.
enfold in four decades. The income gap between the US andthe majority of Asian countries is still sizable,16 indicating that there is still a lot of room to catch up.

14: Singapore’s population comprises not only Singaporean citizens but also non-citizens who have been granted permanent residence in Singapore as well as non-permanent residents such as employment pass holders, work permit holders, and student passholders. It is known that many workers and students commute to Singapore from outside the country every day. According to themost recent census, the share of Singaporean citizens with respect to total population was 74 per cent in 2000, the share of permanent residents who are not Singaporean citizens was 7 per cent, and the share of non-permanent residents was 19 per cent.
15: Generally, Singapore’s GNI is lower than its GDP, and over the past four decades, the divergence was the largest in 2004 with GNI
equivalent to 92.9 per cent of GDP. As the US GNI never goes outside +1.5 per cent of GDP, Singapore would not have overtaken
the US in 2004 if GNI was used for comparisons instead of GDP. However, Singapore’s lead of 22 per cent over the US in 2010 waslarge enough that their relative positions would be independent of whether GNI or GDP was used.

28

3.2 Catching Up in Per Capita GDP

Table 5 presents separately the
figures for seven oil-rich economies (Brunei and the six GCC
countries). At first glance, figuresin 1970 and to a lesser extent in1990 suggest that these economies enjoyed an income manytimes that of Japan and the US.
For example, Kuwait, Qatar, andBrunei had a per capita GDP 7.5
times, 7.4 times, and 3.9 times
that of Japan, respectively, in1970. However, the measurementof GDP as an indicator of income
is misleading for these countries,
as it erroneously includes proceeds from the liquidation of anatural resource stock as part ofthe income flow. In other words,
GDP overestimates income of theoil-exporting economies, as it
does not account for depletion of
their natural resource assets. To
give a rough indication of the extent of distortion, Figure 16 provides comparisons of per capita
GDP excluding production of themining sector (i.e., crude oil, natural gas, and so on). The nonmining GDP per person in Brunei
and GCC economies like Qatar,
the UAE, and Kuwait is almost similar to Japan’s level, although total GDP per capita is much larger.

US=100 in each year

18
16
14

3

12
10
ASEAN
8
6
4
India
2

China

0
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 15 Per Capita GDP of China, India, and ASEAN Relative to the US, 1970–2010___Ratio of per capita GDP at constant market prices, using 2005 PPPs,
relative to the US
Sources: Official national accounts in each country, including author adjustments.

Qatar

33

UAE

32

Japan

49
19

31

2

Brunei

23

24

Kuwait23

24

Bahrain

18

Oman

13

7

Saudi Arabia

12

Iran

12

1

Malaysia1220Non-mining

10

GDP

10

Thousands of US dollars (as of 2010)

20

40

60

80

100

Figure 16 Per Capita Non-Mining GDP in Oil-Rich Countries, 2009___GDP at constant market prices per person, using 2005 PPPs,
reference year 2010
Sources: Official national accounts in each country, including author adjustments.

16: Per capita GDP may have underestimated the welfare of people in some countries. In the ROC, Hong Kong, and Japan, for example, GNI is consistently higher than GDP although the fluctuations are within +5 per cent. The Philippines is the exception
where the divergence between GNI and GDP has been increasing and has become significant for the past two decades, and GNI
was higher than GDP by 33.3 per cent in 2010. Fiji had a GNI 10–16 per cent above GDP in the early 2000s, but since then, GNI has
converged back to the GDP level.

29©2012 Asian Productivity Organization

Catching up to the per capita GDP
level of the advanced economies
is a long-term process that could take several decades to accomplish. Empirical evidence has suggested that there may be a negative correlation between per capita GDP level and the speed of catching up, although not without exceptions. With the possibility of adopting successful practices andtechnologies from the more advanced economies, less advanced economies are poised to experience
faster growth in per capita GDP, enabling them to catch up in average income level. However, as theirincome levels come closer to those of the more advanced countries, their economic growth rates are
expected to decline over time.17 (See Box 5 on the middle-income trap.)

3 Production-Side GDP

Table 5 Per Capita GDP, 1970, 1990, 2000, and 2008–2010___GDP at constant market prices per person, using 2005 PPPs, reference year 2010
1970
Japan
Hong Kong
Singapore
Iran
ROC
Malaysia
Fiji
Korea
Philippines
ThailandMongolia
Sri Lanka
Pakistan
India
Indonesia
Bangladesh
Vietnam
China
Myanmar

1990

(%)

2000

(%)

2008

(%)

2009

(%)

2010

(%)

(%)

14.5 100.0
8.3 57.7
8.2 56.7
7.6 52.3
4.0 27.4
3.1 21.5
2.7 18.9
2.7 18.6
2.3 15.6
1.9 12.8
1.4 9.8
1.2 8.6
1.1 7.9
0.9 6.4
0.9 6.0
0.8 5.8
0.7 4.8
0.4 2.6
0.3 2.3

Japan
Singapore
Hong Kong
ROC
Korea
Malaysia
Iran
ThailandFiji
Philippines
Mongolia
Indonesia
Sri Lanka
Pakistan
India
China
Lao PDR
Vietnam
Nepal
Bangladesh
Cambodia
Myanmar29.5 100.0
28.0 95.0
26.3 89.2
15.1 51.3
12.1 41.1
7.4 25.0
7.1 23.9
4.8 16.2
3.8 13.1
2.9 9.7
2.6 8.8
2.3 7.8
2.2 7.6
1.8 6.1
1.4 4.7
1.2 4.1
1.0 3.5
1.0 3.4
0.9 3.2
0.8 2.7
0.8 2.7
0.4 1.3

Singapore
Hong Kong
Japan
ROC
Korea
Malaysia
Iran
ThailandFiji
Sri Lanka
Indonesia
Philippines
China
Mongolia
Pakistan
India
VietnamLao PDR
Nepal
Cambodia
Bangladesh
Myanmar42.2 100.0
33.1 78.3
32.1 76.0
25.3 60.0
20.8 49.2
11.3 26.8
8.9 21.1
6.7 15.8
4.5 10.6
3.3 7.9
3.1 7.2
3.0 7.1
2.9 7.0
2.5 5.9
2.2 5.1
1.9 4.6
1.8 4.2
1.5 3.6
1.2 2.9
1.2 2.9
1.1 2.7
0.6 1.5

Singapore
Hong Kong
Japan
ROC
Korea
Malaysia
Iran
ThailandChina
Fiji
Sri Lanka
Indonesia
Mongolia
Philippines
India
Vietnam
Pakistan
Lao PDR
Cambodia
Bangladesh
MyanmarNepal

53.5 100.0
45.0 84.3
34.8 65.2
32.9 61.6
28.3 53.0
14.4 26.9
13.0 24.3
9.1 17.0
6.3 11.8
4.8 9.0
4.7 8.7
4.1 7.6
4.0 7.4
3.7 7.0
3.0 5.7
2.9 5.5
2.6 4.9
2.3 4.3
2.2 4.1
1.6 3.0
1.5 2.9
1.4 2.6

Singapore
Hong Kong
Japan
ROC
Korea
Malaysia
Iran
ThailandChina
Sri Lanka
Fiji
Indonesia
Mongolia
Philippines
India
Vietnam
Pakistan
Lao PDR
Cambodia
MyanmarBangladesh
Nepal

51.4 100.0
43.7 85.1
33.0 64.2
32.2 62.7
28.3 55.2
14.0 27.2
13.4 26.1
8.9 17.4
6.9 13.4
4.8 9.3
4.7 9.2
4.2 8.2
3.8 7.5
3.7 7.2
3.2 6.3
3.1 5.9
2.7 5.2
2.4 4.7
2.2 4.2
1.7 3.3
1.7 3.2
1.4 2.8

Singapore
Hong Kong
ROC
Japan
Korea
Malaysia
Iran
ThailandChina
Sri Lanka
Fiji
Indonesia
Mongolia
Philippines
India
Vietnam
Pakistan
Lao PDR
Cambodia
MyanmarBangladesh
Nepal

57.9 100.0
46.3 80.0
35.6 61.5
34.3 59.2
30.0 51.9
14.8 25.5
14.1 24.3
9.6 16.6
7.6 13.0
5.1 8.9
4.7 8.1
4.4 7.6
4.0 6.9
3.9 6.8
3.5 6.0
3.2 5.6
2.7 4.7
2.6 4.4
2.3 3.9
1.8 3.2
1.7 3.0
1.4 2.5

Bahrain20.8 143.5
Kuwait108.0 746.3
Oman
7.3 50.1
Qatar
107.0 739.5
Saudi Arabia 24.2 167.2
UAE
29.9 206.8
Brunei55.8 385.6

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei21.7 73.5
23.3 79.1
17.7 60.0
49.1 166.4
21.5 73.0
80.7 273.7
52.5 178.0

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei27.5 65.1
40.8 96.7
20.5 48.5
74.9 177.2
22.7 53.7
78.3 185.5
50.6 119.8

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei26.4 49.4
50.8 95.1
25.6 47.8
83.3 155.9
23.0 43.1
58.1 108.6
49.2 92.1

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei25.4 49.4
46.2 89.9
24.0 46.7
81.7 159.0
22.5 43.8
51.2 99.8
47.4 92.4

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei25.3 43.6
45.5 78.6
28.9 49.9
88.5 152.9
22.9 39.5
48.0 82.9
47.8 82.6(regrouped)(regrouped)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

2.5 17.6
1.6 11.1
1.7 11.9
2.0 14.0
0.9 6.4
1.2 8.5
32.0 220.9

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

(regrouped)

4.4
3.1
3.3
4.5
1.4
2.7
26.6

15.0
10.6
11.2
15.2
4.7
9.1
90.1

(reference)(reference)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

(regrouped)

5.3
4.3
4.6
6.5
1.9
3.7
30.8

12.4
10.2
10.8
15.4
4.5
8.8
73.0

(reference)

US
EU15

23.1 159.5
16.1 110.9

US
EU15

35.7 121.1
26.0 88.3

Australia

20.6 142.3

Australia

27.5

93.3

US
EU15
EU27
Australia

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

(regrouped)

6.5
6.4
6.7
10.0
2.8
5.1
32.7

12.1
11.9
12.4
18.6
5.3
9.5
61.1

48.0
35.1
31.6
40.0

89.8
65.6
59.1
74.8

(reference)

44.1 104.4
31.6 74.9
27.8 65.8
34.7 82.3

US
EU15
EU27
Australia

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

(regrouped)

6.5
6.5
6.8
10.2
3.0
5.1
31.2

12.6
12.8
13.3
20.0
5.9
10.0
60.7

45.9
33.4
30.1
40.0

89.4
65.1
58.6
78.0

(reference)

US
EU15
EU27
Australia

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

6.8
7.0
7.3
11.1
3.2
5.4
31.8

11.8
12.1
12.6
19.1
5.5
9.4
55.0

47.0
34.0
30.6
40.1

81.1
58.7
52.8
69.3

(reference)

US
EU15
EU27
Australia©2012 Asian Productivity Organization

Unit: US dollar (as of 2010).
Sources: Official national accounts in each country, including author adjustments.
Note: See Appendix A.1 for the adjustments made to harmonize GDP coverage across countries.

Figure 17 plots countries’ initial per capita GDP levels against their respective average growth rates
per year between 1970 (or whichever year data first became available for the country in question) and2010. The two variables have a correlation coefficient of −0.5 (i.e., a negative relationship of medium
strength). In other words, the higher the initial income level, the slower the average growth rate per

17: The OECD (2008) observes that GDP per capita has broadly converged in the OECD (Organisation for Economic Co-operation andDevelopment) countries since the 1970s. However, more advanced economies that started with high income levels in the 1970s
have had lower rates of catch-up, or even stagnated or recently diverged vis-à-vis the US. Between 1973 and 2006, Ireland andKorea managed the highest rates of catch-up in per capita GDP, with 2.3 per cent and 3.8 per cent per year, respectively.

30

3.2 Catching Up in Per Capita GDP% Growth rate of per capita GDP during 1970–20105% Growth rate of per capita GDP during 1970–2010=1970, ×=1990,=1990,

8=2010=1970, ×=1990,=1990, =2010

China
7

MyanmarIndonesia

4

Vietnam
India

ROC

Sri Lanka
5

3
Cambodia

Mongolia

Lao PDR

3

Bangladesh
Nepal

Singapore
Hong Kong

Thailand
Malaysia

4

Pakistan

2

3

Korea

6

Philippines
Fiji

Japan
EU15

2

1
1
Thousands of US dollars (as of 2010)

0

US

Australia

Iran

Thousands of US dollars (as of 2010)

0
0

1

2

3

4

5

6

0

10

20

30

40

50

60

70

Per capita GDP at constant prices

Per capita GDP at constant prices

Figure 17 Initial Level and Growth of Per Capita GDP, 1970–2010___Level and average annual growth rate of GDP at constant market prices, using 2005 PPPs, reference year 2010
Sources: Official national accounts in each country, including author adjustments.

Table 6 Country Groups Based on the Initial Economic
Level and the Pace of Catch-Up___Level and average annual growth rate of GDP at constant market
prices, using 2005 PPPs
Initial GDP
level
to the US

Annual rate of catch-up to the US
(C1)
>3%

(C2)
1%<–<3%

(L1)
60%<
(L2)
20%<–<60%

Singapore

Hong Kong,
Oman

(L3)
5%<–<20%

ROC, Korea

Malaysia,
Sri Lanka, Thailand

(L4)
<5%

(C3)
0%<–<1%(C4)<0%

Japan, EU15

Brunei, Bahrain,
Kuwait, Qatar,
Saudi Arabia, UAE,
Australia
Iran

MongoliaFiji, Philippines

India, Indonesia,
Bangladesh, Nepal,
Cambodia, China Lao PDR, Myanmar,
Pakistan
Vietnam

Sources: Official national accounts in each country, including author adjustments.
Note: The annual catch-up rates are based on the difference in the growths of percapita GDP at constant prices between each country and the US during 1970–2010.
The starting years for some countries are different due to data availability: Cambodia (1987–), Lao PDR (1984–), and Nepal (1974–).

Table 6 summarizes Figure 17 bycountry groups. Four levels of percapita income groups are defined: Group-L1, with per capita GDP at or above 60 per cent of the US;
Group-L2, from 20 per cent to under 60 per cent; Group-L3, from 5 per cent to under 20 per cent; andGroup-L4, below 5 per cent. Likewise, countries are also grouped according to the speed of theircatch-up with the US: Group-C1, at 3 per cent per annum or above; Group-C2, from 1 per cent to under
3 per cent; Group-C3, from 0 per cent to under 1 per cent; and Group-C4, under 0 per cent. The speedof catch-up with the US is defined as the difference in the average annual growth rate of per capita
real GDP between each country and the US. Table 6 shows that many Asian countries (not belonging

31©2012 Asian Productivity Organization

year. However, this is not always
true. Low-income countries like Nepal, Bangladesh, the Philippines,
and Fiji have failed to catch up,
while Thailand and Malaysia could
be expected to have grown evenfaster given their initial income levels. The Asian Tigers have enjoyedrobust growth in the past four dec­ades, but Korea and the ROC, with
their lower initial per capita GDP,
have sustained higher growth rates
than Singapore and Hong Kong.
Mature economies like the US,
EU15, and Japan shared similar
growth experiences (i.e., around 2
per cent on average per year, in thepast four decades).

3 Production-Side GDP

to Group-C4) succeeded in closing the gap in per capita real GDP against the US over the last
four decades.
From Table 6 we can see that the initial economic level does not fully explain the catch-up process. Of
the Asia29 countries, five achieved very fast catch-up (i.e., over 3 per cent a year on average) between
the respective starting years of their data series and 2010. The per capita GDP level varies from GroupL2 (Singapore) to Group-L4 (Cambodia and China). Ten countries in Group-C4 experienced deterioration in their relative income level against the US. Low-income countries like Fiji and the Philippines
have failed to take off. The seven high-income countries in Group-C4 are all GCC countries except
Australia. However, it is worth noting that GCC countries had an exceptionally high GDP (which is
distortionary, as aforementioned) at the beginning of the period. Japan was the only Asian non-oilexporting country with a high income level in 1970. But, like EU15, Japan has since failed to achieve
further catch-up with the US.

3.3 Sources of Per Capita GDP Gap
To understand the diverse performance in the Asian group further, per capita GDP can be broken into
two components, namely labor productivity (defined here as real GDP per worker) and the corresponding labor utilization rate (i.e., number of workers to population ratio, or the employment rate inthis report).18 Figure 18 shows the percentage point differences in per capita GDP decomposed into
the contributions by the labor productivity gap and the employment rate gap relative to the US in
1995 and 2010.19 Most of the Asian countries display a huge per capita GDP gap with the US, predominantly explained by their relative labor productivity performance. Except for the four Asian Tigers, Japan, and Iran, all the other Asian countries had labor productivity gaps of more than 50 per
cent against the US in 2010. Hong Kong and Singapore had the smallest labor productivity gaps ofaround 7 per cent against the US. Allowing for a margin of error of ±10 per cent, these gaps are notstatistically significant. In contrast, the labor productivity gaps of the other two Asian Tigers are stillsizable against the US, at 21 per cent and 39 per cent for the ROC and Korea, respectively.

©2012 Asian Productivity Organization

Figure 19 focuses on explaining a country’s per capita GDP growth by its components: namely laborproductivity growth and the change in the employment rate for the periods 1995–2000 and 2000–
2010, respectively.20 For most countries in Asia, the majority of per capita GDP growth can be explainedby labor productivity, but this should not lead us to underestimate the role played by changes in theemployment rate. On average, Asia29’s per capita GDP grew by 2.9 per cent a year between 1995 and2000, and accelerated to 4.7 per cent a year between 2000 and 2010. The earlier period captured the18: Due to data constraints, labor utilization is measured as the number of workers relative to the population (termed the employment rate in this report), to ensure consistency with the definition of labor productivity (i.e., GDP per worker) that is measured in
all APO member economies, although it is frequently defined as hours worked per capita (OECD 2008). In Section 5.2, we provide
labor productivity measures based on hours worked for some selected countries. Also, in the computation of TFP in Section 5.3,
hours worked data are used.
19: The gap of country x’s per capita GDP relative to the US is decomposed into the sum of the gap of labor productivity and employment rate with respect to the US, as in:
In (GDPxt / POPxt–1) – In (GDPUSt / POPUSt–1) = In (GDPxt / EMPxt–1) – In (GDPUSt / EMPUSt–1) + In (EMPxt / POPxt–1) – In (EMPUSt / POPUSt–1)
Gap of per capita GDP

Gap of labor productivity

Gap of employment rate

where POPxt is population of country x in period t and EMPxt is the number of employment of country x in period t.
20: Country x’s per capita GDP is decomposed into the product of its labor productivity and employment rate, as in:
In (GDPxt / POPxt) = In (GDPxt / EMPxt) + In (EMPxt / POPxt)
where POPxt is population of country x in period t and EMPxt is the number of
Per capita GDP

Labor productivity

Employment rate

employment of country x in period t.

32

3.3 Sources of Per Capita GDP Gap%

MyanmarBangladesh
Cambodia
Nepal
Lao PDR
VietnamSouth Asia
India
Pakistan
China
Mongolia
Sri Lanka
Philippines
Indonesia
ASEAN
Asia23
Asia29Fiji
APO20
East Asia
ThailandIran
Malaysia
Korea
ROC
EU15
Australia
Japan
Hong Kong
Singapore

1995

3

20

4

4

0

3

7
5
−11
−12 −11−33 −14 −9 −23 −11
−6
−48

−20
−40

−97

−41
−56

−72

−85

−84−86−95−91−94−95−81−73−82−84 −85−86 −85−76 −75−90 −85−98−60−38−17 −7

−80
−100

−13
−2

−6
−2

−11−10
−2 −1

−22

−13

−19

−10 −7−13−13 −12−5 −4 −4

2010

%

Nepal
Bangladesh
MyanmarCambodia
Lao PDR
PakistanSouth Asia
Vietnam
India
Philippines
Mongolia
Indonesia
Fiji
Sri Lanka
ASEAN
APO20
Asia23
Asia29China
ThailandEast Asia
IranMalaysia
Korea
EU15
Japan
ROC
Australia
Hong Kong
Singaporedampening effect of the Asian financial crisis of the late 1990s.
Emerging from the crisis, both labor productivity growth and employment growth strengthened.
For most countries, labor productivity explains a larger share of percapita GDP growth than employment, but the employment rate
contribution relative to labor productivity was also highly significant in, for example, Pakistan (45per cent), Cambodia (36 per cent),
Thailand and Bangladesh (34 percent, respectively), and Iran (29per cent).

20
0
−20

4

9

2

7

1

9 11 9

3
−42
−58

7

5

−25 −32−21
−39

5 28
−7 −4

−3 −21−3−77−80 −86−80 −85−84
China’s improvement was the−40−87−85−83−90−80−89−93−91−86−95−89 −104−97
−100
−100
−28
−60
most impressive, achieving per−10−80capita GDP growth of 7.4 per cent−6
−10 −12−15 −7−6 −7 −80 0
−7−1−100 −2
and 9.4 per cent a year on averagein the two periods, respectively.
Employment rate
Labor productivity
Per capita GDP
Over 95 per cent of that growth
was consistently explained by imFigure 18 Labor Productivity and Employment Rate Gap
provement in labor productivity.
Relative to the US, 1995 and 201021
According to official statistics,___Decomposition of per capita GDP gap at constant market prices,
Myanmar achieved a similar perusing 2005 PPPs
formance to China in growth
Sources: Official national accounts in each country, including author adjustments.
terms, with per capita GDP growthof 7.3 per cent and 10.6 per cent a
year on average in the two periods. However, this growth was from a very low base; even in 2010,
Myanmar’s per capita GDP was only 24 per cent that of China (see Table 5). Like China, Myanmar’s per
capita GDP growth was predominantly explained by labor productivity, with its contribution increasing from 76 per cent in the period 1995–2000 to 94 per cent in 2000–2010. Japan had a deteriorating
employment rate in both periods. With an aging population (see Box 2), this pattern may well persist. To sustain per capita GDP growth, labor productivity growth will have to accelerate in order tocounteract the negative effect of its employment rate.

21: Readers should be cautioned about the reliability and quality of Myanmar’s official statistics, which have been questioned. Researchers have suggested that this is not consistent with other variables closely correlated with GDP, such as energy use. Nonofficial estimates put GDP growth at less than half of the official estimates. See ADB (2009) and Economist Intelligence Unit (2010).
Nonetheless, official statistics from Myanmar are presented in this report, as there is no comprehensive and transparent alternative
data source.

33©2012 Asian Productivity Organization

Most countries also have an employment rate short of the US level, substantially in the case of Iranand Pakistan, further reinforcing their poor productivity performances (Figure 18). It is no coincidence
that Iran and Pakistan are among the countries that have the lowest shares of female workers in
employment, at 18 per cent and 20 per cent, respectively (Figure 20). In contrast, a handful ofcountries – most notably Singapore, Cambodia, China, and Thailand – had higher employment rates
than the US, counteracting the negative impact of their productivity performances. In particular, the3 Production-Side GDP

8

0.2

1995–2000
1.7

6

0.5

4

1.4 0.6

7.1
5.6

2

4.7

3.4

©2012 Asian Productivity Organization

0.6

3.9 4.1 4.3

2.5

0.2

0.7

0.8
3.4 3.0 3.5 3.1

1.6

0

−0.1

0.3

2.3 2.6

0.3
3.7

2.6

1.2 0.6 0.9 1.5
1.4

2.0 1.7

1.0

−0.7

−0.1

0.1 0.5
0.1
0.4 1.3
2.5 2.1 1.7
1.9
0.4 1.0
1.2 0.6
0.8 0.3 1.4 1.0
0.6 0.6
−0.3
−0.6
−0.7
−0.5−1.4

−2

%

12
10

0.7

2000–2010

0.0

8
6
4
2

9.9 9.4 2.3 1.4
4.1 4.5

0.5 0.0
0.8 0.6
5.3 5.3

1.0

0.2 0.2
1.3 0.6 1.4

4.4 4.6 3.8 4.6 4.5

3.3 3.7

0.8 0.8

0.5
1.2

0.6 0.3

2.8 3.0 2.9 3.2 2.4 2.8 3.1

0

1.4
1.7

−2

Employment rate

0.7 0.6
0.5 0.7
2.7 1.9 2.0 1.0
0.1 1.0 1.7
0.5 0.8
1.2 1.1 0.7 0.7−0.0−0.3 −0.0−0.5−1.1

Labor productivity

Per capita GDP

Figure 19 Sources of Per Capita GDP Growth, 1995–2000
and 2000–2010___Decomposition of average annual growth rate of per capita GDP
at constant market prices, using 2005 PPPs
Sources: Official national accounts in each country, including author adjustments.

Figure 21 shows cross-country comparisons of employment rates in 2010, based on the labor statistics
of each country. Employment consists of employees,
own-account workers, and unpaid family workers.
Two countries – Cambodia and Singapore – lead the
Asian group with employment rates of 0.62 and 0.60,
which were 0.10–0.12 percentage points higher thanthe US and 0.12–0.14 percentage points higher thanEU15, respectively, in 2010. Two other economies
also had high employment rates – Thailand (0.58)
and Vietnam (0.57).
From Figure 21, it is clear that employment rates havebeen rising in Asia. Japan is the only exception where
the employment rate in 2010 was lower than that in1970. This reflects, among other things, its aging
population. The fastest catch-up countries (i.e., thosein Group C1) are also countries with the largest surge
in employment rates in the past four decades; they
are Singapore, China, Korea, and the ROC. Some of
the countries in Group C2 also experienced significant

34

0.1

GCC
Fiji
US
Japan
EU15
Australia
Nepal
Pakistan
APO20
Philippines
Malaysia
Singapore
Hong Kong
ROC
ThailandIndonesia
Korea
ASEAN
Bangladesh
Sri Lanka
Iran
Asia29Asia23
Mongolia
South Asia
Lao PDR
East Asia
India
Vietnam
Cambodia
China
Myanmar

Other things being equal, increasing employment and improving labor productivity could present a
policy trade-off in the short term
(i.e., they cannot be achieved simultaneously). If the policy target
is to increase employment, productivity may suffer in the short term
as marginal and less-productive
workers are recruited, bringing
down the average productivity performance. The huge labor productivity gap between Asia and the US
discussed in Chapter 5 should
therefore be considered in the context of the generally high employment rate in Asia.

%

Indonesia
ThailandJapan
Hong Kong
ASEAN
Fiji
Philippines
APO20
GCC
Pakistan
Malaysia
Mongolia
Iran
Nepal
Australia
EU15
Asia29Singapore
Asia23
US
East Asia
Lao PDRSouth Asia
India
Sri Lanka
Korea
ROC
Bangladesh
Cambodia
Vietnam
MyanmarChina

positive gap in employment rate
plays a significant role in nudging
Singapore ahead of the US in percapita GDP. More specifically, Singapore’s labor productivity was 7
percentage points short of the US
level, but its employment rate was
30 percentage points higher, giving
an overall per capita GDP 23 percent higher than the US.

Cambodia (2008)
Lao PDR (2005)
Vietnam (2010)
Mongolia (2010)
Hong Kong (2010)
US (2008)
Nepal (2008)
Thailand (2011)
China (2000)
Australia (2008)
ROC (2008)
Singapore (2008)
Korea (2010)
Japan (2008)
Philippines (2008)
Indonesia (2008)
Malaysia (2008)
Sri Lanka (2009)
Fiji (2007)
India (2000)
Kuwait (2005)
Bangladesh (2005)
Bahrain (2001)
Pakistan (2008)
Iran (2007)
Oman (2000)
Saudi Arabia (2008)
Qatar (2008)

51
50
49
47
47
47
46
46
45
45
43
43
42
42
39
38
36
35
32
29
25
24
21
20
18
14
14
11

0

10

20

30

40

50 %

Figure 20 Share of Female Employment___Ratio of female to total employment

Sources: Population census or labor survey in each country.

3.3 Sources of Per Capita GDP Gap

improvements in employment rates: for example, Indonesia and Vietnam. Countries
that have failed to catch up also tend to
make less vigorous improvements over theperiod, and in turn continue to have lower
employment rates. Fiji is the only exception,
where the employment rate has improved
significantly, but this was from a very low
base.

%

65
60

3

55
50
45
40
35
30
25
2010

1990

1970

20
Cambodia
Singapore
Thailand
Vietnam
China
MyanmarLao PDR
Australia
Japan
Hong Kong
Korea
US
Indonesia
EU15
ROC
Nepal
India
Malaysia
Philippines
Mongolia
Bangladesh
Fiji
Sri Lanka
Pakistan
Iran

Figure 21 Employment Rates, 1970, 1990, and2010___Ratio of employment to total population

Sources: Employment and population data by NSO in each country.

Box 2

Populations of Asian Countries

The world’s fertility rate is converging to the replacement level – the level at which a country’s population
stabilizes. According to the United Nations, the number of children a woman is expected to have in her
reproductive years dropped by more than half, from about 6.0 to 2.5 in the last 60 years, compared to thereplacement level of 2.1 children, one of them a girl. There is regional divergence in this trend: in the last 60
years, the total fertility rate dropped from about 6.7 children to 2.6 in Central America, and from about
6 children to 1.6 (i.e., below the replacement level) in East Asia. In comparison, some parts of Africa have
only seen a modest drop in total fertility, which today remains at more than 5 children per woman. What iseven more staggering is the pace of change. For example, it took Britain over 130 years (1800–1930) tohalve its fertility rate, while it took Korea only 20 years to achieve it. This is echoed all around the world.
This widespread social revolution is brought on by a complex mix of economic and social development.
Economic growth, greater access by women to education, income-earning opportunities, and sexual andreproductive health services are all contributing factors to this trend. Coupled with changes in the mortality rate, this can dramatically change the age profile of a country’s population, and with it comes the
economic implications.
continued on next page >35©2012 Asian Productivity Organization

According to the United Nations (2011), the world’s population is estimated to reach 6.9 billion in 2010, of
which Asian countries account for 60.4 per cent. The region is by far the most populous in the world. China
and India account for 19.5 per cent and 17.8 per cent of the world’s population, respectively. It has been
observed that falling fertility rates and rising living standards go hand in hand, although the direction of
causality is less certain. The evolution of the demographic structure implies dynamics in a society that are
not captured by the overall population size or growth. As people’s economic behavior, aspirations, andneeds vary at different stages of life, changes in a country’s age structure can have a significant impact on
its economic performance.

3 Production-Side GDP> continued from previous page

Billion

10
8

BillionLeast developed countries
Less developed regions, excluding
least developed countries
More developed regions

10
8

6

6

4

4

2

2

0

1950

1975

2000

2025

2050

2075

2100

0

Oceania
Northern America
Latin America and the Caribbean
EuropeAfricaOther Asia
ASEAN
China
India

1950

1975

2000

2025

2050

2075

2100

Figure B2.1 Distribution of the World’s Population in Different Regions, 1950–2100
Source: United Nations (Department of Economic and Social Affairs), World Population Prospects: The 2010 Revision (28 June 2011).

1970

2050

1400
1200
1000
800
600
400
350
300
250
200

scale by 50 millions

150
100
50
30
25
20
15
10
5
0

scale by 5 millions©2012 Asian Productivity Organization2010

scale by 200 millions

Million
1600

BruneiFiji
Bahrein
Qatar
Mongolia
Oman
KuwaitSingapore
Lao PDR
Hong Kong
UAE
Cambodia
Sri Lanka
Australia
ROC
Saudi Arabia
Nepal
Malaysia
Korea
MyanmarThailand
IranVietnamPhilippines
Japan
Bangladesh
PakistanIndonesia
US
EU15
India
China

The growth rate of the world’s population has slowed from its peak ofaround 2.0 per cent in the 1970s totoday’s 1.1 per cent a year. With thefalling fertility rate, the UN projects
that the world’s population growthrate will decelerate to 0.40 per centa year by 2050 and further to 0.05
per cent by 2100. Even so, the world
population will still increase by onethird in the next 40 years, from 6.9
billion to 9.3 billion and a further 8
per cent to 10.1 billion by 2100.
These estimates are based on themedium-fertility variant, but with
only a small variation in fertility,
particularly in the more populous
countries, the total could be higher(10.6 billion by 2050 and 15 billion
in 2100) or lower (8.1 billion in 2050
and 6.2 billion in 2100).

Much of this increase is expected tocome from the high-fertility countries, which comprise 39 out of the
Figure B2.2 Asian Countries’ Population Size and55 countries in Africa, nine in Asia,
Projection, 1970, 2010, and 2050
six in Oceania, and four in Latin
America. In contrast, low-fertility
Source: 1970 and 2010: Population census and official national accounts in eachcountries include all countries incountry and World Bank, World Development Indicators (28 July 2011).
2050: World Bank, Population Projection tables by country and Group 2011.
Europe except Iceland and Ireland,
19 out of the 51 in Asia, 14 out of
the 39 in the Americas, two in Africa(Mauritius and Tunisia), and one in Oceania (Australia). Figure B2.1 depicts this shift in the distribution of
the world population with the more developed regions’ share gradually declining from 17.9 per cent to14.1 per cent in 2050 and 13.2 per cent in 2100, compared with 32.1 per cent in 1950, whereas the share of
the least developed countries rising from today’s 12.1 per cent to 18.6 per cent in 2050 and 26.6 per cent in
2100, up from 7.9 per cent in 1950. Turner (2009) highlights the challenge of the continued rapid population growth to economic and social progress in many countries in Africa and the Middle East, and its major
and adverse impact on the global environment.
continued on next page >36

3.3 Sources of Per Capita GDP Gap> continued from previous page

Figure B2.3 shows the demographic
make-up of countries in 2010 (i.e.,
the population proportions of theunder-15 and over-65 age groups,
which together make up the dependent population). Ranking thecountries by the share of old-age
population filters the rich economies to the top end; these economies also have a relatively low shareof the young age group comparedto less developed countries. Thissuggests that demographic transition tends to go in parallel witheconomic progress, although thedirection of causation is not certain.

Japan
EU27
Australia
US
Hong Kong
Korea
ROC
Singapore
ThailandChina
Sri Lanka
VietnamIndonesia
Iran
Myanmar
India
Fiji
Malaysia
Cambodia
Bangladesh
Philippines
Pakistan
Nepal
Mongolia
Lao PDR
Brunei
Saudi Arabia
Oman
KuwaitBahrain
Qatar
UAE

13.1
15.6
18.9
19.8
12.1
16.2
15.6
17.4
20.5
16.6
26.3
23.6
27.0
22.9
25.6
30.6
29.0
27.2
33.0
31.3
34.0
35.4
35.6
27.4
34.5
26.2
30.3
27.2
26.7
20.0
13.5
17.0

40 %

30

20

10

0

Ages 0–14

23.0
17.4
13.5
13.1
12.9
11.0
10.7
9.0
8.9
8.9
6.3
6.0
6.0
5.2
5.1
4.9
4.8
4.7
4.7
4.6
4.4
4.3
4.2
4.0
3.9
3.6
3.0
2.5
2.5
2.1
1.0
0.4

0

5

3

10

15

20

25 %

Ages over 65

Figure B2.3 Population Proportion of the Dependent
Population, 2010
Sources: Population census and official national accounts in each country.

Dependent population (aged under 14 and over 65)=1

3.0
2.5
2.0

Hong Kong
Japan
Korea
Singapore
US

1.5
1.0
1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
Dependent population (aged under 14 and over 65)=1

3.0
2.5

China
India
Indonesia
ThailandAustralia

As countries move from high to low
2.0
mortality and fertility rates, the de1.5
mographic transition produces a“boom” generation that is larger
1.0
1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
than those immediately before andafter it. As this boom generation
gradually works through a nation’s
Figure B2.4 Demographic Dividend, 1950–2100
age structure, it produces a demographic dividend of economic
Source: United Nations (Department of Economic and Social Affairs), World Population Prospects: The 2010 Revision.
growth as people reach their prime.
The improved ratio of productive workers to child dependents
and the increase in available resources for investment open a special window for faster economic growthand human development. It has been suggested that the demographic dividend accounted for a third of
East Asian growth in 1965–1990 (Bloom, Canning, and Malaney 2000).

continued on next page >37©2012 Asian Productivity Organization

Asia’s share will decline from today’s
60.4 per cent to 55.3 per cent in
2050 and 45.4 per cent in 2100,
while Africa’s share will rise from today’s 14.8 per cent to 23.6 per centand 35.3 per cent, respectively.
Figure B2.2 shows the current population size of individual Asian
countries compared with the 1970
level and projection in 2050. As canbe seen from the chart, China’s population is expected to more or lessstabilize around the current level.
China has socially engineered thechange with its one-child policy,
which has made its current population 300–400 million lower than it
would have been otherwise. In lessthan a decade, India is projected toovertake China as the most populous country in the world, and China’s population will drop to under 1billion by 2088.

3 Production-Side GDP> continued from previous page

Although China has a smaller dependent ratio than India, its population is aging rapidly. India, on theother hand, has one of the most favorable demographics in waiting. This demographic dividend can work
wonders to produce virtuous cycles of wealth creation if it is combined with appropriate health, labor, financial, human capital, and growth-enhancing economic policies. If India is able to capitalize on this dividend, it may well overtake China in economic growth in the not-so-distant future. However, the experienceof East Asia suggests that this dividend is far from being automatic but needs to be earned. This one-off
opportunity will pass in a couple of generations, and it will be regrettable if it is missed.
Using past demographic data since 1950 and UN projections up to 2100, we can track the changes in theratio of working population (aged 15–64) to dependent population (aged under 14 and over 65) over time
(Figure B2.4). Where the curve bulks in Figure B2.4, it is when the demography was/will be the most favorable for economic growth. Japan could have received the demographic dividend in the 1960s when its
GDP growth was over 10 per cent on average per year for ten years. In the 2000s and 2010s, China, Hong
Kong, Korea, Singapore, and Thailand have been in the period in which they can reap the demographic
dividend. Based on the projections, Indonesia will have such a privilege in the 2020s and 2030s, and India
in the 2040s.

Box 3

The System of National Accounts 2008

In the past two decades, the economic structure in many countries has been changing at an unprecedented rate, owing to the advances in information and communication technology (ICT). The rapid andwidespread dissemination of the technology has been enabled by the sharp decline in its prices, and the
deep financial markets that can afford funding for innovation to take off. Its penetration of the fabric ofsociety has changed our behavior, revolutionized the way we organize economic activities, extended markets and product ranges, given birth to an array of new industries, and transformed the service industries.
Its far-reaching effects on economies have given rise to new analytical and data needs, and have posed
numerous new challenges to statisticians who aim to track economic activities and measure economic
performance.
To catch up with time, the changes in the 2008 SNA bring the framework of national accounts into line withthe latest economic landscape, advances in methodological research, and needs of users. It introduces
treatments for new aspects of economies that have come into prominence, elaborates on aspects thathave increasingly become the focus of analytical attention, and clarifies guidance on a wide range of issues(SNA 2008, Annex 3). In the interest of a smooth transition from implementation of the earlier versions of
the SNA, fundamental and comprehensive changes have been ruled out. Highlighted below are some key
revisions to the 1993 SNA that strengthen its relevance for the 21st century by improving its coverage andadequately taking into account quality changes.

©2012 Asian Productivity Organization

Improved measurement of the service sector
1. The 2008 SNA adopts the International Standard of Industrial Classification of all Economic Activities
Revision 4 (ISIC Rev. 4), which is a hierarchical, four-level structure of mutually exclusive categories tofacilitate data collection, presentation, and analysis of economic activities in an internationally comparable, standardized way. In the revision effort, continuity was carefully balanced with the need for relevance of ISIC and its comparability with other existing industry classifications. The relative emphasisthat the previous ISIC put on manufacturing at the expense of detail on services was becoming increasingly misaligned with the growing weight of services in most economies of the world and thegrowing attention on the ICT sector. In response, the detail of the classification in ISIC Rev. 4 has been
substantially increased. For service-producing activities, this increase is visible at all levels, including
the top level, while for other activities, such as agriculture, the increase in detail has affected mostly thelower levels of the classification. For example, there is a new industry section for Information and Communication (Section J) and Business Activities has been separated from Real Estates, and classified into
continued on next page >38

3.3 Sources of Per Capita GDP Gap> continued from previous page

Professional, Scientific and Technical Activities (Section M) and, Administrative and Support Service
Activities (Section N). Furthermore, the details of manufacturing have been expanded and the information economy can now be more readily identified for analytical purposes.
2. The 2008 SNA recommends that a producer unit undertaking ancillary activities be recognized as aseparate establishment if it is statistically observable (i.e., with separate accounts for production or ina different geographical location from the establishments). This contrasts its treatment in the 1993 SNA
whereby it is always regarded as an integral part of the establishments it served. This change mainly
affects large establishments that engage in a large diversity of production, and will give rise to morehomogeneous institutional units. As the SNA defines industries in terms of establishments, this amendment will lead to a clearer demarcation of industries, and in turn facilitate analyses of production.

3

3. The 2008 SNA provides a comprehensive overview of financial services to reflect developments in oneof the fastest-changing segments of many economies. The definition of financial services has beenenlarged beyond the financial intermediation to capture financial risk management and liquidity
transformation, by expanding the financial asset boundary and introducing some new functionalclassifications. Further, the method for calculating financial intermediation services indirectly measured (FISIM) has been refined and the option not to allocate FISIM among different users has been
removed. Output of the central bank is classified into three broad groups: financial intermediation,monetary policy services, and supervisory services overseeing financial corporations. Output is further
distinguished between market and non-market services, with their different measurements.

Capitalizing the knowledge economy
4. The 2008 SNA renames the asset type previously called “intangible produced assets” as “intellectual
property products” to reflect that many of these assets are associated with the establishment of property rights over knowledge in one form or another. For the first time, its asset boundary is extended
to include research and development (R&D), which was treated as intermediate consumption in the1993 SNA. With the inclusion of R&D in the asset boundary, patented entities no longer appear separately but are subsumed into R&D assets. The 2008 SNA recommends that all databases with a usefullife of more than one year should be included in the modified asset category of “computer softwareand databases”.
5. The fixed asset boundary has also been expanded to include, under the heading of weapons systems,
all military expenditure that meets the same criteria as for other fixed assets, regardless of the natureof the expenditure or the purpose intended for it. Under machinery and equipment, a new category
called ICT equipment has been introduced to facilitate analysis of the information economy.

Globalization
6. The 2008 SNA makes the application of the principle of change in ownership of goods universal, affecting the recording of goods sent for processing, both abroad and within the domestic economy, andthen returned to the owner. This is to recognize that a lot of physical movements of goods do not incur
actual transactions, and in turn their corresponding financial flows, as there is no change in ownership.
In these situations, only processing services will be recorded.
7. The 2008 SNA recommends the same principle to be applied to merchanting, which concerns activities
as global manufacturing, global wholesaling, and retailing and commodity dealing (i.e., part of the
production process in an increasingly globalized and inter-connected world). The case is the reverse
one to that of goods for processing: there is a change of ownership, and consequences for financial
flows, without the goods entering the merchant’s economy. The 2008 SNA recommends that goods soacquired should be recorded as negative exports on acquisition and positive exports on disposal.

8. The 2008 SNA recommends that estimates of capital services be compiled in a supplementary table,
which will greatly facilitate, among other things, productivity analysis.
continued on next page >39©2012 Asian Productivity Organization

For productivity analysis

3 Production-Side GDP> continued from previous page

9. The 2008 SNA recommends chain-linking for volume and price indices to minimize substitution bias.
Further, the chapter concerning prices and volumes has been significantly updated to reflect the latest
methodological developments in the area, including the measurement of changes in quality over time.
As quality change is an increasing feature of product markets, appropriate quality adjustment procedures have become all the more important in accurately measuring volume changes. For compilingvolume indices of non-market services, prices of which are not available, the 2008 SNA recommends
the direct “output volume method,” where possible, based on quantity indicators, adequately qualityadjusted, and weighted together using average cost weights.
10. Employee stock options have become a common tool used by companies to motivate their employees.
Addressing its omission from national accounts, the 2008 SNA recommends that transactions in employee stock options be recorded in the financial account as the counterpart to the element of compensation of employees represented by the value of the stock option. Ideally, the value of the option
should be spread over the period between the grant date and vesting date; if this is not possible, they
may be recorded at the vesting date. This will help correct the potential downward bias to the contribution of labor to output growth in growth accounting, whereby the labor share of total income isused as weight.

Recording pension entitlements
11. The 2008 SNA recommends changes in recording pension entitlements in case of a defined benefit
plan, for which the treatment in the 1993 SNA proved to be unsatisfactory. As many countries arefacing aging populations, it is increasingly important to have a measurement that accurately reflects
pension liabilities. Previously, the actual social contributions by employer and employee in a period
were the amount actually paid into a pension fund. While this is correct and complete for a defined
contribution scheme, there is no guarantee that the amounts set aside will exactly match the liabilityof the employer to the employee for a defined benefit plan. For the latter, therefore, it is recommended
that the level of the employer’s contribution be recorded as the increase in the net present value of thepension entitlement (determined actuarially) the employee has earned in the period in question, adding any cost charged by the pension fund for operating the scheme and deducting the amount of any
contribution the employee makes.

©2012 Asian Productivity Organization

12. For pensions provided by the government via social security, however, countries have some flexibility
to deviate from this procedure in the set of standard tables, because of the vast diversity of funding
arrangements across countries. However, the 2008 SNA recommends that the full range of information
required for a comprehensive analysis of pensions be provided in a supplementary table that shows
the liabilities and associated flows of all private and government pension schemes, whether funded or
unfunded and including social security.

404.1 Composition of Final Demand

4 Expenditure-Side GDP
In national accounts, GDP is measured by three approaches: production (i.e., by industry or products),
expenditure on final demand, and income to factor inputs. In theory, these three approaches are accounting identities, but in reality, they differ by statistical discrepancies.22 Decompositions of GDP arevaluable in understanding the structure, and in turn the behavior, of an economy. In this chapter, we
look at countries’ economic composition from the expenditure side. We investigate the decomposition of output growth into input growth and total factor productivity growth (the supply side) in
Chapter 5, while countries’ industry structure is presented and analyzed in Chapter 6.

4

4.1 Composition of Final Demand
From Table 7, we can see that country groups display distinctive features in their final demand composition, reflecting their development stage and economic makeup. With the differences in emphasis
and vulnerabilities, their behavior and reaction to economic shocks can be expected to be quite diverse. Table 7 presents comparisons of final demand shares of nominal GDP, covering: (1) household
consumption (including consumption of non-profit institutions serving households: NPISHs), (2) government consumption, (3) investment (or, in national accounts terminology, gross fixed capital formation (GFCF) plus changes in inventories), and (4) net exports (i.e., exports minus imports).
For most countries, household consumption is by far the biggest component of GDP.23 The GCC
countries, Brunei, and China are the exceptions. Over the past four decades, the share of household
consumption for mature economies tends to be rather stable and trending upward in recent years,
while it is more volatile and largely trending downward in economies undergoing rapid transformation, such as the Asian Tigers in the 1970s and 1980s, and India and China currently.
Table 7 Final Demand Shares in GDP, 1970, 1980, 1990, 2000, and 2010___Share of final demands with respect to GDP at current market prices

APO20

Household consumption
Government consumption
Investment
Net exports
1970 1980 1990 2000 2010 1970 1980 1990 2000 2010 1970 1980 1990 2000 2010 1970 1980 1990 2000 2010
51.9 56.2 54.9 58.5 58.2 10.8 13.7 12.8 13.9 13.0 36.5 31.6 31.8 25.2 28.2
0.9 −1.4
0.6
2.4
0.6

Asia23

52.2

55.8

54.1

55.6

49.3

10.8

13.7

13.0

14.4

13.1

36.2

31.8

32.2

27.6

35.7

0.8

−1.4

0.8

2.4

1.9

Asia29

51.8

52.5

53.8

55.0

48.9

10.9

13.7

13.6

14.6

13.2

35.8

30.6

31.3

27.2

35.1

1.5

3.2

1.3

3.2

2.7

East Asia

50.3

54.5

52.3

53.1

42.9

10.9

14.1

13.4

15.6

14.7

37.8

32.5

32.9

29.2

39.1

1.1

−1.1

1.4

2.0

3.4

South Asia

76.3

76.0

67.9

66.2

62.2

8.6

9.2

11.2

11.9

11.0

15.4

19.2

23.4

23.3

30.8

−0.3

−4.4

−2.5

−1.5

−4.0

ASEAN

65.3

58.4

56.1

56.7

57.1

13.3

12.4

10.5

10.0

10.2

26.3

31.7

34.8

24.1

28.2

−4.9

−2.5

−1.4

9.2

4.5

GCC

36.1

29.8

49.9

42.9

40.1

13.9

13.4

24.6

19.7

16.4

19.5

22.4

16.0

18.2

25.3

30.5

34.5

9.5

19.1

18.2

China

55.6

50.2

47.0

46.7

34.9

11.2

14.9

14.1

15.8

13.4

33.1

35.2

36.1

35.1

47.8

0.1

−0.3

2.7

2.4

3.9

India

75.0

74.2

64.8

63.8

58.0

9.4

10.1

12.0

12.9

11.7

15.7

18.7

24.6

24.2

33.6

−0.1

−3.0

−1.4

−0.9

−3.3
1.2

Japan

49.3

54.6

53.0

56.4

59.1

10.7

14.1

13.3

16.9

19.7

38.8

32.3

32.8

25.3

20.0

1.2

−0.9

0.9

1.4

Australia

54.7

55.9

58.4

59.5

54.5

13.9

17.7

18.1

17.7

18.0

31.7

28.3

23.7

22.6

25.9

−0.3

−1.9

−0.2

0.2

1.5

US

62.4

63.0

66.1

68.6

70.5

18.3

16.7

16.7

14.3

17.2

18.9

20.8

18.6

20.9

15.8

0.4

−0.5

−1.3

−3.8

−3.6

EU15

58.1

58.3

58.2

58.8

58.3

16.3

20.1

20.0

19.7

22.3

26.0

24.0

22.6

21.2

18.6

−0.5

−2.4

−0.8

0.3

0.8

22: Countries follow an international framework, called the System of National Accounts (SNA), in compiling their national accounts.
As economies keep evolving, the SNA is revised periodically so it does not lose its relevance to economic realities and compromise on the accuracy of GDP measurement. The latest international effort resulted in the 2008 SNA, which improves on the 1993
SNA. For further details, see Box 3.

41©2012 Asian Productivity Organization

Unit: Percentage.
Sources: Official national accounts in each country, including author adjustments.
Note: Final demand shares in country groups are computed by using the PPPs for GDP. Household consumption includes consumption of
NPISHs. Investment includes gross fixed capital formation plus changes in inventories.

4 Expenditure-Side GDP

China’s household consumption as a share of GDP has been trending downward. It fell from 55.6 percent in 1970 to 46.7 per cent in 2000. This compares with the early Communist era, when household
consumption was more volatile and at a higher level of over 60 per cent of GDP (Figure 22); China wasmuch less well off then. Figure 22 shows how household consumption share and investment sharemirror each other. As the decline in household consumption share accelerated in the 2000s, plummeting to 34.9 per cent in 2010, we see the investment share rising rapidly to 47.8 per cent of GDP. We also
observe a rapid rise in exports as a share of GDP since the 1980s when China began to open its economy, from around 5.0 per cent or below in the 1950s and 1960s to its peak of 37.0 per cent in 2006
before softening to 24.0 per cent in 2010.
With a low consumption ratio, coupled with an unsustainable rise in investment and an overdependence on exports, China faces huge internal and external imbalances, which if not addressed could
jeopardize its medium-term growth prospects. A low consumption share of GDP is not merely a reflection of consumer behavior or preference, but a manifestation of an array of underlying distortions in
the economy. For example, an undervalued currency and a wide range of factor price distortions,which favor the production of tradables over non-tradables, result in an unusually low consumption
ratio and encourage a heavy reliance on exports. Lax corporate governance of state-owned enterprises is not conducive to distribution of dividends and in turn works to subsidize investment in effect.
The absence of a social safety net and well-developed domestic financial markets provides a strong
incentive for precautionary saving on the part of households (Eichengreen, Park, and Shin 2011). Thissuggests that policy levers are available to the government to rebalance the economy.
In recent years, even labor-abundant China faces a tightened supply of surplus labor on the coasts,
which is building an upward pressure on wages. This could be good news for the world, as a higher
labor share of GDP will enable higher household consumption that will help the domestic market
fulfill its potential. This will make China less dependent on foreign demand on the one hand and generate demand for foreign products on the other. Signs that the Chinese economy may have started
moving in the right direction are when the decline in the consumption ratio halted and external imbalance narrowed to less than 2.8 per cent in 2011 – the lowest since 2002.24 Only time will tell if thisis a blip or the start of a more persistent trend that reflects changes in the underlying economy.
India, another fast-emerging economy, has seen its household consumption share declining rapidly
in the past four decades, from 75.0 per cent in 1970 to 58.0 per cent in 2010 (Table 7). In contrast, theshare of household consumption was relatively stable in the US at around 62–63 per cent for the
1970s and 1980s before edging up to 70.5 per cent of GDP in 2010. From a historical perspective, thecurrent level is below that experienced during the Great Depression in the US when the consumption
share was over 75 per cent and even as high as 83 per cent in 1932, and above the all-time low of under 50 per cent in 1944 during World War II (Figure 23).

©2012 Asian Productivity Organization

The share of household consumption in EU15, which is around 58 per cent, has stayed fairly stable
over the past four decades. The Asian average has been hovering in the lower 50 per cent range until
recently when the gap with EU15 widened, largely reflecting the trend in China (Table 7). Australia’s

23: Based on our metadata survey on national accounts in Asian countries, Japan is an exceptional country that estimates GDP
from the expenditure side. In other countries, GDP is estimated from the production side (value added in industries), and somecountries record statistical discrepancy as the difference in the estimates between production-based GDP and the sum of final
expenditures. In this Databook, statistical discrepancy is mainly attributed to household consumption when data are recorded.
Readers should keep in mind that it can have some impacts on the share of final demand: e.g., it accounts for 2.5 per cent of GDP
in 1990 in the Thailand SNA published as of the end of 2011.
24: The Economist, 18 February 2012, “The incredible shrinking surplus.”424.1 Composition of Final Demand%

70

Household Consumption
consumption

60
50
40

4

Investment

30

Exports

20
Imports (−)

10
0
1952

1962

1972

1982

1992

2002

Figure 22 Final Demand Shares in GDP of China, 1952–2010___Share of final demands with respect to GDP at current market prices

Sources: National accounts by National Bureau Statistics of China, including author
interpolation.

%

80
70

Household Consumption
consumption

60

50Overall, Asian countries invest sig40
nificantly more than the US and
EU15. Historically, the wedge in
30
Investment
the investment share of GDP be20
tween Asia29 and EU15 never exImports (−)
10ceeded 10 percentage points, but
Exports0
since 2000, it has started to wid1929
1939
1949
1959
1969
1979
1989
1999
2009
en. In 2010, the wedge was over
17 percentage points. In the
Figure 23 Final Demand Shares in GDP of the US, 1929–
1970s, EU15 was investing 5 per2010
cent more of their GDP than the___Share of final demands with respect to GDP at current market prices
US. Thereafter, the EU15 investSources: National accounts by Bureau of Economic Analysis, US.
ment share converged to the US
level and they were out of synchwith each other temporarily in thelate 1980s and early 1990s. For the past five years, a divergence has opened with the US investment
share of GDP declining faster than that of EU15 (Figure 30.3). In 2010, investment accounted for 15.8
per cent and 18.6 per cent of final demand in the US and EU15, respectively, compared with 35.7 percent for Asia23. Recently, Australia’s investment level has been closer to the level of APO20 than thatof the US/EU15 and in 2010 it accounted for over a quarter of final demand. The share of investment
in China is the biggest final demand component of GDP since 2004 and, at 47.8 per cent in 2010, it isprobably unsustainable in the long term. East Asia has the highest investment ratio among the Asian
regions, but South Asia is catching up fast while the investment intensity has never recovered in
ASEAN since the Asian financial crisis of the late 1990s.

43©2012 Asian Productivity Organization

consumption ratio has never exceeded 60 per cent of GDP and
has dipped significantly in thepast decade to 53.6 per cent,reflecting a pickup in the investment share and the strong positive contribution made by net
exports. Within Asia, all regions
display a decline in household
consumption ratio, except for the
GCC countries. South Asia maintains the highest share among all,even with it falling from 76.3 percent in 1970 to 62.2 per cent in2010. In contrast, GCC economies
are unusually skewed toward net
exports because of their oil. However, mirroring the declining contribution of net exports to final
demand over time, the consumption ratio of GCC countries has
risen from 36.1 per cent in 1970 to
40.1 per cent in 2010.

4 Expenditure-Side GDP

Net exports are gaining weight in Asia29, rising from 0.8 per cent of GDP in 1990 to 1.9 per cent in2010. China explained most of the strengthening between 2000 and 2010, with a net export share of
3.9 per cent in 2010, up from 2.4 per cent in 2000. This compares with the oil-exporting GCC countries’
18.2 per cent in 2010. Including the GCC countries, the contribution of net exports to the GDP of
Asia29 was 2.7 per cent in 2010, compared with 1.5 per cent in 1970 when net exports accounted formore than a third of final demand in GCC countries. In contrast, the deficit between exports and imports has considerably expanded in the US, from 0.5 per cent of GDP in 1980 to nearly 4 per cent in
the mid-2000s before narrowing to 3.6 per cent in 2010. South Asia is the only Asian region that consistently runs a trade deficit with fluctuating sizes over the years. Lately, it has become quite sizable at
4.0 per cent of GDP in 2010. In EU15, net exports have turned into a positive component in the past
two decades, but have shrunk to 0.8 per cent in 2010 from its recent peak.
The regional averages disguise the great variation displayed by individual countries. Figure 24 shows
the cross-country comparisons of final demand shares in current-price GDP in 1995 and 2010; countries are arranged in descending order of their household consumption shares. Although most countries fall to the right of the US, there are a handful of Asian countries that have a higher consumption
ratios than the US. Bangladesh, Cambodia, Nepal, Pakistan, Myanmar, and the Philippines fell to theleft of the US in both years of comparison, and a deficit in net exports tends to be associated with highhousehold consumption. Countries with a low income will struggle to defer consumption. It is no
coincidence that Bangladesh, Cambodia, Myanmar, and Nepal25 have been in the bottom income
1995

%

125
100
75
50
25
0

Qatar
BruneiSingapore
China
KuwaitOman
Saudi Arabia
Malaysia
GCC
East Asia
Korea
ThailandAsia29Asia23Bahrain
ASEAN
Japan
Indonesia
APO20
ROC
EU15
Australia
Fiji
Hong Kong
Iran
UAE
India
Mongolia
South Asia
US
Sri Lanka
Pakistan
Philippines
Vietnam
Myanmar
Nepal
Bangladesh
Cambodia

−25

2010

%

125
100
75
50
25
0

Qatar
Brunei
KuwaitOman
China
Saudi Arabia
Bahrain
Singapore
GCC
East Asia
Malaysia
Asia29Iran
Asia23
Korea
ThailandMongolia
Australia
Indonesia
ASEAN
India
ROC
APO20
EU15
Japan
UAE
South Asia
Hong Kong
Vietnam
Sri Lanka
US
Philippines
MyanmarFiji
Bangladesh
Cambodia
Pakistan
Nepal

−25

©2012 Asian Productivity Organization

Household consumption

Government consumption

Investment

Net exports

Figure 24 Final Demand Shares in GDP, 1995 and 2010___Share of final demands with respect to GDP at current market prices
Sources: Official national accounts in each country, including author adjustments.
Note: Household consumption includes consumption of NPISHs. For Myanmar, however, household consumption includes government consumption due to data limitations. Investment includes gross fixed capital formation plus changes in inventories.

44

4.1 Composition of Final Demand

group among the countries studied inthis report (see Table 14). Besides, countries with a high proportion of dependent population also tend to have ahigh household consumption share in
their GDP (see Figure 25).

Household consumption share in GDP%

90
Cambodia80

Nepal
PakistanFiji
Bangladesh

Myanmar70

US

4

Philippines

Hong Kong

Sri Lanka
VietnamJapan
Indonesia
ROC
India
Thailand Australia
Mongolia
Korea
Iran
Malaysia

60
UAE
At the other end, GCC and other oilexporting countries tend to cluster at50
the low end of household consumption
share of GDP in both years of compariSingapore
40son. The average household consumpOman Saudi Arabia
Bahrain China
tion share for GCC countries has been
Kuwait30
squeezed by net exports (which in turnare dominated by erratic oil revenues),
Brunei20
Qatar
from 50.3 per cent in 1995 to 40.1 percent in 2010.26 Given that a large part10of GCC countries’ GDP is not sustain10
15
20
25
30
35
40
45 %
Dependent population ratio
able income, it may be in fact prudent
for oil-exporting countries not to overFigure 25 Ratio of Dependent Population and Conconsume beyond their sustainable level
sumption Share in GDP at Current Prices, 2010
but purposefully invest much to generSources: Population data by NSO in each country; World Bank, World Developate a steady income stream for the evenment Indicators (28 July 2011); official national accounts in each country withauthor estimates.
tuality of oil depletion, no matter how
distant this may now seem. Among thenon-oil-exporting Asian countries, Singapore had the smallest household consumption share, butsince 2002 China has replaced Singapore in that position, with a share of 34.9 per cent in 2010.

Net exports carry a particularly large weight in a handful of economies: in 2010 it was 28.4 per cent in
Singapore, 17.8 per cent in Malaysia, and 5.4 per cent in Hong Kong, reflecting their entrepôt functionin Asia. This explains why the total values of exports and imports are exceptionally high relative to thesize of GDP in these economies (Figure 26). Once the 2008 SNA is implemented, these values will be
adjusted to reflect only a change in the ownership of goods rather than goods moved for processing
without incurring actual transactions (see Box 3).

25: The Lao PDR is also in the bottom income group; it is, however, omitted from Figure 24 because of a lack of final demand data.
26: It should also be noted that the shares are calculated in current market prices. Revenues from oil exports are notoriously erratic.
It is possible that a sudden surge in export revenues relative to imports can squeeze the shares of other components of final demand without real change in the underlying behavior in the economies. For example, Qatar has the smallest share of household
consumption, which shrank from 32.9 per cent in 1995 to 18.9 per cent in 2010, while over the same period, net exports swungfrom 1.0 per cent to 26.1 per cent. Similarly, net exports for GCC countries as a whole swung from 7.8 per cent to 18.2 per cent,squeezing household consumption from 50.3 per cent in 1995 to 40.1 per cent in 2010.

45©2012 Asian Productivity Organization

Figure 27 shows the long-term trends of household consumption share of GDP for selected Asian
countries. The Asian Tigers have been the high performers, and come at the top for most of the levelindicators presented in Chapter 3. As seen in Figure 27.1, Singapore and Korea showed the most rapid
relative retrenchment in household consumption as a share of GDP in their initial stage of development. While the downward trend continues in Singapore, it has halted and has been mildly reversed
in Korea since the late 1980s. Between 1970 and 2010, the household consumption share of GDP fell
from 68.3 per cent of GDP to 38.9 per cent and from 74.1 per cent to 52.7 per cent in Singapore and4 Expenditure-Side GDP

1995

%

100
80

89 143

182
79

60

59

57

52
37

40

22

20

47

44

35

20

44
29

25
9

19

−2

−8
−14
−18
−19
−25 −29−28 −29
−27
−41
−42
−43
−45
−53
−59
−68

−40
−60
−80
−100

−12
−12 −16

−17

78

73
59

−38
−42 −41−46−48 −43

−36

49

223
74 74

58

56

77

67
39
24 24

55

54

52

20

24 21

47

35
22

15

13

13

22

18

9

0

0
−26
−40 −29

−23
−32

−60
−179

−14
−20
−23
−38
−50

−20
−21
−38

−57

−80
−100

31

22

2010

97

207

40

−20

33 34 31

−148
−93

%

60

11

−166

100
80

11 11 14

1

0
−20

42

35

28

Cambodia
Nepal
Philippines
Sri Lanka
VietnamThailandBangladesh
Hong Kong
Malaysia
Pakistan
US
India
Mongolia
Myanmar
Korea
Australia
Indonesia
Fiji
Qatar
Japan
EU15
ROC
China
Brunei
UAE
Oman
Iran
Saudi Arabia
KuwaitBahrain
Singapore

Korea, respectively. In contrast,
household consumption as ashare of GDP, at 62.7 per cent in2010, has been rather steady inHong Kong over the past four
decades with no established longterm downward trend. The household consumption share did fallfrom 64.8 per cent in 1970 tonearly 55 per cent in the late1980s, but it was subsequently reversed before stabilizing in recent
years. Similarly, relative household consumption fell in the ROC,
from 56.6 per cent in 1970 to under 50 per cent in the mid-1980s.
Since then, it has been on an upward climb until the 2000s when
it stabilized at around 60 per cent.
It is the only country among the
Asian Tigers that has a higher consumption share today than in1970 (i.e., 58.0 per cent comparedwith 56.6 per cent).

−60
−66
−67
−79
−217

−16
−25
−37

−19
−25

−59

−31

−62

−32
−59

−87

©2012 Asian Productivity Organization

Nepal
Fiji
Vietnam
Sri Lanka
Mongolia
Bangladesh
Pakistan
Cambodia
US
India
Philippines
Myanmar
EU15
Japan
Australia
Indonesia
Korea
Iran
China
Hong Kong
Thailand
UAE
ROC
Malaysia
Saudi Arabia
Bahrain
Oman
Qatar
Singapore
KuwaitBruneiFigure 27.2 plots the trends ofhousehold consumption in thethree largest Asian economies byExports
Imports
Net exports
size. The downward long-term
trend in India and China is unmisFigure 26 Export and Import Shares in GDP, 1995 and 2010
takable. When GDP is growing___Share of exports and imports with respect to GDP at current market
faster than consumption, thepricesshare of the latter in GDP will diSources: Official national accounts in each country, including author adjustments.
minish. The falling share of household consumption may partly
reflect the falling labor income share of GDP and/or an uneven distribution of economic gain between the rich and the poor in these countries. Furthermore, the fact that China has a dependent
population (under-15s and over-65s) of 25.5 per cent, compared with 35.5 per cent in India, may help
explain why India has to sustain a much higher share of household consumption than China despite
its falling trend over time (Figure 25). In contrast, the household consumption share in Japan has been
rising slowly since 1970, from just under 50 per cent in 1970 to almost 60 per cent in 2010. With arapidly aging population, this rising trend can be expected to continue. Japan’s population dependency ratio stood at 36.2 per cent in 2010, nearly 60 per cent of which was accounted for by the over65 age group (Figure 28). To a lesser extent, all the Asian Tigers, China, Australia, and the US have ahigh proportion of over-65s relative to other countries.
Figure 27.3 visualizes the observations of Table 7, plotting Asian group averages against those of thereference countries. The US household consumption share has been climbing since the mid-1980s tonearly 70 per cent of GDP in 2010, from a level of around 62 per cent. Today the US level is more than
10 per cent higher than that of EU15 and APO20,27 which have both been fluctuating tightly between

46

4.1 Composition of Final Demand

%

%

80

ROC
Hong Kong
Korea
Singapore

70

80

70

60

60

50

50

40

40

30
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 27.1

70

30
1970

1975

1980

1985

1990

1995

2000

2005

2010

%

80

APO20
Asia29US
EU15Australia

60

50

50

40

40

1975

1980

Figure 27.3

East Asia
South Asia
ASEAN

70

60

30
1970

4

Figure 27.2

%

80

China
India
Japan

1985

1990

1995

2000

2005

2010

30
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 27.4

Figure 27 Long-Term Trend of Household Consumption Share in GDP, 1970–2010___Share of household consumption with respect to GDP at current market prices
Sources: Official national accounts in each country, including author adjustments.

27: It is worth noting that the GDP share of government consumption in EU15 was 9.2 percentage points higher than the average of
Asia23 in 2010 (Table 7). In fact, when it comes to welfare measurement, actual individual consumption, as opposed to household
consumption, is preferred because the former takes into account expenditures by NPISHs and government expenditures on individual consumption goods and services (such as education and health) in addition to household consumption. (For more details
see Box 3.)

47©2012 Asian Productivity Organization

57 per cent and 60 per cent since the mid-1990s. In 1970, household consumption accounted foraround 50 per cent of GDP in APO countries. It rose to a peak of 57.1 per cent in 1983 before fallingback and hovering around 55 per cent. Since the early 1990s, however, it has been trending up toward
60 per cent. The pattern in APO closely follows that of Japan. After the burst of its bubble economy,
the investment share of GDP shrank; household consumption and government consumption rose in
their shares to sustain final demand (see Figure 24). In contrast, the consumption share for Asia29
declined rapidly from 55.6 per cent to around 50 per cent over the past decade. This largely reflects
China’s recent household consumption behavior as it gained weight in the regional economy. Australia’s level has been fluctuating between that of EU15 and Asia29 in the 1970s and 1980s, andconverged to EU15’s level in the 1990s, but its trend in the past decade has diverged again and become similar to that of Asia29. The trends of South Asia and East Asia are dominated by those of India
and China, respectively (Figure 27.4).

4 Expenditure-Side GDP

%

45
40
35

Age 0–14
4

4

4

4

5

5

5

5

30
25
20
15

3

6

6

5

6

13

4

13

7

7

5

4

3

6

3

2

9

5
11 10 9 11 936 35 35 34

33

31 31 31

29 29 30 27

27 26
20

27 27
19

24 24 26 26

13

27

24

27 27
21

13

2
0
1

23
16 16 17 16 17

20
12

17

13

Qatar
UAE
BahrainHong Kong
China
ROC
Singapore
East Asia
Korea
Iran
GCC
KuwaitThailand
Vietnam
Oman
Brunei
MyanmarAsia29Asia23
Mongolia
Malaysia
Australia
Sri Lanka
ASEAN
US
Indonesia
Saudi Arabia
Fiji
APO20
India
Bangladesh
South Asia
Japan
Cambodia
Philippines
Lao PDR
Pakistan
Nepal

0

5

23

10
5

6

Age over 65

Figure 28 Ratio of Dependent Population, 2010
Sources: Population data by NSO in each country; World Bank, World Development Indicators (28 July 2011).

©2012 Asian Productivity Organization

US
Singapore
Korea
ROC
Japan
Hong Kong
Malaysia
India
ThailandIndonesia
Cambodia
Mongolia
BangladeshFiji%
The decomposition of household con100
Miscellaneous goods andservicessumption reveals a huge diversity of
90
Restaurants and hotels
consumption patterns among individual countries, reflecting partly their inEducation
80
come level and partly the idiosyncratic
Recreation and culture70
characteristics of the society under conCommunicationcern. Figure 29 displays strongly theTransport
60
cross-country version of Angel’s Law
Health50
which says that basic necessities will acFurnishings, household
equipment, and routine
count for a high proportion of house40
household maintenancehold consumption for a lower per capita
Housing, water, electricity, gas,30
and other fuels
income group and vice versa. More speClothing and footwear
cifically, countries where food and non20
Alcoholic beverages, tobacco,
alcoholic beverages account for a large
and narcotics
10
proportion of consumption tend to
Food and non-alcoholic
have low income (i.e., in groups L3 or L4
beverages0in Table 14). Among the selected countries, it is staggering to note that in2009, 57.0 per cent of Fiji’s household
consumption was spent on food andFigure 29 Household Consumption by Purpose, 2009non-alcoholic beverages at one end,
Sources: Official national accounts in each country.
compared with only 6.7 per cent in the
Note: For data of Hong Kong, transportation includes communication; recreation and culture includes hotels; miscellaneous goods and services includes
US at the other end. This translates into
restaurants.
the fact that low-income countries
spend 30–50 per cent of their GDP onfood and non-alcoholic beverages. Eating out and recreation and culture are things that the least welloff countries cannot afford as much of as in their richer counterparts. Besides food and non-alcoholic
beverages, housing/utilities and transport are the other two large spending categories. In the richeconomies, these two categories account for bigger shares in household consumption than food andnon-alcoholic beverages. Idiosyncratic spending such as education in Korea and Indonesia, accounting for 7.5 per cent of household consumption in both countries, and health in the US, accounting forone-fifth of consumption, are unmatched in other countries.28

48

4.1 Composition of Final Demand

%

%

50

ROC
Hong Kong
Korea
Singapore

40

50

40

30

30

20

20

10

10

0
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 30.1

0
1970

4

1975

1980

1985

1990

1995

2000

2005

2010

1985

1990

1995

2000

2005

2010

Figure 30.2

%

%

50

50

APO20
Asia29US
EU15Australia

40

40

30

30

20

20

10

10

0
1970

China
India
Japan

1975

1980

Figure 30.3

1985

1990

1995

2000

2005

2010

0
1970

East Asia
South Asia
ASEAN
GCC

1975

1980

Figure 30.4

Figure 30 Long-Term Trend of Investment Share in GDP, 1970–2010___Share of investment with respect to GDP at current market prices
Sources: Official national accounts in each country, including author adjustments.

28: If the household consumption pattern correlates with and differs a great deal according to income level, this undermines the concept of a single representative consumption basket that underpins the construction of a consumer price index (CPI) as a measureof the cost of living. When all prices move together, the difference may not be huge. However, if the rise in CPI is driven for example by soaring oil and food prices, then it is going to bear more heavily upon the poor than the rich. GDP, using CPI as a deflator, inturn inherits this shortcoming of the price index as a welfare measure.

49©2012 Asian Productivity Organization

Figure 30 looks at the long-term trend of investment share in GDP across countries. Historically, Australia’s investment share of GDP has been sandwiched between Asia’s level and that of US/EU15; inrecent years, it has been close to APO20’s average (Figure 30.3). During the financial crisis, the investment share dropped in the US and EU15, opening wider gaps of 19.3 percentage points and 16.6
percentage points with Asia29, respectively, in 2010. Historically, an investment share in the region of
40 per cent or above is unsustainable in the long run. We see that Japan’s investment share of GDP
steadily declined over the past decades from 38.8 per cent in 1970 to 20.0 per cent in 2010 (Figure30.2). In the initial period, Singapore also sustained an investment share of 40 per cent or above. Since
the mid-1980s, however, it has been on a downward trend, in spite of its ups and downs. In 2010, theinvestment ratio was 22.1 per cent. The investment share hit 40 per cent in the ROC and Korea at different times but these were no more than temporary spikes (Figure 30.1). In contrast, the investment
share in China and India has been rising. India in particular has been investing very aggressively since4 Expenditure-Side GDP

1970

%

2010

%

Mongolia

Philippines

Fiji

ROC

India

Indonesia

Malaysia

ThailandHong Kong

Korea

IT capitalJapan

Non-residential buildings

US

China

Iran

VietnamSingapore

Transport equipment

China

Dwellings

Philippines

ROC

Thailand0

Malaysia

0

Fiji

20

Mongolia

20

Indonesia

40

Singapore

40

Japan

60

US

60

Hong Kong

80

Korea

80

Iran

100

India

100

Other structures
Other non-IT capital

Figure 31 Investment by Type of Asset, 1970 and 2010
Sources: Official national accounts in each country, including author estimates based on input–output tables and commodity flow data.

2000, coming as close as 4.3 percentage points to China’s 41.7 per cent share in 2007. Since then, thegap has widened to 14.2 per cent in 2010 (Figure 30.2). If history is any guide, the contribution of investment to final demand in China will drop sooner or later. South Asia and East Asia’s investment
shares are dominated by the effort in India and China, respectively. ASEAN’s investment share used
to be around 35 per cent, but it fell sharply to around 25 per cent during the Asian financial crisis in
the late 1990s and is slowly edging up, reaching 28.2 per cent in 2010. In the past two and a half decades, the investment share in GCC countries has been fluctuating between 20–25 per cent of GDP(Figure 30.4).
Figure 31 shows the nominal investment share of six types of assets for some selected countries.29 For
most countries, investment is still very much construction-based (i.e., in dwellings, non-residentialbuildings, and other structures). However, the expansion of IT capital in the past four decades is significant even at the current price comparisons. The real-term comparisons are conducted at the flow
and stock levels in Chapter 5.

©2012 Asian Productivity Organization

Figure 32 plots the long-term trend of net export share in GDP from 1970 to 2010. Among the selected
countries, India can be identified as prone to running a trade deficit, which deteriorated rapidly fromthe mid-2000s to 5.3 per cent of GDP in 2009 before narrowing to 3.3 per cent in 2010 (Figure 32.2). In
contrast, net exports used to be a huge drag on the Asian Tigers Singapore and Korea in the 1970s, butthey rapidly improved their position. In recent years, net exports are making a positive contribution to
GDP in all the Asian Tigers. The share of net exports in Singapore is particularly large, at 28.4 per centin 2010, compared with 2.6 per cent, 7.1 per cent, and 5.4 per cent for Korea, the ROC, and Hong Kong,
respectively (Figure 32.1). China is another country that has turned around its net exports position
into a significant positive contribution to final demand. The net exports share of GDP peaked at 8.8
per cent in 2007; since then, it has softened to 3.9 per cent in 2010, reflecting weaker foreign demand
as a consequence of the global financial crisis (Figure 32.2).

29: The investment data by type of assets includes our own estimates for the countries where data are not available. Although ourestimates are constructed based on ten classifications of assets, we have aggregated them to six assets in this table. The IT capitalis defined as IT hardware, communications equipment, and computer software.

50

4.1 Composition of Final Demand

Box 4

Quarterly Economic GrowthTimely analysis of the current economic situation is beyond the scope of this Databook, which presents
results based on annual data, and the latest year covered is 2011. In the meantime, if one would like tocatch a glimpse, for example, of the strength of recovery after the global financial storm, one has to rely on
countries’ quarterly national accounts (QNA). Although they are timelier, the QNA are often less precise,and are subject to frequent revisions as more reliable data become available in their normal estimation
cycle. With this trade-off between timeliness and data quality in mind, the APO sees the complementary
benefits of collating and presenting countries’ QNA alongside its database of annual data. As a result, theAPO and KEO have developed an Asian Quarterly Growth Map (AQGM) that provides an instinctive understanding of recent economic growth covering Asian countries. Readers can find it at the APO website(www.apo-tokyo.org/AQGM.html).

4

The AQGM visualizes the seasonally adjusted rates of quarterly economic growth at constant prices. It is
worth noting that there are three constant-price measures of quarterly growth. The first is the quarterly
output compared with the same quarter in the previous year, which is also called the year-on-year quarterly growth. The second is quarterly output of the previous quarter, or the quarter-on-quarter growth rate.
The third is the annualized quarter-on-quarter growth rate, which is also often used in economic analysisof the current economic situation. The first two measures are presented in the AQGM (with year-on-year
growth displayed as a default).

Figure B4.1 Views of Quarterly Economic Growth in Asian Countries by the AQGM
Source: Asian Quarterly Growth Map, January 2012.

continued on next page >51©2012 Asian Productivity Organization

The current version includes 20 Asian countries that publish QNA: China, Hong Kong, India, Indonesia, Japan, Korea, Malaysia, Mongolia, the Philippines, the ROC, Singapore, Sri Lanka, Thailand, Vietnam, Armenia,
Cyprus, Georgia, Israel, Jordan, and Turkey. For the purpose of international comparison, the current version includes 50 non-Asian countries, based on data available from OECD.Stat and independent publications by the respective statistical offices in those countries. The AQGM is updated at least once a month, toreflect revisions and cover newly available data. Based on the AQGM, Figure B4.2 presents year-on-year
quarterly GDP growth for Asian countries, the US, and EU15 from 2009Q4 to 2011Q4.

4 Expenditure-Side GDP> continued from previous page

%
15

China

%
15

ROC

%
15

Hong Kong

%
15

India

12

9

9

6

6

6

6

6

3

3

3

3

3

0

0

0

0

0

−3

−3

−3

−3

−3

%
10

Korea

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4

Japan

%
10

4

4

2

2

2

0

0

0

−2

−2

−2

%
20

Singapore%
9

Sri Lanka

6

10

6

12

4

6

2
0

0

Thailand%
9Vietnam

3

1
0

−8

−5

0

%
4

France

%
4

2

2

2

2

0

0

0

0

−2

−2

−2

−2

−4

−4

−4

−4

%
3

Portugal

0
−2
−4
−6
−8

%
3

Spain

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4

Italy

%
4

0

0

0

0

2

−3

−3

−3

−3

0

−6

−6

−6

−6

−2

United Kingdom

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4Compared to the same quarter in previous year

Greece%2

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4%
3

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1

IrelandGermany−2

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4

Canada0
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4%
4−1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4US−12Australia

%
4
2

3

−4

0

−2

3
6

4
0

5

%
3

8

18

8

15

%
4

%
12

Philippines%
10

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4

4

Mongolia

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q46%
24

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q48

6

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q48

6

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4

8

Malaysia

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q412

9

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q412

9

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q412

9

2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
2010Q3
2010Q2
2010Q1
2009Q4

12%
10

Indonesia%
15

Compared to previous quarter

Figure B4.2 Quarterly Economic Growth in Asian Countries, 2009Q4 – 2011Q4©2012 Asian Productivity Organization

Source: Asian Quarterly Growth Map, January 2012.

Figure 32.3 visualizes the external imbalance of the major economies in the world. Both the US and
EU15 faced a trade deficit at the beginning of the period. While EU15 managed to revert and has beenin surplus since the early 1990s (within a range of 0–2 per cent of GDP), the US position has significantly
deteriorated since the early 1990s, after a tremendous effort in restoring its trade balance in the late1980s. In 2010, the size of the US trade deficit stood at 3.6 per cent of its GDP, compared to its recent
trough of −5.8 per cent of GDP in 2006. Australia has been running a trade deficit for most of the period; only in the past few years has its trade balance been in surplus. In contrast, Asia29’s trade has
been in surplus continuously and a near mirror image of the US. Asia29’s net exports share of GDP was52

4.2 Demand-Side Growth Decomposition

%

30

20

%

10

ROC
Hong Kong
Korea
Singapore

8

China
India
Japan

6
4

10

4

2
0

0
−2

−10

−4
−20
1970 1975 1980 1985 1990 1995 2000 2005 2010

−6
1970

Figure 32.1

Figure 32.2

%

1980

1985

1990

1995

2000

2005

2010

1985

1990

1995

2000

2005

2010

%

6

12

4

9

2

6

0

3

−2

0

−4

1975

East Asia
South Asia
ASEAN

Asia29EU15−3−61970 1975 1980 1985 1990 1995 2000 2005 2010

−6

Figure 32.3

Figure 32.4

APO20
US
Australia

1970

1975

1980

Figure 32 Long-Term Trend of Net Export Share in GDP, 1970–2010___Share of net exports with respect to GDP at current market prices
Sources: Official national accounts in each country, including author adjustments.

2.7 per cent, compared to the recent peak of 5.3 per cent in 2010. Addressing this external imbalancehas been highlighted as a necessary step to a healthier and sustained growth in the world economy.

4.2 Demand-Side Growth Decomposition

30: The Törnqvist quantity index is adopted for calculating the growth of real GDP. Using this index, we can decompose the growth ofreal GDP into the products of contributions by final demands:
In (GDPt / GDPt−1) = ∑ i (1/2) (sit + sit−1) In (Qit / Qit−1)
where Qit is quantity of final demand i in period t and sit is expenditure share ofReal GDP growth

Contribution of final demand ifinal demand i in period t. Thus, the real GDP growth may diverge from the official estimates or those presented in Table 3.

53©2012 Asian Productivity Organization

Figure 33 shows the decomposition of the average annual economic growth by final demand for theperiods 1995–2000 and 2000–2010, respectively.30 Asia29 grew faster in the latter period than theearlier period (at 5.8 per cent on average per annum compared with 4.1 per cent as presented in Table3). The earlier period was atypical in that it embodied the impact of the Asian financial crisis, and we
observe some erratic contributions by the final demand components. On the one hand, investment

4 Expenditure-Side GDP

54

1995–2000

%

10
8
6
4
2
0
−2
−4
−6

2000–2010

%

12
10
8
6
4
2
0
−2
−4
−6

Brunei
Japan
EU15
US
Australia
Saudi Arabia
KuwaitNepal
ROC
Hong Kong
UAE
Korea
Oman
Malaysia
ThailandPhilippines
PakistanIndonesia
Iran
Sri Lanka
Singapore
Bahrain
Bangladesh
Vietnam
India
Cambodia
China
Myanmar
Qatar

On the back of the Asian financial
crisis, investment growth surged
strongly: its impact on real GDP
growth became more significant
in Asia in the 2000s, especially infast-growing economies. For example, investment contributed
6.1 percentage points in China,
3.0 percentage points in Myanmar, 3.4 percentage points in
India, and 3.9 percentage points
in Vietnam. The role played byinvestment in China has strengthened, with its contribution toeconomic growth doubling between 1995–2000 and 2000–2010from 26.2 per cent to 56.4 percent, whereas the contribution of
net exports dwindled from 15.7
per cent to 3.9 per cent. However,for Singapore and the ROC, thestrength of net exports was the
economic story, accounting for60.8 per cent and 66.2 per cent of
their economic growth on average per year between 2000 and2010, respectively (Figure 34). The
reverse was true in India, where
net exports swung from making a
positive contribution of 2.7 percent in the earlier period to beinga drag on economic growth witha negative contribution of −6.3
per cent in the period 2000–2010.
In some of these economies, theIndonesia
ThailandJapan
KuwaitBrunei
Saudi Arabia
Hong Kong
Philippines
Iran
EU15
Oman
Pakistan
Australia
Bahrain
Bangladesh
US
Myanmar
Korea
Malaysia
Sri Lanka
ROC
Cambodia
India
Singapore
UAE
Vietnam
China
Qatar

©2012 Asian Productivity Organization

shaved 4.8 and 3.4 percentage points off the overall economic growth in Thailand and Indonesia, respectively, canceling out growth in other components of final demand and leaving its GDP at a standstill. On the other hand, some countries received a huge boost in net exports, which contributed, forexample, 6.7 and 4.7 percentage points to economic growth in Qatar and Malaysia, respectively. During this period, for most countries in Asia the engine of growth was household consumption while
investment growth was more subdued. Qatar experienced the fastest economic growth among thecountries studied, averaging 8.9 per cent per year, three-quarters of which was driven by net exports.
Unlike the nature of growth in Qatar, China’s growth was more even, with all components making
their fair shares of positive contribution. Out of its average annual growth of 7.7 per cent, 40.4 per cent
was contributed by household consumption, 17.7 per cent by government consumption, 26.2 percent by investment, and 15.7 per cent by net exports. This compares with average annual growths of
4.3 per cent in the US and 3.0 per cent in EU15. The contribution from household consumption was
71.2 per cent and 59.5 per cent in the US and EU15, respectively, whereas investment growth accounted for 37.6 per cent and 32.0 per cent of overall growth in the US and EU15, respectively.

Household consumption
Investment

Government consumption
Net exports

Real GDP

Figure 33 Final Demand Contributions to Economic Growth,
1995–2000 and 2000–2010___Decomposition: Average annual growth rate of GDP at constantmarket prices

Sources: Official national accounts in each country, including author adjustments.

4.2 Demand-Side Growth Decomposition

contribution of household consumption to economic growth was really squeezed: for example, from40.4 per cent in 1995–2000 to 27.6 per cent in 2000–2010 in China, from 39.0 per cent to 29.6 per centin Singapore, and from 61.8 per cent to 34.5 per cent in the ROC. Also, in the latter period net exports
made negative contributions in countries such as Vietnam, Nepal, Cambodia, India, and most of theoil-exporting countries.

4

In the 2000s, economic growth slowed in both the US and EU15: from 4.3 per cent on average per year
in 1995–2000 to 1.5 per cent in 2000–2010, and from 3.0 per cent to 1.2 per cent, respectively. In termsof contributions, household consumption increased from 71.2 per cent to 87.2 per cent and government spending from 7.2 per cent to 20.0 per cent in the US over the two periods. Investment in the US
took a plunge, however, from a contribution of 37.6 per cent to −8.4 per cent over the two periods. Its
net exports improved from −16.0 per cent to 1.3 per cent. EU15 had a similar pattern, where the contribution of government spending nearly tripled over the two periods from 12.5 per cent to 32.1 per
cent, squeezing out the contribution of investment by nine-tenths, while household consumption
remained more or less stable. Its net exports also improved from −4.0 per cent to 6.3 per cent.
Figure 37 shows how the contribution of economic growth by final demand varies across countries
and over time for the period 1970–2010. The immediate impact of the global financial crisis of 2007–2008 has come through our data, although its far-reaching ripple effects go beyond 2010. Most countries felt an adverse impact in 2008 and 2009, with the exception of India where growth reboundedstrongly in 2009 from a slowdown in the previous year. The impact on the Asian countries varied bothin magnitude and in nature. Japan’s recession was particularly deep with the economy contracting by
1.1 per cent and 5.6 per cent in 2008 and 2009, respectively, compared with 2.1 per cent growth in2007, as shown in Figure 35. Besides Japan, other Asian countries either experienced a mild recession
or a growth slowdown. Even so, relative to their rapid growth, the magnitude of the impact could still
be substantial. For example, growth in Singapore dropped from 11.3 per cent in 2007 to 0.4 per centand −0.6 per cent in 2008 and 2009, respectively. Similarly, growth in Hong Kong slowed from 6.2 percent in 2007 to 2.3 per cent 2008 before moving into the negative zone of −2.8 per cent in 2009. The
corresponding real GDP growth figures for the ROC were 5.8 per cent in 2007, 0.9 per cent in 2008, and−1.5 per cent in 2009. India’s growth slowed from 10.7 per cent in 2007 to 1.5 per cent in 2008 before
bouncing back to 9.1 per cent in 2009. In contrast, the slowdown in China was more gradual but lasted
longer; from 13.1 per cent in 2007,
growth decelerated to 10.5 per%cent in both 2008 and 2009, and100
Investment
further to 9.4 per cent in 2010.
80
Most countries experienced a reGovernment consumption
bound (strong in some cases) in
60
2010, but it was largely due to40
Household consumptionsome temporary effects, and did
20
not mark the start of a sustained
Net exports
recovery in the major economies.
0

Figure 34 Final Demand Contribution Shares to Economic
Growth of the Asian Tigers, 2000–2010___Shares of final demand contributions to growth rate of GDP atconstant market prices
Sources: Official national accounts in each country, including author adjustments.

55©2012 Asian Productivity Organization

Korea

Hong Kong

SingaporeROC

The channels through which theadverse impact filtered throughalso varied across countries. Japan’s recession in 2009 was largely accounted for by a sharp fallin investment (3.9 percentage
points) and, to a lesser extent, afall in net exports (1.7 percentage

4 Expenditure-Side GDP

2007–2008%15

2008–2009%15

2009–2010

%

16
14

10

10

5

5

0

0

12
10
8
6
4

−5

−5

2

−10

−10

−2

0
EU15

US

Japan

India

Net exports

China

Hong Kong

ROC

Korea

Investment

Singapore

EU15

US

Government consumption

Japan

India

China

Hong Kong

ROC

Korea

Singapore

EU15

US

Japan

India

China

Hong Kong

ROC

Korea

Singapore

Household consumption

GDP

Figure 35 Impacts of Global Financial Crisis and Recoveries, 2007–2010___Annual growth rates of GDP at constant market prices and contributions of final demands
Sources: Official national accounts in each country, including author adjustments.

points), while the 0.4 per cent growth of government spending canceled out the 0.4 per cent fall inhousehold consumption. Similarly, in the ROC, investment fell by 4.9 per cent in 2009, while the othercomponents of final demand grew albeit more slowly than it had been. In Singapore, net exports andinvestment accounted for −7.8 percentage points and 6.3 percentage points of the final demand
growth, respectively, in 2008. The reverse was true in 2009 with net exports accounting for 5.1 percentage points and investment −6.2 percentage points of final demand growth. In China, net exports
were the only component to contract (by 2.6 percentage points) in 2009 while other final demand
components expanded handsomely. Hong Kong also took a hard hit in net exports in 2009, fallingby 3.4 percentage points, while household consumption slowed considerably over two years. In the
US and EU15, the weakness was in investment and household consumption. Consumers were cautious with their spending as households repaired their balance sheets and job prospects became uncertain. Household consumption fell by 1.3 percentage points and 1.0 percentage points in the US and
EU15, respectively.

©2012 Asian Productivity Organization

Japan was the only Asian country where the global financial storm of 2007–2008 caused a deeper retrenchment in the economy than the Asian financial crisis of 1997–1998 (Figure 36). The latter marked
an exceptional time for many Asian economies. Its impact can clearly be seen in Indonesia, Korea,
Malaysia, Singapore, and Thailand, where investment took a nosedive in 1998; consumption also fell,albeit to a lesser extent. In contrast, net export growth was exceptionally strong, and was likely tohave benefited from the rapid devaluation of the Asian currencies at the time of the crisis. It appears
that some Asian countries, for example, the ROC, Hong Kong, Japan, and Malaysia, also suffered
adversely in 2001 following the burst of the dot.com bubble.
Economic restructuring is a gradual process and could take a long time to establish. Some shifting in
the relative weight of the key drivers of growth may be emerging in some countries, and is discernible
in our data covering almost four decades. For example, in the ROC and Hong Kong, the significant role
played by investment in their early development stage has retreated and besides household consumption, net exports have emerged as a relative important driver of economic growth in the 2000s.
In contrast, investment has become increasingly prominent in explaining economic growth in China

56

4.2 Demand-Side Growth Decomposition%
and India in the past two decades
20
as they undergo rapid develop15
ment. In Japan, investment has
10
faded as a key driver in economic
5
growth after the bubble years of0
the late 1980s came to an end.
−5
Among the Asian Tigers, Singa−10
pore is the most erratic. In the−15
more mature economies like the−20
US and EU15, economic growth islargely driven by household con−25
sumption, followed by investment, over the economic cycle,
while the contribution from net
Household consumption
Government consumption
exports tends to fluctuate. GovInvestment
Net exports
GDPernment consumption has been
expanding proportionately more
Figure 36 Impacts of Asian Financial Crisis, 1997–1998
in some countries (such as EU15,___Annual growth rates of GDP at constant market prices and contribuAustralia, China, and India) thantions of final demands
others (Hong Kong, Vietnam, andSources: Official national accounts in each country, including author adjustments.
the ROC in recent years). Growthof government consumption in
the US appears to be more cyclical than in other countries.

4

Australia
EU15
US
Mongolia
China
VietnamBahrain
Oman
India
Cambodia
Sri Lanka
Bangladesh
Qatar
Myanmar
ROC
KuwaitUAE
Saudi Arabia
Pakistan
Iran
Fiji
SingaporeJapan
Malaysia
Philippines
Korea
Hong Kong
BruneiThailandIndonesia

31: Data from the series of Annual Statistical Abstract, State of Qatar.
32: Data from the Ministry of Finance, Kingdom of Bahrain.

57©2012 Asian Productivity Organization

It is difficult to understand the oil-exporting economies fully without analyzing the oil market in parallel. We can clearly observe its volatility from Figure 37, with huge swings from peak to trough particularly in the 1970s. The oil booms of the 1970s brought benefits, but the downturns also hurt. Net
exports are still erratic, but overall volatility seems to have reduced in the past two decades. Qatar
experienced the fastest GDP growth among the oil-exporting countries in recent years with verystrong investment growth, but its economy is still very dependent on oil and gas and related industries, which accounted for 43.9 per cent of its GDP in 2009 (Figure 65), roughly 80 per cent of its export
earnings, and 70 per cent of government revenues in the 2000s.31 In contrast, Bahrain has diversified
to be a regional banking and financial center and benefited from the regional boom in recent years.
Even so, petroleum production and processing still accounted for less than 30 per cent of its GDP in2009 (Figure 65), about 60 per cent of export earnings, and 75 per cent of government revenues in the
2000s.32 The economic fortunes of these countries are therefore tied with the rest of the world via theirdependence on the oil and gas industry. For example, demand for oil has been driven by the rapid
growth in emerging economies. If, for instance, China’s growth slows, the demand for oil will also
relent. Their future depends on how well they can diversify away from oil and gas while the stock ofnatural resources lasts.

4 Expenditure-Side GDP%
40

Bahrain%20

Bangladesh

Brunei

%
30

15

30

20

10

20

5

10

10

0
0

−10

−20
−30

%
15

0

−5

−10

−10

−15
−20
1971 1976 1981 1986 1991 1996 2001 2006

Cambodia1971 1976 1981 1986 1991 1996 2001 2006

China

%
20

−20

16

12

9

12

8

6

8

4

3

4

0

0

0

−4

−3

−4

−8

−8

−12

1971 1976 1981 1986 1991 1996 2001 2006%
15

Hong Kong

1971 1976 1981 1986 1991 1996 2001 2006

India

%
12

1971 1976 1981 1986 1991 1996 2001 2006

Indonesia

%
18
12

9

10

ROC

%
16

12

−6

1971 1976 1981 1986 1991 1996 2001 2006

6

6
5

0
3
−6

0
0
−5

−10

Iran

18

Japan

%
10

Korea

12
6

4

0

1971 1976 1981 1986 1991 1996 2001 2006

%
18

6

6

0

2

−6

−6

0

−12

−12

−2

−18

−18

−4

−24

%
200

−24
1971 1976 1981 1986 1991 1996 2001 2006

8

12

−30

−18

−6
1971 1976 1981 1986 1991 1996 2001 2006

%
24

−12

−3

1971 1976 1981 1986 1991 1996 2001 2006

Kuwait

150
100
50

−6

%
18

1971 1976 1981 1986 1991 1996 2001 2006

Malaysia−24

1971 1976 1981 1986 1991 1996 2001 2006

Mongolia

%
100

12

75

6

50

0

25

0
−6

0

−12

−25

−150

−18

−50

−200

−24

−50

©2012 Asian Productivity Organization−100

1971 1976 1981 1986 1991 1996 2001 2006

Household consumption

58−75
1971 1976 1981 1986 1991 1996 2001 2006

Government consumption

Investment

1971 1976 1981 1986 1991 1996 2001 2006

Net exports

Real GDP

4.2 Demand-Side Growth Decomposition%
16

Myanmar

12

10

8

8

4

6

0

4

−4

2

−8

0

−12

−2

−16

−4

%
13

1971 1976 1981 1986 1991 1996 2001 2006

Pakistan

Nepal

%
12

%
12

30
20
10
0
−10
−20
1971 1976 1981 1986 1991 1996 2001 2006

Philippines

Qatar

20
10

3

4

0
1

0

−3

−2

−10

−6

−5

%
60

4

1971 1976 1981 1986 1991 1996 2001 2006

6

7

−8

−30

%
30

9

10

Oman

%
40

−20

−9
1971 1976 1981 1986 1991 1996 2001 2006

Saudi Arabia

−12

%
20

1971 1976 1981 1986 1991 1996 2001 2006

Singapore

1971 1976 1981 1986 1991 1996 2001 2006

Sri Lanka

%
18

15

40

−30

12

10
20

6
5

0

0
0

−20

%
20

1971 1976 1981 1986 1991 1996 2001 2006

Thailand−101971 1976 1981 1986 1991 1996 2001 2006

UAE

%
120

−12

90

20

0

60

10

−10

30

0

−20

0

−10

%
10

1971 1976 1981 1986 1991 1996 2001 2006

US

8

−30

1971 1976 1981 1986 1991 1996 2001 2006

EU15

%
6

−20

1971 1976 1981 1986 1991 1996 2001 2006

Australia

%
10
8

4

6

6
2

4
2

4
2

0

0

0
−2

−2
−4

Vietnam

%
30

10

−30

1971 1976 1981 1986 1991 1996 2001 2006

1971 1976 1981 1986 1991 1996 2001 2006

Household consumption−4−21971 1976 1981 1986 1991 1996 2001 2006

Government consumption

Investment−41971 1976 1981 1986 1991 1996 2001 2006

Net exports

Real GDP

Figure 37 Final Demand Decomposition of Real GDP Growth, 1970–2010
Sources: Official national accounts in each country, including author adjustments.
Note: Myanmar’s household consumption includes government consumption due to data limitations.

59©2012 Asian Productivity Organization

−40

−6

−5

5.1 Per Worker Measure of Labor Productivity

5 Productivity
Productivity performance is crucial to a country’s future economic prospects, especially when a lot ofcountries are facing aging populations. As the factors of inputs (labor and capital devoted to production) cannot increase indefinitely, productivity gains, which enable an economy to produce more forthe same amount of inputs, are the only route to sustain economic growth in the long run. It follows
that monitoring and improving national productivity capability (the supply side of the economy) are
important aspects of public policy in many countries.33

5

Used as a ratio of an output volume measure to an input volume measure, productivity is simple as a
notion. When it comes to applying it, however, we quickly realize the complexity in operationalizing
this notion to suit different purposes, especially in a world with data limitations. Consequently, we
have different measures of productivity for different purposes, and different estimation approaches
and definitions subject to the data used. In this report, national accounts are the basis for our productivity estimates, and, in turn, growth accounting with the appropriate choice of index numbers is adopted here as our estimation approach.34 We present two productivity measures in this chapter,
namely labor productivity and total factor productivity (TFP).

33: For example, the UK government sets out public service agreements (PSAs) that outline the improvements that are expected bygovernment expenditure. The PSAs are agreed every three years between the main government departments and the Treasury as
part of the spending review process. At the top of the 30 targets, PSA1 aims to “raise the productivity of the UK economy.” The EU
KLEMS project, which was funded by the European Commission and ran from 2003 to 2008, was also a major initiative responding
to, among other things, the data demands arising from policy evaluation, especially in the assessment of the goals concerningcompetitiveness and economic growth potential as established by the Lisbon and Barcelona Summit goals.
34: The growth accounting approach is based on the microeconomic production theory and the nominal accounting balance of input and output of production. The standard model was presented by Solow (1957) and has been developed by researchers suchas Zvi Griliches, Dale Jorgenson, Charles Hulten, and Erwin Diewert. See OECD (2001) for a presentation of definitions, theoreticalfoundations, and a number of practical issues in measuring productivity.
35: GDP is valued at basic prices in this chapter, as opposed to GDP at market prices used in the previous chapters. GDP at basic prices
is defined as GDP at market prices minus net indirect taxes on products. Since it reflects prices actually paid and received by the
producer, it is more relevant to productivity comparisons. As most Asian countries do not provide the official estimates for GDP
at basic prices in their national accounts, they are calculated based on available tax data. See Appendix A.1 for the methods employed for our calculations.

61©2012 Asian Productivity Organization

Labor productivity can be measured in a number of ways, depending on the definitions of output andlabor input measures. The preferred measure is the basic-price GDP per actual hour worked, which
adjusts for different work patterns across countries and across time.35 However, total actual hours
worked cannot be constructed for all the countries studied. To include all countries and define the
Asian country groups, therefore, the labor productivity measure in terms of GDP per worker is used in
Section 5.1. To the extent that workers in high-performing Asian countries tend to work longer hours
on average than those in the US, the per worker-based labor productivity gaps probably put the Asian
countries in a more favorable light than otherwise. Although being a one-factor or partial-factor productivity measure, interest in labor productivity has never waned due to its simplicity as a concept, its
broad availability, and its direct link to per capita GDP performance. In Section 3.2, we see how the percapita GDP gap with the US for most Asian economies is largely explained by their labor productivity
shortfalls. The cross-country comparisons of labor productivity performance conducted in Section 5.1
are based on a definition compatible with Section 3.3, namely GDP per worker. In Section 5.2, we shift
our focus to our own estimates of the alternative labor productivity measure, namely GDP per hour
worked for some selected Asian countries. In Section 5.3, we include capital input as another key factor of production and present the TFP estimates for 15 Asian countries and the US, based on our estimates of capital services.

5 Productivity

5.1 Per Worker Measure of Labor Productivity
Figure 38 presents the cross-country comparisons of labor productivity levels in 2010, measured as
GDP per worker in US dollars.36 The countries naturally bundle into groups. On this measure, the US isthe leading economy. The close frontrunners in Asia are Singapore and Hong Kong. The other two
Asian Tigers together with Japan follow at some distance. While Iran is close to the top, it is worth noting that it has the lowest employment rate in Asia (Figure 21). Singapore and Hong Kong achieved alabor productivity level that was within −10 per cent that of the US in 2010. Given data uncertainty,
this difference is not deemed statistically significant. The ROC and Japan took the third and fourth
places among the Asian group, with productivity levels 20 per cent and 29 per cent below that of theUS, respectively. Korea followed, with a gap of 36 per cent. Iran and Malaysia achieved productivity
levels that were 48 per cent and 38 per cent of the US level, respectively. Thereafter, among the Asiangroup was a number of countries with labor productivity levels less than 20 per cent that of the US,
pulling down the average performance of the group to 17 per cent for APO20, 16 per cent for Asia29,
and 11 per cent for ASEAN. Included in this list tail were China and India, with productivity levels thatwere 13 per cent and 9 per cent of the US level, respectively.

©2012 Asian Productivity Organization

In the past decade, APO20 as a group achieved
little change in its labor productivity relative tothat of the US, stagnating at around 16 per cent,while Asia 23’s has risen from 11 per cent to 15
per cent (Table 8). Having been the leader in
Asia, Japan started to fall behind the Asian Tigers, when Hong Kong and Singapore caught
up and overtook it in labor productivity in 1991
and 1992, respectively. In 2000, Hong Kong sustained a productivity gap of 19 per cent with
the US, but by 2010 the gap was further narrowed by nearly two-thirds to around 6 percent. In contrast, the relative productivity levelof Singapore against the US has been unchanged in the past decade.
Comparing the new annual data for 2009 and2010 with 2008 shows that productivity
changed little in the three years, stressing thestructural nature of productivity performance,
which requires medium- to long-term efforts tomake statistically significant improvements (Table 8). In the past decade, the top eight countries have maintained their relative positions,although countries have been closing in on theregion’s leader up to 2010 when Singapore’s labor productivity grew faster than the rest. China
and India are the two giant and fast-emerging

93.3
89.9
87.3

US
Singapore
Hong Kong
Australia
ROC
EU15
Japan
Korea
Iran
Malaysia
East Asia
APO20
ThailandAsia29Asia23
Sri Lanka
China
Fiji
ASEAN
Mongolia
Philippines
Indonesia
Pakistan
India
South Asia
VietnamLao PDR
Bangladesh
Cambodia
Myanmar
Nepal

74.3
73.2
69.7
63.9
57.7
45.0
35.0
18.5
15.5
15.3
14.6
14.0
13.6
12.4
12.1
10.4
10.0
9.4
9.0
8.4
8.3
7.9
5.3
4.8
4.4
3.4
3.2
3.0

0

20

Thousands of US dollars (as of 2010)

40

60

80

100

Figure 38 Labor Productivity Level by Per
Worker GDP, 2010___GDP at constant basic prices per worker, using 2005
PPPs, reference year 2010
Source: APO Productivity Database 2012.01.

36: Cross-country level productivity comparisons are notoriously difficult to make and hence subject to a lot of data uncertainty. Estimates should therefore be taken as indicative for broad groupings rather than for precise ranking.

625.1 Per Worker Measure of Labor Productivity

Table 8 Per worker Labor Productivity Levels, 1970, 1990, 2000, and 2008–2010___GDP at constant basic prices per worker, using the 2005 PPPs, reference year 2010
1970

1990

(%)

2000

(%)

2008

2009

2010

12.2 45.1
320.9 1181.0
5.4 19.8

Bahrain46.3 87.9
Kuwait50.9 96.7
Oman
52.6 99.8
Qatar
95.7 181.7
Saudi Arabia 62.7 119.0
UAE
146.2 277.6
Brunei123.5 234.4

Bahrain58.8 77.8
Kuwait67.9 89.8
Oman
65.7 86.9
Qatar
133.6 176.6
Saudi Arabia 70.0 92.6
UAE
126.1 166.7
Brunei111.2 147.0

Bahrain50.0 59.3
Kuwait62.6 74.3
Oman
59.1 70.1
Qatar
127.6 151.4
Saudi Arabia 70.0 83.1
UAE
114.5 135.9
Brunei98.9 117.3

Bahrain46.4 56.6
Kuwait58.9 71.9
Oman
54.7 66.7
Qatar
132.4 161.5
Saudi Arabia 68.9 84.1
UAE
100.7 122.8
Brunei93.9 114.5

Bahrain48.7 54.1
Kuwait58.1 64.6
Oman
65.4 72.8
Qatar
142.7 158.8
Saudi Arabia 70.1 78.1
UAE
94.1 104.7
Brunei93.7 104.2(regrouped)(regrouped)(regrouped)(regrouped)(regrouped)

Saudi Arabia 113.0 415.7
UAE
63.7 234.6(regrouped)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

7.3 26.7
4.2 15.3
4.5 16.4
4.5 16.5
3.0 11.0
3.5 12.7
125.8 462.9

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

11.3 21.5
6.6 12.5
7.0 13.3
7.6 14.3
3.7 7.0
7.2 13.7
71.1 135.0(reference)(reference)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

12.6 16.6
8.8 11.6
9.3 12.3
10.9 14.4
4.9 6.5
7.7 10.2
80.5 106.5(reference)

US
EU15

50.8 186.8
36.0 132.5

US
EU15

65.3 123.9
55.3 104.9

Australia

44.7 164.4

Australia

55.4 105.2

US
EU15
EU27
Australia

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

14.7
12.6
13.2
16.6
6.9
10.0
79.0

17.4
15.0
15.7
19.7
8.2
11.8
93.8

(reference)

78.6 103.9
65.3 86.3
59.2 78.2
68.8 90.9

US
EU15
EU27
Australia

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

82.0 100.0
81.9 99.9
67.4 82.3
60.9 74.3
55.1 67.2
43.5 53.1
33.3 40.6
14.5 17.7
12.8 15.6
12.3 15.0
11.3 13.7
9.6 11.8
9.0 10.9
8.8 10.7
8.3 10.1
7.7 9.4
5.1 6.2
4.5 5.5
4.3 5.2
3.3 4.1
3.0 3.6
3.0 3.6

14.7
13.0
13.6
17.1
7.4
10.0
75.6

17.9
15.9
16.6
20.9
9.0
12.1
92.3

(reference)

89.5 106.1
69.9 82.9
64.5 76.6
73.6 87.4

US
EU15
EU27
Australia

Singapore
Hong Kong
ROC
Japan
Korea
Iran
Malaysia
ThailandSri Lanka
China
Fiji
Mongolia
Philippines
Indonesia
Pakistan
India
VietnamLao PDR
Bangladesh
Cambodia
Myanmar
Nepal(%)

Bahrain
KuwaitOman

84.3 100.0
83.2 98.7
67.9 80.5
63.5 75.4
54.6 64.8
42.8 50.7
34.6 41.0
15.0 17.7
12.5 14.9
12.3 14.6
10.3 12.3
9.4 11.2
9.1 10.8
8.6 10.2
8.3 9.8
7.1 8.5
4.9 5.8
4.3 5.1
4.2 4.9
3.3 3.9
2.9 3.5
2.7 3.2

Singapore
Hong Kong
ROC
Japan
Korea
Iran
Malaysia
ThailandSri Lanka
Fiji
China
Mongolia
Philippines
Indonesia
Pakistan
India
VietnamLao PDR
Bangladesh
Cambodia
Nepal
Myanmar(%)

Japan
Hong Kong
Singapore
ROC
Iran
Korea
Malaysia
Fiji
ThailandPhilippines
Mongolia
Pakistan
Sri Lanka
Indonesia
India
Bangladesh
Nepal
Lao PDR
Vietnam
China
Myanmar75.6 100.0
64.0 84.6
58.0 76.7
55.4 73.2
42.9 56.7
32.5 43.0
26.7 35.3
12.0 15.9
11.5 15.2
9.4 12.4
7.7 10.2
7.5 9.9
6.8 9.0
6.6 8.7
4.8 6.4
4.8 6.3
3.4 4.5
3.4 4.4
3.1 4.0
2.7 3.6
2.3 3.0
1.2 1.6

Singapore
Hong Kong
ROC
Japan
Korea
Iran
Malaysia
ThailandFiji
Sri Lanka
China
Mongolia
Philippines
Indonesia
Pakistan
India
VietnamLao PDR
Bangladesh
Cambodia
Nepal
Myanmar(%)

27.2 100.0
25.6 94.3
24.3 89.5
19.7 72.4
11.9 43.8
11.0 40.5
9.4 34.7
8.9 32.9
6.8 25.0
4.0 14.6
3.8 14.2
3.6 13.4
3.6 13.3
2.6 9.7
2.5 9.3
1.5 5.6
0.8 3.1
0.3 1.1

52.7 100.0
51.5 97.8
51.2 97.2
34.7 65.8
28.8 54.6
27.1 51.4
18.6 35.3
11.0 21.0
7.8 14.9
7.2 13.6
6.4 12.2
6.2 11.7
6.0 11.3
5.1 9.7
3.6 6.8
2.4 4.5
2.2 4.2
2.1 4.0
2.0 3.9
2.0 3.8
0.8 1.4

Singapore
Hong Kong
Japan
ROC
Korea
Iran
Malaysia
ThailandFiji
Sri Lanka
Philippines
Pakistan
Mongolia
Indonesia
China
India
VietnamBangladesh
Lao PDR
Nepal
Cambodia
Myanmar

(%)

Iran
Japan
Singapore
Hong Kong
ROC
Fiji
Malaysia
Korea
Philippines
Sri Lanka
Mongolia
PakistanThailandIndia
Indonesia
Nepal
China
Vietnam

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

89.9 100.0
87.3 97.2
73.2 81.4
63.9 71.2
57.7 64.2
45.0 50.1
35.0 38.9
15.3 17.0
13.6 15.2
12.4 13.8
12.1 13.5
10.0 11.1
9.4 10.4
9.0 10.0
8.4 9.4
8.3 9.2
5.3 5.9
4.8 5.3
4.4 5.0
3.4 3.8
3.2 3.6
3.0 3.3

15.5
14.0
14.6
18.5
7.9
10.4
77.0

5

17.3
15.6
16.2
20.6
8.8
11.6
85.6

(reference)

90.0 109.8
68.0 83.0
62.9 76.7
74.8 91.2

US
EU15
EU27
Australia

93.3 103.9
69.7 77.6
64.4 71.7
74.3 82.7

Unit: Thousands of US dollars (as of 2010).
Source: APO Productivity Database 2012.01.

37: If the comparisons were with the region’s leader at different times, India’s relative labor productivity has actually fallen, while China
has managed to make a substantial leap to close in on the leader, albeit from a very low level.

63©2012 Asian Productivity Organization

economies in Asia. China started off with one-third of India’s productivity level in 1970; but four decades later China is showing signs of pulling ahead of India (Figure 39). China’s relative performanceagainst the US moved up from 2 per cent in 1970 to 6 per cent in 2000 and 13 per cent in 2010, compared with the corresponding figures of 5 per cent, 6 per cent, and 9 per cent for India.37

5 Productivity

Box 5

The Middle-Income Trap and Implications for China

Emerging Asia has been catching up with the leading economies at a spectacular pace. In the past two
decades, China’s real GDP has increased by 630 per cent and India’s by 250 per cent, compared with 60 per
cent in the US and 40 per cent in EU15. In the historical perspective, the pace of economic catch-up is accelerating. It took 32 years for Britain’s economy to double in size between 1830 and 1862, and 17 years for
the US to achieve the same and overtake Britain in the 1870s. The economies of China and India doubled
within a decade (The Economist, “Special Report: The World Economy,” 24 September 2011). The recent
economic development in the world’s two most populous countries has delivered a miraculous rise in living standards, supported global demand when the advanced economies are faltering, and shifted therelative economic balance of different regions with its geopolitical implications. China is already the world’s
second largest economy in current dollars, and The Economist estimates that it may well overtake the US as
the world’s leading economy within a decade. China will overtake the US in 2015 if it can maintain its pacein the 2000s of catching up to the US, and in 2019 if the relative speed of catching up is halved (Figure B5).

©2012 Asian Productivity Organization

Economic convergence has been achieved
US=100before, but it has taken on new significance160
Overtake in 2015
when it involves China and India because of(Case of 8.4%
140
of catch up)
their sheer size. It is nothing new that with a120
suitable policy framework put in place, theUS100
Overtake in 2019late-developing countries can grow more
(Case of 4.2%
80
of catch up)
rapidly than the leading matured economies
60
by imitating and exploiting proven successes.
40
They can improve their productivity performance by high levels of investment and by
20
shifting underemployed resources from agri0
1970
1980
1990
2000
2010
2020
culture to high performing export-oriented
manufacturing (or IT services in the case ofIndia) that utilizes imported technologies.
Figure B5 China’s GDP Forecast Relative to the
The question is how long can this breakneck
US, 2010–2020
growth last – that is, at what point will thisgrowth engine jam and slow down? It is conSources: Official national accounts in each country, including author
adjustments.
ceivable that after all the low-hanging fruits
have been grabbed, further growth will require more ingenuity, and become more innovation-intensive. To sustain growth, countries must rise up to the challenge. Given its economic weight,
the timing and the manner in which the Chinese economy might slow have important implications for theworld economy in the medium term.
Eichengreen, Park, and Shin (2011) set out to identify the precursors of growth slowdowns that were associated with economic maturity in fast-growing economies using international data starting in 1957. A
significant slowdown is defined as a downshift in the seven-year average growth rate by at least 2 percentage points. Based on countries’ experience, 85 per cent of growth slowdowns in fast-growing economies
are explained by the slowdown in total factor productivity growth. The probability of this sort of slowdown
peaks when per capita GDP reaches USD17,000 in 2005 prices, or 58 per cent of that in the lead country, or
when manufacturing accounts for 23 per cent of total employment. Furthermore, higher old age dependency rates, and high and volatile inflation appear to make slowdowns more likely, whereas trade openness has the opposite effect, other things being equal. Interestingly, a low consumption share of GDP also
increases the likelihood of slowdown; such a probability is minimized when consumption is around 64 percent of GDP. Similarly, high investment rates are found to reduce the likelihood of slowdown. More provocatively, the research finds that countries with undervalued real exchange rates face a higher chance ofgrowth slowdowns. It may be that growth reliant on currency undervaluation is vulnerable to external
shocks and policy tensions arising from managing the exchange rates. It may also be that undervalued
exchange rates distort decisions, building up imbalances and excesses in the export sector. This formula
may have worked well in the early catch-up phase to boost growth but it may be less congruous with laterstage development when growth tends to be driven by indigenous innovation, leaving the country
increasingly susceptible to slowing down.
continued on next page >64

5.1 Per Worker Measure of Labor Productivity> continued from previous page

Based on this research, China may hit the middle-income trap in the not-too-distant future. With a percapita GDP of USD7,600 in 2010, China is within reach of the USD17,000 threshold, although it is still somedistance away from the relative income threshold of 58 per cent. It may even have hit the manufacturing
employment landmark of 23 per cent. On its current course, the odds that China can avoid a growth slowdown are not favorable. Although China’s trade openness and high investment rates work to sustain
growth, a double-digit growth rate, rising old-age dependency ratio, exceptionally low consumption shareof GDP, and undervalued currency together push the probability of China experiencing an imminent slowdown to over 70 per cent.
If China is to avoid the middle-income trap, the obstacles are formidable. Among other things, it needs torebalance its economy toward consumption and develop its domestic market. This will mean dislocating
entire industries, and having a more efficient allocation of workers and capital to encourage promising
new ventures and entrepreneurship. This, in turn, requires fundamental structural reforms in the economy
and the development of institutional infrastructure to support more sophisticated growth. Given the scale,
depth, and breadth of this daunting task, it is far from conclusive that China will successfully complete thetransition to upper-middle-income-country status.

5

The figures for GCC countries and Brunei are uncharacteristically high, especially in 1970, but there arealso noticeable variations within the country group. The atypically high figures in the early period reflect the natural resource rents – the value of the resource over and above the cost of extraction –which are erroneously included in these countries’ GDP. The extent of exaggeration appears to be
proportional to their oil production: Saudi Arabia has the largest proven oil reserves in the world andis the largest world oil exporter; Kuwait has the fourth-largest oil reserves in the world; also, Qatar has
become the fourth-largest exporter of liquefied natural gas. In contrast, Bahrain has the smallest oil
reserve compared to its peers. Its dependence on oil is therefore considerably lower and it has worked
to diversify its economy over the past decade (see Figure 82). The GCC countries have also been experiencing high population growth, especially in the late 1970s and the early 1980s. In the last two decades, this has somewhat stabilized at around 2 per cent a year, except in the UAE and Qatar where thepopulation grew in 2010 at 7.9 per cent and 9.6, respectively per cent over the previous year. The
working-age population has been expanding accordingly. Employment is erratic from one year toanother, and this will be reflected in the labor productivity figures.
Thousands of US dollars (as of 2010)

12
10
China

8
6
4

India

2
0
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 39 Labor Productivity Trends of China and India,
1970–2010___GDP at constant basic prices per worker, using 2005 PPPs, reference
year 2010
Source: APO Productivity Database 2012.01.

65©2012 Asian Productivity Organization

When labor productivity growthis compared, the ranking of countries is reshuffled (Table 9). Thereappeared a spurt in labor productivity growth in the low-income
countries in the 2000s. While they
were scattered around the tablein the earlier periods, by 2000–
2005 the seven countries with thefastest labor productivity growth
were all from Group-L4 (as defined in Table 6); and in the latest
period 2005–2010, five out of the
top seven were from Group-L4
and two from Group-L3. Amongthem, China has been sustaining
rapid productivity growth in thepast two decades; its growth accelerated to an average of 10.2

5 Productivity

Table 9 Labor Productivity Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2010___ Average annual growth rate of GDP at constant basic prices per worker, using 2005 PPPs
1990–1995
KuwaitChina
ThailandSri Lanka
Indonesia
Malaysia
Vietnam
ROC
Korea
Cambodia
Singapore
BahrainHong Kong
Lao PDR
Pakistan
MyanmarBangladesh
India
Nepal
Iran
Qatar
Saudi Arabia
Japan
BruneiFiji
Philippines
Mongolia
UAE
Oman

1995–2000

13.1
10.6
8.2
7.5
6.5
6.4
5.2
5.2
5.0
4.3
4.1
4.1
3.7
3.7
3.5
3.3
2.9
2.4
2.4
1.4
0.9
0.6
0.6
−0.2
−0.4
−0.4
−1.3
−3.7
−7.1

(regrouped)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

Oman
China
Qatar
MyanmarVietnam
Korea
ROC
Bangladesh
Singapore
Lao PDR
Cambodia
India
Mongolia
Philippines
Nepal
Sri Lanka
Saudi Arabia
Japan
Fiji
Iran
Malaysia
UAE
BahrainHong Kong
Thailand
PakistanIndonesia
Brunei
Kuwait2000–2005

11.6
7.1
5.7
5.6
4.7
4.2
4.1
3.9
3.7
3.5
3.4
3.4
2.5
1.9
1.7
1.6
1.6
1.3
1.2
1.0
0.8
0.7
0.6
0.6
0.4
0.3
−1.4
−1.9
−7.4

(regrouped)

1.1
3.1
3.1
4.1
2.6
0.7
0.8

(reference)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

1.5
1.9

Australia

2.3

US
EU15
EU27
Australia

2005–2010

10.6
8.6
4.8
3.7
3.7
3.6
3.6
3.3
3.2
3.1
3.0
3.0
2.9
2.7
2.6
2.5
2.3
2.0
1.8
1.5
1.3
1.1
0.6
−0.2
−0.7
−0.8
−1.2
−1.6
−1.8

(regrouped)

1.0
2.6
2.6
3.2
3.0
0.6
1.7

(reference)

US
EU15

Myanmar
China
VietnamIndia
Lao PDR
Cambodia
Indonesia
Hong Kong
Oman
Singapore
Malaysia
Thailand
Korea
MongoliaROC
Sri Lanka
IranPakistan
Bangladesh
Fiji
Japan
Philippines
Nepal
Saudi Arabia
Qatar
KuwaitBruneiBahrain
UAE
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC
US
EU15
EU27
Australia

1990–2010

10.2
9.2
7.3
5.2
5.0
4.9
4.6
4.3
4.2
3.8
3.0
3.0
3.0
2.7
2.7
2.4
2.0
1.8
1.6
0.6
0.5
0.4
0.2
−0.5
−2.2
−2.2
−2.3
−3.3
−4.0

(regrouped)

1.4
3.8
3.7
4.6
3.3
3.2
−0.3

(reference)

2.3
1.4
1.7
2.0

China
MyanmarIndia
Lao PDR
Mongolia
Sri Lanka
Cambodia
Iran
VietnamBangladesh
Korea
Hong Kong
ROC
Philippines
Indonesia
Malaysia
Qatar
Thailand
Nepal
Japan
Pakistan
Singapore
Saudi Arabia
Fiji
BruneiBahrain
Kuwait
Oman
UAE
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC
US
EU15
EU27
Australia

2000–2010

8.8
5.0
4.7
4.6
4.6
4.5
4.3
3.9
3.7
3.6
3.6
3.4
3.3
2.9
2.9
2.6
2.4
2.2
2.2
2.0
1.9
1.2
1.1
1.0
0.8
0.6
0.4
−1.0
−1.5

(regrouped)

2.8
5.5
5.3
6.1
6.3
2.8
−0.7

(reference)

2.1
0.9
1.2
1.3

China
VietnamROC
Korea
Sri Lanka
MyanmarThailandSingapore
Cambodia
Malaysia
Lao PDR
Bangladesh
Qatar
India
KuwaitIndonesia
Bahrain
Oman
Hong Kong
Nepal
Pakistan
Iran
Saudi Arabia
Japan
Philippines
Mongolia
Fiji
BruneiUAE
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC
US
EU15
EU27
Australia

9.9
9.4
5.5
4.5
4.4
4.1
3.8
3.7
3.3
3.2
3.1
3.0
2.8
2.8
2.7
2.4
1.9
1.7
1.2
1.1
1.0
0.7
0.5
0.0
0.0
−1.6
−1.7
−1.9
−2.9

(regrouped)

1.1
2.9
2.8
3.6
2.8
0.7
1.2

(reference)

1.3
0.4
0.5
0.3

Myanmar
China
India
VietnamLao PDR
Cambodia
Mongolia
Sri Lanka
IranIndonesia
Hong Kong
Korea
Bangladesh
ROC
Malaysia
ThailandPhilippines
Singapore
Pakistan
Nepal
Japan
Qatar
Fiji
Saudi Arabia
Oman
KuwaitBruneiBahrain
UAE
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

2.1
4.6
4.5
5.3
4.8
3.0
−0.5

(reference)

1.9
1.7
1.7
2.2

US
EU15
EU27
Australia

1.7
0.7
0.9
0.8

©2012 Asian Productivity Organization

Unit: Percentage.
Sources: APO Productivity Database 2012.01.

per cent a year in 2005–2010 from 7.1 per cent a year in 1995–2000 and 8.6 per cent a year in 2000–
2005. This compares with India’s at 7.3 per cent, 3.4 per cent, and 3.7 per cent over the same periods.
Labor productivity growth in the Asian Tigers was steady, ranging from 2.6 per cent to 3.3 per cent on
average a year in 2000–2005. This performance was sustained in 2005–2010, except in Singapore.
While Singapore’s average annual productivity growth slowed significantly to 0.4 per cent, the others
enjoyed growth of about 3.0 per cent in 2005–2010. Although no match with the fast-emerging Asian
economies, this was a robust performance compared with 1.7 per cent in the US and 0.4 per cent in
EU15. Japan’s labor productivity growth behaved closer to that in other mature economies. Having
managed to grow at 1.3 per cent on average a year for a decade in 1995–2005, labor productivity
growth in Japan has slowed to 0.6 per cent per year on average since 2005. The 2000s were an era

66

5.1 Per Worker Measure of Labor Productivity

when labor productivity deteriorated in GCC countries. The decline accelerated from −0.3 per cent to−0.7 per cent between the two halves of the 2000s.
As a group, Asia23 achieved the highest labor productivity growth in recent years, reaching 5.5 percent on average a year in 2005–2010, up from 3.8 per cent in 2000–2005. Within Asia, labor productivity growth has been accelerating in both South Asia and East Asia, to 6.3 per cent and 6.1 per cent in
2005–2010, respectively. South Asia displayed a newfound vigor in recent years, considering that labor productivity growth had been faster in East Asia previously. In contrast, average annual productivity growth in the US slowed rapidly to 1.3 per cent between 2005 and 2010, after a decade of over 2
per cent growth a year. Average annual labor productivity growth in EU15 has been weakening as
well, slowing in every successive period from 1.9 per cent in the first half of the 1990s to 0.4 per centin the most recent period 2005–2010.

5

Figure 40 shows labor productivity levels relative to the US (= 100) for Asian countries. The samegrouping as in Section 3.2, based on the speed of catch-up with the US in per capita GDP, is used here.
Broadly speaking, countries that are catching up fast with the US in per capita GDP (Group-C1) are also
fast catching up in labor productivity (Figure 40.1). Similarly, countries with deteriorating relative per

90
80
70

Cambodia
China
ROC
Korea
Singapore

US=100
100
90
80
70

Hong Kong
India
Indonesia
Lao PDR
Malaysia
Myanmar
Sri Lanka

60

60

50

50

40

40

30

30

20

20

10

10

0
1970 1975 1980 1985 1990 1995 2000 2005 201001970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 40.1: Group-C1 Countries

Figure 40.2: Group-C2 Countries

US=100100

US=100
100

90

90

80

80

70

70

60

60

50
40
30
20

Bangladesh
Japan
Mongolia
Nepal
Pakistan
EU15

Thailand
Vietnam

50
40
30

Fiji
Iran
Philippines
Australia

20

10

10

0
1970 1975 1980 1985 1990 1995 2000 2005 201001970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 40.3: Group-C3 Countries

Figure 40.4: Group-C4 Countries

Figure 40 Labor Productivity Level Relative to the US, 1970–2010___Indices of GDP at constant basic prices per worker, using 2005 PPPs
Source: APO Productivity Database 2012.01.

67©2012 Asian Productivity Organization

US=100100

5 Productivity

capita GDP (Group-C4) are found also to be deteriorating or of little change against the US in laborproductivity (Figure 40.4).
Among the countries that are catching up with the US in per capita GDP (i.e., Group-C1 and GroupC2), the Asian Tigers have made a tremendous effort in improving their relative labor productivity
over the past four decades. Singapore and Hong Kong have closed the gap from 50–60 per cent in1970 to within 10 per cent in 2010 (Figure 40.1 and Figure 40.2). Similarly, the ROC and Korea have
reduced a gap of around 80 per cent initially to 20 per cent and 40 per cent by 2010, respectively (Figure 40.1). Malaysia has been making steady progress, raising its relative productivity level from 19 percent that of the US in 1970 to 37 per cent in 2010 (Figure 40.2). The rest of the countries in these twogroups all had an initial relative labor productivity level of below 10 per cent, but have shown signs ofa strong and promising start in their catch-up process in the past decade. Among these countries, theimpact of the Asian financial crisis of 1997–1998 in temporarily stalling the progress of Thailand andIndonesia can be clearly seen, but they have slowly recovered the lost ground.
Countries that have managed little catch-up with the US (Group-C3) or have a declining per capita
GDP against the US (Group-C4) are also those with rather stagnant or deteriorating relative labor productivity. Japan is the only high-income Asian country in this group, while the rest (except Iran) are all
low-income countries with per capita GDP less than 20 per cent that of the US. Japan showed strong
catch-up in the earlier period, with relative labor productivity peaking at 81 per cent that of the US in
1991, and since then the gap has widened again to over 30 per cent in 2010. Similarly EU15, a reference economy with high income, has seen its productivity gap double against the US since 1995, from
13 per cent to 25 per cent in 2010, whereas the low-income countries have managed little catch-up(Figure 40.3) or had a declining relative productivity level (Figure 40.4). Iran (a Group-L2 country) experienced a drastic decline in its relative labor productivity from its former peak of 77 per cent in 1976
to 38 per cent in 1988, before reviving to 48 per cent in 2010.

5.2 Per Hour Measure of Labor Productivity©2012 Asian Productivity Organization

The per worker-based labor productivity gaps presented in Section 5.1 are most likely conservative
estimates, since workers in high-performing Asian countries tend to work longer hours than those in
the US on average. To adjust for this discrepancy, total hours worked are constructed in our databasefor 15 Asian countries and the US, although the quality of the estimates may vary considerably acrosscountries.38 Figure 41 shows how the productivity gap against the US in 2010 varies depending on
which measure of labor productivity is used.39 The productivity gap with the US widens for all Asian
countries when the differences in working hours are taken into account. However, for ten of thesecountries, the adjustments are within 2–5 percentage points, and hence are not deemed as statistically significant. In contrast, the choice of labor productivity measure makes a significant difference
for the previously high-performing countries in their relative performance. On a per hour GDP basis,the labor productivity gap against the US widens by 15–25 percentage points for the four Asian Tigers(Korea, the ROC, Singapore, and Hong Kong), suggesting that workers there work much longer hours
38: Cross-country comparisons of hours worked are notoriously difficult, not least because harmonized data are rarely readily available. In the countries studied, three published their total hours worked as part of their official statistics, but not for the whole period studied in this report, and they may be constructed based on different methodologies. Some countries only publish estimates
for average weekly hours worked, which need estimates of number of weeks worked to derive the total average hours worked
per worker. Others may have only estimates of benchmark hours worked available, which are then extrapolated to form a series.
Consequently, growth of employment and growth of total hours worked become identical, as in the case of China and Thailand.
In reading the results, it is therefore important to bear in mind the data limitations. See Box 6 for an explanation of the estimation
procedure of total hours worked.
39: The labor productivity gap for country x is country x’s labor productivity divided by the US’s labor productivity in Figure 41.

685.2 Per Hour Measure of Labor Productivity

Box 6

Measuring Hours Worked

Hours worked are defined in this Databook as the economy-wide hours worked by employees and the selfemployed. Japanese and US national accounts publish estimates of the annual hours worked per employee.
For both countries, the economy-wide hours worked were estimated in this Databook by simply assumingthat annual per worker hours worked are the same for employees and the self-employed.
Other Asian countries do not publish hours worked in their national accounts. For Korea, the Report on
Monthly Labor Survey shows monthly hours worked per employee. The economy-wide annual hours
worked in Korea are calculated from average monthly hours worked per worker and the number of workers. Monthly hours worked per worker are assumed to be the same for employees and the self-employed.

5

For other countries, economy-wide annual hours worked are calculated from average weekly hours worked
and the number of workers. It is necessary to know the number of weeks worked per annum in order tocalculate annual hours worked from weekly hours worked. Benchmark average annual hours worked from
Crafts (1999) and Maddison (1995) are used for our calculation. We utilize Craft’s estimates only for Hong
Kong and Singapore, which are not covered in Maddison (1995).
In simple terms, the procedure of constructing economy-wide annual hours worked consists of three steps
for all countries other than Japan, Korea, and the US. First, we obtain average weekly hours worked and thenumber of workers from official statistics, such as a labor force survey. Second, from annual hours worked
per worker in benchmark years available in Maddison (1995) and Crafts (1999), we obtain the number ofweeks worked in benchmark years. Third, numbers of weeks worked are interpolated over non-benchmark
years under the assumption of a constant growth rate. Multiplying the average hours worked by the
number of workers gives economy-wide average weekly hours worked. Multiplying economy-wide
average weekly hours worked by the number
of weeks worked gives economy-wide annual
hours worked.
Cambodia46
ROC
Bangladesh
Malaysia
Korea
Iran
ThailandHong Kong
Singapore
Indonesia
China
India
Philippines
Pakistan
Sri Lanka
VietnamJapan
Australia
EU15

43
43
43
42
39
37
36
36
36
32
30
30
29
22
13
7
3
−3

0

10

20

30

40

50 %

Figure B6 Average Annual Hours Worked Per
Worker Relative to the US, 2000–2010
Sources: Official national accounts and labor force survey in eachcountry, including author adjustments.

69©2012 Asian Productivity Organization

Figure B6 presents a cross-country comparison of average annual hours worked per worker for 2000–2010, relative to the level of the
US. It indicates that workers in Asian countries
tend to work much longer hours than those in
the US and Europe. In many countries in our
sample, the difference in annual hours worked
per person relative to the US is more than 30
per cent of the US level. Prolonged working
hours are observed in Asian countries regardless of their stage of development, spanning
low-income countries such as Bangladesh andCambodia to high-income countries such as
the ROC and Singapore. Exceptions are Japan
and Vietnam. Workers in both countries arelikely to work much shorter hours than thosein other Asian countries. However, comparedwith the US and EU15, hours worked by workers in Japan and Vietnam are still about 10 per
cent longer.

−6

−20

−40

−38

−31

Australia

−4

−22
−31
−35

EU15

Singapore

Hong Kong

Japan

ROC

Korea

Iran

Thailand

Malaysia

Sri Lanka

China

Philippines

Pakistan

India

Indonesia

0Vietnam%Bangladesh

than their US counterparts. Europeans generally work fewer hours.
This is reflected in that comparisons on hourly labor productivity
shows EU15 in a more favorable
light against the US, albeit only
marginally.

Cambodia

5 Productivity

−29

−23
−25

−20−22

−44
−52

−53

−60
Based on GDP at constant basic−63−64
prices per hour worked, US labor−73−80
productivity has been able to sus−84
Per worker GDP−87 −85−88 −88−90 −91 −91 −90−92 −90
tain a big lead over even the Asian
Per hour GDP
−93
−93
−94
−94
−95
−95
−100 −96−98 −97
high performers (Table 10). In
1970, the US productivity level
Figure 41 Labor Productivity Gap by Per Worker and Per
was nearly 2.5 times that of theHour GDP Relative to the US, 2010___GDP at constant basic prices per worker and hour, using 2005 PPPs
Asian leader, Japan. This gap was
reduced to around 50 per cent in
Source: APO Productivity Database 2012.01.
1990. Since 1990, Japan’s pace inclosing the gap has slowed. By
2010, a sizable gap of 35 per cent still remained. The gap between the US and the Asian leader of thepast decade (i.e., Singapore) has been persistent at around 30 per cent. This is in contrast with thepicture painted by the per worker productivity measure, based on which the Asian leaders (Singaporeand Hong Kong) have almost closed the gap with the US (Figure 40).40 EU15’s lead over the Asianleader was around 20 per cent in 2000, but rapidly eroded to around 10 per cent by 2010.

The levels of labor productivity for the top five countries, Japan and the four Asian Tigers, maintained
their relative positions for almost four decades. The progress of labor productivity in these countries
during 1970–2010 is shown in Figure 42. Within four decades, GDP per hour has roughly tripled for the
top three economies, namely Japan, Singapore, and Hong Kong, and the gap among them has literally disappeared. They are ahead of the ROC and Korea by 20 per cent and 40 per cent, respectively, in
2010, despite their effort in catching up with Japan by 2.0 per cent and 2.4 per cent a year on average,
respectively, over the past four decades. If they could keep up this effort at the same pace, it would
take the ROC 8 years and Korea 14 years finally to catch up with Japan.

©2012 Asian Productivity Organization

Over the past four decades, hourly labor productivity growth ranged from 0.8 per cent (the Philippines) to 6.7 per cent (China) on average per year, compared with that of the US at 1.7 per cent andAustralia at 1.6 per cent (Figure 43). Among the 16 Asian countries compared, only Bangladesh, Iran,and the Philippines grew slower than the two reference economies. Between the two sub-periods(i.e., 1970–1990 and 1990–2010), we observe a deceleration in the hourly productivity growthfor 9 out of 16 Asian countries: for example, 2.4 percentage points and 2.1 percentage points
were shaved off productivity growth in the earlier period in Hong Kong and Japan, respectively.

40: Note that the differentials in the labor quality per hour worked among countries have not been accounted for in this comparison:labor productivity will tend to be overestimated if labor quality has been rising, and vice versa. Jorgenson and Nomura (2007)
provide a comprehensive picture of bilateral productivity comparisons between the US and Japan, based on detailed estimatesfor 164 commodities, 33 assets (including land and inventories), and 1,596 labor categories. Even when the differences in qualityof labor have been adjusted for, they find that the US–Japan labor productivity gap was still sizable, at 34.3 per cent for 2004. They
also point out that the gap in the “level” of TFP has been the major source of the labor productivity gap since the mid-1990s; lower
TFP explains 57.0 per cent of the labor productivity gap in 2004, while non-IT-capital deepening (defined by capital input per unitof labor input) accounts for 37.3 per cent. In the next section, we analyze the gap in labor productivity “growth” among countries,
without the level comparisons of capital deepening and TFP due to lack of data.

705.2 Per Hour Measure of Labor Productivity

Table 10 Per Hour Labor Productivity Levels, 1970, 1990, 2000, and 2008–2010___GDP at constant basic prices per hour, using 2005 PPPs, reference year 2010
1970
Japan
Iran
Singapore
Hong Kong
ROC
Malaysia
Korea
Philippines
Pakistan
Sri Lanka
ThailandIndia
Indonesia
China

Japan
Singapore
Hong Kong
ROC
Iran
Korea
Malaysia
ThailandPhilippines
Pakistan
Sri Lanka
Indonesia
India
VietnamBangladesh
China28.5 235.7

2000

(%)

26.1 100.0
22.9 87.7
22.0 84.4
13.8 53.0
12.5 47.9
10.5 40.4
7.8 29.9
3.6 13.7
3.2 12.2
2.8 10.9
2.8 10.7
2.3 8.9
1.6 6.2
1.2 4.5
1.1 4.3
0.9 3.5(reference)(reference)

US

1990

(%)

12.1 100.0
11.8 97.6
11.0 90.9
7.6 63.0
4.6 38.0
3.9 32.6
3.3 26.9
3.1 25.7
1.7 13.9
1.7 13.6
1.6 13.6
1.2 9.9
1.2 9.5
0.4 3.2

SingaporeJapan
Hong Kong
ROC
Korea
Iran
Malaysia
ThailandSri Lanka
Philippines
PakistanIndonesia
China
India
VietnamBangladesh
Cambodia(reference)US38.6 147.8

Australia

31.1 119.3

US
EU15
Australia

2008

(%)

33.2 100.0
31.9 96.0
28.0 84.3
22.6 67.9
17.1 51.4
14.1 42.5
11.2 33.7
5.3 15.9
4.9 14.7
3.5 10.6
3.4 10.3
3.0 9.1
2.2 6.6
2.2 6.6
1.7 5.2
1.6 4.7
0.9 2.8

Singapore
Hong Kong
Japan
ROC
Korea
Iran
Malaysia
ThailandSri Lanka
China
Philippines
PakistanIndonesia
India
VietnamBangladesh
Cambodia(reference)

46.5 139.9
39.6 119.2
38.9 117.0

2009

(%)

38.1 100.0
37.2 97.6
35.9 94.0
29.1 76.2
24.3 63.8
17.8 46.8
14.7 38.7
6.5 17.2
6.1 16.1
4.7 12.3
4.2 11.0
3.9 10.2
3.8 10.0
3.3 8.6
2.5 6.6
1.6 4.3
1.3 3.5

Singapore
Hong Kong
Japan
ROC
Korea
Iran
Malaysia
Sri Lanka
Thailand
China
Philippines
Pakistan
India
Indonesia
VietnamBangladesh
Cambodia(reference)

US
EU15
Australia

53.8 141.2
43.4 113.9
42.9 112.6

US
EU15
Australia

1985

1990

2010

(%)

37.7 100.0
36.6 97.2
35.6 94.4
29.2 77.4
24.7 65.5
18.6 49.4
14.1 37.5
6.4 17.1
6.4 16.9
5.1 13.6
4.1 10.9
3.9 10.4
3.6 9.4
3.5 9.3
2.5 6.8
1.7 4.5
1.3 3.6

Singapore
Hong Kong
Japan
ROC
Korea
Iran
Malaysia
ThailandSri Lanka
China
Philippines
Pakistan
India
Indonesia
VietnamBangladesh
Cambodia(%)

40.2 100.0
39.1 97.2
36.9 91.8
31.5 78.3
26.3 65.5
20.3 50.4
15.0 37.3
6.7 16.6
6.7 16.5
5.6 14.0
4.3 10.7
3.9 9.8
3.8 9.6
3.6 9.0
2.8 6.9
1.8 4.4
1.4 3.45(reference)

54.8 145.5
42.9 113.7
44.4 117.9

US
EU15
Australia

56.4 140.2
43.7 108.6
44.1 109.6

Unit: US dollar (as of 2010).
Sources: APO Productivity Database 2012.01.

US dollar (as of 2010)40

ROC
Hong Kong
Japan

30

Korea
Singapore

20

10

0
1970

1975

1980

1995

2000

2005

2010

Figure 42 Labor Productivity Trends in Japan and the FourAsian Tigers, 1970–2010___GDP at constant basic prices per hour, using 2005 PPPs, reference
The deceleration of productivity
year 2010
growth in most countries between the two sub-periods reSource: APO Productivity Database 2012.01.
flected weaknesses in output
growth. Figure 44 shows that all
countries except Vietnam experienced a slowdown in hours-worked growth between the sub-periods,
which should have worked to boost labor productivity growth, other things being equal.41 This implies

41: By definition, positive labor productivity growth occurs when output grows faster than labor input. Figures 43 and 44 therefore
tend to have an inverse relationship, namely that the higher the labor input growth, the lower the labor productivity growth,
other things being equal.

71©2012 Asian Productivity Organization

Six countries managed to accelerate their productivity improvement after 1990. Among these,
China’s performance is the mostoutstanding, with productivity
growth more than doubling from
4.3 per cent to 9.1 per cent between the two sub-periods. Productivity also improved in the US
and Australia, with growth accelerating from 1.5 per cent to 1.9
per cent, and from 1.0 per centto 1.7 per cent between the two
periods, respectively.

5 Productivity

1970−2010%10

1970−1990

%

10

8

1990−2010

%

10

8

9.1

8

6.7

6

5.2

6
4.8
4.1 3.94

3.6 3.53.5 3.3

3.2

5.9

6

5.5 5.3
4.3

4

3.9 3.8 3.7

2.9 2.9 2.8
2.1

2

4.6 4.34

3.5 3.4
2.6 2.6

1.7 1.51.4

1.3

2

2.3
1.5 1.5

0.8

04.3 4.2 4.1

3.6

3.3 3.12
1.0

0

0.5 0.3

0.1

2.9 2.8

2.4 2.3 2.2

1.9 1.7 1.7 1.6

1.5

0Philippines
PakistanJapan
Australia
US
Indonesia
Bangladesh
IranSingapore
Hong Kong
Thailand
Malaysia
Cambodia
ROC
Vietnam
India
Sri Lanka
Korea
China

Philippines
Iran
Bangladesh
Australia
India
US
Vietnam
Pakistan
Sri Lanka
Malaysia
Indonesia
SingaporeJapan
Thailand
China
Hong Kong
ROC
Korea

Philippines
Iran
Bangladesh
Australia
US
PakistanJapan
Indonesia
India
Singapore
Malaysia
Sri Lanka
ThailandCambodia
VietnamHong Kong
ROC
Korea
China

Figure 43 Labor Productivity Growth, 1970–2010, 1970–1990, and 1990–2010___Average annual growth rate of GDP at constant basic prices per hour
Source: APO Productivity Database 2012.01.

1970−2010
%

4
3
2
1
0

%

3.9

4

3.0 3.0 2.9 2.9

2.6

1970−1990

4.4
3.6 3.6 3.5

4

3.4

3
2.4 2.3

2.2 2.2

2.0

1.8 1.7

2

1.6
1.1

−0.1

−1

1990−2010%

3.2 3.1

3.4
3.0

2.8 2.8

2.7 2.7

2.53

2.6 2.5 2.4

2

1.7

1

3.0

2.3

2.2

2.1
1.4 1.3 1.3

0.6

1

0

0

−1

−1

1.0

0.8 0.8

0.6 0.5

−0.8

Japan
US
Korea
ROC
China
Hong Kong
Fiji
ThailandMongolia
India
Philippines
Indonesia
Malaysia
Iran
VietnamSingaporeJapan
US
Hong Kong
Vietnam
Iran
India
ROC
Korea
Mongolia
ThailandChina
Fiji
Malaysia
Philippines
Indonesia
SingaporeJapan
US
Hong Kong
Korea
ROC
China
Mongolia
Thailand
Fiji
India
Iran
VietnamPhilippines
Malaysia
Indonesia
Singapore

Figure 44 Labor Input Growth, 1970–2010, 1970–1990, and 1990–2010___Average annual growth rate of total hours worked
Source: APO Productivity Database 2012.01.

©2012 Asian Productivity Organizationthat output growth was decelerating more than labor input in percentage points for labor productivity growth to slow. In China, output growth was reinforced by the slower pace of labor input growth
to result in an extraordinary surge in labor productivity growth. Labor input growth slowed to 0.8 percent a year on average in the latter period, from 3.2 per cent in the previous period. Japan was the only
economy to experience an actual fall in labor input in the period 1990–2010. This had worked to compensate for the sluggish output growth during that period, and to sustain a positive labor productivity growth of 1.7 per cent a year on average.
Table 11 looks more closely at the latter sub-period and provides the growth rates of per hour-basedlabor productivity since 1990. The growth patterns of individual countries generally follow closely
their counterparts in per worker productivity growth as presented in Table 9, but the two measures
diverge, in some countries largely, and are not consistent throughout all the periods compared. For
example, per hour productivity growth had been higher in Japan than per worker productivity
growth, suggesting that growth in hours worked had been less strong (or falling faster) than the number of workers. This contrast was particularly stark in the first half of the 1990s, when Japan’s hourly
productivity growth was 2.0 per cent compared with 1.0 per cent in per worker productivity growth.

72

5.2 Per Hour Measure of Labor Productivity

Table 11 Labor Productivity Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2010___ Average annual growth rate of GDP at constant basic prices per hour, using 2005 PPPs
1990–1995
China
Sri Lanka
ThailandIndonesia
Malaysia
Cambodia
ROC
Korea
Hong Kong
VietnamSingapore
India
Pakistan
Bangladesh
Japan
Iran
Philippines

1995–2000
10.6
9.0
7.4
6.5
6.4
5.6
5.2
5.2
4.6
4.3
3.8
3.4
3.1
2.5
2.0
1.4
0.1

(reference)

China
ROC
Korea
Bangladesh
Singapore
Vietnam
India
Sri Lanka
Japan
Philippines
Cambodia
Iran
Malaysia
PakistanThailandHong Kong
Indonesia

2000–2005

7.1
4.5
4.4
4.1
3.7
3.1
2.5
2.2
2.0
1.9
1.7
1.0
0.8
0.6
0.4
0.2
−1.2

(reference)

US

1.4

Australia

2.2

US
EU15
Australia

China
Vietnam
Korea
Cambodia
India
Indonesia
Hong Kong
ROC
Thailand
Malaysia
Singapore
IranPakistanJapan
Philippines
Sri Lanka
Bangladesh

2005–2010

8.6
6.3
4.2
4.0
3.9
3.3
3.1
3.1
2.9
2.8
2.7
2.3
2.2
1.8
1.4
0.8
−0.5

(reference)

2.3
1.9
2.3

US
EU15
Australia

China
India
Sri Lanka
Iran
Korea
Cambodia
ROC
Hong Kong
Vietnam
Malaysia
Bangladesh
Philippines
ThailandSingaporeJapan
PakistanIndonesia

1990–2010
10.2
7.4
5.4
4.9
4.4
4.2
3.6
3.5
3.2
3.0
2.9
2.7
1.8
1.1
1.1
0.6
0.2

(reference)

2.4
1.3
1.8

US
EU15
Australia

China
Sri Lanka
ROC
Korea
ThailandSingapore
Vietnam
Malaysia
Bangladesh
India
Cambodia
Indonesia
Hong KongJapan
Pakistan
IranPhilippines

2000–2010
8.8
5.6
4.9
4.8
3.9
3.7
3.7
3.6
3.3
3.0
2.8
2.7
2.4
2.0
1.9
1.2
1.0

(reference)

1.4
0.7
0.7

US
EU15
Australia

China
India
Vietnam
Korea
Cambodia
Iran
ROC
Hong Kong
Sri Lanka
Malaysia
ThailandPhilippines
Singapore
Indonesia
Japan
Pakistan
Bangladesh

9.4
5.6
4.8
4.3
4.1
3.6
3.3
3.3
3.1
2.9
2.4
2.0
1.9
1.8
1.5
1.4
1.2

5

(reference)

1.9
1.9
2.2

US
EU15
Australia

1.9
1.0
1.3

Unit: Percentage.
Source: APO Productivity Database 2012.01.
Note: The annual average growth rates for Cambodia and Vietnam during 1990–1995 are their annual average growthover 1993–1995 because of the lack of hours worked data.

However, the divergence has been narrowing to 0.5 percentage points in the 2000s. Korea is anothercountry in which hourly productivity growth was consistently higher than its per worker counterpart,but instead of narrowing, the divergence widened to 1.4 percentage points in the second half of the
2000s. Hours worked in the ROC have also been growing slower than the number of workers, but thewedge ranged from 0.4 to 0.6 percentage points. Such a trend has not been discerned in Singapore orHong Kong.
Sometimes, the two labor productivity measures can paint different pictures.42 For example, in Hong
Kong, labor productivity growth decelerated according to the per worker measure (from 3.3 per centto 3.0 per cent) but accelerated according to the hourly measure (from 3.1 per cent to 3.5 per cent)between the two halves of the 2000s. Similarly in India, per worker productivity growth accelerated
from 2.4 per cent to 3.4 per cent between the two halves of the 1990s while hourly productivity
growth decelerated from 3.4 per cent to 2.5 per cent over the same period. For Cambodia and Vietnam, hourly productivity growth is much more volatile than per worker productivity.

42: For China and Thailand, both measures give the same productivity growth. This is a result of a statistical construct in our current
database rather than the underlying trend.
43: While we are mindful that level comparisons of productivity among countries and over periods are subject to a great degree ofdata uncertainty, they should provide a rough sketch of the productivity divergence in Asia.

73©2012 Asian Productivity Organization

We can identify where countries are today in hourly productivity performance against Japan’s historical experience.43 Figure 45 traces the long-term path of Japan’s per hour labor productivity for theperiod 1885–2010 along the red line, expressed as relative to Japan’s 2010 level (set equal to 1.0). A
structural break is observed during World War II when output collapsed. Countries’ relative hourly5 Productivity

productivity levels against Japan
in 2010 are then mapped against
Japan’s growth experience (ascircles). By so doing, we locate thecorresponding year when Japan’shourly productivity level was theclosest to that of the country under concern. The three countries(i.e., Cambodia, Nepal, and Bangladesh) with the lowest hourly
productivity in 2010 have theirlevels corresponding to Japan’s in
the 1900s. This means that even if
they manage Japan’s long-term
productivity growth of 2.8 percent on average per year, it will
still take them over a century tocatch up with the Asian leaders(i.e., Singapore, Hong Kong, andJapan) today. However, Nepal’s
productivity growth has beenslower than what has beenachieved in Japan, whereas thoseof Cambodia and Bangladesh are
doing better. Most Asian countries are clustered around Japan’slevel achieved in the 1950s andearly 1960s. Among them, China
has been leading in the catch-up
effort, with productivity growing
three times faster than Japan’slong-term average (Table 11), followed by India and Vietnam.

Labor productivity gap in 2010 relative to Japan(Japan's level in 2010=1.0)

Singapore
Hong Kong

1.0
Japan (1885−2010)
0.9

ROC

0.8
0.7

Korea

0.6
Iran

0.5
0.4

Malaysia

0.3
0.2
Bangladesh

0.1
0.0

Cambodia Nepal

Fiji
Philippines
India
China

ThailandSri Lanka
Mongolia
PakistanIndonesia
Lao PDR
Vietnam1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Figure 45 Labor Productivity Trends of Japan over Century
and Levels of Asian Countries in 2010___GDP at constant basic prices per hour, using 2005 PPPs

Sources: For historical data of Japan, the sources of GDP are Long-Term Economic
Statistics by Ohkawa et al. (1974) during 1885–1954 and the JSNA by ESRI, Cabinet Office of Japan, during 1955–2010 (including author adjustments). Hours worked data isbased on KEO Database (Kuroda et al. 1997), Keio University, during 1955–2010. During 1885–1954, the average hours worked per person are assumed to be constant. For
the labor productivity level of Asian countries in 2010, it is based on the APO Productivity Database 2012.01. The estimates for Fiji, Iran, the Lao PDR, Mongolia, and Nepal
are defined by per-worker labor productivity due to data constraints.

1965

1975

1985

1969

1995

Japan (21)

1990

1971

Singapore (23)

1994
1977

Hong Kong (17)

1994
1987

©2012 Asian Productivity Organization

2005

2005

ROC (18)

Korea (19)
1991
2010
At the top end are the Asian Tigers, among which Singaporeand Hong Kong have already surFigure 46 Time Durations Taken to Improve Labor Productivity by Japan and the Asian Tigers
passed Japan. Figure 46 compares
the time periods taken by each
Sources: See Figure 45.
country to raise its labor productivity from 0.3 to 0.7 of Japan’slevel today (i.e., unit of measurement on the y-axis of Figure 45). What Japan and Singapore hadachieved in 21 years (from 1969 to 1990) and 23 years (from 1971 to 1994), respectively, Hong Kong,
the ROC, and Korea achieved in less than two decades (Figure 46). Although the speed of catch-up forlatecomers is increasing, it will still take a long time to catch up with the leaders for most Asian countries that currently cluster around the level Japan achieved in the 1960s.

745.3 Total Factor Productivity

5.3 Total Factor Productivity
Labor productivity in the previous sections is only a one-factor or partial-factor productivity measureand does not provide a full perspective of production efficiency. An observation of low labor productivity could suggest production inefficiency, but it could also be a mere reflection of different capitalintensities in the chosen production method under the relative labor–capital price faced by the economy concerned. By observing relative movements in labor productivity alone, it is not easy to distinguish which is the case. In populous Asian economies, which are relatively abundant in low-skilledlabor, production lines may be deliberately organized in a way that utilizes this abundant, and hence
relatively cheap, resource. It follows that the chosen production method is most likely to be (lowskilled) labor-intensive with little capital, manifested in low labor productivity. This is why economists
analyze TFP, which is GDP per unit of combined inputs, to get a more complete picture of a country’s
production efficiency.44

5Capital input is a key factor for measuring TFP, and is defined by capital services – the flow of services
from productive capital stock, as recommended in the new system of national accounts.45 The required basis for estimating capital services is the appropriate measures of capital stock. The SNA recommended constructing the national balance-sheet accounts for official national accounts, but this is
still not a common practice in the national accounts of many Asian countries.46 Even where estimatesof net capital stocks are available for the whole economy, the assumptions and methodologies candiffer considerably among countries. In response to this challenge, harmonized estimates for productive capital stocks and capital services have been constructed and compiled within the APO Productivity Database built on the same methodology and assumptions.47 In our methodology, changes in
the quality of capital are incorporated into the measurement of capital services in two ways: changes
in the composition are captured by explicitly differentiating assets into ten types, and an appropriate
and harmonized deflator is used for IT capital to reflect the rapid quality change embodied in ITrelated assets (see Appendix A.2).

44: Different types of inputs and outputs are aggregated by using index numbers, and TFP is calculated as the output quantity
index divided by the input quantity index. In this chapter, the Törnqvist index is used for aggregating labor and 10 types ofcapital inputs.
45: See the chapter on capital services and the national accounts of the 2008 SNA (United Nations 2009). The second edition of theOECD Capital Manual (2009) provides a comprehensive framework for constructing prices and quantities of capital services.
46: Based on our metadata survey, half of APO member economies do not estimate the balance-sheet accounts within the official
national accounts; these countries are Bangladesh, the ROC, Iran, Korea, the Lao PDR, Mongolia, Nepal, Pakistan, Sri Lanka, andVietnam (but the National Wealth Survey is available in the ROC and Korea for some selected years).
47: The Department of Statistics Malaysia (2011) published a new set of comprehensive capital stock statistics in April 2011, by following the OECD Capital Manual (2009). The correlations between these official estimates and our estimates for the period of
1970–2010 are high; they are 89.9 per cent and 94.0 per cent for the growth rates of net and productive capital stock, respectively.
In this report, capital input is defined as capital services computed from our estimates of productive capital stock, so as to ensurethat the same methodology and same asset classification are applied for the 15 Asian countries compared.
48: In measuring TFP, income generated from domestic production should be separated into labor compensation and returns tocapital. The national accounts readily provide the estimates of labor compensation for employees as a component of value added;labor compensation for the self-employed is not separately estimated but is combined with returns to capital in mixed income. Asa crude approximation in this Databook, we assume that the per worker wages for self-employed and family workers are 30 per
cent of the per worker wage for employees, using the evidence in the studies for Japan by Kuroda et al. (1997), in order to measure total labor compensation. Note that in the current database this simplification is applied to all countries except China, wherelabor remuneration in the national accounts includes labor income for the self-employed (Holz 2006). For sensitivity of our TFP
results to our assumptions, see Box 7.

75©2012 Asian Productivity Organization

The current APO Productivity Database estimates capital services and TFP for 15 Asian countries forwhich long-time investment data by type of asset are available or estimated.48 Their economic growthis decomposed into its sources from factor inputs and TFP based on the methodology developed byJorgenson and Griliches (1967). This report defines output as GDP at basic prices, and factor inputs as

5 Productivity

labor, IT capital, and non-IT capital.49 Labor input is measured by total hours worked (except for Fiji and
Mongolia), without adjustments for changes in labor quality.50
Cross-country comparisons of TFP growth for the 15 Asian countries and the US are shown in Figure
47 for the period 1970–2010, and the two sub-periods 1970–1990 and 1990–2010. Taking the US as
the reference economy, with TFP growth of 0.8 per cent on average a year, countries fall into three
general groups. Over the entire estimation period, China, Korea, Thailand,51 Vietnam, Hong Kong, theROC, and India achieved significantly higher TFP growth than the US. Within this group, China is in aleague of its own, with TFP growth being 60 per cent faster than that of Korea, while TFP growth in theother countries was 50 per cent to over 100 per cent faster than the US. Indonesia and Mongolia
achieved similar productivity growth as the US, whereas productivity performance in the Philippines
actually deteriorated by 0.18 per cent on average per year over the same period.52
Looking at the sub-periods (i.e., 1970–1990 and 1990–2010), we can discern that the two were not
identical and in fact had quite significant differences in terms of the magnitude of growth and countries’ relative performance. Eight of the 15 Asian countries experienced acceleration in TFP growth.
China and Iran accelerated the most between the two sub-periods: from 1.8 per cent to 4.7 per cent,and from −1.4 per cent to 2.1 per cent, respectively. More modestly, Mongolia’s productivity growth,for example, improved from −0.1 per cent on average a year in the earlier period to 1.5 per cent since1990.53 Four countries saw their productivity growth more than halved: Thailand, Hong Kong, Japan,
and Indonesia, all of which had a TFP growth under 1 per cent on average a year in the second half ofthe 2000s. TFP growth in the ROC, Malaysia, Korea,54 and the US was little changed.
1970−2010%

1970−1990%

54

1990−2010

%

5

5

4

4.7

4

3.2

3
2
1
0

3
1.8 1.8 1.7 1.72

1.5 1.4
0.9 0.9 0.7

0.6 0.5 0.5

1
0.4

0.0
−0.2

−1

0
−1

3

2.6 2.6
1.7 1.7

1.5 1.42
1.2

0.9 0.81

0.5 0.3

2.4

2.1
1.8 1.8

1.5 1.5

1.2

0.9 0.9

0.7

0.5 0.5 0.5

0.3 0.30−0.1−0.1
−0.3
−0.8

−1

−1.4

Fiji
Japan
Philippines
Malaysia
Indonesia
Hong Kong
ThailandUS
Singapore
ROC
Mongolia
Korea
Vietnam
Iran
India
China

Iran
PhilippinesFiji
Singapore
Mongolia
India
Malaysia
US
Japan
Indonesia
Vietnam
ROC
Korea
China
Hong Kong
ThailandPhilippines
Fiji
Iran
Malaysia
SingaporeJapan
Mongolia
Indonesia
US
India
ROC
Hong Kong
Korea
Thailand
Vietnam
China

Figure 47 TFP Growth, 1970–2010, 1970–1990, and 1990–2010©2012 Asian Productivity Organization

Source: APO Productivity Database 2012.01.
Note: The starting period for Vietnam is 1986. The labor inputs for Fiji and Mongolia are defined by numbers of employment.

49: IT capital is defined as a composite asset of IT hardware (computers and copying machines), communications equipment, andcomputer software.
50: The failure to take into account improvements in labor quality leads to TFP overestimation. The current APO Productivity Databaseestimates the labor quality index for only a handful of countries, and covering more Asian countries is the next challenge.
51: Warr (2006) shows that the average annual TFP growths of Thailand were 2.0 per cent in the period of economic boom (1987–1996),−9.0 per cent during the Asian financial crisis (1996–98), and 1.6 per cent in the period of recovery (1998–2002). These comparewith our estimates of 2.7 per cent, −8.7 per cent, and 2.5 per cent, respectively.
52: Negative TFP growth for both countries is also observed in other studies. Baier, Dwyer, and Tamura (2006) estimate the average annual growth rate of TFP of Fiji at −0.75 per cent during 1960–2000. Cororaton (2002) shows that the average annual TFP growth of
the Philippines was −1.09 per cent during 1970–2000.
53: In Mongolia, subsoil assets may have a significant role in economic growth, although they are omitted in our measures of capital inputs.

765.3 Total Factor Productivity

In terms of its contribution to economic growth, TFP has been playing a significant role in Asian fastgrowing economies in the past decades (Figures 48 and 49). During the period of 1970–2010, China
achieved the fastest output growth of 8.7 per cent on average a year. This is followed by Singapore
and Korea, growing at 7.1 per cent and 6.9 per cent on average a year, respectively. Annual average
growth in the ROC and Hong Kong was 6.6 per cent and 5.7 per cent, respectively, while it was 5.9 percent in India. Japan achieved a growth similar to the US at 2.7 per cent. Out of these GDP growths, the
TFP contribution accounted for over 20 per cent of economic growth in 7 of the 15 Asian countries
compared. Among them, the TFP contribution was the largest in China (37 per cent), Thailand (31 percent), and Hong Kong (29 per cent). This compares with 31 per cent in the US. Its contribution wasamong the lowest in Singapore and Malaysia (8 per cent), and was negative in the Philippines. Negative TFP growth, if not due to measurement errors, is not sustainable in the long run. Looking at the
breakdown of the period in Figure 50, we can see that the Philippines was running an overall negative
TFP growth only in the period 1970–1985, at −2.0 per cent on average per annum,55 whereas its TFP
growth was positive in the subsequent two periods.

5

It is clear from Figure 49 that economic growth was predominantly explained by the contribution ofcapital input in most of the Asian countries, which ranged from 39 per cent in Fiji to 80 per cent inJapan. Among the Asian Tigers, the contribution of capital services ranges from 56 per cent in Hong
Kong to 67 per cent in Singapore, whereas in China and India, it accounted for 51 per cent and 55
per cent of their economic growth, respectively. This compares with 43 per cent in the US, of which
16 percentage points were contributed by IT capital, a share unmatched by Asian countries. Japan%9

IT capital
Output8
7

3.2

Non-IT capital80

1.7 1.8
1.5 0.5
1.7 1.8

4.2

3.8
0.6

2.8

3.7

4.2

8

8

Labor

25 26 23

37

15 15

16

9

29 31

31

2.7 2.4

0.0

41

0.1 0.1

0.2

0.3

0

3
12

9

29
15

2
6

2

5

16 20

6
30 30
16

−0.1

6

5

4

16 68

2

61
40

22 21

26 12

27

−5

−2

Fiji

Indonesia
India

Malaysia
ROC
Vietnam
Korea
Singapore

China

Fiji

Japan
US

Philippines

ThailandIranMongolia

Hong Kong
Indonesia

India
Malaysia
ROC

Vietnam
Korea

China

−20

59
49 43

4
5

26

55

27

Japan
US

−0.2

20

48

61

67 53 53

Philippines
Iran
Mongolia
ThailandHong Kong

0.9 0.6 0.9
0.1
0.7
0.4
0.2
0.4
0.2 0.1
0.4 1.8
1.9
1.8
1.8 1.8
1.6
1.5
1.1
1.0 1.3
1.0
0.9 1.2 1.0 1.1
0.7 0.3
0.3

35
3

58
55

2.2

22
59

60
40

TFP
0

0.4

3.1 3.1
2.8 2.4

0.4 0.3

Singapore−1

Non-IT capital

0.7

4

0

IT capital

0.9 0.9
4.1

1

120

0.5

5

2

TFP

100

6

3

Labor

Figure 48 Sources of Economic Growth,
1970–2010

Figure 49 Contribution Shares of Economic Growth, 1970–2010

Source: APO Productivity Database 2012.01.
Note: The starting period for Vietnam is 1986. The labor
input for Fiji is defined by numbers of employment.

Source: APO Productivity Database 2012.01.
Note: The starting period for Vietnam is 1986. The labor
input for Fiji is defined by numbers of employment.

54: Note that economic growth at the aggregate level for Korea has been revised upward considerably in the KSNA published in 2010.
The main revisions stem from the introduction of a chain index in Korea’s system of national accounts. As a result, Korea’s GDP
growth at constant market prices has been revised up from 7.0 per cent to 8.6 per cent on average in the 1970s, from 8.4 per centto 9.3 per cent in the 1980s, and from 5.9 per cent to 6.3 per cent in the 1990s.
55: The Philippine economy shrank by 15.2 per cent for two years from 1983 to 1985 under the regime of Ferdinand Marcos (seeFigure 37).

77

©2012 Asian Productivity Organization%

5 Productivity

1985−2000

1970−1985%

2000−20109

1.0 0.8

6

6.3

2.3 2.2 0.8

2.2

1.3

1.8 1.7 2.2 1.5
−1.0

0.5
4.4

0.1
0.0
1.3

3.9

2.2
3.2

2.3

0.1

0.1

1.5 0.8 0.8

3.4

2.8 1.8

4.1

US
Fiji
Philippines
Iran
India
Japan
ThailandMongolia
Malaysia
Indonesia
China
Hong Kong
Singapore
ROC
Korea

IT capital

1.9

3.2 2.3 1.4 1.0
4.1

1.4 1.5−0.2−0.9

2.1 2.2
2.0 1.5
1.4 2.7 0.6 0.2 1.8
1.8
1.0
0.5 0.3
0.4 0.6 0.4
0.2
1.2 1.7 0.7 0.5 0.7
0.2
1.8
0.6
0.4 0.3 0.6
1.6 1.9
0.5 0.1 0.2
1.1 1.2 1.3 0.8
1.0 0.6 1.0 0.3
0.1
0.3
0.4 0.3−0.1 0.3 0.2
−0.3
0.4

3.7
0.8

0.9

0.1
0.1
0.9
0.0 0.1
2.4 2.8
2.0 1.6 0.1 1.6 0.3
0.3
1.4 1.3
1.0
0.8
0.3
0.0
−1.3
−1.8−2.0

4.8

Japan
Fiji
US
ROC
Hong Kong
Korea
Thailand
Malaysia
Philippines
Indonesia
Singapore
Iran
Mongolia
Vietnam
India
China

0.2

3.9

5.2

3.2

2.1 1.1

Mongolia
Japan
Fiji
Iran
US
Philippines
Hong Kong
Indonesia
India
Thailand
Vietnam
Malaysia
ROC
Korea
Singapore
China

3.5
0.5
0.3 0.4

−3

2.2

0.3

2.1
4.1

0

1.5
0.8

5.4 5.3

3

4.3

3.5

0.0

0.1

3.2

0.5 0.5

1.3 1.6 1.0

0.9

Non-IT capital

0.2
0.3
2.5
1.3

3.6
0.4
1.1

2.2

2.8

0.1 0.2
1.6 1.5

3.1

0.5

1.0

4.7

1.2 1.0 0.7

1.8 0.6
1.8
0.7 0.6
0.5 0.2
1.6 0.1
0.6 0.1 0.1
0.4 0.8
0.6 0.9 1.1 1.0 1.2

Labor

2.9

1.9 2.0

TFP

OutputFigure 50 Sources of Economic Growth, 1970–1985, 1985–2000, and 2000–2010
Source: APO Productivity Database 2012.01.

has been leading Asian countries in terms of contribution from IT capital (12 per cent of economic
growth) whereas it has been 3–10 per cent in other Asian countries, with China and India at the low
end. However, labor input growth explained 61 per cent and 40 per cent of economic growth in Fijiand the Philippines, respectively, during this period. In Japan, the contribution of labor input has been
negative overall.
China’s productivity performance has been outstanding in this period. The average TFP growth was
3.2 per cent per year during 1970–2010 (Figure 48). This compares to the long-run estimates of 3.8 percent during 1978–2005 in Holz (2006) and also 3.8 per cent during 1978–2004 in Bosworth and Collins(2008). The Chinese experience of long-term TFP growth of about 3 per cent is not unprecedented in
Asia. According to Jorgenson and Nomura (2005), Japan achieved an annual TFP growth of 3.1 percent during 1960–1973, even after improvements in labor quality had been taken into account in theestimation of labor growth (and, as such, eliminating overestimation in TFP).56 Both the ROC and Korea
also achieved a TFP growth of 2.2 per cent during the period 1985–2000,57 as shown in the second
chart of Figure 50, whereas in the last decade, TFP growth was 3.2 per cent in India.

©2012 Asian Productivity Organization

One prevalent characteristic of Asian countries is their investment intensity as a share of GDP (Figure30) and in turn its contribution to economic growth (Figures 49 and 51). There is policy significance in
identifying the driver(s) behind the rapid economic growth in Asian countries. If growth has been
driven more by capital accumulation rather than capital assimilation, the Asian model may prove to
be too expensive for many less well-off countries to be relevant. According to our findings (Figures 50
and 51), it is true that, historically, capital accumulation has played a much more significant role in the

56: In the same period 1960–1973, the average annual contribution rate of labor quality improvement to growth is measured as 0.54
per cent in Jorgenson and Nomura (2005). As a measure of the TFP contribution that is comparable with the estimates in thisDatabook, their estimate can be recognized as 3.6 per cent per year during the same period.
57: The National Statistics, Republic of China, published the TFP estimates for the period 1982–1999. The correlation of TFP growth
rates between their estimates and ours is 0.76 for the whole period. For 1985–2000, our estimate is around 1 percentage point
smaller than their estimate of 3.6 per cent (1985–1999), but closer to the 2.0 per cent (1985–1996) in Timmer and van Ark (2000).

78

5.3 Total Factor Productivity

1970−1985

%

120
100

12

2 28

35

4

59
47

5

52

21 21

1
3

20
27

0
−12

39

18
30 33

31

28

15 16 16
28

28 23

30

75
1

2

2

1

1

20 17

37

2
13

26

95

30

19

40

84

7 38 37

50 47

10
45

71

33

28 58

2
6

22

53
41

7

14 13

62

52 19
18

3

11

2
15

8

71

46

5
38
20

6

3

6

20
7
24 4 66
47

30 29
17

−1

26

33 34

42

15

3

30

14

40 10 25
10
36
30

38 39
22
8

5

21

47

31
14 8 42
10

37
22

14

46

9

9
−2

6
−16

−50

−56

Japan
Fiji
US
ROC
Hong Kong
Korea
Thailand
Malaysia
Philippines
Indonesia
Singapore
Iran
Mongolia
Vietnam
India
China

Non-IT capital

Labor

5

34

22 8

Mongolia
Japan
Fiji
Iran
US
Philippines
Hong Kong
Indonesia
India
Thailand
Vietnam
Malaysia
ROC
Korea
Singapore
China

US
Fiji
Philippines
Iran
India
Japan
ThailandMongolia
Malaysia
Indonesia
China
Hong Kong
Singapore
ROC
Korea

IT capital

15 17

39

40

10 4

3

−9
−52 −58 −39

40
2

6

12

46
31 33
48 52 50

35

22 45
7

45

20

51

58

2

10

25
39

43 43
34

75
72

7
3

21

62

64 65

40

5

11

13

30 30
79

−20

2000−2010
98

0
12 9

80
60

1985−2000
113 83 54

TFP

Figure 51 Contribution Shares of Economic Growth, 1970–1985, 1985–2000, and 2000–2010
Source: APO Productivity Database 2012.01.

Asian countries than in the US. However, the relative contribution shares are not constant across countries and over time; there have been periods when (and in some countries where) capital assimilation
as reflected in TFP growth also contributed significantly toward driving growth.

Figure 52 places our estimates among those of OECD for 16 other OECD countries to give readers awider perspective.58 Countries are arranged according to their average economic growth per annum
for the past decade in descending order. In so doing, the wedge in economic growth is clearly displayed, with all Asian countries (barring Fiji and Japan) having been filtered out to occupy the top end.
Ireland is the only fast-growing economy from Europe. Asian countries are also among those that experienced the fastest TFP growth in the 2000s: 4.3 per cent in China, 3.2 per cent in India and Mongolia,

79©2012 Asian Productivity Organization

Looking at Figure 51, capital accumulation was the dominant factor in the early period 1970–1985,
typically explaining two-thirds to three-quarters of economic growth achieved. In China, Hong Kong,
and Thailand, however, the contribution of TFP growth was still significant, accounting for 30–35 percent of their respective economic growth. In the subsequent periods, the contribution of capital input
became progressively smaller, falling to a share of below 50 per cent on average, while the contribution of TFP became progressively more significant, rising to a share of above 40 per cent on average inthe 2000s. The evident rise in the contribution of IT capital is also noteworthy. In 1970–1985, IT capital
accounted for below 5 per cent of economic growth in all Asian countries, except Japan. By the 2000s,
the IT capital share rose to above 5 per cent in most countries, with the exceptions being India, Iran,and Indonesia. Between 1985–2000 and 2000–2010, the contribution of IT capital more than doubled
in Fiji, Malaysia, and Japan, from 4 per cent to 10 per cent, from 5 per cent to 14 per cent, and from 15
per cent to 36 per cent, respectively. Hong Kong sustained an IT share of 10 per cent over the same
periods. This yearly accumulation of IT investment may have paved the way for countries to capitalizeon the productivity gain from the IT revolution. Reflecting on these results, capital accumulation appears to be a necessary step to economic growth, and countries may go through cycles of capital accumulation and assimilation. Although a prerequisite, capital accumulation does not guarantee TFP
growth. Some countries may be more capable than others in reaping the benefits through capital assimilation, but the reasons as to why this is so are beyond the scope of this report.

5 Productivity

%

9

4.4

6

TFP

Capital

4.3

3.2

5.3
1.1

3.2

2.3
2.9

1.4
2.5

1.0
2.2

1.4
2.2

1.7

3

1.5
2.4

2.1
1.3

2.2

1.3
1.1

2.1

2.0
1.6

1.5

0.4
1.3

2.1

0.4
1.0

3.2

0

0.3

Output

1.3
4.5

3.1

1.1

Labor

1.2

1.3

0.8

1.6

1.9

1.0

0.6

1.6

1.0

1.5
0.3

−0.1

1.2

1.1
0.9
0.5

0.2

0.1
1.1
1.4
0.5
0.3

1.1
0.6
0.3

0.1
1.0
0.8

0.8
0.0

0.9
0.5
1.0
0.5

0.2

0.8
0.7
0.1

0.7
0.4
1.1 0.6

0.3
0.6

0.5

0.6

0.2
0.7
0.2

−0.3

0.5
0.2

0.7 0.7
0.5

0.4

0.3
−0.4

−0.9

Italy

Japan

Fiji

FranceSwitzerland

Belgium

US

SwedenFinlandDenmark

Germany

Spain

Netherlands

Austria

United Kingdom

New ZealandAustralia

ROC

Hong Kong

CanadaThailand

Korea

Malaysia

Philippines

Indonesia

Singapore

Iran

Mongolia

VietnamIndia

IrelandChina

Figure 52 Comparison of Sources of Economic Growth with OECD Countries, 2000–2010
Sources: APO Productivity Database 2012.01 for APO member economies and China and the US; OECD Stat (Dataset: Multi-Factor Productivity) for OECD countries (except Japan and Korea). The ending years are different: Denmark, the Netherlands, and the UK are until 2008 andAustralia is until 2009.

2.2 per cent in Korea, and 2.0 per cent in Hong Kong. Their performance was only beaten by Ireland,with TFP growth at 4.4 per cent. Though growing at a more subdued pace, the contribution made by
TFP in the slower-growing, mature economies should not be underestimated: TFP accounted for half
or more of economic growth in, for example, Austria, the Netherlands, Finland, Germany, and the US.

©2012 Asian Productivity Organization

Figure 53 and Table 12 show the growth accounting decomposition for individual countries in fiveyear intervals covering the period 1970–2010. It is clear that there has been a slowdown in long-term
overall growth in Japan and the Asian Tigers when compared with their own performance in the 1970s.
The deceleration, from 4.9 per cent in the late 1980s to 1.4 per cent in the early 1990s, was particularly sharp in Japan, and since then, its growth has never recovered. Korea and Singapore achieved
their peaks in economic growth in the late 1980s, whereas Hong Kong and the ROC achieved theirs in
the late 1970s. Although their growth performance in the most recent period of 6 per cent for Singapore and 3–4 per cent for the other three Tigers is still robust compared to other mature economies,
it is a shadow of their own heydays. In contrast, in the past four decades, growth in China and India
has been on a clear path of acceleration. Still, the experience of the Asian Tigers lends support to thelikelihood of a slowdown; the question is more likely to be when than if (See Box 5). In other countries,
their development efforts have been more interrupted. Since the Asian financial crisis, growth in Thailand, Malaysia, and Indonesia has not yet returned to these countries’ former peaks even after morethan a decade.

58: The multi-factor productivity in the OECD Productivity Database, referred as TFP in this report, defines total input as the weighted
average of the growth rates of total hours worked and capital services. Comparing OECD’s TFP estimates for the whole economy
with ours, there are mainly two differences in assumptions. First, capital services of residential buildings are included in our estimates of capital input in order to be consistent with output that includes the imputed cost of owner-occupied housing. Second,the compensation of capital is defined in our estimates as the residual of the value added and the compensation of labor (compensations for employees, self-employed persons, and contributing family workers), whereas the OECD defines it as the imputed
value of capital services based on the assumptions of an ex-ante rate of returns on capital. Thus, although both apply the same
Törnqvist index, the weights to aggregate labor and capital can differ. Other than these, our methodology and assumptions inmeasuring capital services are designed to be largely consistent with the OECD methodology, and the impact of the differencesin assumptions on the volume estimates of capital services is judged to be limited.

80

5.3 Total Factor Productivity

China

%

12

ROC

%

10

Fiji

%

6

Hong Kong

%

12

2.2

8

8
6
4
2

3.1
2.8
0.5 1.2
0.7
1.0 1.1
1.8
0.6
4.3 3.8 4.3
4.2 4.0
3.4
0.0 0.0 0.0 0.1 0.1 0.2

4.1
0.2

5.3

4.2

0.7 0.6

2005–2010

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

0.8

1.7
0.9

0.7
1.3

0.9 1.2
0.7 0.7

1.1 1.0 0.7 0.7 0.5

1.2
0.7 0.3
0.6 0.6
0.3

0.2 0.3 0.4 0.5 0.5 0.8 −0.1 −0.4

2005–2010

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

TFP

1975–1980

1970–1975–1

2005–20100

2000–2005−0.4
2005–2010

2000–2005

1995–2000

1990–1995

0.3

1995–2000

0.6

0.2 0.1 0.3

1990–1995

3.3

1

1985–1990

2

0.5

1.5

0.6

0.5

1986–1990

2005–2010

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

Labor

1980–1985

1.6 1.2

2.7

0.5 0.3

US

1.2

1.8

3.1

4.9

1.6 3.02

1975–1980

–8

4

4

0.9 2.0
1.2
0.9
1.9
1.7

−6.4

–4

3

1.4

2.0

%

2.7

2005–2010–2

2000–2005

1.9
0.7
2.6
1.0
2.6
3.5 3.1
1.0
2.0
1.9 0.4
0.1 0.8 0.1
0.1 0.1
0.1
−0.2
−0.8

2

3.3

1970–1975

2005–2010

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

Vietnam

3.6 1.1

1995–2000

4

–6

−2.6

6

1990–1995

0.2 0.30

0.5
0.3 0.4

Philippines

60.7
2.0 2.3

2.0
1.8 0.2 0.9
0.9 0.3
0.4 0.3 0.3 0.4 0.5
0.1−0.4 −0.7 −0.4 0.1
0.2 0.2−0.3−0.5
1985–1990

4.0

−0.7

0.4

2.0

1980–1985

2.4

0.5
0.2 0.2 1.0
0.1 0.5
0.0 0.1−0.2 0.1−1.6−2.6

1975–1980

–3

2.9

3.5

2.0

0.4
2.7

1975–1980

2.3

3.0 3.3

05

0.5 0.3

0.9 1.6
5.0

1970–1975

2005–2010

2000–2005

1995–2000

1990–1995

1985–1990

0.6

1975–1980
0.5

2

%

0.9 7.00

Non-IT capital

1970–1975

2005–2010

2000–2005

1995–2000

1990–1995

1985–1990

Mongolia

3.2

1.1
0.8
1.2
0.7 1.3
0.3 0.4

3

–1

8

1.9
0.3

4

–12

%

2.7
2.8
2.2 2.2 2.3
0.3
0.1−0.2 0.2 0.2 0.3 0.6−2.5

IT capital

2.0
1.9 1.6 0.1
1.1 2.4 3.0
1.1
0.1 0.2 0.2

1.9
1.2 0.8
0.9
0.2 0.1
0.1−0.1

0 −0.3

3

−2.1

1.8
2.2
0.5
0.2
1.3 1.2

Japan

–9

10

2.7
3.4 4.0 1.9
5.4 0.2
0.9

1970–1975

2005–2010

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

–4

0.6

–3

3.7 4.2 3.1 3.5 2.8
0.7

0.2 0.2 0.3 0.4 0.4

1

1980–1985–2

1980–1985

0.6 0.6

0.7

0

0.4

1970–1975

0

2.6

−9.7

1975–1980

2.0 1.8

0.5
4.4 5.3 1.2
2.1
0.1 0.0 0.0

1970–1975

2

2.0

0.7
1.5

2.8

0.2 3.6
1.9 0.9
1.0
1.2
0.4 0.25

2.9 1.1
1.6

3

1.9

6

1.0

2005–2010

1.2
2.3
0.9

0.4
0.3
0.2 0.1
0.1 0.0
−0.3

1.4

%

1.6

6

2000–2005

0.4 −1.1 0.8 0.9 0.7

4

1995–2000

3.0 3.3 3.9

1.6

−2.5

1990–1995

5.7

2.0 0.9

1985–1990

1980–1985

1975–1980

1970–1975

2005–2010

4.0
1.1

1.1

–6

Thailand%

1975–1980

−2.6

6

0.6

0.6

0
–3

3.9

9

0.5

0.2 0.3

1970–1975

0.1

3

1.3

Iran

%

1.4
6.0 5.3 0.6

3.1

6

2.3

2005–2010

0.1 0.1

6.0

10

0.1

2000–2005

4.8 4.9–2–4

1995–2000

0

1990–1995−0.3

2

1985–1990

1.6
0.2

2000–2005

1995–2000

1990–1995

1985–1990
2.0

7.9

−1.9

1980–1985

2.4

1.5

–3

0.2

1.6
1.1 1.5 1.5
1.1
1.4
1.7 1.7
1.9

8

5.3

2.9

Malaysia

0.2
2.4 1.5 2.5 1.9

3

1975–1980

4

0.3 0.5 0.4 0.5 0.5

1980–1985

1975–1980

1970–1975
2.6

0.8

2.5 3.1 2.9 1.7
0.1
0.0 0.1 −1.5 0.1 0.2 0.1 0.2−3.4

1970–1975

2005–2010

2000–2005

1.4 1.4

Singapore

6–3

1995–2000

−1.8

%

0

6

3.9 4.0 4.1 2.9 0.1
1.9

12
9

1.5

0.3
0.2

–6

8

6.5

2

–2

1990–1995

5.7

4.5 3.9%

1.3
0.3 1.9

0

9
0.1

3.5

2.6 0.7 1.2 1.9

10

3.8
3.2
1.2

4

0

1985–1990

1980–1985

1975–1980

1970–1975

6

2.2

1.9

2.3

6

0.7
1.0 1.2 0.7
0.1 0.0 1.3 0.1 0.3 0.7
0.0
0.0
−0.6
−0.2 −0.6
−1.2
−2.1

%

–3

Korea

%

1.5

1.6 2.3
2.0

2.8 1.9

2.0 2.1

12

0.0 0.1 0.1 0.1 0.2 0.2

108

2.1 0.2
1.4

2005–2010

0.0 0.0

0.6
0.2 2.4

2000–2005

3.6−0.4 −0.4

2.4 1.6

3.8

0

2.2 2.3 2.3 2.2 2.2 2.3 2.2

1.5

Indonesia3

1.9 1.8

2
0

6

1995–2000

0.9

3.3

1990–1995

2.0 2.1–2

1985–1990

1.1 1.1

0.4

3.1 3.4

0.5

2.6

1.8

4.0

1980–1985

4

1.3

0.7
1.3 1.1 0.3

5.2

2.8

3

2.2

0 −0.6 0.4 0.4 0.3 0.3 0.8 0.6 0.0

9

3.8
1.4

5.3

2

%

6
0.7

6.7

1975–1980

8

3.8

0.6
1.2

1970–1975

2005–2010

India

%

4

9

4.1

2.1

6

0.4

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

0

4.9 0.4

4.6

7.1

1.9

OutputFigure 53 Individual Countries’ Growth Accounting Decomposition, 1970–2010
Source: APO Productivity Database 2012.01.

81©2012 Asian Productivity Organization

10

5 Productivity

Table 12 Output Growth and Contributions of Labor, Capital, and TFP
Output©2012 Asian Productivity Organization

China
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Fiji
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
India
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Iran
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Korea
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Mongolia
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Singapore
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Vietnam

1986–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010

Labor

IT

CapitalNon-IT

5.7
6.3
10.2
7.6
11.6
8.3
9.3
10.6
8.7

1.0
1.1
1.8
2.8
0.6
0.7
0.4
0.2
1.1

5.6
3.7
0.7
3.8
2.7
2.1
2.0
0.1
2.6

4.1 (73)
2.8 (76)
1.5 (204)
1.0 (27)
1.9 (70)
0.7 (32)
0.3 (15)0.4 (286)
1.6 (61)

0.1 (1)0.0 (1)0.0 (6)0.1 (3)0.3 (10)0.0 (−2)
0.1 (5)0.1 (72)
0.1 (3)2.0 (36)
2.1 (56)
1.3 (178)−0.2 (−5)
1.2 (44)
0.7 (34)0.2 (12)0.0 (−27)
0.9 (35)−0.6 (−11)−1.2 (−34)−2.1 (−289)
2.8 (75)−0.6 (−24)
0.7 (36)
1.3 (68)−0.3 (−231)
0.0
(0)

2.9
3.1
5.0
5.8
5.0
5.7
6.8
8.1
5.3

1.1
1.1
2.0
2.1
0.9
1.9
1.8
0.4
1.4

0.0
0.0
0.0
0.1
0.1
0.1
0.2
0.2
0.1

2.2
2.3
2.3
2.2
2.2
2.3
2.2
3.6
2.4

(76)
(76)
(46)
(38)
(45)
(41)
(33)
(45)
(46)

−0.4 (−14)−0.4 (−13)
0.7 (13)
1.4 (25)
1.8 (36)
1.3 (23)
2.6 (38)
3.8 (48)
1.4 (26)

9.4
−2.9
3.8
1.4
3.7
4.1
6.8
5.2
4.0

1.1 (11)
1.6 (−55)
1.2 (31)
1.2 (89)
0.8 (23)
1.1 (26)
1.6 (23)
0.1 (1)1.1 (27)

0.0 (0)0.0 (−2)
0.0 (1)0.1 (4)0.1 (2)0.1 (2)0.2 (3)0.2 (3)0.1 (2)4.4 (47)
5.3 (−183)
2.1 (56)
0.2 (16)0.9 (24)
1.1 (26)
2.4 (35)
3.0 (57)
2.4 (61)

3.9 (41)−9.7 (340)
0.5 (12)−0.1 (−9)
1.9 (52)
1.9 (45)
2.6 (39)2.0 (39)
0.4
(9)

9.3
7.3
8.5
9.7
7.4
4.9
4.5
3.9
6.9

1.9
2.2
1.2
1.4
1.4
0.3
0.1
–0.3
1.0

(20)
(30)
(14)
(14)
(19)
(6)
(3)
(−9)
(15)

0.2 (2)0.3 (4)0.3 (3)0.5 (5)0.4 (5)0.5 (11)0.5 (12)0.2 (5)0.4 (5)

5.7
6.5
3.9
4.0
4.1
2.9
1.9
1.6
3.8

(62)
(90)
(45)
(42)
(56)
(58)
(43)
(41)
(55)

1.5 (16)−1.8 (−24)
3.2 (37)
3.8 (40)
1.5 (20)
1.3 (26)
1.9 (42)2.4 (63)
1.7 (25)

6.5
5.4
6.6
3.8
−1.8
3.6
6.3
6.3
4.6

0.6
0.9
1.0
2.3
−0.2
0.5
2.0
0.7
1.0

(9)
(17)
(15)
(59)
(12)
(14)
(31)
(11)
(21)

0.0 (1)0.1 (1)0.2 (3)0.2 (4)0.1 (−5)0.1 (4)0.3 (4)0.4 (7)0.2 (4)3.0 (46)
3.3 (62)
7.0 (106)
4.0 (105)
1.0 (−57)
0.5 (14)0.5(8)2.3 (37)
2.7 (59)

2.9 (45)
1.1 (20)−1.6 (−25)−2.6 (−68)−2.6 (150)
2.4 (68)
3.5 (56)
2.9 (46)
0.7 (16)

9.1
8.2
6.6
8.3
8.2
5.6
4.7
6.3
7.1

2.6
2.4
1.5
2.0
2.0
0.9
0.9
2.3
1.8

(28)
(29)
(22)
(24)
(25)
(16)
(20)
(37)
(26)

0.6
0.4
0.6
0.8
0.9
0.7
0.6
0.6
0.6

7.9
5.3
5.7
3.0
3.3
3.9
2.0
1.8
4.1

−1.9 (−21)0.2(2)−1.1 (−17)
2.5 (30)
1.9 (23)0.1(3)1.2 (25)
1.6 (25)
0.5
(8)

4.8
7.9
6.7
7.2
6.8
6.8

1.6
3.0
2.7
0.5
1.8
1.9

(18)
(17)
(18)
(37)
(5)
(8)
(4)
(2)
(12)

(37)
(36)
(39)
(36)
(18)
(33)
(27)
(5)
(27)

(34)
(38)
(40)
(7)
(26)
(29)

0.0
0.0
0.0
0.1
0.1
0.2
0.7
0.6
0.2

0.2
0.1
0.3
0.3
0.6
0.3

(1)
(1)
(0)
(1)
(1)
(3)
(7)
(5)
(3)

(1)
(1)
(1)
(1)
(2)
(3)
(2)
(3)
(2)

(6)
(5)
(9)
(10)
(11)
(12)
(13)
(9)
(9)

(4)
(1)
(4)
(4)
(9)
(4)

4.2
4.0
3.4
4.3
3.8
4.3
4.2
5.3
4.2

1.6
1.2
2.7
3.3
4.9
2.8

Unit: Average annual growth rate (percentage).
Source: APO Productivity Database 2012.01.

82

TFP

(73)
(64)
(33)
(57)
(33)
(52)
(45)
(50)
(48)

(87)
(64)
(86)
(36)
(41)
(70)
(42)
(29)
(58)

(33)
(15)
(41)
(45)
(71)
(41)

0.5
1.2
4.9
0.4
7.1
3.1
4.1
4.6
3.2

(9)
(19)
(48)
(5)
(61)
(37)
(44)
(43)
(37)

1.4 (29)
3.6 (46)
1.1 (16)
3.1 (43)−0.4 (−6)
1.8 (26)

OutputROC
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Hong Kong
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Indonesia
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010Japan
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Malaysia
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Philippines
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Thailand
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010US
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010

Labor

IT

CapitalNon-IT

8.5
10.1
6.2
8.5
7.0
5.1
3.5
4.0
6.6

1.9
2.1
1.2
1.3
1.1
0.3
0.2
0.2
1.0

(22)
(21)
(19)
(15)
(15)
(6)
(6)
(6)
(16)

0.5 (6)
0.4 (4)0.4 (6)
0.3 (4)0.3 (5)0.8 (16)0.6 (18)
0.0 (1)0.4 (6)

6.7
5.3
4.0
3.1
3.4
3.3
2.1
1.4
3.7

6.2
11.0
5.6
7.4
5.1
2.6
4.1
3.9
5.7

1.9
1.9
0.9
0.4
0.2
1.2
0.5
0.2
0.9

(30)
(17)
(16)
(5)
(5)
(48)
(12)
(5)
(16)

0.2 (3)0.2 (2)0.3 (5)0.4 (6)
0.4 (8)0.7 (25)0.5 (13)0.3 (8)0.4 (6)

2.8 (44)
3.7 (33)
4.2 (76)
3.1 (42)3.5 (68)
2.8 (109)
1.3 (32)
1.2 (30)
2.8 (49)

1.4 (23)
5.2 (47)0.2(3)3.6 (48)
1.0 (19)−2.1 (−81)
1.8 (43)
2.2 (57)
1.7 (29)

8.3
7.8
4.8
7.5
7.6
0.8
4.6
5.5
5.9

2.0 (25)
1.6 (20)
2.3 (48)
2.6 (35)0.7(9)1.2 (152)
0.8 (17)2.9 (53)
1.8 (30)

0.0 (1)0.1 (2)0.1 (3)0.1 (2)0.2 (3)0.1 (18)
0.2 (3)0.2 (4)0.1 (2)

3.8 (46)
4.5 (58)
3.9 (81)
2.5 (33)
3.1 (41)
2.9 (356)
1.7 (38)
2.3 (41)
3.1 (53)

2.4 (29)
1.6 (21)−1.5 (−32)
2.3 (30)
3.5 (47)−3.4 (−426)
1.9 (42)0.1(2)0.9 (15)

4.4
4.3
4.2
4.9
1.4
0.8
1.2
0.3
2.7

−0.3 (−6)
0.9 (22)
0.4
(9)
0.4
(8)
−0.4 (−26)−0.7 (−80)−0.4 (−32)−0.5 (−156)−0.1 (−2)

0.4
0.2
0.2
0.4
0.3
0.3
0.4
0.1
0.3

(8)
(5)
(6)
(9)
(23)
(39)
(34)
(47)
(12)

5.0 (114)
2.7 (62)
2.0 (47)
2.0 (41)
1.8 (125)
0.9 (111)
0.3 (26)
0.1 (20)
1.8 (68)−0.7 (−16)
0.5 (11)
1.6 (39)2.0 (42)−0.3 (−23)
0.2 (30)
0.9 (72)
0.5 (189)
0.6 (22)

7.7
8.2
5.0
6.6
9.1
4.7
4.6
4.4
6.3

1.7
1.7
1.5
1.5
1.1
1.4
0.6
0.7
1.3

(23)
(21)
(30)
(23)
(12)
(30)
(12)
(16)
(20)

0.1 (1)0.1 (1)0.1 (2)0.2 (2)0.3 (3)0.5 (11)0.7 (15)0.6 (13)0.3 (5)4.8 (62)
4.9 (59)
6.0 (120)
3.1 (46)
6.0 (67)
5.3 (113)
2.0 (43)
1.5 (35)
4.2 (67)

1.1 (14)
1.5 (19)–2.6 (−52)
1.9 (28)
1.6 (18)−2.5 (−54)
1.4 (30)
1.6 (36)
0.5
(8)

5.6
5.9
−1.3
4.6
2.2
3.5
4.5
4.8
3.7

3.3 (59)
2.0 (35)
1.9 (−146)
1.0 (22)1.0 (47)
0.7 (19)
1.2 (27)
0.9 (18)
1.5 (40)0.1 (2)0.1 (2)0.1 (−11)
0.1 (3)0.1 (3)0.4 (11)0.5 (11)0.3 (5)0.2 (6)

2.0 (36)
3.5 (59)
3.1 (−239)
0.8 (18)
1.9 (86)
2.6 (75)
1.9 (42)1.7 (35)
2.2 (59)

0.2
(3)
0.3
(5)
−6.4 (496)
2.6 (57)−0.8 (−36)−0.2 (−5)
0.9 (20)
2.0 (41)−0.2 (−5)

5.5
7.4
5.3
9.8
8.2
0.7
5.3
3.6
5.7

−0.2 (−3)
4.0 (54)
0.9 (17)
2.7 (28)0.3(4)0.2 (23)
1.2 (22)0.8 (22)
1.2 (22)0.1 (1)0.2 (2)0.2 (4)0.3 (3)0.6 (7)0.3 (44)
0.3 (6)
0.4 (11)0.3 (5)2.2 (41)
2.2 (29)
2.3 (43)
2.8 (28)
5.4 (66)
2.7 (381)
0.7 (12)1.3 (36)
2.4 (43)

3.4 (61)
1.1 (15)
1.9 (36)
4.0 (41)
1.9 (23)−2.5 (−348)
3.2 (59)
1.1 (31)
1.8 (31)

2.7
3.6
3.2
3.2
2.5
4.2
2.4
0.7
2.8

0.5 (20)
1.7 (48)0.9 (27)
1.3 (41)0.7 (28)
1.2 (29)−0.1 (−3)−0.4 (−61)
0.7 (26)

0.2
0.3
0.4
0.5
0.5
0.8
0.6
0.3
0.4

1.1
1.0
0.7
0.7
0.5
0.7
0.7
0.6
0.7

0.8
0.6
1.2
0.7
0.9
1.5
1.2
0.3
0.9

(8)
(7)
(14)
(16)
(18)
(18)
(25)
(47)
(16)

(79)
(53)
(65)
(36)
(49)
(64)
(59)
(34)
(55)

TFP

(42)
(28)
(22)
(22)
(19)
(17)
(29)
(77)
(27)

−0.6
2.2
0.6
3.8
2.2
0.7
0.6
2.4
1.5

(−7)
(22)
(10)
(45)
(31)
(15)
(17)
(59)
(23)

(30)
(17)
(37)
(20)
(34)
(35)
(49)
(37)
(31)

5.3 Total Factor Productivity

The relative importance of drivers behind economic growth changes over time. It is a common experience in most countries that a large part of the vibrant growth in the initial period was driven by input
growth while TFP growth became more prominent and made a steady contribution in the later periods. Hong Kong’s TFP growth peaked at 5.2 per cent in 1975–1980, and was robust at 3.5 per cent in
1985–1990, when TFP growth also peaked in the ROC, Korea, Japan, and Singapore, at 3.8 per cent, 3.8
per cent, 2.0 per cent, and 2.5 per cent, respectively. Thereafter, TFP growth slowed until recent years
when countries experienced a productivity growth resurgence. This resurgence is also shared by Malaysia and the Philippines. TFP growth in Mongolia has been particularly strong since 1995. It has also
bounced back in Indonesia59 and Thailand60 from negative after the Asian financial crisis of the late
1990s, but has softened again since 2005. In contrast, the US experienced a surge in TFP growth in thesecond half of the 1990s, which was sustained into the early 2000s before the adverse cyclical effecthit in 2005–2010. Over the whole period of estimation, TFP accounted for a quarter or more of economic growth in Hong Kong (29 per cent), the ROC (23 per cent), and Korea (25 per cent), while it was
22 per cent in Japan. In contrast, TFP performance has been erratic in Singapore, resulting in its relatively small contribution of only 8 per cent to economic growth over the same period. Among the lessdeveloped economies, TFP has been contributing 31 per cent to economic growth in Thailand, 15 percent in Indonesia, and 8 per cent in Malaysia.

5

Looking at the decomposition of economic growth in China and in India, the two key drivers havebeen non-IT capital input growth and TFP growth. While the contribution from non-IT capital has
been relatively stable in terms of percentage points, it is their TFP performance that has more bearing
in determining the overall economic growth over time. For example, the trough of economic growththat China experienced in 1985–1990 was largely explained by the lack of TFP growth. Similarly, when
output growth slowed from its peak in the latter half of the 1990s, it was due to the slowdown in TFP
growth from 7.1 per cent on average per annum in the previous period to 3.1 per cent. Thereafter,
output growth has accelerated to reflect largely the pickup in TFP growth in the 2000s. In India, TFP
growth was insignificant in the 1970s; since then, it has been accelerating and increasingly accounting
for a greater proportion of economic growth. In the second half of the 2000s, India achieved TFP
growth of 3.8 per cent – its highest in the past four decades. Through trials and errors, China and India
invested first and then learned how to combine the inputs efficiently. They have reaped the benefitsof their efforts in robust TFP growth, while the contribution from labor input growth dwindles in bothcountries over time.

59: Van der Eng (2008) provides estimates of capital stock for Indonesia and Van der Eng (2009) shows that annual average TFP growthincreased from −4.4 per cent during 1995–2000 to 1.7 per cent during 2000–2007 in Indonesia. Warr (2006) also finds that TFP
growth increased from −8.4 per cent during 1996–1998 to 1.5 per cent during 1998–2002.
60: Bosworth (2005) shows that annual average TFP growth increased from −4.6 per cent during 1996–1999 to 2.1 per cent during
1999–2004 in Thailand. Warr (2006) also finds that TFP growth increased from −9.0 per cent during 1996–1998 to 1.6 per cent during 1998–2002.

83©2012 Asian Productivity Organization

Tracking the size and growth of IT capital has become a standard practice in productivity research,following attempts to establish the driving force behind productivity resurgence in developed economies, starting with the US in the 1990s. Unlike technological advancements in the past, which werelargely confined to manufacturing, IT is a technology that can permeate the economy and bring aboutsignificant production gains in, for example, wholesale and retail, banking and finance, and transportation and telecommunications (i.e., service sectors that traditionally have struggled with slow productivity growth). Given the weight of the service sector in the economy (Figure 67), its potential andimplications for economic development and productivity gains could therefore be immense. A frequent question asked by policymakers and researchers is how best to capitalize on the productivity
potential brought forth by this IT revolution. As with non-IT capital, it involves a process of accumula-5 Productivity

tion and assimilation. IT capability becomes a factor that determines an economy’s long-term growthprospects. Formally acknowledging the importance of the IT sector to the modern economy, the 2008
SNA makes the IT sector more easily identified and separable in industry classification and asset type(see Appendix A.1).
Japan has been leading Asian countries in terms of IT capital contribution to economic growth (Figures 49 and 51). Japan’s shift in capital allocation took off in earnest in the mid-1990s, with the contribution of IT capital to capital input growth rising from a low of 11 per cent in 1995 to a peak of 65 percent in 2005 (Figure 54).61 It took place in a period when Japan’s overall investment growth slowed
significantly after the burst of its bubble economy in the early 1990s (Figure 37); after years of excesses, Japan shifted away from non-IT to IT capital as a profitable investment. In contrast, the US
started its shift toward IT capital much earlier than any Asian economy and over a longer period oftime. For two decades (i.e., be%%Japan
tween 1983 and 2003), IT capital
8.0
80
accounted for over 40 per cent of
7.0
70
capital input growth, reaching its
6.060
height of over 50 per cent at the
5.0
50
turn of the millennium. In the
4.0
40
most recent years, the slowdown
3.0
30
in total capital growth concentrat2.0
20
ed more on non-IT capital, result1.0
10ing in spikes in the contribution of
0.00
IT capital in both Japan and the−1.0–10
US. Our findings are in accordance
1971
1976
1981
1986
1991
1996
2001
2006
with Jorgenson, Ho, and Stiroh%%
US(2005). Based on their measure80
3.0
ment, IT capital in the 1980s con70
2.5
tributed 31.9 per cent of the60
growth of total capital inputs in
2.0
50
the US, but only 13.5 per cent in
40
1.5
Japan.62 Since 1995, the Japanese
economy had been rapidly30
1.0
shifting its capital allocation from20
non-IT to IT capital. In 2002, the0.5
10contribution of IT capital in Japan
0.0
0rose to 54.1 per cent, which is
1971
1976
1981
1986
1991
1996
2001
2006
higher than the 49.8 per cent in
IT capital contribution to capital input growth
the US.
Non-IT capital (right-axis)©2012 Asian Productivity Organization

A similar allocation shift to IT capital is also found in the Asian Tigers(Figure 55).63 In Korea, the ROC,
and Hong Kong, the contribution

IT capital (right-axis)

Figure 54 IT Capital Contribution to Capital Input Growthof Japan and the US, 1970–2010
Source: APO Productivity Database 2012.01.

61: Japan’s capital services recorded negative growth in 2009–2010, for the first time after World War II, although IT capital services
increased. We omitted this period from our calculations of the IT capital contribution share in total capital input.
62: Based on our own estimates presented, IT capital contributes 38.5 per cent in the US and 18.5 per cent in Japan to the growth of
total capital input. Although the estimates in the 1980s in this report are somewhat higher than the industry-level estimates in
Jorgenson, Ho, and Stiroh (2005) and Jorgenson and Nomura (2005), the trends of both the US and Japan shown in Figure 54 arevery similar to Figure 3 in Jorgenson and Nomura (ibid.).

84

5.4 Enhancement of Labor Productivity

%

40

30

%

40

ROC
Hong Kong
Korea
Singapore

30

20

20

10

10

0
1971

1976

1981

China
India

1986

1991

1996

2001

2006

0
1971

5
1976

1981

1986

1991

1996

2001

2006

Figure 55 IT Capital Contribution to Capital Input Growth of Asian Tigers, China, andIndia, 1970–2010
Source: APO Productivity Database 2012.01.

of IT capital to total capital input peaked at 30 per cent or above at the turn of the millennium, from ashare of 10 per cent or below before 1995. In contrast, Singapore had two local peaks. The earlier one
was reached in the mid-1990s when the contribution of IT capital reached 29 per cent, and the otherwas in 2005–2006, when it peaked at 31 per cent. China has been a latecomer as far as investing in IT
capital is concerned. Its surge in the contribution of IT capital took off around 2000 and peaked at 16
per cent in the early 2000s. We have not observed as big a push in IT pickup in India as in other Asian
countries. Rather, the process has been gradual with a clear step-up in effort from a minimal level inthe early 1990s. The share of IT capital reached 7 per cent in the early 2000s before softening recently.

5.4 Enhancement of Labor Productivity
Although TFP more accurately measures how efficiently an economy utilizes its factor inputs, laborproductivity and its drivers are of interest not least because of the close link to GDP per capita. Within
the same growth accounting framework, average labor productivity growth at the aggregate levelcan be decomposed into effects of capital deepening (as measured by capital input per hour worked),which reflects the capital–labor substitution, and of TFP. In other words, these factors are key in fostering labor productivity.

63: The quality of the data on investment for IT capital (IT hardware, communications equipment, and computer software) varies considerably among countries. If the official estimates are not available in their national accounts, the investment data by type of asset in benchmark Input–Output Tables (IOT) and the time-series IOTs (if available) are used to separate IT capital investment fromGFCF in the national accounts. In the years when the IOTs are not available, domestic production and import data (UN Comtrade
Database) for IT hardware and communication equipment is used to interpolate the estimates of IT investments. Data inconsistency could be a problem. Where software is excluded from the GFCF definition compliant to the 1968 SNA, software investment
is estimated as described in Appendix A.1. In addition, the constant-quality prices for IT capital are hardly available for most Asian
countries. If they are not available, the prices for IT capital are estimated by harmonizing Japan’s price indices, as described in Appendix A.2. Thus, readers are cautioned about data uncertainty here and should expect that the decompositions of contributionsof capital services into IT and non-IT capital can be considerably revised for some countries, when more reliable data sources for
estimation become available.

85©2012 Asian Productivity Organization

Capital deepening has been taking place in all the countries compared, albeit to various degrees(Figure 56). Experience of countries suggests that capital deepening is an accompanying process of
rapid economic development. The relatively early starters (i.e., Japan and the Asian Tigers) underwent

5 Productivity

1970−2010%12

1970−1990

%

12

10.4

10
8
6
4
2

10

8.9
7.9 7.88
6.1
5.4 5.2 5.1 5.0

6

4.9
3.7 3.7
2.94
2.4

2.0 1.9

2
0.8

10
7.7

8

7.1
5.7 5.5

7.4

6.9

6

5.5 5.2

6.2
4.6 4.5 4.4 4.4

4.2
3.3 2.94
2.8

2.4 2.1 2.1
0.9

4.2
3.3

3.1

2.7
1.8

2

1.5
0.7 0.5

0

Iran
Fiji
Mongolia
Philippines
US
SingaporeJapan
Malaysia
Indonesia
Hong Kong
Thailand
India
ROC
Vietnam
Korea
China

0

10.4
9.5

Fiji
US
Philippines
Vietnam
India
ThailandIranMongolia
China
Malaysia
Indonesia
Hong Kong
Japan
Singapore
ROC
Korea

Fiji
Iran
Philippines
US
Mongolia
ThailandIndia
Malaysia
Indonesia
Hong Kong
Japan
Singapore
Vietnam
China
ROC
Korea

0

1990−2010%

12

Figure 56 Capital Deepening, 1970–2010, 1970–1990, and 1990–2010
Source: APO Productivity Database 2012.01.
Note: The starting period for Vietnam is 1986. The labor input for Fiji is defined by numbers of employment.

more rapid capital deepening than any other countries compared, and in the earlier rather than thelatter period. The reverse is true for the emerging Asian economies where concerted effort was madeto increasing their capital intensity in the later period. In 1990–2010, China, Vietnam, India, and Thailand moved up to occupy the top spots among the Asian Tigers, while Singapore and Japan moved
down in the rankings. In 1970–1990, the capital–labor ratio was rising by 10.4 per cent and 9.5 percent on average a year in Korea and the ROC, respectively; it slowed to 7.4 per cent and 6.2 per cent in
the subsequent two decades. Meanwhile, China’s pace doubled between the two periods, from 5.2
per cent to 10.4 per cent on average a year. In Vietnam, it more than doubled from 2.4 per cent to 6.9
per cent. The pace of capital deepening also hastened in the US from 2.1 per cent to 2.7 per cent between the two sub-periods.

©2012 Asian Productivity Organization

While labor productivity steadily improved for all countries (Figure 43), the growth rate of capital
productivity as the other measure of partial productivity is negative for all countries during 1970–2010 (Figure 57). The rates of capital deepening in Korea and the ROC have been outstanding, at
8.9 per cent and 7.9 per cent per year, but their capital productivity experienced the sharpest declineof over 3.0 per cent per year on average during this period (Figure 58). In contrast, the deterioration ofcapital productivity (by 1.1 per cent) was relatively mild in China as shown in Figure 59, despite its fast
capital deepening of 7.8 per cent (Figure 56). Looking at the two sub-periods, overall the rate of deterioration in capital productivity for all countries was slower in the latter period. China’s performance isparticularly impressive. Its acceleration in capital deepening in the latter period did not compromise
its capital productivity as much as the early starters. In 1990–2010, China’s capital–labor ratio rose by
10.4 per cent whereas capital productivity fell by 1.3 per cent. This compares with Korea’s performance in 1970–1990 when its capital–labor ratio rose by 10.4 per cent but capital productivity fell
by 4.5 per cent.
Labor productivity growth can be decomposed into contributions from capital deepening and TFP
growth. Capital deepening should raise labor productivity, other things being equal. However, bycomparing Figures 56 and 60, it is observed that countries that underwent the fastest capital deepening were not necessarily those enjoying the fastest labor productivity growth. In other words, TFP
growth can make a significant difference to labor productivity performance. China achieved the fastest labor productivity of 6.7 per cent on average a year in the period of 1970–2010, while it was only
third in its pace of capital deepening. This was because China’s labor productivity was bolstered by thefastest TFP growth of 3.2 per cent over the same period, compared with 1.7 per cent and 1.5 per cent86

5.4 Enhancement of Labor Productivity

1970−2010

%

2

2

1

1

0

0

−1
−2
−3
−4

−0.5 −0.5 −0.6 −0.7

−0.8 −1.0 −1.1

−1

−1.2
−1.6
−2.1 −2.1 −2.2

−2.4
−3.7

2

−0.1

−0.6

−0.2 −0.3 −0.3 −0.3

−1−0.9 −0.9
−1.3

−1.7

−0.8

−1.1

−2

−2.0 −2.0 −2.1
−3.0

−4

−1.3 −1.3−1.6 −1.6−2.1 −2.2
−2.6

−3
−3.3

5

−2.8

−4

−4.0 −4.0
−4.5

Korea
VietnamIndonesia
ROC
Japan
Hong Kong
ThailandChina
Malaysia
US
Philippines
India
Singapore
Fiji
Mongolia
Iran

−5

Korea
Singapore
ROC
Japan
Iran
Malaysia
Indonesia
Philippines
Mongolia
India
China
Fiji
US
Hong Kong
VietnamThailand

−5

0.7

0
−0.4

1990−2010

2.0

1

−3

−3.1

%

0.9

−2

Korea
ROC
Japan
VietnamSingapore
Indonesia
Malaysia
Philippines
China
Hong Kong
India
US
Fiji
Iran
Mongolia
Thailand−5−0.2

1970−1990%

Figure 57 Capital Productivity Growth, 1970–2010, 1970–1990, and 1990–2010
Source: APO Productivity Database 2012.01.
Note: The starting period for Vietnam is 1986.

Despite that, capital deepening
remains the prime cause of laborproductivity growth, generally explaining 50 per cent or more oflabor productivity growth; the US
is the only exception to this observation (Figure 61). Within thislong period, the composition oflabor productivity growth has
been shifting (Figures 62 and 63).
In the earlier period of 1970–1985,
TFP growth was enjoyed by justover eight out of the 15 Asian
countries compared, and it was asignificant drag on labor productivity growth in four countries (i.e.,Singapore, Iran, the Philippines,
and Fiji). During the middle period of 1985–2000, all countries (except Mongolia) achieved positive

1970=1.0
1.2
1.0
0.8
0.6

0.4
0.2

0.0
1970

ROC
Hong Kong
Japan
Korea
Singapore
1975

1980

1985

1990

1995

2000

2005

2010

Figure 58 Capital Productivity Trends in Japan and theFour Asian Tigers, 1970–2010
Source: APO Productivity Database 2012.01.

1970=1.0
1.2
1.0
0.8
0.6
0.4
0.2

China
India

0.0
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 59 Capital Productivity Trends in China and India,
1970–2010
Source: APO Productivity Database 2012.01.

87©2012 Asian Productivity Organizationachieved by Korea and the ROC,
respectively. Japan was sixth interms of capital deepening but
came in 11th place in labor productivity growth because of its
lackluster TFP growth of 0.6 percent over the period. Thailand, on
the other hand, fared well on labor productivity growth in sixth
place, compared to its 11th placeranking on capital deepening, because of its robust TFP growth of
1.8 per cent.

5 Productivity

%

%

7

IT capital
Output65
4

1.7

Non-IT capital

1

33 31
48

1.5
1.7

102

TFP

100
80

30

41 45
50

21

27

31

47

52

60
1.8
1.4
1.9

80

0.5 0.5

1.8

3.3 3.2 2.9
2.1

2.5 2.2
1.5

0.4 0.3 0.3 0.2 0.3
0.2 0.3

0.5

0.9 0.6

1.9

61 61

51

49

1.9

0

67

48 43

3

6

8

8

63 24

50

6

8

7

11
3

67

24

15
4

6

20

19

5

−22

Fiji

Philippines
Iran

US
Mongolia
Japan
Indonesia
India

Singapore
Malaysia

Thailand
VietnamHong Kong
ROC
Korea

China

Fiji

−20

68
66

20

0.9 0.4
1.5 0.4
0.9 0.8
0.3 0.1 0.4
0.1 0.2 0.0
0.1 0.1
0.2
0.0
−0.2

1.5

76

40
0.7

Philippines
Iran
US
Mongolia
Japan
Indonesia
India
Singapore

Malaysia
Thailand
VietnamHong Kong
ROC
Korea
China

−1

IT capital

3.2

1
0

120

TFP

15 17

3
2

Non-IT capital

Figure 60 Sources of Labor Productivity
Growth, 1970–2010

Figure 61 Contribution Shares of Labor
Productivity Growth, 1970–2010

Source: APO Productivity Database 2012.01.

Source: APO Productivity Database 2012.01.

1970−1985%

1985−2000

2000−2010

10

8

4.3

6
3.5

1.0 0.8

42

2.2 2.3 0.8

2.2

2.2
1.1

0.8

3.2 1.3
0.8

4.2 2.1
3.1 3.0

2.6

3.4
0.9

2.6

1.2
0.4 1.3
1.3
0.1 0.1 0.1 0.5
0.1 0.6
0.3 0.0 0.0
0.0
−1.0
−1.8
−1.3
−2.0

0.2 0.4 0.0 0.2 0.1 0.3

0.1

3.1 2.7 2.8 2.6

1.6
0.4 0.4 0.4 0.5 0.6

2.1
2.9

1.5

0.7

3.2 2.3

TFP

1.5

2.0

1.5
0.7 1.4
0.7 2.1 1.4 0.7 0.1 1.0 0.7
1.5
1.0
1.1
0.3
0.3
0.5 0.5
0.6
0.6
0.4 0.4 0.3
0.3 0.3 0.5 0.4 0.6 0.3
0.1 0.3 0.4
0.2
0.1
−0.1
−0.1
0.1
3.0

2.0 1.1 1.7 1.0 0.5
1.1
0.1 0.8 1.0 1.2
0.3 0.1 0.1 0.1 0.4
0.6
0.2 0.1
0.5
0.0 0.1 0.1−0.9 −0.9

Non-IT capital

2.2

4.5

0.8

2.3

1.8

Fiji
Japan
Indonesia
Singapore
US
Philippines
Thailand
Malaysia
Hong Kong
ROC
Iran
Mongolia
Korea
Vietnam
India
China

IT capital

3.0

1.5

0.3

Mongolia
Iran
Fiji
Philippines
US
Japan
India
Indonesia
Vietnam
Malaysia
Singapore
Hong Kong
Thailand
ROC
Korea
China

Fiji
Philippines
Iran
India
US
Malaysia
Indonesia
ThailandSingaporeJapan
Mongolia
Hong Kong
China
ROC
Korea

−2

0.5

4.2 4.1
2.7 2.30

0.0

OutputFigure 62 Sources of Labor Productivity Growth, 1970–1985, 1985–2000, and 2000–2010©2012 Asian Productivity Organization

Source: APO Productivity Database 2012.01.

TFP growth to bolster labor productivity growth. By 2000–2010, TFP growth had become the dominant driver of labor productivity growth in 11 out of the 15 countries compared. At the same time, thecontribution from IT capital deepening is also strengthening, from a range of 1–12 per cent in 1970–
1985, to 2–17 per cent in 1985–2000, and 3–21 per cent in 2000–2010. This may have boosted countries’ TFP performance. In contrast, the contribution of non-IT capital was negative in Thailand and Fijiin 2000–2010. The contribution of IT capital deepening in the US is always ahead of Asian countries,
but it was the largest in the middle period of 1985–2000, accounting for 32 per cent of labor productivity growth. Coincidentally, it was also the period when the share of TFP growth was the largest, at
61 per cent.

885.4 Enhancement of Labor Productivity

1970−1985%

120

1985−2000

1

100
18 15

80

20

2000−2010306 270174

115

355 395

101

12
24

26

45 47

53

54

61

9

21

39 42

24

26
56

63

78

97

80

78

78

65

74
36

20
4

65

1

4

2

7

17

12
3

45

2

2

2

5

4

−9

2

7

8

8

12

8

4

14
5

3

48

11 9

−269 −43

Mongolia
Iran
Fiji
Philippines
US
Japan
India
Indonesia
Vietnam
Malaysia
Singapore
Hong Kong
Thailand
ROC
Korea
China

IT capital

Non-IT capital

9

5

38
42

3

95

8

24

9
8

31
4

29 21
9 11

32
25 8
20 34 20
15
17
12 14
8
−2

−12

Fiji
Japan
Indonesia
Singapore
US
Philippines
Thailand
Malaysia
Hong Kong
ROC
Iran
Mongolia
Korea
Vietnam
India
China

−3

−212 −161 −78

6

58 48
72

91

46

40

15

−3
−27

70

63

8
32 54

42

33

17

37
60 55

83

Fiji
Philippines
Iran
India
US
Malaysia
Indonesia
ThailandSingaporeJapan
Mongolia
Hong Kong
China
ROC
Korea

−20

7

62
69

43

54 50

29

83

67

45

50

57

95

55 49

0

46

61

60
40

28

35

41

TFP

Figure 63 Contribution Shares of Labor Productivity Growth, 1970–1985, 1985–2000, and 2000–2010
Source: APO Productivity Database 2012.01.

89©2012 Asian Productivity Organization

Figure 64 and Table 13 show the decomposition of labor productivity growth for individual countries
in five-year intervals covering the period 1970–2010. Productivity is procyclical in nature, and, in turn,it is difficult to discern fundamental shifts from short-term fluctuations. However, over a period spanning four decades, it can be observed that labor productivity growth in the two fast-growing emerging Asian economies (i.e., China and India) is accelerating. China clearly has leapt from a growth rateof around 4 per cent in the 1970s to a rate of 8–10 per cent in the 2000s, and the transition period wasin the early 1990s. India’s passage to accelerating labor productivity growth is more gradual thanChina’s, from around 1 per cent in the 1970s to 7.4 per cent in the second half of the 2000s. Both TFP
growth and capital deepening took a leap in 2005–2010 to reinforce the positive trend. In contrast,
the early starters (i.e., Japan and the Asian Tigers) have been experiencing a slowdown in labor productivity growth since their peaks achieved in the later 1980s. Labor productivity growth appeared tohave stabilized in the 2000s, but at a lower rate than previously, in both Hong Kong and Korea. Singapore’s productivity performance, albeit robust compared with other mature economies like the US,
has been very modest against its Asian counterparts. Its recent peak was 3.7–3.8 per cent in the 1990s,
compared with over 6 per cent in Hong Kong and the ROC, and 7.4 per cent in Korea in the late 1980s.
The US clearly enjoyed a labor productivity growth spurt in the late 1990s (2.3 per cent) and early
2000s (2.4 per cent), the origin of which attracted a lot of research attention at the time. In the recent
years, it has returned to its long-term average of under 2 per cent.

5 Productivity

China

%

12

ROC

%

7

4.6
7.1

6

3

3.1

0.4

5.1

3.9

1
0

2005–2010
0.2

2.0

–0.3

2005–2010

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985–2

1.6

Philippines
0.3
0.9
2.6
1.7
0.9 0.4 0.1
0.2 2.0 1.3
0.2 0.1 0.1 0.1
0.0–0.1 0.0 –0.2 0.4
–0.8
–6.4

2.0
0.6
0.2

–4
–6

2005–2010

2000–2005

1995–2000

1990–1995

1985–1990

2

3.1

2

0.9

0.1

0.7

0.1 0.2

0.8

Output2000–2005

0.4

1995–2000

0.5 0.4 0.7 0.6

1990–1995

0.2 0.2 0.4

1980–1985

–1

0.3
0.7

2005–20100

1975–1980

2005–2010

Figure 64 Decomposition of Labor Productivity Growth, 1970–2010

2000–2005

1995–2000

1990–1995

TFP

0.9 0.6 0.3
0.2

3.1

1.8
0.5
0.7 0.6
0.1 0.1 0.2 0.3 –0.4
1986–1990

2005–2010

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

Non-IT capital

–1

2.9

1.4

1.2

1

3.6 1.1

1985–1990

1

1.2
1.5

0.8

3

0

Source: APO Productivity Database 2012.01.

1980–1985

3

4

2.6 3.2
2.5 1.1 1.7
1.1
0.7 0.5 0.3 0.2 0.4
0.1
0.1
0.2 0.2
0.3
–0.4
–0.5
–2.5

1970–1975

2005–2010

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

–4

US

%

1970–1975–2

1975–1980

–1.1

0

1.2

1.1 1.6
0.3
0.6 0.7 0.6 0.5 –0.8

0.5 0.7

1970–1975

2.8

2
3.0 1.2

2005–2010

Vietnam–86

1.9 4.0 5.0

1.9

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

3.9 2.5

1970–1975©2012 Asian Productivity Organization

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

0

5.4

3.5
2.4
1.7
0.6 1.2
0.2 0.1 0.1 0.1 0.2 0.4
0.0 0.1
0.0
–1.0
–1.6
–2.6 –2.6

1975–1980

7

3.4

IT capital90–1

1975–1980

2.9
1.1

1970–1975

2005–2010

2000–2005

1995–2000

–3

%

1.9

0.1

0.2

0.3

0.5
0.4

–0.7

0.5

4

2.9

5

–1.9

2

5.2

1970–1975

00.5

1975–1980

0.3

1970–1975

0.7

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

8

4

0.5

2005–2010

1.0

0.2
0.9
2.1 1.7 1.7 2.0
1.3 0.6
0.4 0.2 0.2 0.4 0.3 0.4 0.4

Japan

%

2.1 2.0

1.6

–2.5

6

5.9

2005–20100.4

0.1 0.3

1.4

Thailand%

62

2000–2005

1.3

–2.6

2005–2010

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

8

2.9

0.3

–2

Singapore%

2000–2005

0.2

1995–2000

0.3 0.4 0.3 0.5 0.5

0.1

Mongolia

63
4.4 1.9 4.5

0.0 0.1

1990–1995

0.1

0

1985–1990

1.8

3

2

2.8 2.9

1.0

0.1 0.2 0.3 0.4 0.4 0.6 0.5

40
1980–1985

1.8

0.3

–9.7

%

1.5

2.4

2

–10

–3

1

1975–1980

1.9

0

1.7

5

2.0
0.5
3.2 3.7 0.9
2.8
1.9 1.9 2.6
0.1
0.0
0.0
0.1
0.1
0.0
0.0 0.1 –0.5
–1.3 –0.5 –0.9
–0.1

–4

1.6
1.1

2.2

3.3 2.8 3.2

6

3.9

1970–1975

3.2 3.1 3.4 2.7

2005–20105.0

2000–2005

4.4

4

1995–2000

6
3.8
1.3

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

2005–2010

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

Malaysia

8

1.8
0.9

1.6 2.1

%

–8

%

1.5

Iran

–6

–3.4

–4

3.2

–2

1995–2000

0

1.9
2.2
1.2 0.1
0.1
0.1
0.1 0.0

1990–1995

2

2.3
2.7
2.4
2.1
1.2
0.1
0.0 0.1
0.1 0.2
–1.5

1.4

–2.1
1985–1990

4

–2

Korea

–2

8

2.4

3

0.2

–2.1

6

3.1

–1.2

–1

%

3.5

1.0

0.0
0.8
0.2 0.7
0.2 0.5 0.1 0.1–0.1 0.0 0.0 0.1–0.1 0.1 –0.2
–0.6
–0.6
–0.3
–0.6

1980–1985

0

0

3.6

5.2
0.7 1.3

1975–1980

Indonesia

1.6

6

1970–1975

2005–2010

2000–2005

0.2

–1.8

–2

1995–2000

3.4

1.3
1.4
0.7
1.6 1.0 1.1
1.4 1.5
0.0 0.0 0.9 0.8
0.0 0.0 0.1 0.1 0.1–0.4 –0.4

4

0

0.0

1990–1995

2

2.6

1.8

1.5

4

–0.6 0.4 0.3 0.3 0.3 0.8 0.6
1985–1990

4

6

–2

2.4

1.9

6

8

0

2.8

1.2

3.8

%

2

2.2

8

4

–2

3.0

3.2

0.5

%

6

0

3.8

1980–1985

India

8

2

9

2.8

1
0.6

1975–1980–1

2.2 0.7

5.2

1970–1975

2000–2005

1995–2000

1990–1995

1980–1985

1975–1980

1985–1990

0.5
2005–2010

3.8

3.4
1.9 1.9
0.7
0.0 0.0 0.0 0.1 0.1 0.2

%

0.6

2

4.9
0.5 1.2
3.2 3.0

3.8

4

4.1

1970–1975

0Hong Kong

%

2

2.2

5
8

2

3

6

10

4

Fiji

%

5.4 Enhancement of Labor Productivity

Table 13 Role of TFP and Capital Deepening in Labor Productivity Growth, 1970–2010
TFP

China
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Fiji
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
India
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Iran
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Korea
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Mongolia
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Singapore
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Vietnam

3.7
4.2
6.9
2.4
10.6
7.1
8.6
10.2
6.7

0.0
0.0
0.0
0.1
0.1
0.2
0.7
0.5
0.2

0.5
1.2
4.9
0.4
7.1
3.1
4.1
4.6
3.2

−0.5
−0.5
−1.2
2.3
−0.4
1.2
1.5
−0.5
0.2

−0.1 (18)0.0 (5)0.0 (−2)
0.1 (4)0.2 (−54)−0.1 (−4)
0.1 (6)0.1 (−20)
0.0 (19)0.2 (−42)
0.7 (−139)
0.8 (−66)−0.6 (−26)0.0(0)
0.5 (42)0.1(6)−0.2 (47)0.2 (80)−0.6 (124)−1.2 (234)−2.1 (168)
2.8 (122)−0.6 (154)0.7 (62)
1.3 (88)−0.3 (73)0.0 (1)

1.1
1.1
1.6
2.3
3.4
2.5
3.9
7.4
2.9

0.0
0.0
0.0
0.0
0.1
0.1
0.1
0.2
0.1

(2)
(2)
(2)
(2)
(2)
(5)
(3)
(3)
(3)

1.4 (136)
1.5 (133)
0.9 (55)
0.8 (34)
1.6 (46)
1.0 (42)1.1 (30)
3.4 (45)
1.5 (50)−0.4 (−38)−0.4 (−35)
0.7 (43)
1.4 (64)
1.8 (52)
1.3 (53)
2.6 (67)
3.8 (52)
1.4 (47)

7.2
−6.0
1.4
−1.4
1.4
1.0
2.3
4.9
1.3

0.1 (1)0.0 (−1)
0.0 (2)0.0 (−3)0.0 (3)0.1 (7)0.1 (6)0.1 (3)0.1 (5)3.2 (45)
3.7 (−60)
0.9 (64)−1.3 (94)−0.5 (−39)−0.9 (−89)−0.5 (−22)
2.8 (56)
0.9 (67)

3.9 (54)−9.7 (161)
0.5 (34)−0.1 (9)1.9 (136)
1.9 (182)
2.6 (116)
2.0 (41)0.4 (27)

6.0
3.5
6.6
7.4
5.2
4.4
4.2
4.4
5.2

0.1 (2)0.3 (8)0.3 (4)0.4 (6)
0.3 (6)
0.5 (11)0.5 (12)0.2 (5)0.3 (6)

4.4 (73)
5.0 (143)
3.2 (48)
3.1 (42)
3.4 (65)
2.7 (60)
1.8 (44)
1.8 (40)
3.2 (61)

1.5 (25)−1.8 (−51)
3.2 (48)
3.8 (52)
1.5 (29)
1.3 (29)
1.9 (44)
2.4 (55)
1.7 (33)

5.1
3.1
3.9
−1.9
−1.3
2.5
2.7
5.0
2.4

0.0 (1)0.1 (2)0.2 (5)0.1 (−5)0.1 (−7)
0.1 (5)0.2 (8)0.4 (8)0.1 (6)

2.1 (42)2.0 (64)
5.4 (136)
0.6 (−34)
1.2 (−89)
0.0 (−2)−1.0 (−39)
1.7 (34)
1.5 (63)

2.9 (58)
1.1 (34)−1.6 (−41)−2.6 (138)−2.6 (196)
2.4 (96)
3.5 (131)
2.9 (58)
0.7 (31)

4.5
3.2
3.2
3.8
3.8
3.7
2.7
1.1
3.2

0.5
0.3
0.5
0.6
0.7
0.6
0.5
0.3
0.5

5.9 (133)
2.8 (86)
3.9 (119)0.7 (17)
1.2 (31)3.0 (81)1.1 (39)−0.8 (−69)
2.2 (68)−1.9 (−43)
0.2 (5)−1.1 (−35)
2.5 (66)
1.9 (51)
0.1 (4)
1.2 (43)
1.6 (144)
0.5 (17)

1986–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010

2.3
4.3
3.1
6.3
3.2
3.9

(1)
(1)
(1)
(3)
(1)
(3)
(8)
(5)
(3)

(11)
(9)
(16)
(17)
(18)
(15)
(18)
(25)
(15)

0.1 (6)0.1 (2)0.2 (7)0.3 (4)0.5 (16)0.3 (6)

3.2
3.0
1.9
1.9
3.4
3.8
3.9
5.1
3.3

0.7
0.6
1.8
2.9
3.1
1.9

(86)
(71)
(28)
(82)
(32)
(54)
(45)
(50)
(49)

(32)
(14)
(59)
(46)
(97)
(48)

Labor
Productivity
(13)
(28)
(71)
(15)
(67)
(43)
(47)
(45)
(48)

1.4 (62)
3.6 (84)
1.1 (34)
3.1 (49)−0.4 (−13)
1.8 (45)

ROC
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Hong Kong
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Indonesia
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010Japan
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Malaysia
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Philippines
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010
Thailand
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010US
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–2010
1970–2010

Capital DeepeningIT
Non-IT

TFP

5.1
6.4
4.2
6.3
5.2
4.5
3.1
3.6
4.8

0.5 (9)0.4 (6)
0.3 (8)0.3 (4)0.3 (6)
0.8 (17)0.6 (19)0.0 (1)0.4 (8)5.2 (102)
3.8 (60)
3.2 (77)
2.2 (35)
2.8 (53)
3.0 (67)
1.9 (61)
1.2 (33)
2.9 (61)

−0.6
2.2
0.6
3.8
2.2
0.7
0.6
2.4
1.5

3.2
7.5
3.8
6.7
4.6
0.2
3.1
3.5
4.1

0.1 (4)0.2 (3)0.3 (7)0.4 (6)
0.4 (9)0.6 (273)
0.5 (15)0.3 (8)0.3 (8)1.6 (51)
2.1 (28)
3.3 (88)
2.8 (41)
3.2 (70)
1.7 (838)
0.9 (29)
1.0 (29)
2.1 (51)

1.4
(45)
5.2
(70)
0.2
(5)
3.6
(53)
1.0
(21)
−2.1 (−1012)
1.8
(56)
2.2
(63)
1.7
(41)

4.5
4.9
1.0
3.6
6.5
−1.2
3.3
0.2
2.9

0.0 (1)0.1 (2)0.1 (10)0.1 (3)0.2 (3)0.1 (−10)
0.1 (4)0.1 (60)
0.1 (4)2.1 (47)
3.1 (64)
2.4 (247)
1.2 (34)
2.7 (42)2.2 (−183)
1.2 (37)
0.0 (−5)
1.9 (66)

2.4
(53)
1.6
(33)
−1.5 (−157)
2.3
(63)
3.5
(55)
−3.4 (293)
1.9
(59)
0.1
(45)
0.9
(30)

4.8
2.8
3.6
4.2
2.0
2.0
1.8
1.1
2.8

0.4
0.2
0.2
0.4
0.3
0.4
0.4
0.2
0.3

(8)
(7)
(6)
(10)
(17)
(19)
(23)
(16)
(11)

5.2 (107)
2.1 (76)
1.7 (48)
1.7 (41)2.0 (98)
1.3 (69)
0.6 (30)
0.4 (34)
1.9 (67)

−0.7
0.5
1.6
2.0
−0.3
0.2
0.9
0.5
0.6

4.0
4.5
1.9
3.3
6.4
0.8
3.0
2.4
3.3

0.0 (1)0.1 (2)0.1 (4)0.1 (4)0.3 (4)0.4 (51)
0.7 (22)0.5 (20)
0.3 (8)2.8 (71)
2.9 (64)
4.4 (235)
1.3 (39)
4.5 (70)
2.9 (349)
1.0 (33)
0.3 (13)
2.5 (76)

1.1
(28)
1.5
(34)
−2.6 (−139)
1.9
(57)
1.6
(26)
−2.5 (−301)
1.4
(46)
1.6
(67)
0.5
(15)

0.4
2.3
−4.9
2.6
0.1
1.9
1.4
2.7
0.8

0.0
0.1
0.1
0.1
0.0
0.4
0.4
0.2
0.2

(8)
(3)
(−2)
(4)
(36)
(19)
(29)
(7)
(20)

0.2 (54)
2.0 (85)
1.3 (−27)−0.1 (−2)
0.9 (838)
1.7 (89)0.1(5)0.6 (20)0.8 (102)

0.2
(37)
0.3
(12)
−6.4 (129)2.6(99)−0.8 (−774)−0.2 (−8)
0.9
(66)
2.0
(73)
−0.2 (−22)

5.9
0.8
3.8
5.0
7.4
0.4
2.9
1.8
3.5

0.1 (1)0.1 (12)0.2 (5)0.2 (4)0.5 (7)0.3 (79)
0.2 (8)0.3 (18)
0.2 (7)2.5 (42)−0.4 (−48)
1.7 (45)
0.7 (15)5.0 (68)
2.6 (672)−0.5 (−17)
0.4 (21)
1.5 (43)

3.4(57)
1.1 (136)
1.9
(50)
4.0
(81)
1.9
(25)
−2.5 (−651)
3.2 (109)
1.1
(61)
1.8
(50)

1.9
1.0
1.9
1.2
1.4
2.3
2.4
1.4
1.7

0.2
0.2
0.4
0.5
0.4
0.7
0.6
0.4
0.4

0.9
0.2
0.3
0.1
0.2
0.1
0.7
0.8
0.4

0.8
0.6
1.2
0.7
0.9
1.5
1.2
0.3
0.9

(10)
(21)
(22)
(38)
(29)
(30)
(24)
(26)
(24)

(47)
(19)
(15)
(9)
(11)
(6)
(29)
(55)
(24)

(−11)
(35)
(15)
(60)
(42)
(16)
(20)
(66)
(31)

5

(−15)
(17)
(45)
(49)
(−16)
(13)
(47)
(50)
(21)

(42)
(60)
(63)
(54)
(60)
(64)
(47)
(19)
(52)

Unit: Average annual growth rate (percentage).
Source: APO Productivity Database 2012.01.

91©2012 Asian Productivity Organization

Capital DeepeningIT
Non-IT

Labor
Productivity

5 Productivity

Box 7

Sensitivity of TFP Estimates

TFP computations based on the growth accounting framework depends on data that are sometimes hardto observe. One difficult task is to observe the wages for the self-employed and unpaid family workers. Asa crude approximation in this report, we assume that per worker wages for the self-employed and unpaid
family workers are 30 per cent of the per worker wage for employees in order to estimate the labor compensation for total employment. The future review on this assumption affects TFP estimates directly
through the revision of factor income shares and indirectly through the estimates of the ex post rate of
return and thus the aggregate measure of capital services.
The right-hand chart of Figure B7.1 presents the labor income share (the ratio of compensation for employees to the basic-price GDP) based on the official national accounts (including author adjustments in basicprice GDP for some countries) in 15 Asian countries and the US in 2010. There is a large divergence in labor
income share for employees among the Asian countries. Roughly, we find two groups: countries with anapproximately 50 per cent share and countries with an approximately 30 per cent share of compensationfor employees. This does notnecessarily reflect the differ100 %
80
60
40
20
0
0
20
40
60 %
ences in the number of em93
59
US
ployees to total employment.
54
China
86
53
Japan
The left chart provides the51
93
Hong Kong
employee share to total em50
Korea
71
50
ployment. Although Malaysia
43
Fiji
46
77
ROC
has a high employee share of
44
94
Singapore
78 per cent, the labor income
41
32
Indonesia
33
30
India
share is only 28 per cent.
ThailandPhilippines
Mongolia
Malaysia
Vietnam
Iran

45

30

29
29
28
28
21

Labor income share for employees

Share of employees to total employment

Figure B7.1 Labor Income Share for Employees, 2010
Sources: Official national accounts in each country, including author adjustments.

%

4

3.9

3

3.1

2

2.3

1.9

1

TFP(vL+10)
TFP
TFP(vL−10)

2.7

1.0

2.1
1.8
1.4

2.3
1.7
1.0

2.2
1.7
1.1

2.3
1.5
0.7

1.7
1.4
1.0

1.1
0.9
0.6

0

1.4
0.9
0.4

1.0
0.7
0.5

1.1
0.6
0.1

1.1
0.6
0.0

1.0
0.5
0.0

0.5
0.4
0.2

0.1 0.0
0.0−0.1 −0.2−0.4

Philippines

Fiji

Iran

Malaysia

SingaporeJapan

Mongolia

Indonesia

US

India

ROC

Hong Kong

Thailand−1

Vietnam©2012 Asian Productivity Organization

37
54

Korea

92

44
78

China

Figure B7.2 gives the sensitivity of TFP estimates by changing the factor income share
during the period 1970–2010.
In general, the growth rate ofcapital input is higher thanthat of labor input, so thehigher income share of labor
gives higher estimates in TFP
growth. In other words, labor productivity is improved
much faster over a given period than capital productivity,
the growth of which tends tobe frequently negative (seeFigures 43 and 57). The TFP estimate reflects the improvement of labor productivity
more when the labor income
share increases. In Malaysia,
with a TFP growth of 0.6 percent on average during theperiod 1970–2010, the true
estimate could be 1.1 per centif the current labor income
share is underestimated by 10
per cent.

54

Figure B7.2 Sensitivity of TFP Estimates by the Change ofIncome Share, 1970–2010
Source: APO Productivity Database 2012.01.
Note: The starting period for Vietnam is 1986. The labor inputs for Fiji and Mongolia aredefined by number of employment.

6 Industry Perspective
This chapter provides the industry origins of economic growth and labor productivity growth in Asian
countries. Industry decomposition allows an insight into the source of a country’s economic dynamics, which in turn determines its overall performance and characteristics, its strengths, and its vulnerabilities. On the one hand, a broad industry base reflects diversification and sophistication in
the economy, and in turn is more resourceful in weathering economic shocks. On the other hand, anarrow-based economy is vulnerable to shocks and in turn more susceptible to volatility. Industry
structure is a key indicator of an economy’s stage of development. As a rough sketch, at one end of
the spectrum are predominantly agricultural- and rural-based economies, while at the other end theagriculture sector is negligible and the service sector is the dominant economic base. In the middle
is a stage where manufacturing may be the main driver of economic growth. As an economy matures,its depth and sophistication will increase and its resilience to economic shocks should accordingly bestrengthened. Furthermore, the different composition of economic activities among countries isalso one of the main sources of the huge gap in average labor productivity at the aggregate level,
as observed in Chapter 5. By analyzing the industry structure of Asian economies, we can clearlytrace the path of economic development and identify countries’ respective stages based on theircharacteristics.64

6

6.1 Output and Employment
Table 6 in Section 3.2 introduces a country grouping according to stages of development (as measured by per capita GDP relative to the US). Table 14 regroups countries based on the same set of criteria as in Table 6, but applied to countries’ 2010 income levels. The difference in countries’ relative percapita GDP between the two tables reflects the impact of their catch-up efforts since 1970 or the beginning year of the data series in this report for the countries concerned.

64: Constructing the industry origins of labor productivity growth requires confronting a large volume of data from different sources.
Issues of data inconsistency arising from fragmentation of national statistical frameworks can present enormous hurdles to researchers in this area. The industry data in this chapter are mainly based on official national accounts. Where back data are notavailable, series are spliced together using different benchmarks and growth rates. Data inconsistencies in terms of concepts,
coverage, and data sources have not been fully treated. Levels of breakdown are deliberately chosen to minimize the potential
impact of these data inconsistencies. In this sense, APO industry data should be treated as a work in progress and it is difficult toadvise on data uncertainty. We will further develop and examine these data issues in the near future. Readers should bear thesecaveats in mind in interpreting the results.
65: The reason for Cambodia’s failure to move up in income group is its short time series, which starts in 1987. Therefore, despite its
average catch-up speed of 3.3 per cent per annum, it has had less time to catch up than other countries with series starting from1970. Between 1987 and 2008, Cambodia’s relative income moved up from 2.3 per cent to 4.6 per cent of the US level.

93©2012 Asian Productivity Organization

Comparing Table 14 with Table 6, we observe that 12 Asian countries have moved up in income group,
whereas ten have been stagnant and five have stayed in the top income group. Among them, themost upwardly mobile countries are the ROC and Korea, both in the fast catch-up group, which have
moved up two income levels during the past four decades to join Japan in the top income group.
Singapore and Hong Kong have also moved up one income group to the L1 level. Malaysia and Thailand have moved up one level to L2. Both China and India have moved up to L3, although they are indifferent catch-up groups. Indonesia, the Lao PDR, Vietnam, and Pakistan (in Group-C2) have also improved their income level to L3. This means that the number of lowest-income countries has been
reduced from ten at the start of the period to four (Cambodia,65 Myanmar, Bangladesh, and Nepal) by
2010. As expected, there were few movements in country groups with little or no catch-up. Only Pakistan moved up one level (as it marginally crossed the boundary of income groups from 4.9 per cent to
5.7 per cent that of the US), whereas Saudi Arabia and Bahrain are the only two countries that have
moved backward in their income level from L1 to L2.

6 Industry Perspective

Table 14 Country Groups Based on the Current Economic Level and the Paceof Catch-Up___Level and average annual growth rate of GDP at constant market prices, using 2005 PPPs
Per capita GDP levelto the US in 2010
(L1)
60% <

Annual rate of catch-up to the US
(C1)
>3%

(C2)
1% <–< 3%(C3)
0% <–< 1%

(C4)
<0%

ROC, Korea, Singapore

Hong Kong, OmanJapan, EU15

Brunei, Kuwait, Qatar,
UAE, Australia(L2)
20% <–< 60%(L3)
5% <–< 20%
(L4)
< 5%

Iran, Bahrain,
Saudi Arabia

Malaysia, Thailand
China

Cambodia

India, Indonesia,
Lao PDR, Sri Lanka,
Vietnam
MyanmarMongolia, PakistanFiji, Philippines

Bangladesh, Nepal

Sources: Official national accounts in each country, including author adjustments.
Note: The annual catch-up rates are based on the data during 1970–2010. The starting years for some countries
are different due to data availability: Cambodia (1987–), the Lao PDR (1984–), and Nepal (1974–).

Countries at the low rungs of the development ladder tend to have a bigger agriculture sector as ashare of value added.66 Figure 65 shows the industry composition67 of the Asian economies in 2009,and indicates a broad negative correlation between the share of the agriculture sector and the relative
per capita GDP against the US. Half of the Asian countries compared have an agriculture sector accounting for over 10 per cent of total value added, and they all have a relative per capita GDP that is
20 per cent below that of the US. Among them, the three countries with the biggest agricultural share
are all in the lowest income group (i.e., with a per capita GDP less than 5 per cent that of the US). In
contrast, the agriculture sector is 10 per cent or less of the total value added for Group-L2 countries,
compared to 3 per cent or less for Group-L1 economies. In particular, agriculture accounts for less than
1 per cent in the US, while it is negligible in Hong Kong and Singapore. Note also how finance, realestate, and business activities grow in weight as we move up income levels. The finance sector is especially prominent in Hong Kong (38 per cent), Singapore (30 per cent), and the US (33 per cent). Mining is what defines the oil-exporting countries, typically accounting for over 40 per cent of total value
added, except in Bahrain (22 per cent), Iran (15 per cent), and the UAE (28 per cent). These countries
have managed to diversify away from the dominance of mining. Finance is the biggest sector in Bahrain, accounting for 27 per cent of total value added, whereas it is the second largest sector (17 percent) in the UAE, following mining.

©2012 Asian Productivity Organization

Manufacturing is a key sector in propelling countries to make a leap in economic development. It accounts for around 20 per cent or above in nine of the 29 Asian countries compared. Among them,
manufacturing is the largest sector in China and Thailand, equivalent to around 30 per cent of total
value added, while it accounts for a quarter or more in Korea, the ROC, Malaysia, and Indonesia. At theother end are eight countries with manufacturing accounting for less than 10 per cent of total value

66: In Chapter 5, GDP is adjusted to be valued at basic prices (including our estimates, if the official estimates at basic prices are notavailable). However, the definition of GDP by industry differs among countries in this chapter due to data availability. GDP is valued at factor cost for Fiji, India, and Pakistan; at basic prices for Cambodia, Hong Kong, Korea, the Lao PDR, Mongolia, Nepal, andSingapore; at producers’ prices for Bangladesh, the ROC, Iran, and the Philippines; and at market prices for Indonesia, Japan, Malaysia, Sri Lanka, Thailand, and Vietnam.
67: The nine industries are 1–agriculture; 2–mining; 3–manufacturing; 4–electricity, gas, and water supply; 5–construction; 6–wholesale and retail trade, hotels, and restaurants; 7–transport, storage, and communications; 8–finance, real estate, and business activities; and 9–community, social, and personal services. See Appendix A.5 for the concordance with the International Standard
Industry Classification of All Economic Activities (ISIC), Revision 3.

94

6.1 Output and Employment

added. Among them, five are oilexporting countries and the otherthree are Hong Kong (2 per cent),68
Mongolia (7 per cent), and Nepal (6per cent). These compare with thevalues for the US at 11 per cent andAustralia at 9 per cent.

MyanmarGroup-L4
Cambodia
Nepal
Lao PDR
Pakistan
VietnamMongolia
BangladeshGroup-L3（except for
India
Bangladesh）
Indonesia
PhilippinesFiji
Sri Lanka
China
Thailand
Malaysia
Group-L2
Iran
Saudi Arabia
Korea
Australia
ROC
Oman
Japan
US
Group-L1
UAE（except for
Bahrain）
BruneiBahrain
Kuwait
Qatar
Hong Kong
Singapore
100 %6

Figure 66 shows the breakdown of
the manufacturing sector, consisting of nine sub-industries, for 17 selected Asian countries and the US.69
The dominance of machinery andequipment in Asian manufacturing
can be clearly seen, particularly in
the ROC and Singapore (close to 60
per cent of manufacturing’s total
value added), and Korea (50 percent) and Japan (43 per cent). These
compare with 39 per cent in the US.
At the other end are countries domi0
10
20
30
40
50
60
70
80
90
nated by light manufacturing (e.g.,
the food products, beverages, and
1. Agriculture
2. Mining
3. Manufacturing
4. Electricity, gas, and water supply
tobacco products sector in the Phil5. Construction
6. Wholesale and retail trade, hotels, and restaurants
ippines, Sri Lanka, Fiji, and Mongo7. Transport, storage, and communications
8. Finance, real estate, and business activities
9. Community, social, and personal services
lia, and the textiles, wearing apparel,and leather products sector in CamFigure 65 Industry Shares of Value Added, 2009
bodia and Bangladesh). Coke,
Sources: Official national accounts in each country, including author adjustments.
refined petroleum products, chemicals, rubber, and plastic products arealso a prominent subsector, notleast in Kuwait, where it accounts for two-thirds of the country’s manufacturing value added.

68: It reflects a process of manufacturing hollowing out of Hong Kong to the hinterland of China.
69: Manufacturing consists of nine sub-industries: 3.1–food products, beverages, and tobacco products; 3.2–textiles, wearing apparel,and leather products; 3.3–wood and wood products; 3.4–paper, paper products, printing, and publishing; 3.5–coke, refined petroleum products, chemicals, rubber, and plastic products; 3.6–other non-metallic mineral products; 3.7–basic metals; 3.8–machineryand equipment; and 3.9–other manufacturing. See Appendix A.5 for the concordance with ISIC, Revision 3.
70: The group averages as industry share of value added are based on a country’s industry GDP, using exchange rates for the whole
economy without consideration of the differences in relative prices of industry GDP among countries.
71: The service sector is defined in this Databook as 6–wholesale and retail trade, hotels, and restaurants; 7–transport, storage, andcommunications; 8–finance, real estate, and business activities; and 9–community, social, and personal services.

95©2012 Asian Productivity Organization

Figure 67 shows the industry shares of value added and employment by the four country groups
based on 2010 income levels, compared with the Asia29 average and the US for the years 1980, 1990,
2000, and 2009.70 The first thing to note is that in 2009, the service sector accounts for the largest shareof total value added in all country groups, independent of their economic development.71 That said,Group-L1 has always had the biggest service sector among all Asian countries, and this has becomemuch more distinctive as the weight of the economy in this group continues to shift heavily toward
services over time. By 2009, the service sector accounted for 70 per cent of total value added in GroupL1, compared to 81 per cent in the US and 52 per cent in Group-L2.72 The weight of the service sector

6 Industry Perspective

is similar in Group-L3 and Group-L4
at 46–47 per cent. This reflects therelative importance of manufacturing to the former and agriculture forthe latter at their particular stagesof development.

Mongolia
Sri Lanka
Philippines
Fiji
Indonesia
Hong Kong
ThailandBangladesh
Cambodia
Japan
US
Iran
India
Malaysia
Kuwait
ROC
Korea
Singapore

Second, Asia29 is still a region dominated by agriculture as far as employment is concerned, despite its
downward trend. In the past three
decades, the agricultural employment share for Asia29 dropped from
62 per cent in 1980 to 41 per cent in2009, while its share in total value
added rose from 6 per cent in 1980
to 10 per cent in 2009, implying that
agriculture is getting more laborefficient. In the past three decades,
the value-added share of agriculture in Group-L3 was more thanhalved from 31 per cent in 1980 to
13 per cent in 2009, with the most

%

1980

0

20

60

80

Figure 66 Industry Shares of Value Added in Manufacturing,2009
Sources: Official national accounts in each country, including author adjustments.

2000

%

%

90

90

90

90

80

80

80

80

70

70

70

70

60

60

60

60

50

50

50

50

40

40

40

40

30

30

30

30

20

20

20

20

10

10

10

10

0

0

0

0

Group Group Group Group Asia29 US
L-1
L-2
L-3
L-4

1. Agriculture
4. Electricity, gas, and water supply
7. Transport, storage, and communications

Group Group Group Group Asia29 US
L-1
L-2
L-3
L-4

2. Mining
5. Construction
8. Finance, real estate, and business activities

2009

Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.

100

Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.

100

Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.

100

Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.

100

Group Group Group Group Asia29 US
L-1
L-2
L-3
L-4

100 %

3-1. Food products, beverages, and tobacco products
3-2. Textiles, wearing apparel, and leather products
3-3. Wood and wood products
3-4. Paper, paper products, printing, and publishing
3-5. Coke, refined petroluem products, chemicals, rubber, and plastic products
3-6. Other non-metallic mineral products
3-7. Basic metals
3-8. Machinery and equipment
3-9. Other manufacturing

1990

%

40

Group Group Group Group Asia29 US
L-1
L-2
L-3
L-4

3. Manufacturing
6. Wholesale and retail trade, hotels, and restaurants
9. Community, social, and personal services

Figure 67 Industry Shares of Value Added and Employment by Country Group, 1980, 1990, 2000, and 2009©2012 Asian Productivity Organization

Sources: Official national accounts in each country, including author adjustments.

72: If Figure 65 was to rank by the size of the service sector, Hong Kong would top the table at 92.6 per cent, followed by the US (80.7
per cent), and other Group-L1 countries, namely the ROC (68.5 per cent), Japan (72.1 per cent), and Singapore (72.1 per cent). Fijiis an exception, with a large service sector share (67.2 per cent) relative to its per capita GDP level.

966.1 Output and Employment

rapid shift out of the sector taking place in the 1990s; employment in the sector was also cut by onethird over the same period. The least well-off countries, in contrast, have not been as successful in diversifying away from agriculture, which accounted for 27 per cent of total value added and 50 per centof employment in 2009, compared with 33 per cent and 69 per cent, respectively, in 1980. In themeantime, the richest economies continued to squeeze out agriculture even though it had a share of
only 3 per cent in total value added and 17 per cent in total employment in 1980. By 2009, the figures
had fallen to 2 per cent and 5 per cent, respectively.

6

Comparisons of the value added and employment shares also reveal some interesting facts. Agriculture is the only industry sector that consistently has a disproportionately higher employment sharethan justified by its share in value added across all country groups. This suggests that agriculture is still
highly labor-intensive and/or there may be a high level of underemployment in the sector in Asia,
both of which imply that the labor productivity level is low compared to other industry sectors.73 Thus,
countries with a big agriculture sector often have low per capita GDP, and shifting out of agriculture
will help boost economy-wide labor productivity. The US is an exception, where its agricultural valueadded share and employment share are similar, suggesting that labor productivity in this sector ishigher than experienced by Asian countries. The reverse is true for the sector of finance, real estate,and business activities, which often generates a much bigger value added share than suggested by its
employment share. In 2009, the sector accounted for 33 per cent of total value added generated by 19
per cent of employment in the US, and 14 per cent and 3 per cent, respectively, in Asia29. While thevalue-added share of the sector has grown by 50 per cent in the US over the past three decades, it has
only grown by 20 per cent in Asia29.
Third, the industry structure in Asian countries differs from that in the US in the relative importance of
manufacturing, even in Group-L1 countries, where manufacturing accounts for 20 per cent of theeconomies’ value added, compared with 11 per cent in the US in 2009. The US economy is highly
skewed toward the service sector, accounting for 81 per cent of the total value added, compared withan average of 70 per cent in Group-L1 countries. Especially, its share of finance, real estate, and business activities at 33 per cent is much larger than the share in Group-L1 countries, at 20 per cent. Thissuggests that Asian economies could experience further deindustrialization and a shift in prominence
toward services as they continue to mature. The relative prominence of manufacturing in the Asian
regional economy as a whole is reflected in the fact that income groups are not filtered out by thesize of a country’s manufacturing sector.74 In Asia, the manufacturing employment share is typicallysmaller than the value-added share that it generates. Furthermore the value-added share of the sector has been shrinking in the high-income groups (i.e., Group-L1 and Group-L2) whereas it has been
relatively stable in Group-L3 countries and slowly expanding in Group-L4, reflecting their different
development stages.

73: Gollin, Parente, and Rogerson (2004) and Caselli (2005) demonstrate the negative correlation between employment share of agriculture and GDP per worker. They show that the agriculture sector was relatively large in less well-off countries and agriculturallabor productivity was lower than that in other sectors.
74: If Figure 65 was to rank by the size of the manufacturing sector, China would lead with a share of 32.3 per cent, followed by Thailand and Korea at 29.8 per cent and 27.8 per cent, respectively.

97©2012 Asian Productivity Organization

Figure 68 shows how the share of the agriculture industry in total value added shrank over time in the
Asian economies. This could reflect the actual decline in agricultural output and/or the relatively rapid
expansion in other sectors. Despite the wide spread, the downward trend is unmistakable, even forGroup-L4 countries. The share of the agriculture sector displays a long-term declining trend in all
countries, albeit at different paces and at different starting times. Looking at the available data, theshare of agriculture in most Asian countries (excluding the oil-exporting countries) clustered around6 Industry Perspective

%

%

30

ROC
Hong Kong
Japan
Korea
Singapore
Brunei
Kuwait
Oman
Qatar
UAE
Australia

25
20
15
10
5
0
1970

1975

1980

1985

1990

1995

2000

2005

2010

50

25
20
15
10

0
1970

1975

1980

1985

1990

1995

2000

2005

2010

1985

1990

1995

2000

2005

2010

%

China
Indonesia
Pakistan
Philippines
Sri Lanka
VietnamFiji
Lao PDR

70

India
Mongolia

60
50

40

40

30

30

20

20

10
1970

ThailandBahrainSaudi Arabia

Group-L2

%

60

Iran
Malaysia

5Group-L1
70

30

1975

1980

1985

1990

1995

2000

2005

2010

Group-L3

10
1970

Bangladesh
Cambodia
Myanmar
Nepal

1975

1980

Group-L4

Figure 68 Long-Term Trends of Value Added Share in the Agriculture Sector, 1970–2009
Sources: Official national accounts in each country, including author adjustments.

©2012 Asian Productivity Organization

the 30–50 per cent band in the 1970s, trending down to the 10–20 per cent band by 2009. Vietnam
and Mongolia are two countries where the agriculture sector experienced similar relative decline but
within a much shorter time span (from the late 1980s and mid-1990s, respectively). The relative decline of agriculture was most rapid in Korea, from 29 per cent of total value added in 1970 to 2.7 percent in 2009. In many countries, the share of the agriculture sector was more than halved between
1970 and 2009: for example, from 47 per cent to 15 per cent in Indonesia, from 42 per cent to 18 percent in India, and from 39 per cent in 1972 to 19 per cent in Bangladesh. In China, the share of this
sector also significantly declined, from 36 per cent in 1970 to 10 per cent in 2009.
Despite the relative decline of agriculture’s share in total value added, employment in the sector for
Asia as a whole still accounted for 41 per cent of total employment in 2009. Figure 69 shows countries’
industry shares in total employment, and ranks them by size of employment in the agriculture sector.75 Group-L4 and Group-L3 countries plus Thailand cluster at the top end in Figure 69, with the shareof agricultural employment ranging from 34 per cent (Sri Lanka) to 75 per cent (Nepal). In contrast,
the service sector accounts for the biggest share in total employment in Group-L1 countries, ranging

75: Data for the Lao PDR and Myanmar are unavailable for Figure 69.

986.1 Output and Employment

from 55 per cent (UAE) to 87 percent (Hong Kong); Qatar is theon-ly exception with a share of 40
per cent.

Nepal
Cambodia
India
Vietnam
Pakistan
BangladeshIndonesia
Mongolia
China
ThailandPhilippines
Sri Lanka
Iran
Malaysia
Fiji
Oman
Korea
ROC
Japan
UAE
Saudi Arabia
Australia
KuwaitBahrain
Qatar
US
BruneiSingapore
Hong Kong

Group L-4

Group L-3
(except for
Bangladesh andThailand)The trend of employment shareover time (Figure 70) suggeststhat the relative decline in theshare of agriculture in total value
Group L-2
(except for Fiji)
added has been accompanied bya downward trend in its share in
total employment. This trend isunmistakable in most countries
plotted in Figure 70. However, theGroup L-1
(except for
decline in share does not always
Bahrain andreflect an actual fall in employSaudi Arabia)
ment for the agriculture sector; rather, it could reflect total
employment rising faster thanem-ployment in agriculture. Coun0
10
20
30
40
50
60
70
80
90 100 %tries that have been experiencing
1. Agriculture
2. Mininga consistent fall in actual employ3. Manufacturing
4. Electricity, gas, and water supply
5. Construction
6. Wholesale and retail trade, hotels, and restaurants
ment in the agriculture sector are,
7. Transport, storage, and communications
8. Finance, real estate, and business activities
for example, the ROC, Hong Kong,
9. Community, social, and personal services
Japan, and Korea, whereas in
Figure 69 Industry Shares of Employment, 2009
Cambodia, India, Iran, Nepal, andPakistan, actual employment has
Sources: Official national accounts in each country, including author adjustments.
been rising. Other countries suchas Thailand, Indonesia, Singapore,
Malaysia, and Vietnam have no established trend in employment growth. China, however, has seen
actual employment in agriculture falling since the turn of this millennium.

6

Manufacturing is a main absorption sector for workers who have been displaced from the agriculture
sector, especially in the initial stages of economic development. Figure 71 traces the time path of thegrowth rates of GDP and employment in combination in manufacturing for some selected Asian
countries and the US for the past four decades. Each dot represents the average annual growth rate in
the 1970s, 1980s, 1990s, and 2000s. If manufacturing GDP and employment grow at the same rate, itwill be on a 45° line through the origin running from the lower left to upper right quadrants. In the US

76: Nepal’s employment by industry is constructed by interpolating benchmark data taken from its labor force survey as well as its
population census. Figure 69 indicates that its share of agriculture has increased since 1999. This reflects the employment share of
agriculture at 66 per cent in the population census of 2001 and its share of 74 per cent in the labor force survey of 2008.

99©2012 Asian Productivity Organization

As shown in Figure 70, the decline in agricultural employment share has been rapid in some countries.76 Between 1970 and 2009, the employment share in agriculture shrank from 50 per cent to 7 percent in Korea and from 20 per cent to 5 per cent in Japan. Employment in agriculture also fell rapidly
in the ROC, from 25 per cent in 1978 to 5 per cent in 2009. In all these countries, the decline reflects anactual fall in employment in the agriculture sector. In China, the share has declined from 71 per centin 1978 to 39 per cent in 2009.

6 Industry Perspective

%

%

60

90

ROC
Hong Kong
Japan
Korea
Singapore
Brunei
Kuwait
Oman
Qatar
UAE
Australia

50
40
30
20

70
60
50
40
30
20

10
0
1970

Iran
Malaysia
ThailandBahrainSaudi Arabia

80

10
1975

1980

1985

1990

1995

2000

2005

2010

Group-L1

0
1970

1975

1980

1985

1990

1995

%

70

90
80

50
40

70

30

0
1970

2010

Bangladesh
Cambodia
Myanmar
Nepal

60

10

2005

%

100

80

20

2000

Group-L2

60
China
Fiji
Indonesia
Pakistan
Sri Lanka

1975

Group-L3

1980

India
Mongolia
Philippines
Vietnam

1985

1990

50

1995

2000

2005

2010

40
1970

1975

1980

1985

1990

1995

2000

2005

2010

Group-L4

Figure 70 Long-Term Trends of Employment Share in the Agriculture Sector, 1970–2009
Sources: Official national accounts in each country, including author adjustments.

©2012 Asian Productivity Organization

and Japan, growth in manufacturing employment has been relatively stable, whereas output growthhas been fluctuating within a bigger range. In Korea, the growth of manufacturing output has beenslowing the past four decades. Employment growth slowed more than output in the 1990s, implying
a labor productivity boost in manufacturing during that period. The reverse is true for the 2000s. In the
middle chart of Figure 71, Singapore, Indonesia, and Thailand experienced a slowdown in manufacturing output growth throughout the whole period. The bulk of the employment adjustment in
Singapore took place in the 1970s when employment growth fell faster than output. Thereafter, employment growth has been relatively stable compared to output as manufacturing output growthcontinues to slow. In China, India, Pakistan, Sri Lanka, and Iran, the job creation role of manufacturing
is still effective or becoming more important, and at times, output growth and employment growth
go in different directions, meaning that employment growth is accelerating even when output growthis slowing.

1006.2 Industry Growth

%

10

8

Growth ofemployment in mnf

Growth ofemployment in mnf

7

8

5

India
Iran
Pakistan
Sri Lanka

6
Growth of
GDP in mnf

0
−8

%

%

10

Growth ofemployment in mnf

−4

4

8

−5

12

16 %

ROC
Hong Kong
Japan
Korea
US
Australia

−10

−15

6
China
Indonesia
Singapore
Thailand

4
2

5
4
3
2

0
−2

0

5

10

15

20 %

Growth of
GDP in mnf

61
Growth of GDP in mnf

0
0

2

4

6

8

10 %

Figure 71 Job Creation in Manufacturing, 1970–2009___Average annual growth rates of GDP at constant prices and number of employment

Sources: Official national accounts in each country, including author adjustments.
Note: Each dot represents the average annual growth rate in manufacturing (mnf ) in the 1970s, 1980s, 1990s, and 2000s (2000–
2009). The white dot indicates the rate in the latest decade.

6.2 Industry Growth
In Section 3.2, we see that, as a region, growth in Asia29 accelerated in the latest period 2005–2010,averaging 5.8 per cent per annum, up from 5.3 per cent in 2000–2005. China and India have been thetwo main drivers among the Asian economies, accounting for 70 per cent and 18 per cent of the region’s growth during 2000–2010, respectively. However, looking at the industry composition, the origins of economic growth in China and India are quite different. For the period 1978–2004, Bosworth
and Collins (2008) indicate that China’s economic growth has been fueled by industry sector expansion,77 whereas for India economic growth has been led by service sector expansion. Although ourfindings broadly support their conclusion, we also discern that the nature of growth in China may
have started shifting more toward services in recent years.

77: The industry sector in Bosworth and Collins (2008) is equivalent to the industry groups 2–5 in this report.
78: The Törnqvist quantity index is adopted for calculating the growth of real GDP. Using this index, we can decompose the growth ofreal GDP into the products of contributions by industries:
In (GDPt / GDPt−1) = ∑ i (1/2) (sjt + sjt−1) In (Qjt / Qjt−1)
where Qjt is real GDP of an industry j in period t and sjt is the nominal GDP share
Real GDP growth

Contribution of an industry jof an industry j in period t.

101©2012 Asian Productivity Organization

The effect of extending our latest period to include 2009 has noticeably pulled down the averages forthis period. The adverse impact of the global financial crisis has been significant for most countries
and deep in some, turning the period atypical for comparisons. Our results show that manufacturing
had been the biggest contributor to economic growth in China until the 2000s when the service sector overtook manufacturing in this respect (Figure 72).78 The gap between contributions of manufacturing and services was the widest in the early 1990s; it narrowed in the late 1990s until they switchedover in relative importance in the 2000s, with manufacturing and services accounting for 34 per centand 44 per cent of economic growth, respectively. In contrast, economic growth in India has always
been dominated by services and this character of its growth is getting more pronounced over time.
The contributions of manufacturing and services to economic growth were 16 per cent versus 64 percent in 2000–2009, compared with 18 per cent and 51 per cent in 1985–1990. The increased prominence of the service sector was eroding not so much the weight of manufacturing but agriculture, thecontribution of which shrank from 18 per cent in the late 1980s to 7 per cent in the latest period ofcomparisons. In the US and Australia, the main driver of growth has been services, contributing over

6 Industry Perspective

%

%

12

12

1985–1990

10

1990–1995

10

8

8

6

6

4

4

2

2

0

0

−2

−2

−4

−4
Mongolia
Japan
Philippines
US
Saudi Arabia
Fiji
Qatar
Brunei
Australia
Bangladesh
Pakistan
Nepal
Bahrain
MyanmarIndia
Oman
Sri Lanka
Iran
Lao PDR
ROC
Cambodia
Indonesia
Korea
Vietnam
UAE
ThailandSingapore
KuwaitMalaysia
China

Myanmar
KuwaitIranBahrainBruneiUAE
Oman
Lao PDR
Sri Lanka
US
Australia
Saudi Arabia
Bangladesh
Qatar
Fiji
Mongolia
Japan
Philippines
Nepal
Vietnam
Pakistan
India
Indonesia
China
ROC
Singapore
Malaysia
Korea
Thailand
%

%

12

12

1995–2000

10

2000–2009

10

8

8

6

6

4

4

2

2

0

0

−2

−2

−4

−4
Japan
BruneiUS
Fiji
Saudi Arabia
ROC
Australia
Hong Kong
Korea
Malaysia
Nepal
ThailandOman
Singapore
Philippines
Pakistan
Sri Lanka
Indonesia
UAE
Iran
Bahrain
Bangladesh
Mongolia
KuwaitVietnamIndia
Lao PDR
Cambodia
China
Qatar
MyanmarThailandIndonesia
Japan
Mongolia
BruneiFiji
KuwaitSaudi Arabia
Hong Kong
Oman
Philippines
Australia
Pakistan
Iran
Bahrain
US
Nepal
Korea
Sri Lanka
Bangladesh
ROC
Malaysia
Lao PDR
India
Singapore
UAE
Vietnam
Cambodia
Myanmar
China
Qatar
1. Agriculture

2. Mining

3. Manufacturing

4. Electricity, gas, and water supply

5. Construction

6. Wholesale and retail trade, hotels, and restaurants

7. Transport, storage, and communications

8. Finance, real estate, and business activities

9. Community, social, and personal services

Real GDP

Figure 72 Industry Origins of Economic Growth, 1985–1990, 1990–1995, 1995–2000, and 2000–2009___Industry decomposition: Average annual growth rate of GDP at constant prices

Sources: Official national accounts in each country, including author adjustments.

©2012 Asian Productivity Organization

70 per cent during all the periods compared. The contribution of manufacturing to economic growthin Australia has been under 10 per cent while in the US, the share was between 15–22 per cent before
falling to 5.5 per cent in the latest period.
In the second half of the 1980s, manufacturing was a clear driver behind the fastest-growing countries
in Asia (i.e., Thailand, Korea, Malaysia, Singapore, the ROC, and China), contributing between 2 and 3.5
percentage points to economic growth. Such a pattern was not repeated in the subsequent periodsof comparisons. Only China with a significant manufacturing contribution manages to be among thefastest-growing countries in the later periods of comparisons, whereas the main growth driver has
been mining in Qatar and agriculture in Myanmar. Manufacturing has sustained its prominence inThailand, Korea, and the ROC, contributing 34 per cent, 36 per cent, and 45 per cent to economic
growth in 2000–2009, respectively, while its importance waned in Singapore from 27 per cent in
1990–2000 to 21 per cent in 2000–2009 (Figure 74). In Hong Kong, it has been a drag on economic
growth in the past decade or so. During the Asian crisis, the most impaired economies were Thailand
and Indonesia, and the sectors which bore the brunt were (1) construction, (2) wholesale and retailtrade, hotels, and restaurants, and (3) finance, real estate, and business activities. In contrast, manufacturing played a significant role in bolstering the economy at the time (Figure 73).
The service sector plays an equally, if not more, important role in Asian economic growth. Services
made the biggest contribution to economic growth in all Asian countries except Qatar (Figure 76).

102

6.2 Industry Growth

4.0 3.0

2.0

1.0

0.0 −1.0 %

3.4
2.5
2.3
2.2
1.8
1.6
1.6
1.4
1.3
1.2
1.1
0.8
0.8
0.8
0.7
0.7
0.7
0.6
0.5
0.5
0.5
0.5
0.5
0.4
0.3
0.2
0.2
0.2
0.0
−0.4

Contribution

−0.8

China
Cambodia
Korea
Malaysia
VietnamSingapore
UAE
ROC
Lao PDR
Sri Lanka
Iran
Bangladesh
US
Philippines
India
Indonesia
MyanmarThailandOman
FijiPakistan
Nepal
Qatar
Saudi Arabia
Brunei
Australia
Japan
Bahrain
KuwaitHong Kong
Mongolia

−30

0

30

60 %
42

4.0 3.0

2.0

0.0 −1.0 %

2.4

35
47

2.1

40

1.6

26

1.4

27

1.4

25

1.4

26

1.2

23

1.2

25

1.2

27

1.2

17
18

1.2

20

0.9

1.0

12

0.9
90

0.9

9

0.8
0.7

110

0.7

17
31

0.6

13

0.6

10

0.5

4

0.4
0.3

17
26

0.1

6

0.1
26

0.0

6

0.0

−2

0.0

−14
−67

1.0

3.4

−0.1

Contribution share

Contribution

−0.2

China
MyanmarVietnam
Cambodia
Korea
ThailandROC
Pakistan
BangladeshIndonesia
India
Iran
Oman
Bahrain
Singapore
Lao PDR
Malaysia
Philippines
Sri Lanka
Mongolia
KuwaitSaudi Arabia
UAE
Qatar
Australia
US
Fiji
Nepal
BruneiJapan
Hong Kong

−30

0

30

60 %
35

20
31
21
36
34
45
26
21
24
16

6

22
24
17
21
12
20
16
15
11
9
21
8
2
3
5
3
0
−5
−37
−4

Contribution share

Figure 73 Contribution of Manufacturing to
Economic Growth, 1995–2000

Figure 74 Contribution of Manufacturing to
Economic Growth, 2000–2009

Sources: Official national accounts in each country, including
author adjustments.

Sources: Official national accounts in each country, including
author adjustments.

The story behind India’s recent growth has been about services. Modern information and communication technology has allowed India to take an unusual path in its economic development, bypassing a
stage when manufacturing steers growth.79 Within the service sector, contribution is quite evenly
spread among the sub-sectors. More recently, the iron/steel and motor vehicle sectors have been
rapidly developing in India.80 For further improvement in per capita GDP and to capitalize on the demographic dividend (see Box 2), expansion of labor-intensive manufacturing may be required for more
job creation.

79: The computer software industry in India depends considerably on export demands. According to India’s Input–Output Table 2006–
2007, 82.0 per cent of the output in computer and related activities is exported. This export is equivalent to 14.8 per cent of totalexports in India and is the second-largest export product (among 130 products in this table).
80: In 2011, India was the 6th largest producer (3.9 million) of motor vehicles (80.1), following Korea (4.7), Germany (6.3), Japan (8.4), theUS (8.7), and China (18.4), based on a survey by OICA (International Organization of Motor Vehicle Manufacturers). India moved up
in the rankings from 15th (0.8) in 2000 to 12th (1.6) in 2005.

103©2012 Asian Productivity Organization

Economic growth in the Asian Tigers was also dominated by the service sector, albeit more so in Singapore and Hong Kong than in the ROC and Korea, where manufacturing remained a significant force.
The service sector accounted for 56 per cent of growth in the ROC for the period 2000–2009, 54 percent in Korea, 76 per cent in Singapore, and 107 per cent in Hong Kong (to counterbalance the negative contribution of 5 per cent by manufacturing and 4 per cent by construction) (Figure 76). These
compare with 106 per cent in the US (to counterbalance the negative contribution of 13 per cent byconstruction). In the 2000s, growth in Hong Kong was highly skewed toward wholesale and retailtrade, hotels, and restaurants, accounting for 42 per cent of growth. This compares with 23 per cent in
Singapore and 19 per cent in the ROC. In contrast, the sector contributed only 6 per cent to Korea’s

6 Industry Perspective

5.0 4.0 3.0 2.0 1.0 0.0 −1.0 %
4.0
4.0
3.7
3.4
3.2
3.1
3.0
2.9
2.9
2.8
2.8
2.7
2.5
2.5
2.5
2.3
2.3
2.3
2.2
1.9
1.8
1.8
1.6
1.4
1.4
1.1
1.1
0.8
0.8
0.3
−0.1

Contribution

−30

ROC
Singapore
India
UAE
US
China
Australia
Hong Kong
Cambodia
Sri Lanka
Malaysia
Iran
Myanmar
Korea
Bahrain
Nepal
VietnamBangladesh
Philippines
KuwaitPakistan
Mongolia
Qatar
Lao PDR
Oman
Fiji
Saudi Arabia
BruneiJapan
ThailandIndonesia −18

0

30

60

90 %
74

6.0 5.0 4.0 3.0 2.0 1.0 0.0 %
4.7

65

4.4

63

4.4

55

4.4
77

39

4.4
4.2

79

3.7

103

3.7

42

3.7
58

3.6

51

3.3
69

3.3

33

3.2
53

3.1

60

3.0

50

2.8

34

2.7
45

2.7
60

2.7
97

2.6
2.6

48

2.6

144

2.3

15

2.1

26

2.1

43

1.7

68

1.4

54

1.4

62

1.3

80

1.2

55

0.5

Contribution sharecontribution
Contribution

India
China
MyanmarBahrain
Qatar
KuwaitLao PDR
Hong Kong
Mongolia
Cambodia
UAE
Singapore
Iran
Sri Lanka
Bangladesh
Philippines
Oman
Malaysia
PakistanIndonesia
Vietnam
Nepal
Australia
Korea
ThailandROC
Saudi Arabia
Fiji
US
Brunei
Japan

0

30

60

90 %
64

45
38
81
38
68
50
107
60
46
66
76
61
64
53
65
63
69
56
53
39
64
74
54
51
56
59
96
106
275
261

contribution share
Contribution
share

Figure 75 Contribution of Service Sector to
Economic Growth, 1995–2000

Figure 76 Contribution of Service Sector to
Economic Growth, 2000–2009

Sources: Official national accounts in each country, including
author adjustments.

Sources: Official national accounts in each country, including
author adjustments.

©2012 Asian Productivity Organization

growth over the same period (Figure 78). Finance, real estate, and business activities also played an
important part, contributing 44 per cent to growth in Hong Kong, 31 per cent in Singapore, and 15 percent in the ROC.
The oil-exporting countries have different industry structures from other countries, with their relianceon mining for growth. The sector is volatile in nature and could in turn give rise to big swings in these
economies from one period to another. In 2000–2009, mining accounted for half of economic growthin Qatar, but less than 10 per cent in the UAE, Kuwait, and Saudi Arabia, and only 1.0 per cent in Iran,reflecting a drop in the demand toward the end of 2008 and 2009. (Excluding 2009, the figures are
one-third in the UAE, Kuwait, and Saudi Arabia, and 14 per cent in Iran in 2000–2008.) Still, it has beena drag, and a significant one in some cases, on growth: its contribution was −6 per cent in Bahrain, −13
per cent in Oman, and −219 per cent in Brunei, reflecting a reduction in oil or gas production. These
countries have to learn to diversify. Bahrain has been successful in branching into finance, real estate,and business activities, which accounted for 39 per cent of the 5.4 per cent overall growth over thesame period. Oman also sustained growth of 3.9 per cent on average a year, 68 per cent of which
originated from the service sector. Brunei has not managed as well, with dismal growth of 0.5 per centon average a year between 2000 and 2009. Oil and gas production activities are also reflected in Mongolia and the Lao PDR, where mining accounted for 17 per cent and 21 per cent of overall economic
growth, respectively, in the 2000s.
Japan’s growth rate in the 2000s (at 0.7 per cent in Table 3) was one of the slowest in the region. As
Japan was among those most affected by the global financial crisis, the industry contribution for thisperiod is atypical for Japan. Figure 78 shows that Japan is the only country where the contribution of104

6.2 Industry Growth

2.0 1.5

1.0

0.5

0.0 −0.5 %

1.8
1.4
1.3
1.2
1.2
1.1
1.0
1.0
0.8
0.8
0.8
0.8
0.8
0.7
0.7
0.7
0.6
0.6
0.6
0.5
0.5
0.4
0.4
0.3
0.3
0.3
0.0
0.0
−0.1
−0.1

Contribution−0.2

MyanmarUAE
Sri Lanka
Iran
ROC
Vietnam
India
US
Nepal
Philippines
Cambodia
China
Bangladesh
Lao PDR
Mongolia
Hong Kong
Singapore
Malaysia
Australia
Korea
Fiji
Qatar
Pakistan
Oman
BahrainSaudi Arabia
KuwaitIndonesia
BruneiJapan
Thailand

−20

0

20

40

60 %

23

3.0 2.5 2.0 1.5 1.0 0.5 0.0 −0.5 %
2.4

23

1.9
1.4

26
31

1.4

22

1.3

16

1.2

17

1.1
23

1.1

18

1.0

22

1.0

12

1.0

10

0.9

15

0.9

13

0.9
0.8

57

0.8

25
10

0.8

11

0.7

15

0.7
0.6

11

0.5

32

0.5

4
10

0.4

9

0.4
0.4

7

0.3

12

0.2

2

0.2

−1

0.1

−8

0.1

−14
−46

Contribution share

Contribution−0.1

MyanmarLao PDR
Hong Kong
India
Vietnam
China
UAE
Sri Lanka
Cambodia
Singapore
Bangladesh
Qatar
Iran
Indonesia
Philippines
Malaysia
Pakistan
Oman
Mongolia
ROC
BahrainThailand
KuwaitAustralia
Fiji
Saudi Arabia
Korea
Brunei
US
Nepal
Japan

−20

0

20

40

60 %

21
25
42
19
19
12
21
22
14
23
17
8

6

17
17
18
20
16
15
11
19
10
12
7
12
24
11
6
38
9
3
−71

Contribution share

Figure 77 Contribution of Wholesale and Retail to Economic Growth, 1995–2000

Figure 78 Contribution of Wholesale and Retail to Economic Growth, 2000–2009

Sources: Official national accounts in each country, including
author adjustments.

Sources: Official national accounts in each country, including
author adjustments.

wholesale and retail trade, hotels, and restaurants was negative (−71 per cent). In contrast, the contribution to growth is more evenly spread among the service sub-sectors in the US, with finance, realestate, and business activities leading with a 53 per cent contribution (Figure 72).

Comparing across the country groups in Table 15, Asia enjoyed more vibrant growth than the US in all
sectors, noting that the US was more directly affected by the global financial crisis of 2008–2009.
Overall construction retrenched in the US in the 2000s, while their growth has been the strongest inSouth Asia and GCC countries, at 8.6 per cent and 8.8 per cent a year on average respectively. Apartfrom construction, the other fast-growing sector in GCC countries and South Asia was transport,

81: In Myanmar, agriculture accounted for over 38 per cent of GDP in 2009. Since 1988, the government has continued its modest
steps to liberalize the sector and marketing controls have been made less onerous. As a result, farm production has increased. According to official statistics, the quality of which has been questionable, this sector accounted for 34.7 per cent of GDP growth in
2000–2009.

105©2012 Asian Productivity Organization

For some Asian countries, agriculture is still the biggest sector. The four countries where the agriculture sector has the largest share in total value added are Myanmar, Cambodia, Nepal, and the Lao PDR(Figure 65). For the period 2000–2009, agriculture in Myanmar, Nepal, and Cambodia had the highest
contribution to economic growth among all Asian countries, accounting for 35 per cent, 26 per cent,and 22 per cent of growth, respectively.81 In the latest period, agricultural output is still expanding in
the majority of Asian countries, suggesting that the shrinkage in its value added share (Figure 68) over
the recent period is more a result of rapid growth in other sectors than any actual contraction of thesector. The agriculture sector is contracting in the ROC, Fiji, Hong Kong, Japan, Qatar, and the UAE,
with the deepest retrenchment (of −4.3 per cent) in Hong Kong (Table 15).

6 Industry Perspective©2012 Asian Productivity Organization

Table 15 Output Growth by Industry, 2000–2009
3. Manufacturing

4. Electricity, gas,
and water supply

5. Construction

Bahrain
Bangladesh
Brunei
Cambodia
China
ROC
Fiji
Hong Kong
India
Indonesia
Iran
Japan
Korea
KuwaitLao PDR
Malaysia
Mongolia
Myanmar
Nepal
Oman
Pakistan
Philippines
Qatar
Saudi Arabia
Singapore
Sri Lanka
Thailand
UAE
Vietnam

1.4 −1.5
3.2
7.9
3.1 −1.6
5.1
16.7
4.1
10.6
−0.1 −6.1−1.0
0.8−4.3 −4.1
2.6
4.6
3.5
0.8
3.3
0.1
−1.5 −10.9
2.0 −0.3
3.0
2.4
2.8
46.4
3.0
0.5
2.8
5.5
8.3
13.2
3.0
4.0
1.8 −1.0
2.9
5.9
3.1
10.7
−1.7
10.6
1.1
0.7
0.1
0.0
2.4
11.8
2.3
5.0
−2.6
0.8
3.6
2.3

8.2
7.3
−0.4
8.4
10.6
5.1
0.3
−4.7
7.7
4.3
8.6
−0.4
5.3
8.3
8.7
2.6
8.0
20.0
0.1
11.5
7.2
2.9
4.2
5.2
3.2
3.7
4.8
3.9
10.1

7.3
6.8
2.9
12.4
10.6
2.4
0.3
1.8
5.9
7.9
8.0
−0.2
5.5
15.3
−0.8
4.3
4.1
10.8
6.1
11.3
−0.2
3.8
5.4
6.2
3.7
6.1
5.6
9.5
12.5

8.5
7.3
4.9
11.1
11.8
−1.8
1.4
−4.1
9.1
6.7
5.3
−3.1
2.5
8.2
5.6
2.4
4.1
19.3
3.5
21.2
2.8
3.7
21.6
3.6
2.4
5.9
3.3
10.2
8.8

6. Wholesale andretail trade, hotels,
and restaurants
7. Transport,
storage, andcommunications
8. Finance, realestate, andbusiness activities
9. Community,social, andpersonal services

2. Mining___Average annual growth rate of industry GDP at constant prices
1. Agriculture

storage, and communications (atover 10 per cent a year on average), probably reflecting their effort in building and upgrading
infrastructure for their development needs. Finance, real estate,and business activities also enjoyed robust expansion at 9.0 per
cent and 6.9 per cent a year on average in South Asia and GCC
countries, respectively, comparedwith 2.0 per cent in the US and 4.0
per cent in Australia. For East Asia,
mining is the sector that has enjoyed the most rapid growth at
10.1 per cent a year on average.
Manufacturing has been growing
at 6.7 per cent a year on averagein Asia23 and 5.3 per cent in GCC
countries, compared with under 1
per cent in both the US andAustralia.

5.1
6.5
5.1
7.2
12.0
3.0
2.1
5.3
8.5
5.5
5.7
−0.9
2.0
8.2
10.7
6.2
6.1
10.9
0.9
7.6
4.4
4.9
14.6
4.6
5.5
4.4
2.7
5.8
7.4

8.4
7.3
3.8
7.4
8.6
2.4
2.2
4.0
12.2
12.0
9.6
5.2
4.8
14.1
9.0
5.7
14.3
17.1
9.8
12.0
3.7
7.3
28.3
8.1
3.6
7.9
5.7
9.7
8.8

7.7
4.3
4.7
10.3
11.4
2.4
1.6
4.5
9.5
6.6
7.1
0.6
3.8
12.6
8.6
6.9
7.1
23.5
5.0
6.5
7.2
5.9
13.2
3.8
5.1
5.6
5.7
6.6
1.3

7.8
5.4
3.9
10.5
10.8
2.5
2.3
1.4
6.6
5.1
4.3
0.2
3.7
5.7
11.3
5.4
4.0
12.1
7.9
5.4
6.3
4.1
12.0
2.9
4.0
4.1
3.3
7.1
7.9

Looking at countries individually,
it is interesting to note that all
sectors in China grew faster thanthose in India, except transport,
storage, and communications,
showing India’s special strength.
(regrouped)Industrial specialization in servicAPO20
2.5
1.5
3.7
3.2
2.8
3.7
7.1
4.2
2.5
Asia23
3.3
5.3
6.7
6.3
5.7
5.8
7.6
5.7
4.5
es has intensified in Hong Kong,
Asia29
3.2
3.9
6.7
6.4
5.8
5.8
7.7
5.8
4.5
with manufacturing hollowing
East Asia
3.6
10.1
6.9
6.5
4.8
5.3
6.7
4.8
4.1
out and agriculture, construction,
South Asia
2.6
4.9
7.5
5.0
8.6
7.7
10.3
9.0
6.4
ASEAN
3.6
1.4
4.5
6.1
5.6
5.2
7.9
5.9
4.8
and mining, all contracting at
GCC
0.5
1.7
5.3
8.7
8.8
6.0
10.6
6.9
4.5
over 4 per cent a year on average.
(reference)
This process is probably a reflecUS
3.5
0.8
0.4
−1.3
−4.0
0.8
3.4
2.0
1.1
tion of its economic integration
Australia
1.5
2.6
0.7
1.4
6.8
3.0
3.7
4.0
2.9
with the Chinese economy folUnit: Percentage.
lowing the handover in 1997: theSources: Official national accounts in each country, including author adjustments.
two economies are evolving tocomplement each other. Manufacturing maintains its prowess as a fast-growing sector in Korea (5.3 per cent) and the ROC (5.1 per cent),
while Singapore’s relative strength is more evenly distributed across sectors. Growth has been weak inJapan all-round, partly reflecting the impact of the global financial crisis in 2009. Mining has been suffering badly, contracting by 10.9 per cent a year on average. Construction is also declining by 3.1 percent on average a year. The strongest growth of 5.2 per cent in Japan has been experienced in transport, storage, and communications.
Figure 79 presents the sub-industry origins of average annual growth of manufacturing GDP for
selected Asian countries for the periods 1995–2000 and 2000–2009.82 Manufacturing in Asia has been106

6.2 Industry Growth

1995–2000%

20

2000–2009

%

10
8

16

6

12

4

8

2

6

4
0
0
−2

Japan
US
Singapore
Malaysia
KuwaitPhilippines
Indonesia
Thailand
ROC
Korea
Cambodia
Bangladesh
India
Iran

−2

Japan
ThailandIndonesia
Philippines
India
US
Bangladesh
ROC
Iran
Malaysia
Korea
Cambodiadominated by machinery andequipment, accounting for 40 per
cent or more of overall manufacturing growth in half of the Asian
countries compared. In Korea andthe ROC, it was over 80 per cent.
The food products, beverages,
and tobacco products sub-sector
is the largest contributor in thePhilippines for both periods, accounting for 57 per cent of manufacturing output growth in 1995–
2000 and rising to 80 per cent in
2000–2009. In Bangladesh andCambodia, manufacturing growthhas been dominated by the subsector of textiles, wearing apparel, and leather products, whereas
in Kuwait, and to a lesser extent in
Singapore and Malaysia, it is coke,
petroleum, chemicals, rubber,and plastic products.

3-1. Food products, beverages, and tobacco products
3-2. Textiles, wearing apparel, and leather products
3-3. Wood and wood products
3-4. Paper, paper products, printing, and publishing
3-5. Coke, petroluem, chemicals, rubber, and plastic products
3-6. Other non-metallic mineral products
3-7. Basic metals
3-8. Machinery and equipment
3-9. Other manufacturing
3. Manufacturing

Figure 79 Industry Origins of Output Growth in Manufacturing, 1995–2000 and 2000–2009

82: The Törnqvist quantity index is adopted for calculating the growth of real GDP of manufacturing. Using this index, we can decompose the growth of real GDP of manufacturing into the products of contributions by sub-industries of manufacturing:
In (GDPt / GDPt−1)= ∑ i (1/2) (sjt + sjt−1) In (Qjt / Qjt−1)
where Qit is real GDP of a sub-industry j in period t and sit is the nomReal GDP growth of manufacturing

Contribution of a sub-industry jinal GDP share of a sub-industry j in period t.
83: Asian averages are calculated using the Törnqvist index to aggregate the growth rates of industry GDP of each country based on
the two-period average of each country’s shares of industry GDP to the gross regional products as weights.

107©2012 Asian Productivity Organization

Figure 80 contrasts industry con___Sub-industry decomposition: Average annual growth rate of GDP attributions to economic growth forconstant prices of manufacturing
the periods 1995–2000 and 2000–
Sources: Official national accounts in each country, including author adjustments.
2009, as well as between the US
and Asian averages.83 Even withinsuch a short period, we can see that the industry structure of growth is changing. The first striking
feature is the dominance of manufacturing in the Asian countries. Between 1995 and 2000, its contribution to economic growth in Asia23 was 32 per cent compared with 18 per cent in the US. Although
its significance has fallen in recent years, it still accounted for 29 per cent of economic growth in
Asia23 between 2000 and 2009, compared with 5 per cent in the US. This, however, masks the divergence within Asia. In the earlier period, manufacturing accounted for 37 per cent of growth in East
Asia but only 13 per cent in South Asia. The corresponding figures were 33 per cent and 17 per cent in
the 2000s, so the differential is narrowing. Another big difference between East Asia and South Asia
was the contribution made by agriculture, at 5 per cent and 16 per cent, respectively, in the late 1990s.
In the 2000s, its contribution was halved to 8 per cent in South Asia, although it was still twice as big
as in East Asia. Over the same period, the contribution from construction increased by 50 per cent,from 6 per cent to 9 per cent in South Asia. The country group most dominated by manufacturing in
the late 1990s was ASEAN, with a contribution of 39 per cent. Yet, in recent years manufacturing’s

6 Industry Perspective%

1995–2000

100

16

120

2000–2009

23

26

22

21

23

10

10

8

19

80

40

11

13

12

11
1
4

11
1
4

11
9
0
4

32

0

32

37

26

0

2

8

8

2
7

3
5

15

13

14

14

12

18

11

14

14
19

39

2

23

4
0
18

18

13
−9

14
6
3

16

18

5

11

2
−1

12

10
13

8

4

4

−2

14

16

13

16

14

11

9

15

1

19

6

17

6
3

4

20

10

14

33
10

11

12

17

15

13

60

13
5
14

14
6

12
5
4

18
13

19
6
3

3

5
2

9
29

28

33

53
12

11
3

1

25

21

12

17

21
1

4
6

6

4
5

5
4

2
8

9
2
9

16
0

5
2
3
−2
−15

US

GCC

ASEAN

South Asia

East Asia

Asia29Asia23

1. Agriculture
3. Manufacturing
5. Construction
6. Wholesale and retail trade,hotels, and restaurants
8. Finance, real estate, andbusiness activities

APO20

US

GCC

ASEAN

South Asia

East Asia

Asia29Asia23−20

APO20

contribution was reduced to 25 per cent,while wholesale and retail trade, hotels, andrestaurants increased from 10 per cent to 18
per cent. The latter also increased its weightin APO20, from 12 per cent to 16 per centbetween the two periods compared. In theUS, the finance, real estate, and businessactivities sub-sector made the biggest
contribution in both periods, accounting
for 33 per cent of economic growth in 1995–
2000 and rising to 53 per cent in 2000–2009.
In contrast, its contribution in Asia was 14
per cent in the period 2000–2009. Mining in
GCC countries took a hit in 2008–2009 dueto the downturn in the world economy.
Consequently, the contributions of mining
fell from 18 per cent to 16 per cent between
the two periods while construction’s share
increased from 4 per cent to 11 per cent. Finance, real estate, and business activities
became the biggest contributor to economic growth in GCC countries, with its
share rising from 17 per cent to 19 per centbetween the two periods.

2. Mining
4. Electricity, gas, andwater supply
7. Transport, storage, andcommunications
9. Community, social, andpersonal services

The agriculture sector is much more significant in Asia23 than in the US, with a contriFigure 80 Industry Origins of Regional Economic
bution of 8 per cent compared with 2 per
Growth, 1995–2000 and 2000–2009
cent for the period 1995–2000. In the 2000s,___Contribution share
however, the relative significance of the agSources: Official national accounts in each country, including author
riculture sector in Asia23 fell to 6 per cent.
adjustments.
Construction was hit hard in the ASEAN
countries during the Asian financial crisis,
pulling down economic growth by 9 per cent in the latter half of the 1990s. It bounced back subsequently and contributed 6 per cent to growth in the 2000s. The corresponding figures for Asia23 were
1 per cent and 6 per cent. The reverse was true in the US, where the contribution of construction was
4 per cent in the earlier period but fell to −15 per cent in the later period in the 2000s. The contributionof wholesale and retail trade, hotels, and restaurants was also high in the US. In 1995–2000, it accounted for 23 per cent of US economic growth compared with 11 per cent in Asia23. Though in
2000–2009 its contribution was reduced to 9 per cent in the US, its significance to economic growthrose to 14 per cent in Asia23.

©2012 Asian Productivity Organization

Figure 81 presents industry contributions to regional economic growth in Asia29 during 2000–2009,decomposing Figure 7 in Section 3.1 into countries’ industry origins.84 In each industry contribution,

84: The average growth rate of the Asian economy for 2000–2009 is set at 100 per cent. Asian economic growth is calculated as thesum of the contributions over countries and industries:∑ x (1/2) (sxt + sxt−1) ∑ i (1/2) (sx,t j + sx,t−1j ) In (Qx,t j / Qx,t−1j )where Qx,t j is real GDP of an industry j in a country x in period t, sx,t j is GDP share ofContribution of an industry j in a country x

an industry j in a country x with respect to GDP of a country i in period t and sxt is GDP share of a country x with respect to the regional GDP in period t. All the industries whose contribution is more than 0.25 per cent are shown in Figure 81.
1086.2 Industry GrowthOver a long period of four decades, we can see the shift of theindustry origins of economic
growth in countries (Figure 82).
For the ROC and Korea, manufacturing has been a clear driving
force behind economic growth on
the whole. In the decade between
the mid-1980s and the mid-1990s,
however, the importance of manufacturing retreated in the ROC
temporarily while the economy
developed its service sector. Since
the mid-1990s, the role of manufacturing in explaining growth in
the ROC has increased again,
though compared to its heydaysof the 1970s and 1980s, the impact in terms of percentage
points is much reduced.
Comparing the industry profilesof China and India over time, thedifferences in the nature of their
growth can clearly be seen. In
contrast to the dominance of

3. Manufacturing
18.3

0

5
China

2.8

10

15

Korea

Indonesia

India

1.4 0.8 0.8

3.5

20

25
ROC

30 %

Rest of the Asia

9. Community, social, and personal services
7.9

0

2

4

China

0.7 0.4 0.4

2.1

India

2.7

6

8

10

Korea

Iran

Japan

12

Rest of the Asia

0.6 0.6 0.4

2.5

6

14 %

6. Wholesale and retail trade, hotels, and restaurants
6.9

0

2

3.2

4

China

6

India

8

Indonesia

10
Iran

12

14 %

ROC

Rest of the Asia

8. Finance, real estate, and business activities
5.6

0

3.3

2

4

China

India

0.8

0.7 0.5

3.2

6

8

10

Korea

Iran

Japan

12

14 %
Rest of the Asia

7. Transport, storage, and communications
3.8

0

2.3

2
China

1.8

4

6

Japan

Indonesia

India

0.6 0.4

2.3

8

10
Iran

12 %

Rest of the Asia

5. Construction
3.7

0

1

1.6

2

China

3

India

0.3

4

Indonesia

0.3 0.2 0.0

5

UAE

6%

Korea

Rest of the Asia

1. Agriculture
2.7

0

1
China

2
India

1.1

0.3 0.2 0.2

Iran

Pakistan

3

Indonesia

0.8

4

5

6%
Rest of the Asia

2. Mining
3.1

0

0.4

1
China

2

Qatar

0.3

3

India

0.2 0.1

0.4

4

Saudi Arabia

5%

KuwaitRest of the Asia

4. Electricity, gas, and water supply
2.1

0

0.5
China

0.3

1
India

1.5
Iran

2
Korea

0.1 0.1 0.1

2.5
Vietnam

0.4

3

3.5 %

Rest of the Asia

Figure 81 Industry Origins of Asian Economic Growth,
2000–2009___Contribution to regional growth of GDP at constant prices, using
2005 PPPs
Sources: Official national accounts in each country, including author adjustments.

109©2012 Asian Productivity Organization

we present the top eight countries. The top four industries interms of contributions to regional
growth were manufacturing (28per cent), wholesale and retailtrade (14 per cent), finance, realestate, and business activities (14per cent), and community, social,
and personal services (14 percent). A total of 28 per cent of
Asian economic growth originated from the expansion of its
manufacturing sector, two-thirdsof which was accounted for by
China. In other words, China’s
manufacturing sector alone accounted for nearly 19 per cent of
the region’s economic growth.
This was followed by China’s community, social, and personal services (7.9 per cent) and wholesale
and retail trade, hotels, and restaurants (6.9 per cent).

6 Industry Perspective

Bahrain%50

Bangladesh%
14

Brunei

%
20

12

40

10

30

10

8
6

20

0

4
10

2

−2

−10
−20

−20

−4
1971

1976

1981

1986

1991 1996

2001

2006

Cambodia

%
12

6

3

0

1971

1976

1981

1986

1991 1996

2001

2006

Hong Kong

%
16

−6

1971

1976

1981

1986

2006

−30

12

12

10

10

8

8

6

6

4

4

2

2

0

0

−2

−2

1971

1976

1981

1986

1991 1996 2001

1971

1976

1981

2006

India

−4

1971

1976

1981

5

3

0

0

−5

−3

−10

1991 1996 2001

2006

1986

1991 1996 2001

2006

Indonesia

%
10

6

1986

ROC

%
14

14

%
9

12

1991 1996 2001

China

%
16

9

−3

−10

0

0

8
4
0
−4
−8

1971

1976

1981

1986

1991 1996

2001

2006

Iran

%
20

−6

1971

1976

1981

1986

1991 1996 2001

2006

Japan

%
10

1976

1981

1986

1991 1996 2001

2006

Korea

12

6
9

4
0

−10

2

6

0

3

−2

0

−4

−20

−3

−6
−30

1971

%
15

8
10

−15

1971

1976

1981

1986

1991 1996

2001

2006

Kuwait

%
60

−8

1971

1976

1981

1986

1991 1996 2001

2006

Lao PDR

%
15

−6

1971

1976

1981

1991 1996 2001

2006

Malaysia

%
12

40

1986

8

10
20

4
5

0

0
−20
0

−4

−40

©2012 Asian Productivity Organization

−60

1971

1976

1981

1986

1991 1996

2001

2006

−5

1971

1976

1981

1. Agriculture
2. Mining
5. Construction
6. Wholesale and retail trade, hotels, and restaurants
9. Community, social, and personal services

110

1986

1991 1996 2001

2006

−8

1971

1976

3. Manufacturing
7. Transport, storage, and communications
Real GDP

1981

1986 1991

1996 2001

2006

4. Electricity, gas, and water supply
8. Finance6.2 Industry Growth

Mongollia%
9Myanmar

%
15

6
3

Nepal

%
8

10

6

5

4

0

2

−5

0

−10

−2

0
−3
−6
−9
−12

1971

1976

1981

1986

1991 1996

2001

2006

Oman

%
30

−15

1971

1976

1981

1986

1991 1996

2001

2006

Pakistan

%
10

1976

1981

1986

1991 1996

2001

2006

Philippines

6

6

6
10

1971

%
9

8

20

−4

3

4
0
2

0

−3

0
−10

−20

−6

−2

1971

1976

1981

1986

1991 1996

2001

2006

Qatar

%
45

−4

1971

1976

1981

1991 1996

2001

2006

Saudi Arabia

%
20

30

1986

15

12

10

10

1971

1976

1981

1986

1991 1996

2001

2006

Sri Lanka%
91991 1996

2001

2006

2001

2006

2001

2006

2001

2006

Singapore

2
0
−2

−20

−4
1971

1976

1981

1986

1991 1996

2001

2006

Thailand

%
16

−6

1971

1976

1981

1986

1991 1996

UAE

%
100

12
6

1986

4

−15

−25

1981

6

0

−10

−15

1976

8

−5

0

1971

%
14

5
15

−9

80

8

60

4
3

40
0
20

−4

0

−8
−3

1971

1976

1981

1986

1991 1996

2001

2006

Vietnam

%
9

3

0

1971

1976

1981

1986

1991 1996

1971

1976

1981

1986

2001

2006

1991 1996

2001

2006

US

%
7

6

−3

−12

−20

6

5

5

4

4

3

3

2

2

1

1

0

0

−1

−1

−2

−2
1971

1976

1981

1. Agriculture
2. Mining
5. Construction
6. Wholesale and retail trade, hotels, and restaurants
9. Community, social, and personal services

1986

1991 1996

1976

1981

2001

2006

−3

1986

1991 1996

Australia

%
7

6

−3

1971

1971

1976

3. Manufacturing
7. Transport, storage, and communications
Real GDP

1981

1986

1991 1996

4. Electricity, gas, and water supply
8. Finance

Figure 82 Industry Origins of Economic Growth, 1970–2009___Industry decomposition: Average annual growth rate of GDP at constant prices
Sources: Official national accounts in each country, including author adjustments.

111©2012 Asian Productivity Organization06 Industry Perspective

manufacturing in China (and in, for example, Korea, the ROC, and Japan in their similar development
stages), manufacturing has never driven economic growth in India. Similarly, Australia has never beena country propelled by manufacturing. Over the years, agriculture has become less important in driving economic growth, while service industries gain significance in China. In Singapore, finance, realestate, and business activities, as well as wholesale and retail trade, hotels, and restaurants are important driving industries alongside the manufacturing sector. With the limited data we have, Hong Kong
has been a clear service-driven economy in recent years. The lack of diversification of the oil-exporting
countries cannot be missed. Historically, the preponderance of the mining sector underlay the volatility faced by these economies. Yet, in recent years the GCC countries have been making efforts in diversifying, especially into the service sector, with different degrees of success. Bahrain and Oman areleading the way and have yielded results. The largely agricultural countries are Myanmar, the Lao PDR,
Cambodia, Nepal, and Pakistan, and, to a lesser extent, Vietnam and Bangladesh. In the Philippines,
construction was driving economic growth in the first half of the period compared, but it has neverrecovered its dominance after its crash in the mid-1980s. In the second half, economic growth wasbetter balanced, with the development of finance, real estate, and business activities in particular.

6.3 Labor Productivity by Industry
Section 5.1 discusses per worker measures of labor productivity performance in level terms, andidentifies a large gap between Asia as a whole and the US. In 2010, Hong Kong and Singapore werethe countries that had labor productivity levels comparable to that of the US. Besides these two, thebest performers in Asia achieved productivity levels that were at least 40 per cent that of the US; yet,
Asia collectively was dragged down by a long tail of countries with labor productivity less than 20 per
cent of the US level, pulling down the average performance to 17 per cent that of the US for APO20 and
15 per cent for Asia23. In growth terms, however, Asia’s performance far exceeded that of the US,
allowing the countries to close the gap with the US gradually over time. Labor productivity growth in
Asia23 was 5.5 per cent per annum on average between 2005 and 2010, compared to 1.3 per cent in
the US (Table 9).

©2012 Asian Productivity Organization

Table 16 presents cross-country comparisons in labor productivity growth by industry85 for the period
2000–2009.86 Positive labor productivity growth was achieved across all sectors for Asia23. Our findings highlight the fact that service industries are no longer a drag on an economy’s productivity performance but are as capable as manufacturing in achieving productivity growth. In fact, the sector
that managed the fastest labor productivity growth was transport, storage, and communications (at4.7 per cent on average a year). Agriculture, utilities, and manufacturing came next at 4.1 per cent, 3.3
per cent, and 3.1 per cent, respectively. Construction was the sector with the slowest productivity
growth at 1.4 per cent. Labor productivity achieved by the other sectors ranged from 1.9 per cent (incommunity, social, and personal services) to 2.7 per cent (in wholesale and retail trade, hotels, and

85: Labor productivity in Table 16 is defined simply as per-worker GDP at constant prices by industry (vj). The industry decompositionof labor productivity growth for the whole economy (v) in Figure 83 is based on the equation v = ∑ jwjvj* where the weight is thetwo-period average of value-added shares. In this decomposition, the number of workers as a denominator of labor productivity (vj*) is adjusted, weighting the reciprocal of the ratio of the real per-worker GDP by industry to its industry average. Thus, theindustry contribution (wjvj*) is emphasized more in industries in which the per-worker GDP is higher than the industry average, incomparison with the impact (wjvj) of using the non-adjusted measure of labor productivity.
86: Data presented in this chapter are subject to bigger uncertainty than those in the previous chapters and the quality across countries is also more varied. Employment data of the less developed countries often lack frequency as well as industry details. Neither
does the industry classification of employment data necessarily correspond to those of industry output data. Consequently, thequality of labor productivity estimates at the industry level is adversely affected. Furthermore, estimates on the manufacturingsector should be of better quality than those on the service sector because many countries do not have a census covering theservice sector but have occasional manufacturing censuses.

1126.3 Labor Productivity by Industry

Table 16 Labor Productivity Growth by Industry, 2000–2009
4. Electricity, gas,
and water supply

5. Construction−6.7 −9.4
2.2
21.5
0.5 −4.0
4.1
11.1
6.9
8.1
3.3
2.7
2.5 −0.7
−0.7
3.8
1.8
1.2
2.9 −9.7
3.1 −1.7
0.4 −4.5
5.4 −3.6
−5.0
3.3
0.0
0.0
3.6 −8.6
2.6
2.4
0.0
0.0
−0.1 −6.4−5.5 −10.4
0.2 −3.4
1.0
4.8−8.2 −3.7
1.3
3.1
−6.2
0.0
2.1
10.0
1.7
3.4
−4.3 −3.6
3.6
0.8

−0.7
1.9
−4.4
0.2
7.0
4.6
2.0
−0.2
2.4
3.3
6.6
1.6
6.5
2.2
0.0
4.6
7.3
0.0
−0.9
4.6
2.4
2.2
−4.3
4.3
1.1
0.8
3.2
0.1
3.5

−0.8
16.5
−0.1
−5.6
7.1
2.7
−4.4
3.7
2.9
−4.5
4.4
−0.2
1.0
9.1
0.0
2.4
2.7
0.0
0.4
−0.7
−3.5
2.9
6.1
6.7
1.4
13.3
6.6
2.4
7.3

0.2
4.6
2.3
−3.1
6.6
−1.2
−9.7
−2.8
6.1
2.6
−0.2
−1.1
1.6
2.2
0.0
−0.8
−3.7
0.0
1.4
12.3
−2.1
0.4
0.3
−0.7
−0.3
3.3
−1.5
−1.5
−1.3

−3.6
2.5
2.0
−1.3
8.3
1.9
−0.3
4.4
5.5
3.6
2.5
−1.2
2.4
1.5
0.0
1.9
1.8
0.0
−1.3
1.8
−1.3
−0.9
3.1
0.9
2.1
1.7
−0.8
−1.5
3.2

0.2
−1.0
1.2
0.6
7.0
2.3
2.1
3.6
9.2
8.9
3.0
1.5
0.3
7.2
0.0
2.3
5.4
0.0
6.1
5.4
−0.2
4.3
12.8
3.8
0.7
4.3
3.8
3.1
5.0

−0.9
−10.9
1.6
1.8
8.6
−0.5
−3.5
1.9
6.5
0.8
0.8
0.7
−0.3
2.1
0.0
0.1
6.1
0.0
−0.9
−0.9
−3.4
−2.1
−3.7
−4.9
−0.8
−1.0
1.2
−6.7
−7.0

−0.8
3.5
0.7
0.7
7.9
0.1
1.8
−0.7
3.6
1.0
3.0
−0.2
−0.7
0.0
0.0
3.5
0.2
0.0
10.4
−0.9
5.5
3.6
9.0
−0.5
−0.8
5.2
−0.1
2.6
0.9

Compared with Asia23, the US87
was stronger in labor productivity
growth in four sectors:, agriculture (4.1 per cent versus 4.9 percent), wholesale and retail trade,hotels, and accommodations (2.7
per cent versus 1.4 per cent),
transport, storage, and communications (4.7 per cent versus 4.7
per cent), and finance, real estate,and business activities (2.2 percent versus 2.1 per cent). If we(regrouped)look at individual countries, howAPO20
1.7 −2.6
0.1
1.2
−0.1
0.8
3.3
0.6
0.2
Asia23
4.1
2.2
3.1
3.3
1.4
2.7
4.7
2.2
1.9
ever, there was stronger perforAsia29
4.1
0.8
3.0
3.3
1.5
2.7
4.7
2.2
1.9
mance than the US in these sectors:
East Asia
6.4
7.7
4.1
3.4
0.6
2.6
4.6
2.4
1.6
for example, agriculture in China
South Asia
1.7
1.8
2.3
3.9
5.3
4.2
6.2
5.4
4.1
ASEAN
3.0 −6.1
2.4
1.6
0.5
1.9
4.8
−0.4
1.2
(6.9 per cent) and Korea (5.4 per
GCC−1.2 −1.1
1.8
6.5
−0.1
0.7
4.8
−3.3
0.3
cent); wholesale and retail trade,(reference)
hotels, and restaurants in China
US
4.9 −1.6
4.6
−0.5
−3.1
1.4
4.7
2.1
−0.2
(8.3 per cent), India (5.5 per cent),
Australia
3.4 −5.5
1.4
−2.9
2.5
1.2
2.3
1.6
−0.1
and Hong Kong (4.4 per cent);
Unit: Percentage.
transport, storage, and communiSource: APO Productivity Database 2012.01.
cations in India (9.2 per cent), Indonesia (8.9 per cent), and China(7.0 per cent); and finance, real estate, and business activities in China (8.6 per cent) and India (6.5 percent). Note that although different countries top the ranking in different industries, China was the
only country with labor productivity persistently strong and close to the region’s leaders acrossall sectors. In contrast, Japan experienced negative labor productivity growth in five out of thenine sectors.

87: The strengths and weaknesses of the US might have been distorted by the impact of the global financial crisis during thelate 2000s.

113

6©2012 Asian Productivity Organization

3. Manufacturing

Bahrain
Bangladesh
Brunei
Cambodia
China
ROC
Fiji
Hong Kong
India
Indonesia
Iran
Japan
Korea
KuwaitLao PDR
Malaysia
Mongolia
Myanmar
Nepal
Oman
Pakistan
Philippines
Qatar
Saudi Arabia
Singapore
Sri Lanka
Thailand
UAE
Vietnam

6. Wholesale andretail trade, hotels,
and restaurants
7. Transport,
storage, andcommunications
8. Finance, realestate, andbusiness activities
9. Community,social, andpersonal services

2. Mining___Average annual growth rate of industry labor productivity
1. Agriculture

restaurants). Within Asia, the divergence between South Asia
and East Asia is stark. While South
Asia had a much higher labor productivity in services and construction, and less so in utilities, East
Asia led by quite a distance in theother three sectors of agriculture,mining, and manufacturing. Including the GCC countries does
not make a significant difference
to the Asian averages except forthe mining sector, labor productivity growth in which was pulled
down from 2.2 per cent for Asia23
to 0.8 per cent for Asia29.

6 Industry Perspective

Figure 83 shows the industry origins of average labor productivity growth per annum in four periods:
1985–1990, 1990–1995, 1995–2000, and 2000–2009.88 Among these periods, labor productivity clearly slowed in the second half of the 1990s due to the general impact of the Asian financial crisis. Countries gradually recovered in the 2000s, but at different paces. Table 9 suggests that Asia23’s laborproductivity growth was more than fully restored to the pre-crisis rate in the first half of the 2000s.
Thereafter, there was a strong pick-up to 5.5 per cent in 2005–2010. China has been leading laborproductivity growth among the countries compared by a big margin since 1990, but in the past five
years, India has been closing on China’s productivity performance. In the past two-and-a-half decades,
we can see that the role played by agriculture (both positive and negative) has been diminishing in
Asian countries. While the importance of manufacturing has never waned in some countries (e.g.,
Korea, the ROC, China, and Thailand), it has not been a major contributor in India in its recent development process, or in Hong Kong and Sri Lanka in the 2000s.
The manufacturing sector has been a major driving force behind productivity growth in most Asian
countries, as shown in Figures 84 and 85. In the late 1990s, manufacturing accounted for a significant
part of labor productivity growth in Korea (68 per cent), Malaysia (78 per cent), and China (55 per
%

%

12

12

1985–1990

9

1990–1995

9

6
6

3

3

0
−3

0

−6
−3

−9

%

−6

Mongolia
Philippines
Fiji
Japan
US
Nepal
Australia
Bangladesh
India
MyanmarCambodia
Pakistan
IranSingapore
Korea
ROC
VietnamIndonesia
Malaysia
Sri Lanka
Thailand
China

Myanmar
Iran
Sri Lanka
Mongolia
Australia
Bangladesh
US
Fiji
China
Indonesia
India
Philippines
Pakistan
Japan
Nepal
Singapore
Malaysia
Thailand
ROC
Korea

−12

%

10

10

1995–2000

8

2000–2009

8

6

6

4

4

2

2

−4

−4

Japan
Singapore
Fiji
Australia
PakistanUS
Nepal
Philippines
Thailand
Malaysia
ROC
Iran
Hong Kong
Korea
BangladeshIndonesia
Sri Lanka
Mongolia
Cambodia
Vietnam
India
China

0
−2
Indonesia
Mongolia
ThailandHong Kong
Iran
Pakistan
Fiji
Japan
Nepal
Sri Lanka
Malaysia
Australia
Philippines
US
MyanmarCambodia
India
Bangladesh
Korea
Singapore
ROC
Vietnam
China

0
−2

1. Agriculture

2. Mining

4. Electricity, gas, and water supply

5. Construction

3. Manufacturing
6. Wholesale and retail trade, hotels, and restaurants

7. Transport, storage, and communications

8. Finance, real estate, and business activities

9. Community, social, and personal services©2012 Asian Productivity Organization

Real GDP

Figure 83 Industry Origins of Labor Productivity Growth, 1985–1990, 1990–1995,
1995–2000, and 2000–2009___Industry decomposition: Average annual growth rate of GDP at constant prices

Source: APO Productivity Database 2012.01.

88: Not all Asian countries are included, because employment by industry sector is not available for some countries.

1146.3 Labor Productivity by Industry

4.0 3.0 2.0 1.0 0.0 −1.0 %
3.8
2.8
1.7
1.5
1.3
1.3
1.0
0.8
0.7
0.7
0.7
0.6
0.5
0.4
0.4
0.3
0.2
0.1
0.0
−0.2
−0.4
−0.4
−0.5

Contribution
contribution

China
Korea
Singapore
Cambodia
Vietnam
Malaysia
ROC
Bangladesh
USJapan
Hong Kong
Philippines
ThailandSri Lanka
Indonesia
Iran
Australia
FijiPakistan
Myanmar
India
Nepal
Mongolia

−30

0

30

60 %

3.0 2.5 2.0 1.5 1.0 0.5 0.0 −0.5 %

55

2.9
68

1.6

41

1.3

46

1.3

28

1.2
78

1.2

22

1.1

21

0.9

32

0.8

46

0.7

78

0.6

28

0.6

283

0.6

24

0.5

−25

0.4

37

0.4

12

0.3

6
−4

0.2

−6

0.2

−11

0.2

−29

0.1

−275

Contribution share toaggrergate labor productivity−0.1

Contribution

China
Korea
Vietnam
ROC
Malaysia
ThailandIndonesia
Cambodia
Iran
Bangladesh
Philippines
Pakistan
Mongolia
US
Singapore
Fiji
Japan
India
Sri Lanka
Australia
Hong Kong
Nepal

−10

10

30

50

70 %

31
60
31
57
55
57
34
22
32
23
39

6

46
17
35
66
42
79
4
5
17
4
−6

Contribution share toaggrergate labor productivity

Figure 84 Contribution of Manufacturing toLabor Productivity Growth, 1995–2000

Figure 85 Contribution of Manufacturing toLabor Productivity Growth, 2000–2009

Sources: APO Productivity Database 2012.01.

Sources: APO Productivity Database 2012.01.

Traditionally, it has been difficult for the service sector to realize productivity growth, but modern
advancements in information and communication technology have changed that. A lot of IT-intensive
users are in this sector, which is capable of capturing the productivity benefits arising from IT utilization. We have observed the growing importance of services in explaining productivity growth inWestern economies in recent decades. In Asia, the contribution from services matches that of manufacturing. Among the four industries in the service sector, three are potentially IT-using industries:
wholesale and retail trade, hotels, and restaurants; transport, storage, and communications; and finance, real estate, and business activities. Figures 86 and 87 present the contribution of services inlabor productivity growth by country. In the 2000s, services were contributing at least one-third or
more to labor productivity growth in most Asian countries. The contribution was predominant inHong Kong and India, accounting for 94 per cent and 78 per cent of labor productivity growth, respectively. It also accounted for around two-thirds or more of labor productivity growth in the US, Sri
Lanka, and Singapore. Korea had the lowest share from the service sector, accounting for less than
one-fifth of labor productivity growth. We see a slight expansion of the role played by services in
China, from 32 per cent to 38 per cent between the two periods. The contribution of services was also
highly significant in South Asian countries like Bangladesh, India, Nepal, and Pakistan over the same
period. Finance, real estate, and business activities made the largest contribution of 1.4 percentage
points in India and 1.5 percentage points in Hong Kong, respectively, while transport, storage, andcommunications made the largest contribution of 1.8 percentage points in Mongolia. It was particularly prominent that in India all four industries significantly contributed to the improvement of
economy-wide labor productivity for the period 2000–2009, while the contribution of manufacturing
was negative for the period 1995–2000 and 4 per cent in 2000–2009.

115©2012 Asian Productivity Organizationcent). Nevertheless, its role has lessened in the 2000s to 60 per cent, 55 per cent, and 31 per cent, respectively. In contrast, the contribution by manufacturing strengthened from 22 per cent to 57 percent in the ROC and from 46 to 79 per cent in Japan between the two periods. However, in some
economies, like India, Hong Kong, Sri Lanka, and Nepal in the 2000s, manufacturing played a negligible role.

6 Industry Perspective

4.0 3.0 2.0 1.0 0.0 −1.0 −2.0 %
3.1
2.6
2.4
2.3
2.2
2.2
1.5
1.5
1.4
1.3
1.1
1.1
1.0
0.9
0.8
0.7
0.4
0.3
0.3
0.3
0.1
−0.9
−0.9

0

Contribution

60

90 %

0

5.0 4.0 3.0 2.0 1.0 0.0 %
4.0

90
59

3.5

57

2.5

59

2.4
68

2.4

32

1.8

67

1.6

92

1.5

70

1.5

91

1.4

648

1.3

22

1.3

104

1.2

36

1.0

20

0.8

98

0.8

26
16

0.7
38

0.7

18

0.5

12

0.5
0.4
67

0.0

Contribution share toaggrergate labor productivity

Contribution

India
China
Sri Lanka
Hong Kong
Nepal
Mongolia
Iran
Cambodia
Indonesia
Vietnam
Pakistan
Bangladesh
Philippines
US
Thailand
Malaysia
ROC
Fiji
Korea
Australia
Singapore
Japan

20

40

60

80 100 %
78

38
73
94
175
49
64
38
47
32
101
47
71
71
39
35
32
81
19
50
60
1

Contribution share toaggrergate labor productivity

Figure 86 Contribution of Service Sector toLabor Productivity Growth, 1995–2000

Figure 87 Contribution of Service Sector toLabor Productivity Growth, 2000–2009

Sources: APO Productivity Database 2012.01.

Sources: APO Productivity Database 2012.01.

1.2 0.8 0.4 0.0−0.4 −0.8−1.2 %
1.0
0.8
0.8
0.7
0.7
0.6
0.6
0.4
0.4
0.3
0.2
0.2
0.2
0.2
0.2
0.0
0.0
0.0
0.0
−0.3
−0.4

Contribution©2012 Asian Productivity Organization

30

India
ROC
Singapore
Bangladesh
Cambodia
China
US
Sri Lanka
Australia
Nepal
Mongolia
Vietnam
Pakistan
Myanmar
Korea
Iran
Japan
Philippines
Hong Kong
Malaysia
Fiji
Thailand −471
Indonesia

Myanmar
Sri Lanka
India
Bangladesh
US
ROC
China
Iran
CambodiaFiji
Mongolia
Australia
Philippines
Pakistan
Hong Kong
Nepal
Korea
Japan
VietnamSingapore
Malaysia−1.1 Thailand−1.1 Indonesia

−30

0

30

60 %

2.0

1.5

1.0

0.5

0.0 −0.5 %

1.1

37
51
23

1.1
0.9

19

0.7
31

0.7

15

0.5

9

0.4
53

0.3

12

0.3

27

0.3

127

0.3

10

0.2

9

0.0

17

0.0

20

0.0

3

−0.1

1
−2

−0.1

−1

−0.1
−0.2

−7

−0.2

−26

−0.3

−570

−0.3

78

Contribution share toaggrergate labor productivity

Contribution

Hong Kong
India
China
Vietnam
Sri Lanka
Indonesia
Iran
ROC
Korea
Singapore
Bangladesh
US
Mongolia
Australia
Cambodia
Pakistan
Nepal
Fiji
Malaysia
Japan
ThailandPhilippines−30 −10 0 10

30

50 %
44

22
10
17
19
15
16
15
12
46
11
15
1
−1
0
−6
−7
−14
−8
−45
−12
−20

Contribution share toaggrergate labor productivity

Figure 88 Contribution of Wholesale andRetail Sector to Labor Productivity Growth,
1995–2000

Figure 89 Contribution of Wholesale andRetail Sector to Labor Productivity Growth,
2000–2009

Sources: APO Productivity Database 2012.01.

Sources: APO Productivity Database 2012.01.

116

7 Real Income
The standard GDP concept does not adequately measure welfare, as discussed in Section 3. Amongthe shortcomings is its neglect of the terms-of-trade effect. An improvement in the terms of trade (i.e.,
the relative prices of a country’s exports to imports) unambiguously raises real income and in turnwelfare.89 In many ways, a favorable change in the terms of trade is synonymous with technologicalprogress as it makes it possible to get more for less; that is, for a given trade balance position, a country can either import more for what it exports, or export less for what it imports.

7.1 Real Income and Terms of Trade7

By focusing on production per se, the real GDP concept does not capture this beneficial effect of the
improvement in the terms of trade.90 In contrast, real income focuses on an economy’s consumption
possibilities, and in turn captures the impact of a change in the relative price of exports to imports.
Real income growth attributed to changes in the terms of trade can be significant when there arelarge fluctuations in import and export prices and the economy under concern is highly exposed tointernational trade, like many Asian economies (see Figure 26). For example, real income growth foroil-exporting countries was more than double that of real GDP growth in recent years (as in Saudi
Arabia and Brunei), while there has been no significant difference between real income growth andreal GDP growth in Myanmar, which is a relatively closed economy (Figure 96). In the recent decade,the trading gain has also driven a significant wedge between real income and real GDP in Australia.
That is partly because import prices have fallen, but more because prices of its commodity exports
have risen.
The distinction between real income and real GDP lies in the differences between the corresponding
deflators. Real GDP is calculated from a GDP deflator aggregating prices of household consumption,
government consumption, investment, exports, and imports,91 while real income is calculated fromthe prices of domestic expenditure, consisting of household consumption, government consumption, and investment. Therefore, real income can be considered as how much domestic expenditure
can be purchased with the current income flow.92 As such, real income captures the purchasing powerof the income flow. Furthermore, in this report we adopt the concept of GNI (gross national income)instead of GDP in our estimation of real income, to take into account net income transfer from abroad.93
Applying the method proposed by Diewert and Morrison (1986), the annual growth rate of real income can be fully attributed to three components: annual growth rate of real GDP, real income growth
attributed to changes in prices of exports and imports (referred to as the trading gain),94 and the effectof net income transfer.95

89: See Diewert and Morrison (1986) and Kohli (2004).
90: Kohli (2004) explains this point: “if real GDP is measured by a Laspeyres quantity index, as it is still the case in most countries, animprovement in the terms of trade will actually lead to a fall in real GDP.”
91: The weight for import price changes is negative. Thus, if import prices decrease, this tends to raise the GDP deflator.
92: This definition of real income is the same as in Kohli (2004, 2006). An alternative definition is nominal GDP deflated by the price ofhousehold consumption; this is adopted by Diewert, Mizobuchi, and Nomura (2005) and Diewert and Lawrence (2006).
93: Note that this is a departure from the Databook 2011, which defines income by domestic production as encapsulated in the concept of GDP.
94: The term “trading gain” is used by some authors (Kohli, 2006). This term is adopted in this report.

117©2012 Asian Productivity Organization

The general observation is that the trading gain effect is small on average over a long period of time,
but over a shorter period it could be very significant.96 Our findings presented in Table 17 confirm thisobservation. Excluding the oil-exporting countries, the trading gain effect in 17 out of 22 economies
compared fell within the margin of ±10 per cent of real GDP growth on average for the long period of
1970–2010. Movements in terms of trade have been consistently unfavorable to Japan and the ROC.

7 Real Income

Table 17 Real Income and Terms of Trade, 1970–2010, 1995–2000, 2000–2005, and 2005–2010___Average annual growth rate of real income, real GDP, trading gain, and net primary income transfer from abroad

Trading gain

Net primary income
from abroad

Bahrain
6.39
Kuwait
6.04
Oman
6.82
Qatar
13.80
Saudi Arabia 4.81
UAE
8.18
Brunei
5.39

2.93
4.42
4.09
5.83
2.00
1.87
3.59

−0.35
−0.06
−0.38
−0.97
0.43
−0.27
0.00

Bahrain
7.04
Kuwait
11.01
Oman
7.82
Qatar
13.38
Saudi Arabia 9.02
UAE
6.48
Brunei
8.00

Bahrain3.21 5.39 −0.58 −1.60
Kuwait−0.93 −1.14 1.07 −0.85
Oman
8.55 5.14 3.81 −0.41
Qatar
19.93 17.94 1.99
0.00
Saudi Arabia 3.52 1.88 1.36
0.28
UAE
3.91 3.27 0.59
0.05
Brunei4.85 −2.40 7.26
0.00

4.25 0.07
2.96 −0.08
2.70 −0.11
3.70 0.12

0.00
0.07
0.06
0.15

3.82
1.68
3.12
8.93
2.38
6.57
1.81

(reference)

US
EU15

2.76 2.81 −0.07
0.02
2.20 2.24 −0.03 −0.01

Australia

3.52 3.30

0.31 −0.09

US
EU15
EU27
Australia

5.91
7.56
3.44
9.14
4.18
4.69
2.85

1.18 −0.05
4.63 −1.18
4.17
0.21
4.19
0.05
4.90 −0.07
1.74
0.05
5.15
0.00

(reference)

4.32
2.96
2.66
3.97

US
EU15
EU27
Australia

Real income

Real GDP

0.01
0.00
0.01
−1.48
−0.44
−0.09
0.00
0.83
1.04
1.13
0.23
0.42
−0.05
0.13
0.33
0.10
0.30
0.04
0.13
0.28
0.04
−0.86

Net primary income
from abroad

China
11.31 11.40 −0.10
Myanmar10.15 10.14 0.01
India
8.34 7.97 0.35
Mongolia
7.54 6.61 2.41
Vietnam
7.47 6.88 1.03
Cambodia7.43 6.41 1.11
Sri Lanka
6.31 5.90 0.41
Bangladesh 6.28 6.13 −0.67
Singapore
6.18 6.41 −1.27
Philippines
5.88 4.82 −0.07
Malaysia
4.94 4.05 0.65
Indonesia
4.88 5.25 −0.78
Nepal
4.83 3.87 1.01
Iran
4.61 2.98 1.50
Pakistan
3.91 4.56 −0.98
Thailand3.88 3.78 0.00
Hong Kong3.34 3.86 −0.82
Korea
3.12 3.97 −0.89
ROC
1.81 4.01 −2.33
Lao PDR
0.28 0.00 0.00
Japan
−0.13 0.28 −0.45
Fiji−0.33 −0.14 0.67

Trading gain

Myanmar11.86 11.86 0.00
0.00
China
11.15 10.20 0.61
0.34
Cambodia10.39 10.68 −0.03 −0.26
Mongolia
9.87 7.10 3.08 −0.32
Iran8.80 7.14 1.97 −0.30
Vietnam
7.27 7.32 0.06 −0.11
India
6.96 7.20 −0.31
0.07
Malaysia
6.82 4.82 1.25
0.75
Sri Lanka
5.50 4.67 0.72
0.11
Philippines
5.41 4.25 −0.28
1.44
Bangladesh 5.23 5.41 −0.45
0.27
Pakistan
4.63 4.77 −0.80
0.65
Thailand
4.54 5.17 −0.01 −0.62
Indonesia
3.96 4.55 −0.96
0.37
Fiji
3.72 3.40 0.87 −0.55
Korea
3.71 4.47 −0.84
0.08Singapore
3.55 4.69 0.12 −1.25
Hong Kong2.89 4.01 −1.01 −0.11
Nepal
2.64 3.11 −0.55
0.07
ROC
2.36 3.60 −1.47
0.22
Japan
1.05 1.18 −0.34
0.21
Lao PDR−0.22 0.00 0.00 −0.22

Real GDP

0.08
−0.27
−0.27
1.69
0.01
−0.03
0.15
−0.31
−0.15
−0.79
−0.61
0.12
1.00
−0.02
−0.37
−0.04
0.09
−0.81
−0.77
0.02

Real income

Net primary income
from abroad(reference)

2005–2010

Trading gain

Bahrain5.17 4.77 0.67 −0.31
Kuwait4.81 0.37 4.04
0.42
Oman
7.75 6.40 1.23
0.12
Qatar
7.77 6.67 1.02
0.07
Saudi Arabia 5.78 4.13 0.60
0.71
UAE
10.59 10.37 −0.16
0.38

2000–2005

China
6.96 7.73 −0.85
Vietnam
6.80 6.86 0.21
Singapore
6.33 6.38 0.22
Philippines
5.53 2.70 1.15
India
5.36 5.53 −0.17
ROC
5.34 5.47 −0.11
Iran
5.19 2.72 2.32
Cambodia5.18 5.46 0.03
Sri Lanka
4.82 5.04 −0.07
Malaysia
4.73 5.03 0.48
Myanmar4.34 4.94 0.00
Bangladesh 4.07 4.15 −0.20
Fiji
3.58 3.65 −1.09
Korea
3.07 4.98 −1.89
Pakistan
2.74 3.14 −0.02
Hong Kong2.71 2.40 0.35
Japan
0.76 0.83 −0.16
Indonesia −0.21 −0.08 0.68
Lao PDR−0.77 0.00 0.00
Thailand−0.87 0.31 −1.20

Real GDP

0.00
−0.07
−0.03
−0.05
−0.19
0.08
−0.03
0.05
0.11
−0.11
0.00
−0.12
−0.07
0.09
0.76
0.14
0.22
0.07
−0.23

Real income

Trading gain

Net primary income
from abroad

China
8.58
Singapore
7.26
Korea
6.70
Malaysia
6.66
Vietnam
6.66
ROC
6.36
Indonesia
6.03
Hong Kong
5.77
Iran
5.54
Thailand
5.38
India
5.23
Myanmar
5.09
Sri Lanka
4.95
Pakistan
4.50
Philippines
4.25
Fiji
4.07
Bangladesh 2.98
Japan
2.52
Lao PDR−0.23

1995–2000

8.57 0.01
7.36 −0.03
7.18 −0.44
6.23 0.49
6.71 0.13
7.12 −0.84
5.36 0.70
5.78 −0.07
3.48 1.96
5.85 −0.37
5.21 0.02
5.20 0.01
5.20 −0.18
4.68 −0.28
3.47 0.03
3.27 0.66
3.06 −0.30
2.74 −0.29
0.00 0.00

Real GDP

Real income

1970–2010(reference)

2.39
2.00
1.98
4.32

2.36 −0.04
0.08
1.79 0.06
0.15
1.80 0.06
0.12
3.38 1.17 −0.24

US
EU15
EU27
Australia

0.75
0.55
0.78
3.90

0.73 −0.08
0.11
0.69 −0.10 −0.03
0.81 −0.02 −0.02
2.53 1.42 −0.06

Unit: Percentage.
Sources: Official national accounts in each country, including author adjustments.
Note: See footnote 95 for the definition of real GDP growth, real income growth, and trading gain growth. The starting years for some countries are different due to data availability during 1970–2010: Brunei (1989–), Cambodia (1993–), Mongolia (2000–), and Nepal (2000–).

95: Real income growth can be decomposed into two components as follows:( )Pt

In (GNIt−1) − In P t−1D = In ( GNIt−1/GDP t−1 ) + In (GDPt / GDPt−1) − (1/2) ∑ i (sit + sit−1) In (Pit / Pit−1) +GNIt

GNIt/GDP t

D©2012 Asian Productivity Organization

Real income growth(

Income transfer effect)

Real GDP growth()(1/2) (sXt + sXt−1) In ( PXt / PXt−1 ) − In ( PDt / PDt−1 ) − (1/2) (sMt + sMt−1) In ( PMt / PMt−1 ) − In ( PDt / PDt−1 )Real income growth attributed to changes in the terms of trade (=trading gain)

where Pit is price of final demand i in period t and sit is expenditure share of final demand i in period t. D is domestic expenditure,
X is export, and M is import. Note that the real GDP growth based on this formulation may differ from that used in other chapters,
since the implicit Törnqvist quantity index is adopted for calculating it.
96: Short-term trends in export and import prices cannot continue indefinitely. Negative and positive trading gain effects in shorter
periods cancel each other out. In the end, the accumulated effect over a long period of time often becomes negligible.

1187.1 Real Income and Terms of Trade

In the shorter terms, the spread of the trading gain effect is wider across countries. Australia has been
benefiting from the continual surge in commodity prices in the past decade or so; as such, its terms oftrade have been turning strongly in its favor. The trading gain effect therefore has been rising in Australia from 3 per cent on average a year in 1995–2000, to 35 per cent in 2000–2005, and 56 per cent in
2005–2010 of its real GDP growth. In terms of percentage points, the trading gain added 0.12, 1.17,
and 1.42 points to real GDP growth in the three consecutive periods. For the oil-exporting countries,
the trading gain effect is almost always positive and significant, and makes it possible to sustain a risein purchasing power with little real GDP growth in some countries, such as in Kuwait or Saudi Arabia
and Brunei in the second half of the 2000s.

7Over the past four decades, net primary income from abroad does not move outside the margin of±10 per cent of real GDP growth on average for all 29 countries compared, except the Philippines,
Kuwait, and Saudi Arabia. Net primary income from abroad has been a long-term significant contribution to the purchasing power of the Philippines, with remittances from its large number of overseas
workers. When real GDP growth slows (such as during the late 1990s), net primary income from abroadplays an even greater role in cushioning the real income of Filipinos. Over the past four decades, net
primary income from abroad augmented real GDP growth by 2.5 per cent and 0.6 per cent on averagea year in Japan and the US, respectively, but it has grown to be more significant (i.e., around 15 percent) in both countries as real GDP growth has slowed in recent years.
Figure 90 plots the time series of net primary income from abroad as a percentage of GDP. The role ofnet primary income from abroad has been shifting from negative to positive in Hong Kong, with thetransition taking place in the mid-1990s leading up to the handover of Hong Kong from British rule to
China in 1997. Since then, net primary income from abroad has been positive. A shift in the role of net
primary income from abroad has also taken place in Korea from negative to a more or less neutral
position in the 2000s, whereas it has been positive in the ROC, oscillating around +2 per cent of GDP,
since 1980. Singapore’s net primary income from abroad displays the largest fluctuations, ranging
from +1.9 per cent in 1997 to −7.1 per cent in 2004, but on the whole, it has been more negative thanpositive. In Japan and the Philippines, net primary income from abroad has been rising strongly, albeit at different magnitudes. In Japan, it rose from 0.6 per cent of GDP in 1990 to 3.3 per cent in 2008
before falling to 2.5 per cent in 2010, compared with 1.4 per cent in 1990 and 33.3 per cent in 2010 in
the Philippines. In China and India, it has been fluctuating within ±1.6 per cent and with a range from
−1.5 to 0.2 per cent, respectively. In the US, it has always been positive, fluctuating tightly within +1.5

%
6
4

ROC
Korea

Hong Kong
Singapore

%
4

3

China
Japan
EU15

India
US

%
40

30

Bangladesh
Fiji
Malaysia
Pakistan

Cambodia
Indonesia
Mongolia
Philippines

2
2

20

1

10

0

0

−1

−10

0

−2

−6

−2

−8
1970 1975 1980 1985 1990 1995 2000 2005 2010−20
1970 1975 1980 1985 1990 1995 2000 2005 2010

1970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 90 Effect of Net Income Transfer on GDP, 1970–2010
Sources: Official national accounts in each country, including author adjustments.

119©2012 Asian Productivity Organization−4

7 Real Income

per cent of GDP, whereas it has
been marginally negative for
EU15 for three decades between
1975 and 2005 before turning
mildly positive. For the smaller
Asian economies, net primary income from abroad tends to fluctuate within a bigger range of ±10
per cent of GDP.
Combining both the trading gain
effect and net primary income
from abroad, real income growth
for most countries compared fallwithin the margin of ±20 per centof real GDP growth (Figure 91);
Kuwait and Brunei appear to be
the outliers, with real income
growth being 13.1 times and 3.4
times their respective long-term
dismal real GDP growth of 0.4 percent and 1.3 per cent.97%

12(+20%)(+20%)

Real Income
incomeGrowth
growth

UAE

10

Oman
−(20%)

China

Vietnam

8

Qatar

Singapore
Korea
ROC
Saudi Arabia
Hong Kong
India
Iran
ThailandBahrain
Myanmar
KuwaitBruneiPakistanFiji
Sri Lanka
Austrarlia Philippines
Indonesia

6

4

US
EU15
2

Malaysia

Bangladesh
Japan
Real
RealGDPGDP
Growth
growth

0

0

2

4

6

8

10

12 %

Figure 91 Real Income and Real GDP Growth, 1970–2010___Average annual growth rate of GDP at constant prices and real
incomeSources: Official national accounts in each country, including author adjustments.
Note: The starting years for some countries are different due to data availability during
1970–2010: Brunei (1989–), Cambodia (1993–), Mongolia (2000–), and Nepal (2000–).

Unlike the oil-exporting countries, at any one time, roughly half of the Asian countries compared sustain a negative trading gain effect, albeit at variable extents, whereas the impact from net primary
income from abroad is relatively less pronounced. The period 1995–2000 reflects the impact of the
Asian financial crisis. For Thailand, the trading gain effect more than outweighed the small positive
average real GDP growth per year (of 0.3 per cent), giving rise to a marginal fall in real income of −0.9
per cent. In Korea, the negative trading gain also shaved 37 per cent off real GDP growth of 5.0 per
cent, producing a real income growth of 3.1 per cent. At the start of the 2000s, the Asian economy
recovered from the financial crisis, but the trading gain effect worked against welfare for some countries, and such a negative impact even intensified after 2005. For example, in the ROC, the trading gain
effect caused real income growth to be 41 per cent lower than real GDP growth in the period 2000–
2005, but in the period 2005–2010 it wiped out 58 per cent of the handsome 4.0 per cent real GDP
growth on average a year, leaving real income to grow at 1.8 per cent. Similarly, in Korea the trading
gain effect caused real GDP growth to overestimate real income growth by 19 per cent in the first halfof the 2000s, which increased to 22 per cent in the years 2005–2010 (Table 17 and Figure 92). In Japan,
the negative trading gain effect more than wiped out the 0.4 percentage points of real GDP growth,leaving real income actually falling by 0.1 per cent a year on average in the period 2005–2010.

©2012 Asian Productivity Organization

In contrast, the trading gain has worked to counterbalance falling real GDP in Brunei, leaving it with ahandsome real income growth of 4.8 per cent, despite its contracting real GDP of 2.4 per cent in thelatest period. In Saudi Arabia, real income growth was more than 174 per cent faster than its real GDP
growth. This takes place against the backdrop of strong oil prices, which spiked in mid-July 2008 to

97: According to Kohli’s (2004) study on real income of 26 OECD countries during 1980–1996, the trading gain on average over theentire period varies across countries, from the smallest effect of −0.8 per cent (−30.9 per cent of real income growth) per year in
Norway to the largest of 0.63 per cent (29.4 per cent of real income growth) per year in Switzerland.

1207.1 Real Income and Terms of Trade

USD147 a barrel; after dropping sharply to USD40
per barrel by the end of 2008 (reflecting the fall indemand after the collapse of Lehman Brothers), it
has steadily risen to, and held at, over USD100 abarrel since 2010 (Figure 93). Relatively, the trading
gain effect has been small in EU15, making a difference of ±15 per cent between real GDP and real income growth. In the US, the trading gain effect has
been unfavorable more often than not, but its positive net primary income from abroad has worked tocounterbalance it and the difference between real
GDP and real income growth is reduced. For example, in the latest period 2005–2010, the trading gain
effect shaved 10.8 per cent off real GDP growth but
it was counterbalanced by the positive effect fromnet primary income from abroad, which added 14.6
per cent to real GDP growth, leaving real income
growth slightly faster than real GDP.

7.3
3.8
2.4
2.0
1.5
1.4
1.4
1.1
1.1
1.0
1.0
0.7
0.7
0.6
0.4
0.4
0.0
0.0
−0.1
−0.1
−0.1
−0.1
−0.4
−0.6
−0.7
−0.8
−0.8
−0.9
−1.0
−1.3

BruneiOman
Mongolia
Qatar
Iran
Australia
Saudi Arabia
Cambodia
KuwaitVietnam
Nepal
Fiji
Malaysia
UAE
Sri Lanka
India
MyanmarThailandPhilippines
US
China
EU15
Japan
Bahrain
BangladeshIndonesia
Hong Kong
Korea
Pakistan
Singapore
ROC

7

98: Following Kohli (2006), trading gain can be decomposed into two components as follows:

(

)

(

)

(1/2) (sXt + sXt−1) In ( PXt / PXt−1 ) − In ( PDt / PDt−1 ) − (1/2) (sMt + sMt−1) In ( PMt / PMt−1 ) − In ( PDt / PDt−1 ) =Real income growth attributed to changes in the terms of trade (=trading gain)()(1/4) (sXt + sXt−1 + sMt + sMt−1) In ( PXt / PXt−1 ) − In ( PMt / PMt−1 ) +Terms-of-trade effect()(1/2) (sXt + sXt−1 − sMt − sMt−1) (1/2) In ( PXt / PXt−1 ) + (1/2) In ( PMt / PMt−1 )− In ( PDt / PDt−1 ) .
Real exchange rate effect121©2012 Asian Productivity Organization−2.3
Figure 94 provides the results of further decompo−2.5
0
2.5
5.0
7.5 %
sition of the trading gain into the terms-of-tradeeffect and the real exchange rate effect in Asian
Figure 92 Trading Gain Effect, 2005–2010
countries for the period 1970–2010.98 The terms-of___Average percentage points
trade effect is the part of real income growth attribSources: Official national accounts in each country, including
uted to the change in the relative price between
author adjustments.
exports and imports, while the real exchange rate
effect refers to the part of real income growth attributed to changes in the relative prices of traded goods and domestically consumed goods. By applying this result, real income growth can be decomposed into real GDP growth, terms-of-trade effect,
real exchange rate effect, and net primary income from abroad. The left-hand chart in Figure 94 applies this decomposition to Asian countries for the period 1970–2010. It shows that the real exchange
rate effect is generally much smaller than the terms-of-trade effect, implying that the relative prices oftraded versus domestically consumed goods have been largely stable in most countries. The exceptions are Kuwait and Brunei where the real exchange rate effect accounted for 37 per cent and 23 percent of real income growth. This might have reflected the weight of oil in the composition of theirtraded goods. The right-hand chart shows the decomposition for the most recent period 2000–2010.
It shows that the trading gain, particularly the terms-of-trade effect, is highly significant and favorable
for the oil-exporting countries, but is significant and negative in a handful of Asian economies such as
Hong Kong, the ROC, Korea, and Pakistan.

7 Real Income

Dollars per barrel

150

145.31113.39125109.39

100

77.05

75
41.07

50

75.4

25
0
Jan 02,
1986

30.28
10.82

Jan 02,1988

Jan 02,1990

Jan 02,1992

Jan 02,1994

Jan 02,
1996

Jan 02,
1998

Jan 02,2000

Jan 02,
2002

Jan 02,
2004

Jan 02,2006

Jan 02,2008

Jan 02,2010

Jan 02,2012

Figure 93 Price of Crude Oil, 1986–2012
Source: US Energy Information Administration, WTI spot prices FOB (Cushing, Oklahoma).

EU15
Japan
US
Bangladesh
Australia
Fiji
Philippines
BruneiPakistan
Kuwait
Sri Lanka
MyanmarBahrainIndia
ThailandIranHong Kong
Saudi Arabia
Indonesia
ROC
Vietnam
Malaysia
Korea
Singapore
Oman
Qatar
China
UAE

1970–2010
Figure 95 shows the decompo%
12
sition of average annual real
income growth covering two
9periods of major economic shocks
6
faced by the Asian economies:
during 1973–1979, which in3
cludes the two oil price hikes in01974 and 1979, and 1996–1998 tocapture the impact of the Asian−3
financial crisis. High oil prices improved the terms for oil-exporting
countries, such as Iran and Indonesia, and worsened the terms of
2000–2010%18
trade for oil-importing countries.
15
During the Asian financial crisis,12
the terms-of-trade effect was still
the predominant factor in decid9
ing the difference between real6
income growth and real GDP
3growth. In Brunei, the terms-of0
trade effect further reinforced the−3negative real GDP growth of −6.3
per cent, reducing its real income
growth a further 8.1 percentage
points. In Iran, the negative termsReal exchange rate effectTerms-of-trade effect
Real GDPNet primary income from abroad
Real incomeof-trade effect counteracted the0.9 per cent real GDP growth, givFigure 94 Decomposition of Real Income Growth, 1970–
ing real income growth of −1.5
2010 and 2000–2010
per cent. In Indonesia, the trading
Sources: Official national accounts in each country, including author adjustments.
gain effect worked to counterbalance the contraction in real GDP,
whereas in Thailand, it reinforced the negative real GDP growth. In the Philippines, although thestrong favorable terms-of-trade effect was moderated by the negative real exchange rate effect, theresulting real income growth more than quadrupled the real GDP growth.99©2012 Asian Productivity Organization

Japan
EU15
US
Fiji
ROC
Hong Kong
Korea
Nepal
Australia
Thailand
PakistanIndonesia
Singapore
KuwaitBahrain
UAE
Philippines
Bangladesh
Malaysia
Sri Lanka
Saudi Arabia
Brunei
Iran
Vietnam
India
Oman
Mongolia
Cambodia
Myanmar
China
Qatar

122

7.1 Real Income and Terms of Trade

Bangladesh
EU15
US
Japan
Australia
India
Philippines
Myanmar
Sri Lanka
China
Thailand
PakistanFiji
Singapore
Hong Kong
Iran
ROC
Malaysia
Korea
Indonesia

1973–1979
Figure 96 shows this decomposition of%
10
real income in each Asian country, alongwith the US, EU15, and Australia100 from51970, or whichever year a country’s time0
series starts. The trading gain can be positive or negative, depending on the direc−5tion of change in the terms of trade. Its
impact is modest for most countries, adding less than ±1 percentage point to an1996–1998%
nual real GDP growth, except for some10
oil-rich countries. However, historically5
the trading gain has been significant insome oil-rich countries (e.g., annual real0
income growth being 4.0 percentage−5
points, 3.1 percentage points, and 2.0
percentage points higher than annual−10real GDP growth on average in Kuwait,−15
Brunei, and Iran between 1970 and 2010,
respectively). In the short term, we cansee extreme spikes in trading gain. For instance, as a consequence of the first oil
Real exchange rate effectTerms-of-trade effect
Real GDPNet primary income from abroad
price shock, the improvement in theReal income
terms of trade was responsible for over 80
per cent of the 41.9 per cent increase in
Figure 95 Decomposition of Real Income Growth,real income in Iran in 1974. The opposite
1973–1979 and 1996–1998___Decomposition: Average annual growth rate of real income
was true in EU15, where the negative
trading gain effect counterbalanced real
Sources: Official national accounts in each country, including author
GDP growth, leaving virtually no growth
adjustments.
in real income in the period 1974–1975.
The effect of the second oil spike can be seen in the early 1980s. Sri Lanka, Malaysia, and Indonesia
also experienced volatile variations in trading gains in the 1970s. The trading gain has been working
against Singapore’s and the ROC’s welfare for most of the period covered. For Australia, the trading
gain effect has clearly switched from being negative in the early half of the period covered to positivein the past decade or so.

7123©2012 Asian Productivity Organization

BruneiIndonesia
Thailand
Korea
Iran
Japan
Malaysia
Fiji
Hong Kong
Pakistan
MyanmarPhilippines
EU15
Australia
Singapore
US
Cambodia
ROC
Bangladesh
India
China
Vietnam
Sri Lanka

099: Kohli (2006) calculated the trading gain, the terms-of-trade effect, and the real exchange rate effect of Canada during 1982–2005.
The average annual trading gain over the entire period is very low, at 0.1 per cent. This is small by the standard of Asian economies. However, the trading gain became significant, especially for the three years 2002–2005. Over these years, the average trading gain is 1.6 per cent per year. This effect is decomposed into a terms-of-trade effect of 1.4 per cent and a real exchange rate
effect of −0.1 per cent.
100: There are several studies on the decomposition of real income growth for other countries: Kohli (2004) for 26 OECD countries
during 1980–1996, Kohli (2006) for Canada during 1981–2005, and Diewert and Lawrence (2006) for Australia during 1960–2004.

7 Real Income

Bahrain%40

Bangladesh

%
15

20

10

20

15

5

0

10

0

5

−20
−5
−40

0

−10

−60

−15

−80

−20

1971 1976 1981 1986 1991 1996 2001 2006

Cambodia

%
14

−5
−10
1971 1976 1981 1986 1991 1996 2001 2006

China

%
15

12

1971 1976 1981 1986 1991 1996 2001 2006

ROC

%
18

12

9

8

−15

15

12

10

9

6

6

6
3

4

3

0

2

0

−3

0
−2

Brunei%25

1971 1976 1981 1986 1991 1996 2001 2006

Hong Kong

%
16

−6

−3
1971 1976 1981 1986 1991 1996 2001 2006

India

%
12

12

9

8

6

4

3

0

0

−4

−3

−8

−6

−6

1971 1976 1981 1986 1991 1996 2001 2006

Indonesia

%
20
15
10
5
0

1971 1976 1981 1986 1991 1996 2001 2006

Iran

%
45

−5
−10

1971 1976 1981 1986 1991 1996 2001 2006

Japan

%
8

36

−15

1971 1976 1981 1986 1991 1996 2001 2006

Korea

%

16

6

12

4

8

2

4

0

0

−2

−4

27
18
9
0
−9
−18
−27

1971 1976 1981 1986 1991 1996 2001 2006

Kuwait%90−41971 1976 1981 1986 1991 1996 2001 2006

Malaysia

%

20
15

60

1971 1976 1981 1986 1991 1996 2001 2006

Mongolia

%

75
50

10

30

−8

25

5
0
−30

©2012 Asian Productivity Organization

−60

0

0

−25

−5

1971 1976 1981 1986 1991 1996 2001 2006

Real GDP124−101971 1976 1981 1986 1991 1996 2001 2006

Trading gain

−50

1971 1976 1981 1986 1991 1996 2001 2006

Net primary income from abroad

Real income

7.1 Real Income and Terms of Trade

Myanmar

%

15

Nepal

%

8

Oman

%
45

12
9
6
3
0
−3
−6

6

30

4

15

2

0

0

−15

−9
−12

1971 1976 1981 1986 1991 1996 2001 2006

Pakistan%
10−21971 1976 1981 1986 1991 1996 2001 2006

Philippines

%
16

8
6
4
2

−30

12

40

8

30

4

20

0

10
0

−8

−10

−2

−12

−20

−4

−16

1971 1976 1981 1986 1991 1996 2001 2006%
150

Saudi Arabia

100
50

1971 1976 1981 1986 1991 1996 2001 2006

Singapore

%
20

Qatar

%
50

−4

0

1971 1976 1981 1986 1991 1996 2001 2006−30

71971 1976 1981 1986 1991 1996 2001 2006

Sri Lanka

%
20

16

15

12

10

8

5

4

0

0
−50

0

−5

−100

−4

−10

−150
1971 1976 1981 1986 1991 1996 2001 2006

−8

%
15

Thailand1971 1976 1981 1986 1991 1996 2001 2006

UAE

%
100

6

40

4

20

2

0
−5

%
8

0

0

−2

−10
−15

Vietnam

%
12

8

60

5

1971 1976 1981 1986 1991 1996 2001 2006

10

80

10

−15

−20

1971 1976 1981 1986 1991 1996 2001 2006

US

−40

−4
1971 1976 1981 1986 1991 1996 2001 2006

EU15

%
6

6
4

−6

1971 1976 1981 1986 1991 1996 2001 2006

Australia

%
8

4

6

2

4

0

2

−2

0

−4

−2

2
0

−4
−6

1971 1976 1981 1986 1991 1996 2001 2006

Real GDP−61971 1976 1981 1986 1991 1996 2001 2006

Trading gain

−41971 1976 1981 1986 1991 1996 2001 2006

Net primary income from abroad

Real income

Figure 96 Sources of Real Income Growth, 1970–2010
Sources: Official national accounts in each country, including author adjustments.

125©2012 Asian Productivity Organization−2

7 Real Income

7.2 Terms of Trade andProductivity Growth%5
4

Terms-of-trade effectKuwait©2012 Asian Productivity Organization

When the trading gain is highly
Brunei3
favorable, it can breed a sense ofcomplacency, and productivity
Iran2
performance can suffer as a result.
India
Oman
Qatar
Resource-rich economies are sus1
FijiIndonesia Bahrain Malaysia
Saudi Arabia
ceptible to this pitfall because
Cambodia Vietnam
Australia
Nepal Singapore
Myanmarthey are poised to reap some exPhilippines
EU15
0Hong Kong
China
UAE US
tremely positive trading gains
Korea
Pakistan Japan−1
ROC
when commodity prices turn in
Bangladesh
ThailandSri Lanka
their favor over a sustained period−2of time. While commodity prices
−4.5
−3
−1.5
0
1.5
3
4.5
6
7.5 %
Labor productivity growth
can rise, they can also fall. This
is when countries’ real income
Figure 97 Terms-of-Trade Effect and Labor Productivity
growth could suffer if fundamenGrowth, 1970–2010
tals for real GDP growth are weak.
Sources: Official national accounts in each country, including author adjustments.
Over the past four decades, only
Note: The starting years for some countries are different due to data availability during 1970–2010: Brunei (1989–), Cambodia (1993–), Mongolia (2000–), Nepal (2000–),
four countries have enjoyed a faand Vietnam (1986–).
vorable trading gain effect over
1.0 per cent per annum. They are
Kuwait, Brunei, Iran, and Qatar (all oil-exporting countries), and only Iran could achieve a positive
growth in labor productivity (Figure 97). Australia is a rising economy that has benefited from the recent hikes in commodity prices, which are likely to stay for a period of time, as a response to the vibrant growth in the emerging economies especially China. The surge in its multifactor productivity
growth in the 1990s stopped around the end of the century and then turned negative about five years
ago,101 just when they enjoyed an all-time-high positive trading gain effect, with real income growthfaster than real GDP growth by 53 per cent (Table 17). A resource-rich country can suffer from “Dutch
disease,” which describes the phenomenon in which a country’s currency is pushed up by the commodity boom, making other parts of its economy less competitive and potentially increasing thecountry’s dependence on its natural resources. This is how resource abundance can easily lead to resource dependence. A way to counteract Dutch disease is broad-based robust productivity growthand industry diversification, in which Bahrain and Oman have shown some success (see Section 6.2
and Figure 72).
Figure 97 also shows that many Asian countries have succeeded in achieving high growth of laborproductivity while having to accept a deteriorating trading gain over the long run. They are typicallyresource importers. Their voracious demand for commodities has pushed up their import prices,whereas export prices tend to fall as a result of their achievement in productivity improvement, resulting in unfavorable movements in their terms of trade. This is especially the case in countries where
economic growth is highly dependent on export promotion. In this sense, a negative trading gain ispartly a side effect of their own productivity success. Although the trading gain effect partly negates
their real GDP growth, they are still much better off than before their development took off and without productivity improvements.

101: The Economist, 28 May 2011, “Special Report on Australia: No worries?”

126

Appendix
A.1

GDP Adjustments

The database used in the Databook series includes author adjustments made to harmonize GDP
coverage better across countries. Although this edition mainly follows the 1993 SNA, it excludes
investment of valuables and includes software investment and final consumption of financial intermediation services indirectly measured (FISIM). In addition to these adjustments, an extra adjustment is necessary to harmonize the price concept of GDP. Procedures for all these adjustments are explained below.

Among the 20 APO member economies, eight countries – Bangladesh,
Cambodia, Indonesia, the Lao PDR,
Nepal, Pakistan, Sri Lanka, and Vietnam – do not allocate FISIM to final
demands in their official national
accounts, as a result of them still not
following the 1993 SNA recommendation. Thus, the GDP values inthose countries are smaller thanothers by definition. In addition,even in the countries whose national accounts follow the 1993 SNA’s
recommendation on FISIM, the available data sometimes do not cover
the whole periods of our observation. To harmonize the GDP concept
among countries and over periods,
final demands of FISIM are estimated for those countries in the APO
Productivity Database, using available estimates of value added in Imputed Bank Service Charge (IBSC) or
financial intermediation (in casedata of IBSC is not available). The ratios of value added of IBSC or
financial intermediation on FISIM
allocated to final demand are assumed to be identical with the average ratios observed in the countries
in which the data is available. Figure
A1 describes the countries andmethods to adjust FISIM. As described there, for the case that both
value added data are not available,
the trend of the FISM share on GDP
is applied simply to extrapolate theestimates in the past (although theimpacts on GDP are minor).

1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Bangladesh
Cambodia
Fiji
India
Indonesia
Iran
Japan
Korea
Lao PDR
Malaysia
Mongolia
Nepal
Pakistan
Philippines
Sri Lanka
Thailand
Vietnam
Brunei
MyanmarBahrain
KuwaitOman
Qatar
Saudi Arabia
UAE

1970
1970
1970
1970

1950
1951

App.

1980
1993
1977

1960
1959

1955
1953

1970

1955

1970

1981 1985
1990

1960
1974

1964
1960
1946

1967
1959

1972
1970

1951
1955

1986
1970 1974
1990

1962
1970

1975

1962

1982
1970
1970
1970
1970

1975
1975

Adjustment of using value added of imputed bank service charge
Adjustment of using value added of financial intermediation
Using the average trend of FISIM share in GDP

Figure A1 Adjustment of FISIM%

3.5

FISIM share in GDP (average in the 2000s)

Hong Kong
3.0
2.5
2.0
1.5
1.0

India
Philippines
Fiji

Japan

Thailand

Pakistan
China
Indonesia
Mongolia
Nepal

Lao PDR
0.5
Vietnam
Cambodia
Bangladesh
Sri Lanka
Myanmar
0.0
0
10

US

Korea
ROC

Malyasia

Shingapore

Australia

Iran

BruneiThousands of US dollars (as of 2010)

20

30

40

50

60

Per capita GDP in 2010 (using 2005 PPPs, reference year 2010)

Official national accounts
Our estimates using value added in financial intermediation
Our estimates using value added in imputed bank service charge

Figure A2 FISIM Share in GDP in the 2000s
Sources: Official national accounts in each country and author estimates.

127©2012 Asian Productivity Organization

1) FISIM

Appendix

Figure A2 presents a plot of the per capita GDP level in 2010 and the FISIM share in GDP in the 2000s(including both of the original estimates in the official national accounts and our estimates). In the
countries where their GDP are adjusted, the proportions by which author adjustments for FISIM increase GDP are 0.9–1.4 per cent for Brunei, Indonesia, Nepal, and Pakistan and the impact on GDP isless than 0.5 per cent in others.

2) Software
The treatment of software also varies across countries. Among the countries studied, software investment is available for the ROC, Japan, Korea, Mongolia, Philippines, Singapore, Thailand, and China. To
harmonize data, a country’s GDP is adjusted to include software investment (through its software
industry) by using the ratio between software investment and GDP (hereafter software ratio)
and the tangible GFCF to GDP ratio (hereafter GFCF ratio). Data from the OECD Productivity Database(Schreyer, Bignon, and Dupont 2003) and the APO Productivity Database suggest an inverse relationship between these two ratios (Figure A3). Countries with a low GFCF ratio tend to be those withhigh per capita GDP, and the observed data suggest that information technology tends to play a more
important role in these countries than in less developed countries. Furthermore, it is observed
from the OECD and APO software data that the software ratio has been gradually increasing over the
past 25 years.
We apply this inverse relationship between these two ratios observed from the OECD countries andnational accounts in Asian non-OECD countries to estimate the software ratio in 2006 for those APO
member economies that do not capitalize software investment. The estimated ratios for individual
countries in 2006 are gradually tapered off as we move back in time. However, there is an exception.
Countries at the very early stage of economic growth are found to have a GFCF ratio as low as countries with high per capita GDP, but for a different reason. The low GFCF ratio is explained by the factthat these countries have not experienced economic development yet, and in turn this does not imply
an important role for software investment. In this report, we reSoftware investment/GDP
gard Cambodia, the Lao PDR, and%Sweden2.0
USJapan
Nepal as countries at the very
Denmark
early stage of economic developFinland
Korea
ment, and assign Vietnam’s softFrance
New Zealand
1.5
Switzerland
United Kingdom
ware ratio, which is the lowest of
ROC
Netherlands
Canadaall APO member economies, tothese countries.

©2012 Asian Productivity Organization

1.0

Another problem arises from partial software capitalization. There
are three types of software: prepackaged software, custom software, and own-account software.
Countries may have capitalized
one or two types of software, but
software investment data are often not available separately. We
attempt to adjust for the variedlevel of capitalization acrosscountries by adding the type ofsoftware not capitalized to countries’ GDP. In the case of Japan’s

128

Germany

0.5

Cambodia

Singapore
Austria
Italy
Fiji
Indonesia

Australia
Spain
Bangladesh
Sri Lanka

Philippines Malaysia
Nepal

Iran

0.0
13

18

IrelandThailandPortugal

Mongolia

23

28

Vietnam

China

India
33

38

43 %

Tangible GFCF/GDPCountries in which software is included
Countries in which software is excluded
Countries in which custom and own account software are excluded
Countries in which pre-package and own account software are excluded
Countries in which own account software is excluded

Figure A3 Software Investment Ratio and GFCF Ratio toGDP, 2005
Source: OECD Productivity Database (30 March 2012) and author estimates.

A.1 GDP Adjustments

own-account software and ownership transfer cost, we used estimates by Nomura (2004) and added
these to the GDP of Japan’s software industry and GFCF.

3) Valuables
Valuables are defined as “goods of considerable value that are not used primarily for purposes of production or consumption but are held as stores of value over time” (United Nations 1993: para. 10.7).
They are held under the expectation that their prices will not deteriorate and will rise in the long run.
Valuables consist of precious stones and metals such as diamonds; art-works such as paintings andsculptures; and other valuables such as jewelry made from stones and metals. In some countries, suchas Fiji, India, Iran, Mongolia, Pakistan, and Vietnam, net acquisitions of valuables are recorded as a partof capital formation. Our current decision is to harmonize the data by excluding net acquisition ofvaluables from GDP in the APO Productivity Database. According to our calculation, the figures were
1.1 per cent of GDP for India.

App.

4) GDP at basic prices
GDP can be valued using different price concepts: factor cost, basic prices, and market prices. If theprice concept is not standardized across countries, it will interfere with the international comparisons.
All the countries we have covered in this Databook officially report GDP at market prices (or at purchasers’ prices), but this is not true for GDP at factor cost and GDP at basic prices. International comparisons in Chapter 3 (on economic scale and growth) and Chapter 4 (on final demand) are based on
GDP at market prices. However, by valuing output and input at the prices that producers actually pay
and receive, GDP at basic prices is a more appropriate measure of countries’ output than GDP at market prices for international comparisons of total factor productivity and industry performance as it isa measure from the producers’ perspective. Hence, Chapter 5 on whole-economy productivity performance is based on GDP at basic prices, including our estimates.

Readers should bear these caveats in mind in interpreting the results in Chapter 6, since the definition
of GDP by industry differs among countries due to data availability. GDP is valued at factor cost for Fiji,
India, and Pakistan, at basic prices for Cambodia, Hong Kong, Korea, the Lao PDR, Mongolia, Nepal,
and Singapore, at producers’ prices for Bangladesh, the ROC, Iran, and the Philippines, and at market
prices for Indonesia, Japan, Malaysia, Sri Lanka, Thailand, and Vietnam. In this sense, APO industry data
should be treated as a work in progress and it is difficult to advise on data uncertainty. We will further
develop and examine these data issues in the future.

129©2012 Asian Productivity Organization

These concepts of GDP differ in the treatment of indirect tax and subsidies (and import duties). The
difference between GDP at basic prices and GDP at market prices is “taxes on products” minus “subsidies on products.” “Taxes on products” are the indirect taxes payable on goods and services mainly
when they are produced, sold, and imported, and “subsidies on products” are subsidies payable on
goods and services mainly when they are produced, sold, and imported. Since GDP at basic prices isavailable for some economies, such as Hong Kong, India, Korea, Nepal, Singapore, and Sri Lanka, weneed to construct GDP at basic prices for all other countries. To obtain GDP at basic prices, we subtract“taxes on products” and “duties on imports” from and add “subsidies on products” to GDP at market
prices, which is available for all the countries studied. The main data sources for estimating “taxes on
products” and “subsidies on products” are tax data in national accounts, the IMF’s GFS, and the Input–
Output Tables in each country.

Appendix

A.2

Capital StockAt present, half the APO member economies publish estimates of capital stocks in their systems ofnational accounts. Even if the estimates are available, users must be careful about a difference inmethodologies and assumptions used to estimate capital stock and a large diversity in the treatmentof quality adjustment in price statistics among countries. In the APO Productivity Database 2012.01, a
harmonized methodology is applied in estimating capital stock and capital services, covering 15 Asian
economies: China, the ROC, Fiji, Hong Kong, India, Indonesia, Iran, Japan, Korea, Malaysia, Mongolia,
the Philippines, Singapore, Thailand, and Vietnam, and the US as a reference country.
Quality changes in the aggregate measure of capital input
can originate from two kinds of sources, namely the composition change by type of assets and the quality change
in each type of asset. To take the composition change ofassets into account, our current database classifies ten
types of assets (shown in Table A1). For countries in which
detailed investment data are not available in their national
accounts, the ten types of investment data are estimatedbased on the benchmark input–output tables and our estimates of the commodity flow data of domestic production and export/import of assets. The starting years for
estimating capital stock based on the perpetual inventory
method are 1901 for the US, 1951 for the ROC, 1952 for
China, 1953 for Korea, 1955 for Japan, 1960 for Singapore,
1961 for Hong Kong, and 1970 for other countries.

Table A1 Parameters in Hyperbolic
FunctionT

β

1. IT hardware

7

0.50

2. communications equipment

15

0.50

3. transportation equipment

15

0.50

4. other machinery and equipment

15

0.50

5. residential buildings

30

0.75

6. non-residential buildings

30

0.75

7. other construction

40

0.75

8. cultivated assets

10

0.50

9. computer software

3

0.50

10. other intangible assets

7

0.50

Source: APO Productivity Database 2012.01.

©2012 Asian Productivity Organization

It is well known that prices of constant-quality IT capital have been falling rapidly. For cross-country
comparisons, it has been noted that there is great diversity in the treatment of quality adjustment inprice statistics among countries. Cross-country comparisons will be significantly biased if some countries adjust their deflators for quality change while others do not. Price harmonization is sometimes
used in an attempt to control for methodological differences in the compilation of price indexes, under the assumption that individual countries’ price data fail to capture quality improvements. Assuming that the relative price of IT to non-IT capital in the countries compared is set equal to the IT to
non-IT prices relative in the reference country, the harmonized price is formulated as: ∆ ln P̃ITX = ∆ ln
X
ref+ (∆ ln PITref − ∆ ln PnlT), where the superscript X denotes the country included in the comparisons, PIT
PnlT
is the price of IT capital, and PnIT is the price of non-IT capital. The price of IT capital in country X, P̃ITX , isrefX
in the reference country and PnlTin X . Schreyer (2002)
computed by the observed prices PITref and PnlTand Schreyer, Bignon, and Dupont (2003) applied price harmonization to OECD capital services, with
the US as a reference country, since the possible error due to using a harmonized price index would
be smaller than the bias arising from comparing capital services based on national deflators.
In this Databook, the same price harmonization method is applied to adjust the quality improvement
for IT hardware and communications equipment in countries where the appropriate quality-adjusted
price data are not available, with Japan’s prices as a reference country. A similar procedure was appliedin cases where the prices for some assets were not available, to estimate missing data based on therelative price of these assets to total GFCF. In measuring capital services, this Databook basically follows the framework of the OECD Productivity Database (see Schreyer, Bignon, and Dupont, ibid.). The
OECD assumes the truncated normal distribution as profiles for asset discarding (retirement) and thehyperbolic distribution as profiles for asset decaying. The age-efficiency profile (AEP) is defined as a

130

A.3 Rate of Return and Capital Services

%

4.0

3.8

3.5
3.0

1980

3.4

2.8 2.8 2.8

2.7

2.7

2.5

2.7
2.3

2.7

2.6

2.6

2.3

2.4 2.4

2.0

2.0

1.7

1.5

2010

3.2

3.1

2.9

1.5

1.8

1.7

2.3

2.3

2.3

2.1

2.0

1.9

1.7

1.1

1.0
0.5
0.0
India

Philippines

Mongolia

Malaysia

US

VietnamHong Kong

China

Singapore

Fiji

ROC

Iran

ThailandIndonesia

Korea

Japan

combined distribution of discardand decay of assets. The AEP ineach asset is based on the two parameters in the hyperbolic function: T (average service life) and β(−∞<β≤1). The hyperbolic function becomes one-hoss shay (nodecay until T) when β=1 and linear when β=0. We set these twoparameters as shown in Table A1.
The estimates of productive capital stock by type of asset are usedin measuring capital services (seeAppendix A.3).

App.

Figure A4 Capital-Output Ratio, 1980 and 2010___Ratio of the beginning-of-period net capital stock to GDP at current
pricesFigure A4 presents the estimatedSource: APO Productivity Database 2012.01.
capital-output ratio (stock coefficient) that is defined by the ratioof the beginning-of-period net capital stock (all types of produced fixed assets owned by private andpublic institutions) to the basic-price GDP at current prices. Japan has the highest capital-output ratio
among Asian countries, at 3.8. However, the ratio may not work well for cross-country comparison
since the price differential between that for GDP and fixed assets in each country is not accounted for.
Compared to the 1980 level in each country, all Asian countries except Mongolia have an increasing
trend of capital-output ratio, unlike the ratio in the US, which is stable.

A.3

Rate of Return and Capital Services

In the analysis of production and productivity, capital service provides an appropriate concept ofcapital as a factor of production. The fundamental assumption in measuring capital services is proportionality between the (productive) capital stock and capital services in each type of asset. Thus, thegrowth rates of capital services can differ from that of capital stock only at the aggregate level. For
aggregating different types of capital, the user costs of capital by type of asset should be estimated.
This box outlines the methodology of the user cost of capital estimation and presents the estimatedresults of endogenous rate of return for Asian countries in the APO Productivity Database 2012.01.

One of the main difficulties in applying the ex ante approach for measuring user cost of capital is obtaining proper estimates for real rates of return, which can differ considerably among countries andover time. On the other hand, the ex post approach originated by Jorgenson and Griliches (1967) enables us to estimate it based on observed data. Assuming constant returns to scale and competitivemarkets, capital compensation can be derived from the summation of the capital service cost Vtk for131©2012 Asian Productivity Organizationk, is defined
The user cost of capital of a new asset (with type of asset denoted as k of the period t), ut,0
k
k
k
k
k
k
as qt−1,0 {rt + (1 + t ) P,t,0 − t }, where rt, P,t,0, and qt,0 are the expected nominal rate of return, crosssection depreciation rate, and asset price, respectively. The asset-specific inflation rate tk is defined askk/ qt−1,0−1). The OECD assumes the country-specific ex ante real rate of return r * that is constant for(qt,0
the whole period, and defines the nominal rate of return as rt = (1 + r *)(1 + ρt) − 1, where ρt represents
the expected overall inflation rate, defined by a five-year centered moving average of the rate ofchange of the consumer price index (see Schreyer, Bignon, and Dupont, 2003).

Appendix

each asset, which is defined as the product of the user cost of capital and the productive capital stock,kStk) . Based on this identity and the n-equations of user cost of capital, the n+1(i.e., Vt = Σk Vtk = Σk ut,0kvariables of ut,0 and rt are simultaneously determined, using the observed capital compensation Vt askis not indethe total sum of Vtk that is not observable in each asset. Note that the depreciation rate P,t,0
pendent of the estimated rt.
The estimated results of the ex post real rate of return based on rt* = (1 + rt) / (1 + ρt)−1 for 15 Asian
countries and the US are shown in Figure A5. Although there are large fluctuations in countries likeThailand, Mongolia, and Vietnam, we may find a decreasing trend in the (endogenous) real rate of
return for many Asian countries, compared to the US, which has a stable rate of around 10 per cent. In
2010, the real rate of return ranged from 6 per cent (Japan) to 25 per cent (Indonesia). Using these ex
post estimates, the aggregate capital services are measured in this report. The difference caused by
the ex ante and ex post approaches may provide a modest difference in the growth measure of capital
services, regardless of the substantial differences in the rates of return and capital compensations(Nomura 2004).
%
0.5

China

%
0.5

%
0.5

Fiji

0.4

0.4

0.4

0.3

0.3

0.3

0.3

0.2

0.2

0.2

0.2

0.1

0.1

0.1

0.1

0.0

0.0

0.0

%
0.5

India

1971 1981 1991 2001%
0.5

Indonesia

%
0.5

Iran

1971 1981 1991 2001
%
0.5

0.4

0.4

0.4

0.3

0.3

0.3

0.3

0.2

0.2

0.2

0.2

0.1

0.1

0.1

0.1

0.0

0.0

0.0

%
0.5

Korea

1971 1981 1991 2001%
0.5

Malaysia

Mongolia

1971 1981 1991 2001
%
0.5

0.4

0.4

0.4

0.4

0.3

0.3

0.3

0.3

0.2

0.2

0.2

0.2

0.1

0.1

0.1

0.1

0.0

0.0

0.0

1971 1981 1991 2001%
0.5

Singapore

1971 1981 1991 2001%
0.5

Thailand

Vietnam1971 1981 1991 2001
%
0.5

0.4

0.4

0.4

0.4

0.3

0.3

0.3

0.3

0.2

0.2

0.2

0.2

0.1

0.1

0.1

0.1

0.0

0.0

0.0

1971 1981 1991 2001

1971 1981 1991 2001

US

0.0
1971 1981 1991 2001

Figure A5 Ex Post Real Rate of Return in Asia, 1970–2010
Source: APO Productivity Database 2012.01.
Note: The starting period for Vietnam is 1986.

Philippines

0.01971 1981 1991 2001

%
0.5

Japan

0.0
1971 1981 1991 2001%
0.5

Hong Kong

0.01971 1981 1991 2001

0.4

1971 1981 1991 2001

132

%
0.5

0.4

1971 1981 1991 2001

©2012 Asian Productivity Organization

ROC

1971 1981 1991 2001

A.4 Data Sources

A.4

Data Sources

Most of the data for APO member economies have been prepared by national experts of each country and the research effort of KEO, Keio University. A list of the national experts is given in Section
1.2. Employment data have been constructed using statistics listed in the table at the end of each section. These data provided by the national experts are supplemented by the use of external data
sources such as the ILO Yearbook of Labor Statistics (http://laborsta.ilo.org), the World Bank’s World
Development Indicators, UN data (National Accounts Official Country Data – http://data.un.org), and
the Asian Development Bank’s Key Indicators for Asia and the Pacific (www.adb.org/documents/books/
key_indicators).

App.

The exchange rates used in this edition are the adjusted rates, which are called the AMA (Analysis ofMain Aggregate) rates, in the UNSD National Accounts Main Aggregate Database. The AMA rates coincide with IMF rates except for certain periods in countries with official fixed exchange rates and highinflation, when there could be a serious disparity between real GDP growth and growth converted to
US dollars based on IMF rates. In such cases, the AMA adjusts the IMF-based rates by multiplying the
growth rate of the GDP deflator relative to the US.
There are three reference countries, for which the authors collected and constructed data. For China,
we use multiple data sources. GDP for the whole economy, industry GDP, final demand, and employment are taken from CEIC Data Company. Income data are taken from China National Income 1952–
1995 and China Statistical Yearbook. Time-series data of GFCF during 1952–2010 are constructed by
the authors. Main references for GFCF construction are Statistics on Investment in Fixed Assets of China
1950–2000, China Statistical Yearbook, and1987, 1992, 1997, 2002, and 2007 Input–Output
Sources for Employment Data
Tables of China. Multiple data sources for manuBangladesh Labor Force Survey, Populations Census
facturing, electrics, and trade data from China’s
Cambodia Socio-Economic Survey, Labor Force Survey
Yearbook of Manpower Survey Statistics in Taiwan Area,
Customs Statistics are also utilized.102
ROC

Tax data of member economies are supplemented by the IMF’s Government Finance Statistics (GFS). From its tax revenue data, “taxes
on goods and services” and “taxes on imports”
are used for calculating taxes on products.
From its expenditure data, “subsidies” aretaken. Data taken from GFS play a key rolein adjusting GDP at market prices to GDP atbasic prices.

Lao PDR

Hong Kong

Taiwan Statistical Data Book
Annual Employment Survey, Population Census, Estimates by
FIBOS (Fiji Islands Bureau of Statistics)
Data download from Census and Statistics Department of

India

Hong Kong Statistics
Census of India

Indonesia

Labor Situation in Indonesia

Iran

Population Census

Japan

Labor Force Survey, National Accounts
Census on Basic Characteristics of Establishment, Economically

Korea

Malaysia

Active Population Survey, Monthly Labor Survey
ADB Key Indicators for Asia and the Pacific
Economic Report Various Issues, Malaysia Economic

Mongolia

Statistics-Time Series, Labor Force Survey Report
Mongolian Statistical Yearbook

Nepal

Population Census

Pakistan

Pakistan Economic Survey

Philippines

Labor Force Survey, Philippines Statistical Yearbook
Labor Force Survey, Singapore Yearbook of Manpower

Singapore
Sri Lanka

Statistics
Central Bank of Sri Lanka Annual Report

ThailandLabor Force Survey

VietnamEstimates by General Statistics Office

102: Holz (2006) provides a useful reference on Chinese official statistics.

133©2012 Asian Productivity Organization

The data source for EU15 and EU27 is OECD.
Stat (http://stats.oecd.org/). The data for the US
and Australia are taken from the website of the
US Bureau of Economic Analysis (http://www.
bea.gov) and the Australian Bureau of Statistics(http://www.abs.gov.au/), respectively.

FijiAppendix

A.5

Industry Classification

The concordance between the industry classification used in Chapter 6 and the International Standard Industry Classification of All Economic Activities (ISIC), Rev. 3, is shown in the following table.
ISIC
Databook
Rev.3
A - Agriculture, hunting and forestry

01
02

B - Fishing05

1

Fishing, operation of fish hatcheries and fish farms; service activities incidental to fishingC - Mining and quarrying

10
11

2
2

12
13
14
15
16
17
18
19
20

2
2
2
3
3
3
3
3
3

21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
40
41

3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
4
4

Mining of coal and lignite; extraction of peat
Extraction of crude petroleum and natural gas; service activities
incidental to oil and gas extraction excluding surveying
Mining of uranium and thorium ores
Mining of metal ores
Other mining and quarrying
Manufacture of food products and beverages
Manufacture of tobacco products
Manufacture of textiles
Manufacture of wearing apparel; dressing and dyeing of fur
Tanning and dressing of leather; manufacture of luggage, handbags, saddlery, harness and footwear
Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles ofstraw and plaiting materials
Manufacture of paper and paper products
Publishing, printing and reproduction of recorded media
Manufacture of coke, refined petroleum products and nuclear fuelManufacture of chemicals and chemical products
Manufacture of rubber and plastics products
Manufacture of other non-metallic mineral products
Manufacture of basic metals
Manufacture of fabricated metal products, except machinery and equipment
Manufacture of machinery and equipment n.e.c.
Manufacture of office, accounting and computing machinery
Manufacture of electrical machinery and apparatus n.e.c.
Manufacture of radio, television and communication equipment and apparatus
Manufacture of medical, precision and optical instruments, watches and clocks
Manufacture of motor vehicles, trailers and semi-trailers
Manufacture of other transport equipment
Manufacture of furniture; manufacturing n.e.c.
RecyclingF - Construction

45

5Construction

G - Wholesale and retail trade; repair ofmotor vehicles, motorcycles andpersonal and household goods

50
51
52

6
6
6

Sale, maintenance and repair of motor vehicles and motorcycles; retail sale of automotive fuelWholesale trade and commission trade, except of motor vehicles and motorcycles
Retail trade, except of motor vehicles and motorcycles; repair of personal and household goods

H - Hotels and restaurants

55

6

Hotels and restaurants

I - Transport, storage andcommunications

60
61
62
63
64

7
7
7
7
7

Land transport; transport via pipelines
Water transport
Air transport
Supporting and auxiliary transport activities; activities of travel agencies
Post and telecommunications

J - Financial intermediation

65
66
67

8
8
8

Financial intermediation, except insurance and pension funding
Insurance and pension funding, except compulsory social security
Activities auxiliary to financial intermediation

K - Real estate, renting and businessactivities

70
71
72
73
74

8
8
8
8
8

Real estate activities
Renting of machinery and equipment without operator and of personal and household goods
Computer and related activities
Research and development
Other business activities

L - Public administration and defence;compulsory social security

75

9

Public administration and defence; compulsory social security

M - Education80

9

Education

N - Health and social work

85

9

Health and social work ther community, social andO-O
personal service activities

90
91
92
93

9
9
9
9

Sewage and refuse disposal, sanitation and similar activities
Activities of membership organizations n.e.c.
Recreational, cultural and sporting activities
Other service activities

P - Private households with employedpersons

95

9

Private households with employed persons

Q - E xtra-territorial organizations andbodies99

9Extra-territorial organizations and bodies

D - Manufacturing©2012 Asian Productivity Organization

E - Electricity, gas and water supply

1
1

Agriculture, hunting and related service activities
Forestry, logging and related service activities

3.1
3.1
3.2
3.2
3.2
3.3
3.4
3.4
3.5
3.5
3.5
3.6
3.7
3.8
3.8
3.8
3.8
3.8
3.8
3.8
3.8
3.9
3.9

Note: “n.e.c” represents “not elsewhere classified.”

134

Electricity, gas, steam and hot water supply
Collection, purification and distribution of water

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136