©2013 Asian Productivity Organization©2013 Asian Productivity Organization

All rights reserved. No part of this work, including
the figures, tables, and charts, may be reproduced
or used in any form or by any means, graphic,

Contents1

1.1 Databook 20131

1.2 List of Contributors

2

2 Overview

5

3 Growth of Asian Economy

13

3.1 Economic Scale and Growth14

3.2 Catching Up in Per Capita GDP

23

3.3 Sources of Per Capita GDP Gap

29

4 Expenditure37

4.1 Composition of Final Demand37

4.2 Demand-Side Growth Decomposition49

5 Productivity

57

5.1 Per-Worker Measure of Labor Productivity

57

5.2 Per-Hour Measure of Labor Productivity

63

5.3 Total Factor Productivity

68

5.4 Enhancement of Labor Productivity

80

6 Industry Perspective87

6.1 Output and Employment87

6.2 Industry Growth94

6.3 Labor Productivity by Industry

106

7 Real Income

111

7.1 Real Income and Terms of Trade111

7.2 Terms of Trade and Productivity Growth120

Appendix123

A.1 GDP Harmonization

123

A.2 Capital Stock127

A.3 Rate of Return and Capital Services

129

A.4 Hours Worked

131

A.5 Other Data

133

A.6 Industry Classification

134

References

135

iii

©2013 Asian Productivity Organization

1 Introduction

Contents

Box
Box

1

National Accounts in Asian Countries

22

Box

2

Population and Demographic Dividend

33

Box

3

Quarterly Economic Growth

48

Box

4

Turning Point in China

60

Box

5

Sensitivity of TFP Estimates

86

Box

6

Resource-Rich Countries and the Possible Dutch Disease

121

Table

©2013 Asian Productivity Organization

Table

1

Cross-Country Comparison of GDP using Exchange Rate, 1970, 1980, 1990, 2000, 2010,
and 2011

14

Table

2

Cross-Country Comparison of GDP using PPP, 1970, 1980, 1990, 2000, 2010, and 2011

16

Table

3

GDP Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2011

18

Table

4

Cross-Country Comparison of Per Capita GDP using Exchange Rate, 1970, 1980, 1990,
2000, 2010, and 2011

24

Table

5

Per Capita GDP, 1970, 1980, 1990, 2000, 2010, and 2011

27

Table

6

Country Groups Based on the Initial Economic Level and the Pace of Catching Up

28

Table

7

Final Demand Shares in GDP, 1970, 1980, 1990, 2000, and 2011

37

Table

8

Per-Worker Labor Productivity Levels, 1970, 1980, 1990, 2000, 2010, and 2011

59

Table

9

Labor Productivity Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2011

61

Table 10

Per-Hour Labor Productivity Levels, 1970, 1980, 1990, 2000, 2010, and 201164

Table 11

Labor Productivity Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2011

66

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

76

Table 13

Role of TFP and Capital Deepening in Labor Productivity Growth, 1970–2011

84

Table 14

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

88

Table 15

Output Growth by Industry, 2000–2010

100

Table 16

Labor Productivity Growth by Industry, 2000–2010

106

Table 17

Real Income and Terms of Trade, 1970–2011, 1995–2000, 2000–2005, and 2005–2011

112

Table 18

Asset Classification and Parameters in Hyperbolic Function

127

Table 19

Input–Output Tables and Supply and Use Tables

127

Table 20

Average Ex Post Real Rate of Return in Asia

130

Table 21

Sources of Labor Data

132

Table 22

Industry Classification

134

iv

FigureFigure1

GDP Growth of Asia, the EU, Japan, and the US, 1970–2011

13

Figure2

Share of Asia in World GDP in 2011 and Projection for 201813

Figure3

Relative Prices of GDP, 2005

15

Figure4

Regional GDP of Asia and the EU Relative to the US, 1970–2011

17

Figure5

GDP of China, India, and Japan, 1970–2011

17

Figure6

Regional GDP of South Asia, ASEAN, and GCC, 1970–2011

17

Figure7Country Contributions to Regional GDP Growth, 1970–1990 and 1990–2011

19

Figure8Correlation of GDP Growth, 1990–1999

20

Figure9Correlation of GDP Growth, 2000–2011

21

Figure 10

Share of Asian Population in the World in 201123

Figure 11

Cross-Country Comparison of Per Capita GDP using Exchange Rate of Japan and Australia Relative to the US, 1970–2011

25

Cross-Country Comparison of Per Capita GDP using Exchange Rate of Asian Tigers
Relative to the US, 1970–2011

25

Figure 13

Per Capita GDP of Japan, the EU, and Australia Relative to the US, 1970–2011

25

Figure 14

Per Capita GDP of Asian Tigers Relative to the US, 1970–2011

25

Figure 15

Per Capita GDP of China, India, and ASEAN Relative to the US, 1970–2011

26

Figure 16

Per Capita Non-Mining GDP in Oil-Rich Countries, 2010

26

Figure 17

Initial Level and Growth of Per Capita GDP, 1970–201128

Figure 18

Labor Productivity and Employment Rate Gap Relative to the US, 1995 and 201129

Figure 19

Sources of Per Capita GDP Growth, 1995–2000 and 2000–201130

Figure 20

Share of Female Employment

31

Figure 21

Employment Rates, 1970, 1990, and 201131

Figure 22

Final Demand Shares in GDP of China, 1952–2011

39

Figure 23

Final Demand Shares in GDP of the US, 1929–2011

39

Figure 24

Final Demand Shares in GDP, 1995 and 201140

Figure 25

Ratio of Dependent Population and Consumption Share in GDP at Current Prices, 201141

Figure 26

Export and Import Shares in GDP, 1995 and 201142

Figure 27

Long-Term Trend of Household Consumption Share in GDP, 1970–2011

43

Figure 28

Share of Dependent Population, 201144

Figure 29

Household Consumption by Purpose, 2010

45

Figure 30

Engel Curve of Japan during 1949–2010 and Levels of Asian Countries in 2010

45

Figure 31

Long-Term Trend of Investment Share in GDP, 1970–2011

46

Figure 32

Investment Share by Type of Asset, 1970 and 201146

Figure 33

Long-Term Trend of Net Export Share in GDP, 1970–201147

Figure 34

Final Demand Contributions to Economic Growth, 1995–2000 and 2000–201150

Figure 35

Final Demand Contribution Shares to Economic Growth of the Asian Tigers, 2000–2011

51

Figure 36

Impacts of Global Financial Crisis and Recoveries, 2007–2011

52

Figure 37

Impacts of Asian Financial Crisis, 1997–1998

53

Figure 38

Final Demand Decomposition of Real GDP Growth, 1970–2011

54

Figure 39

Labor Productivity Level by Per-Worker GDP, 2011

58

Figure 40

Labor Productivity Trends of China and India, 1970–2011

60

Figure 41

Labor Productivity Level Relative to the US, 1970–2011

62

Figure 42

Labor Productivity Gap by Per-Worker and Per-Hour GDP Relative to the US, 2011

64v

©2013 Asian Productivity Organization

Figure 12©2013 Asian Productivity Organization

Contents

Figure 43

Labor Productivity Trends in Japan and the Four Asian Tigers, 1970–2011

65

Figure 44

Labor Productivity Growth, 1970–2010, 1970–1990, and 1990–2011

65

Figure 45

Labor Input Growth, 1970–2010, 1970–1990, and 1990–2011

65

Figure 46

Labor Productivity Trends of Japan during 1885–2011 and Levels of Asian Countries in 2011

67

Figure 47

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

68

Figure 48

TFP Growth, 1970–2011, 1970–1990, and 1990–2011

70

Figure 49

Sources of Economic Growth, 1970–2011

71

Figure 50

Contribution Shares of Economic Growth, 1970–2011

71

Figure 51

Sources of Economic Growth, 1970–1985, 1985–2000, and 2000–2011

72

Figure 52

Contribution Shares of Economic Growth, 1970–1985, 1985–2000, and 2000–2011

72

Figure 53

Comparison of Sources of Economic Growth with OECD Countries, 2000–201073

Figure 54

Individual Countries’ Growth Accounting Decomposition, 1970–2011

75

Figure 55

IT Capital Contribution to Capital Input Growth of Japan and the US, 1970–2011

78

Figure 56

IT Capital Contribution to Capital Input Growth of Asian Tigers, China, and India, 1970–2011

78

Figure 57

Individual Countries’ Growth Accounting Decomposition (year-on-year), 1970–2011

79

Figure 58

Capital Deepening, 1970–2011, 1970–1990, and 1990–2011

80

Figure 59

Capital Productivity Growth, 1970–2011, 1970–1990, and 1990–2011

80

Figure 60

Capital Productivity Trends in Japan and the Four Asian Tigers, 1970–2011

81

Figure 61

Capital Productivity Trends in China and India, 1970–2011

81

Figure 62

Sources of Labor Productivity Growth, 1970–2011

81

Figure 63

Contribution Shares of Labor Productivity Growth, 1970–2011

81

Figure 64

Sources of Labor Productivity Growth, 1970–1985, 1985–2000, and 2000–2011

82

Figure 65

Contribution Shares of Labor Productivity Growth, 1970–1985, 1985–2000, and 2000–2011

82

Figure 66

Decomposition of Labor Productivity Growth, 1970–2011

83

Figure 67

Industry Shares of Value Added, 201089

Figure 68

Industry Shares of Value Added in Manufacturing, 201089

Figure 69

Industry Shares of Value Added and Employment by Country Group, 1980, 1990, 2000,
and 2010

90

Figure 70

Long-Term Trends of Value-added Share in the Agriculture Sector, 1970–2010

92

Figure 71

Industry Shares of Employment, 2010

93

Figure 72

Employment Share of Agriculture in Japan during 1885–2011 and Levels of Asian Countries in 2010

93

Figure 73

Long-Term Trends of Employment Share in the Agriculture Sector, 1970–2010

94

Figure 74

Job Creation in Manufacturing, 1970–2010

95

Figure 75

Industry Origins of Economic Growth, 1985–1990, 1990–1995, 1995–2000, and 2000–2010

96

Figure 76

Contribution of Manufacturing to Economic Growth, 1995–2000 and 2000–2010

97

Figure 77

Contribution of Service Sector to Economic Growth, 1995–2000 and 2000–201098

Figure 78

Contribution of Wholesale and Retail to Economic Growth, 1995–2000 and 2000–201099

Figure 79

Industry Origins of Output Growth in Manufacturing, 1995–2000 and 2000–2010

101

Figure 80

Industry Origins of Regional Economic Growth, 1995–2000 and 2000–2010

102

Figure 81

Industry Origins of Asian Economic Growth, 2000–2010

103

Figure 82

Industry Origins of Economic Growth, 1970–2010

104

Figure 83

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

Figure 84vi

and 2000–2010

107

Contribution of Manufacturing to Labor Productivity Growth, 1995–2000 and 2000–2010108

Contribution of Service Sector to Labor Productivity Growth, 1995–2000 and 2000–2010

Figure 86

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

108

and 2000–2010

109

Figure 87

Effect of Net Income Transfer on GDP, 1970–2011

113

Figure 88

Real Income and Real GDP Growth, 1970–2011

114

Figure 89

Trading Gain Effect, 2005–2011

114

Figure 90

Price of Crude Oil, 1986–2013

115

Figure 91

Decomposition of Real Income Growth, 1970–2011 and 2000–2011

116

Figure 92

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

117

Figure 93

Sources of Real Income Growth, 1970–2011

118

Figure 94

Terms-of-Trade Effect and Labor Productivity Growth, 1970–2011

120

Figure 95

Adjustment of FISIM

124

Figure 96

FISIM Share in GDP in the 2000–2011

124

Figure 97

Software Investment Ratio and GFCF Ratio to GDP, 2005

125

Figure 98

Capital-Output Ratio, 1980 and 2011

128

Figure 99

Ex Post Real Rate of Return in Asia, 1970–2011

129

Figure 100

Average Annual Hours Worked Per Worker Relative to the US, 2000–2011132

Figure B1

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

22

Figure B2.1

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

33

Figure B2.2

Asian Countries’ Population Size and Projection, 1970, 2011, and 2050

34

Figure B2.3

Proportion of the Dependent Population, 201134

Figure B2.4

Demographic Dividend, 1950–2100

35

Figure B3.1

Views of Quarterly Economic Growth in Asian Countries by the AQGM

48

Figure B3.2

Quarterly Economic Growth in Asian Countries, 2010Q4 – 2012Q4

49

Figure B4.1

Price of Labor Relative to Capital in China, Japan, and the Asian Tigers, 1970–2011

60

Figure B5.1

Labor Income Share for Employees, 201186

Figure B5.2

Sensitivity of TFP Estimates by the Change of Income Share, 1970–2011

86

Figure B6.1

Trading Gain Effects and Value-added Share in Mining Sector, 1970–2010

121

vii

©2013 Asian Productivity Organization

Figure 85

Abbreviations
ADB

Asian Development BankAPO

Asian Productivity Organization

APO20

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

AQGM		

Asian quarterly growth map

ASEAN

Association of Southeast Asian Nations: Brunei, Cambodia, Indonesia, the Lao
PDR, Malaysia, Myanmar, the Philippines, Singapore, Thailand, and Vietnam

Asia23

APO20 plus the People’s Republic of China, Brunei, and Myanmar

Asia29Asia23 plus GCC countries

CLMV

Cambodia, the Lao PDR, Myanmar, and Vietnam

CPI

consumer price index

EU

European Union

EU15

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

EU27

European Union: EU15 plus Bulgaria, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovak Republic, and Slovenia

FISIM

financial intermediation services indirectly measured

GCC

Gulf Cooperation Council: Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and©2013 Asian Productivity Organization

the UAE

viii

GDP

gross domestic product

GFCF

gross fixed capital formation

GNI

gross national income

IMF

International Monetary Fund

ISIC

International Standard Industry ClassificationIT

information technology

KEO		

Keio Economic Observatory, Keio University

Lao PDR		

Lao People’s Democratic Republic

NPISHsnon-profit institutions serving households

OECD

Organisation for Economic Co-operation and Development

PPP

purchasing power parity

QNA

quarterly national accounts

ROC

Republic of China

SNA

System of National Accounts

TFP

total factor productivity

UAE

United Arab Emirates

UN

United Nations

UNSD

United Nations Statistics Division

US

United States

Foreword
I am pleased to release this, the sixth edition of the APO Productivity Databook(Databook 2013) to the readers. The Databook 2013 is an analytical reportbased on comparative data on productivity and economic growth, which has
been constructed from timely and reliable sources of data and information. In
conjunction with the online data published on the APO website, the APO Productivity Database and the Asian Quarterly Growth Map, the Databook 2013
offers a comprehensive overview of Asia’s productivity data and expert analysis
for development planners, public and private policy makers, industries and researchers, and the general public.
It is evident from the statistical data and analysis contained in this edition that
Asian economies have generally been resilient and quickly recovered from therecent global financial crisis which has devastated so many other regions. Asia
is steadily gaining a reputation as a vibrant center of the world economy, now
contributing approximately two-fifths of global value added. In the context ofsuch Asian dynamism, it is our ambitious expectation that all the APO members
will eventually enjoy a high standard of living. Our challenge to this ambition is
productivity; Asia must not be complacent in its efforts towards efficiency andcompetitive economic performance.
The APO continues working to propel all its member economies to be moreproductive and competitive through the mainstreaming of innovation-led productivity tools and techniques to further strengthen the region’s engines – itssmall and medium enterprises and the human capitals that power them. In thisendeavor, the APO is mindful of equally distributing productivity gains acrossthe populations. At the same time, it is our strong conviction that the productivity journey be navigated in tandem with the concept of sustainable development. The APO has therefore been proactive in addressing the importance ofenvironmental sustainability in pursuing production efficiency, together withpromotion of Green Productivity.
This publication is the fruit of the research efforts of the APO Productivity Databook Project, implemented by the Research and Planning Department of the
APO Secretariat in collaboration with Keio Economic Observatory, Keio University in Tokyo. My profound gratitude goes to Professor Koji Nomura, Professor Fukunari Kimura, Ms. Eunice Y. M. Lau, Ms. Kyoko Ishikawa, Ms. Shinyoung Oh, andMr. Hiroshi Shirane. I also wish to thank all the national experts for providing
their respective economic data. The APO continues, and will continue, to workwith our members and their respective statistical offices to improve the data
quality and coverage that underpins the data presented in the APO Productivity
Databook series.

Ryuichiro Yamazaki
Secretary-General
Asian Productivity Organization
Tokyo, August 2013ix

©2013 Asian Productivity Organization

I am confident that readers will appreciate this publication as a reference andfind practical uses for it.

1.1 Databook 2012

1 Introduction
1

1.1 Databook 2013This is the sixth edition in the APO Productivity Databook series. The publication aims to provide across-country comparison of economic growth and productivity levels of Asian economies in relation
to global and regional economies. Productivity analysis will allow valuable insights into the longterm growth potential of an economy. With a focus on long-term analysis, the APO Productivity Databook not only looks at a country’s productivity performance, but also its economic composition andsources of growth in order to provide readers with a more comprehensive description and comparison of a given country’s economic structure and characteristics.
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 (ROC), Fiji, Hong Kong, India, Indonesia, the Islamic Republic of Iran (Iran), Japan,
the Republic of Korea (Korea), the Lao People’s Democratic Republic (Lao PDR), Malaysia, Mongolia,
Nepal, Pakistan, the Philippines, Singapore, Sri Lanka, Thailand, and Vietnam, and nine non-member
economies in Asia – the People’s Republic of China (China), Brunei, Myanmar, and the Gulf Cooperation Council (GCC) that consists of Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United ArabEmirates (UAE). In addition, Australia, the European Union (EU), Turkey, and the United States (US)are included as reference economies. Turkey has been newly included in this edition as a reference
country. This edition covers the period 1970–2011.

To analyze the overall productivity improvement as well as partial productivity improvement (i.e.,labor productivity and capital productivity), the Databook project constructs estimates of capital services appropriate to the concept of capital input introduced in the 2008 SNA. Based on these estimates, the sources of economic growth in each economy are further decomposed to factor inputs oflabor and capital and total factor productivity (TFP) for 17 Asian economies – ROC, Fiji, Hong Kong,
India, Indonesia, Iran, Japan, Korea, Malaysia, Mongolia, Pakistan, the Philippines, Singapore, Sri Lanka, Thailand, Vietnam, and China – along with the US as a reference economy. It is a notable achievement that the TFP estimates for Pakistan and Sri Lanka are newly developed in the APO Productivity
Database 2013 and are presented in this edition of the Databook. This edition reflects the revisions to
the official national accounts and other statistical data published as of March 2013.
Most of the official national accounts and metadata information used for constructing the APO Productivity Database 2013 have been prepared by national experts in the APO member economies

1©2013 Asian Productivity Organization

The productivity measures in this report are based on data and estimates collated for the APO Productivity Database project since September 2007, as a joint research effort between the APO and the Keio
Economic Observatory (KEO), at Keio University. Its estimates are based primarily on the System of
National Accounts (SNA) in 1993. In this edition, some significant revisions on the national accounts
were incorporated. New developments for the upgrading of statistics systems in APO member economies have resulted in Malaysia and Hong Kong publishing their accounts based on the 2008 SNA
in May and September 2012, respectively. In May 2011, the Philippines published its new accounts
based on the 1993 SNA and elements of the 2008 SNA. While there are movements toward upgrading
the SNA, some countries, such as Cambodia and Indonesia, have still not fully introduced the 1993
SNA. The different statuses of SNA adaptions among the member economies can result in discrepancies between data definitions and coverage, calling for data harmonization in order to perform comparative productivity analyses. This Databook project tries to reconcile the national accounts variations
that are based on the different concepts and definitions, and provide harmonized estimates for international comparison.

1 Introduction

through questionnaires designed at KEO. The names of these experts are listed in Section 1.2. The
submitted data was then examined and processed at KEO where further information was collected onlabor, production, prices, and taxes as required. The project was managed by Koji Nomura (KEO, Keio
University), under the consultancy of Professors Dale W. Jorgenson (Harvard University) and W. Erwin
Diewert (University of British Columbia), and with coordination by Yasuko Asano (Research andPlanning Department, APO). The text, tables, and figures in the report were authored by Koji Nomura,
Fukunari Kimura (Department of Economics, Keio University), and Eunice Ya Ming Lau (KEO, Keio University) with support from research assistants Kyoko Ishikawa, Shinyoung Oh, and Hiroshi Shirane.

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

Dr. Fukunari Kimura
Professor, Department of Economics,
Keio University

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

Research Assistants at KEO, Keio University
Ms. Kyoko Ishikawa
Ms. Shinyoung Oh

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, Economics Statistics Division,
Fiji Islands Bureau of Statistics,
P.O. Box 2048, Government Buildings, Suva

Mr. Hiroshi Shirane
APO Officer
Ms. Yasuko Asano
Program Officer, Research and Planning
Department, Asian Productivity Organization,
1-24-1 Hongo, Bunkyo-ku, Tokyo
113-0033, Japan

National Experts©2013 Asian Productivity Organization

Bangladesh
Mr. Ziauddin Ahmed
Deputy Director, Bangladesh Bureau of Statistics,
Parishankhan Bhaban, E/27/A, Agargaon,
Sher-e-Bangla Nagar, Dhaka

2

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

Islamic Republic of Iran
Mr. Hamid Azarmand
Consultant, National Iranian Productivity
Organization, No. 15, Daneshsara St.,
Baharestan Sq., Tehran

1.2 List of Contributors

Japan
Mr. Takashi Watanabe
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, National Accounts Division,
Department of Economic Statistics, Lao Statistics
Bureau, Ministry of Planning and Investment,
Ban Sithanneau, Souphanouvong Road, Vientiane

Malaysia
Ms. Hezlin Suzliana Binti Abdul Halim
Assistant Director, National Accounts Statistics
Division, Department of Statistics, Malaysia, Ting.
3, Unit 01-05, Wisma Minlon, Batu 12 Lebuhraya
Sg. Besi, 43300 Seri Kembangan, Selangor

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

Pakistan
Mr. Shahid Mahmood Butt

1

Deputy Director General, National Accounts,
Statistics Division, Pakistan Bureau of Statistics,
Statistics House 21, Mauve Area G-9/1,
Islamabad

Philippines
Ms. Estela T. de Guzman
Director, Industry and Trade Statistics Department,
National Statistics Office, Solicarel Building,Ramon Magsaysay Blvd., Sta. Mesa, Manila 1016

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

Thailand
Ms. Wannapa Khlaisuan
Senior Professional, National Accounts Office,National Economic and Social Development
Board, 962 Krung Kasem Road, Pomprab,Bangkok 10100

VietnamMs. Thi Hai Ha Nguyen
Statistical Officer, Trade and Services Department,
General Statistics Office of Vietnam, 6B Hoang
Dieu Street, Ba Dinh District, Hanoi

Nepal
Mr. Rajesh Dhital

3©2013 Asian Productivity Organization

Statistical Officer, Central Bureau of Statistics,
Ramshapath, Thapathali, Kathmandu©2013 Asian Productivity Organization

APO member economies
Non-member Asian economies included in Databook 2013

1 Introduction

4

Overview

2 Overview
The year 2012 was a relatively strong one for economic growth in most Asian countries, despite theEU’s chronic slump and growing uncertainty in the US. The Euro crisis that started in 2008 graduallycalmed down, although it appears it will take a few more years for the EU to resume its stable growthpath. The US economy looked set to recover its vigor, but its relative importance as a trading partnerof Asia remained lower than pre-global financial crisis levels. Asia, in contrast, grew almost by itself inthese few years to become a notable growth center of the world despite some Asian countries showing signs of a slowdown in the short run.

2

China has been a champion of economic growth both in Asia and the world for decades, and other
Asian countries also performed fairly well. Latecomers in ASEAN1, namely Cambodia, the Lao PDR,
Myanmar, and Vietnam (CLMV), have shown higher gross domestic product (GDP) growth rates thantheir six ASEAN forerunners over the past decade and a half. India, Bangladesh, Sri Lanka and otherdeveloping Asian countries have also presented sustained economic growth. These indicate the narrowing of development gaps, and the increased upward mobility that has been steadily advancing
across Asia. Aggressive introduction of foreign direct investment and participation in international
production networks – made possible through enhancing physical and institutional connectivity andutilizing the abundant unskilled labor which is moving from the rural/informal sector to the urban/
formal sector – can help Asia’s developing economies jump-start industrialization and approach the
middle-income level.
After the global financial crisis, economic ties among East Asian countries tightened further still, due
to extended and entrenched international production networks. East Asia, including both Northeast
Asia and Southeast Asia, is a region where the international division of labor in terms of production
processes or tasks, so-called the second unbundling (Baldwin, 2011), is the most advanced in theworld, particularly in machinery industries. Although similar production networks are observed in
Mexico, Costa Rica, and several countries in Latin America and Eastern Europe, those in East Asia are
distinctive in their significance within these economies, extending across many countries in the region and with a sophistication that combines intra-firm and inter-firm transactions (Ando and Kimura,2005). The fragmentation theory proposed by Jones and Kierzkowski (1990) explains why East Asia
can develop such a distinct new model – the differences in wage levels and development stages
among East Asian economies yielding substantial savings in production costs and a physical and institutional connectivity allowing low service-link costs to connect fragmented production blocks, thereby making the new type of international division of labor economically viable.

The past decade was a rare period when almost all developing countries in the world enjoyed higheconomic growth. The origins and industry sources of this growth, however, varied hugely acrossregions and, indeed, countries. In the 2000s there were drastic, observable hikes in the world pricesof natural resources and fuels, pushing up the income levels of resource-exporting economies
with aggressive resource-oriented investment and local currency appreciation. In response, therelative prices between manufactured goods and natural resources worsened substantially, leaving

1: ASEAN (Association of Southeast Asian Nations) consists of Brunei, Cambodia, Indonesia, the Lao PDR, Malaysia, Myanmar, the Philippines, Singapore, Thailand, and Vietnam.

5©2013 Asian Productivity Organization

Since 2008, intra-regional trade in East Asia has grown at a fast pace, China and Korea have been moredeeply involved with the East Asian economy, and CLMV as well as India have gradually come into
international production networks. East Asia has developed greater self-sufficiency, depending moreon their own market. It may not have achieved a complete de-coupling from the rest of the world, but
it is certainly less reliant on external economies.

2 Overview

resource-importing Asian economies vulnerable to an aggravation of the terms of trade. This undeniably lowered the welfare level of the economies involved, while at the same time strengthening
their competitiveness in manufacturing activities. Wage increases (in US dollars terms) in East Asia
have been more modest than in the rest of the world, while East Asia has started exporting massive
amounts of machinery parts and components to Eastern Europe and other industrial agglomerations(Ando and Kimura, 2013). The dominance of East Asia as a manufacturing base will surely be uncontested in the coming five-to-ten years. On the other hand, resource-exporting economies may wantto avoid the “Dutch disease”2 by avoiding drastic currency appreciation and promoting the growth of
productive sectors.
There have recently been big debates about whether the Asian economies are prey to a “middleincome trap”, or not. Felipe (2013) reviews the long-run economic growth performance of 124 countries during 1950–2010, classifying their income levels as one of four income groups, i.e., low-income,lower-middle-income, upper-middle-income, and high-income, and counting the number of years it
took a country to cross the income thresholds in terms of its economic growth. According to this simplistic categorization of the Asian economies as of 2010, the Philippines and Sri Lanka may be in alower-middle-income trap while Malaysia, Saudi Arabia, and Syria are caught in an upper-middleincome trap; other Asian economies covered by the study are mercifully not, as such, in traps. Although such simplistic numerical results are not gospel, one should be attentive for signs of slowed
growth as in, for example, the six ASEAN forerunners after the Asian currency crisis, and perhaps in the
China of the future. The East Asian developing economies in particular have been extremely successful in jump-starting industrialization by using the mechanics of production networks, and are now
approaching the uncharted territory of graduating from middle-income to fully developed economies. It is going to be a big challenge, one that certainly requires the substantial transformation of
their industrial structure, together with industrial upgrading, productivity growth, and the enhancement of human capital.

©2013 Asian Productivity Organization2012 was also the year of domestic politics. In the US, President Obama was reelected while Japan,
Korea, and China all elected new political leaders. Today, political moves toward regional economic
integration appear accelerated; the extended negotiations over the Trans-Pacific Strategic Economic
Partnership agreement started in March 2010 and included some Asian countries. The advancementof Trans-Pacific Strategic Economic Partnership negotiations will stimulate regional integration efforts
in East Asia, including the Regional Comprehensive Economic Partnership in the ASEAN+6 framework3 and the China-Japan-Korea Free Trade Agreement. It is hoped that the competitive advancement of these regional initiatives will promote beneficial overall economic integration, will acceleratenecessary domestic reforms, and will provide a model of new international economic order.
At the timing of writing (May 2013), there is wide journalistic coverage of a set of new economic policies in Japan, so-called Abenomics. Abenomics is aimed at combining monetary policy, fiscal policy,
and economic reform to escape Japan’s long-lasting recession. Although it is certainly too early
to evaluate its outcome, people’s expectations for the future have dramatically altered, at least in
the short run, and are tentatively returning to normal. Possible adverse effects of the yen depreciation – returning only now to pre-global financial crisis levels – on neighboring countries seem so far
to be minimal. Whether this can become a new prescription for stagnant developed economies is ofglobal interest.

2: “Dutch disease” describes a phenomenon in which a country’s currency is pushed up by the commodity boom, making otherparts of its economy less competitive and potentially increasing the country’s dependence on its natural resources. See 7.2 for the
Asian countries’ experiences in the long-term changes of terms of trade and labor productivity improvement.
3: The ASEAN+6 are the ASEAN and its six major trading partners: China, India, Japan, Korea, Australia, and New Zealand.

6

Overview

Asia is full of economic dynamism and one must pay considerable attention to the rapid and vigorouschanges in its economic performance in the short run. However, to fully understand its economic dynamism, it is essential to appreciate its growth performance, structural changes, and the advancement of its economic development within a context of its middle- and long-term performance. Asia,
in particular, consists of a variety of countries at different development stages, with diversified resource endowments, and under various political regimes. The APO Productivity Databook provides
concise information and useful insights into the basis of growth performance and economic structureof Asian countries by presenting such long-term data analysis.

2International comparisons of economic performance are never a precise science; instead, they are
fraught with measurement and data comparability issues. Despite our best efforts in harmonizing
data, some data uncertainty remains. Operating within a reality of data issues, some of the adjustments in the Databook are necessarily conjectural, while others are based on assumptions with scientific rigor. In addressing this shortcoming, findings drawn from the research are cross-referenced
against other similar studies. However, the magnitude of variations in the economic indicators is often
subject to a certain degree of data uncertainty.
Bearing in mind these caveats, the main findings from our analysis are as follows:
Recent economic growth of Asia
u In terms of exchange-rate-based GDP, China overtook Japan in 2010 as the largest economy in Asiaand the second largest economy in the world, after the US. On this measure, Asia29 was 44% and
51% larger than the US and EU15 in 2011, 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 98% and 113% larger than the US and EU15 in2011, respectively. China has overtaken Japan as the largest Asian economy since 2002, and its size
was 75% relative to that of the US in 2011. India was a close third in 2011 with its GDP using PPPvery nearly catching up with that of Japan (Table 2 and Figure 5).
u During the period 2000–2011, Asia29 grew at 5.8% on average per annum, compared with 1.5%

and 1.3% in the US and EU15, respectively. Japan was the slowest growing economy among theAsia29 at 0.6%, compared with 14 of the 29 Asian economies with a recorded over 5.0% of annual
economic growth (Table 3 and Figure 1).
u For the past two decades (1990–2011), China and India have emerged as the driving force propel-ling Asia forward, accounting for 47% and 15% of regional growth, respectively (Figure 7).
u The global financial crisis slowed Asia29’s growth significantly from a recent peak of 8.0% during

u The correlation coefficients between China and other Asian economies strengthened between

the two decades suggest that China has become more integrated within the Asian economy. For
most Asian countries, the correlation with the US and EU15 has also grown stronger (Figures 8 and 9).

7©2013 Asian Productivity Organization

2006–2007, to 4.5% during 2007–2008 and further to 3.6% during 2008–2009, before rebounding
strongly to 7.9% during 2009–2010. This is in comparison to the deep recession of −3.1% and−4.4% experienced by the US and EU15, respectively, during 2008–2009 (Figure 1).

2 Overview

Catching up in per capita GDP
u Our results show the outcome of the dramatic development effort of the four Asian Tigers.4 Singa-pore and Hong Kong have managed to close a per capita GDP gap with the US of around 65% injust under four decades. Singapore has even surpassed the US since 2004, and in 2011 its per ca­
pita GDP was 26% higher. In contrast, veteran Japan has fallen behind and its gap with the US has
widened to 28%. In 2011, the ROC’s and Korea’s per capita GDP was 78% and 65% of the US level,
respectively (Table 5 and Figure 14).
u Despite their rapid growth, per capita GDP of China and India was 17% and 7% that of the US in

2011, respectively, due to their population size. Even so, it represents a tenfold increase in China’s
relative per capita GDP over the last four decades. The level achieved by Asia29 was 16% that of theUS, indicating that there is ample room for catch-up (Table 5).
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% or higher (Figure 18).
u For most countries in Asia, the majority of per capita GDP growth can be explained by improve-

ment in labor productivity. However, the employment rate contribution relative to labor productivity was also highly significant in Pakistan, Nepal, the Philippines, Bangladesh, Cambodia, and Iran
(Figure 19).
u There is a large diversity in Asia’s employment rates from 30% to over 60% at present. The employ-ment rates have been rising in most countries in Asia and are 10–15 percentage points above thatof the US in Cambodia, Singapore, Thailand, Vietnam, and China (Figure 21).
Changes in Demand compositionu With a few exceptions, household consumption is the biggest component of final demand. In re-cent years, Asia29’s consumption ratio has dropped to 50.1% of GDP, largely reflecting the trend in
China. This compares with 71.2% in the US, 58.2% in EU15, and 54.1% in 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 dependent
population (under-15s and over-65s) sustain a high consumption ratio to GDP (Figures 24 and 25).
u 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 the
US/EU15. In 2011, Asia29 invested 35% of its GDP, compared with 15.5% for the US, 18.8% for EU15,
and 27.5% for Australia (Table 7 and Figure 31).

©2013 Asian Productivity Organizationu China faces huge internal and external imbalances. The investment share of GDP (at 47.6%) as thebiggest component in final demand and the household consumption share plummeted to 36.4%
in 2011. In contrast, the weight of net exports has been rising in the past decade, although it isslackening in recent years due to weak foreign demand (Figure 22).

4: Refers to Hong Kong, Korea, Singapore, and the ROC.

8

Overviewu GCC economies are unusually skewed toward net exports because of their oil. Net exports ac-

counted for 26.9% of final demand in 2011, compared with Asia29’s 1.9% and China’s 2.6%. Only
the US and South Asia run trade deficits of a more persistent nature, which accounted for −3.8%
and −7.1% of final demand, respectively, in 2011 (Table 7).

2

u Basic necessities account for a high proportion of household consumption in lower-income coun-tries – the cross-country version of Engel’s Law, which says that basic necessities will account for ahigh proportion of household consumption for a lower per capita income group and vice versa.
They spend 30–50% of total consumption for food, which corresponds to Japan’s experience in the
1950s and the 1960s (Figures 29 and 30).
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
their economic growth. The growth slowed in the US and EU15, and the contributions of government consumption to growth nearly tripled as contributions from investment took a plunge(Figures 34 and 38).
Labor Productivity
u For most Asian countries, the per capita GDP gap with the US is largely explained by their laborproductivity shortfalls of 80% or more against the US level. Only Singapore and Hong Kong haveeffectively closed that gap. The relative labor productivity of Asia23 was 15% that of the US in 2011
(Table 8 and Figure 39).
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% on average per year in 2005–2011,
followed by India’s 7.7% – this compares with the US’s 1.3%. Singapore’s 0.4% growth over thesame period was the weakest performance among the Asian Tigers and Japan (Table 9 and Figure
41).
u 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 16–27 percentage points for the Asian Tigers, suggesting that people work
much longer hours than in the US (Figure 42).
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% to 9.1% between 1970–1990 and 1990–2011, compared to that of the US at 1.5% and 1.8%
over the same periods (Figure 44).

the level that Japan achieved in the 1950s and 1960s, with the Asian Tigers being the clear frontrunners, sprinting away from the pack. This indicates that most Asian countries are still half acentury away from catching up with Japan (Figure 46).

9©2013 Asian Productivity Organizationu Mapped onto Japan’s historical trajectory of GDP per hour, most Asian countries cluster around2 Overview

Total factor productivity
u Ten of the 17 Asian countries compared experienced faster TFP growth than the US over the period

1970–2011, with China in a league of its own. Its TFP growth was at 3.2% on average a year, compared with that of Sri Lanka at 1.9% in second place and Thailand at 1.8% in third place and that of
the US at 0.9%. With TFP growing at 0.6% on average per year, Singapore’s productivity performance has been weak relative to its economic counterparts (Figure 48).
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% of economic growth in ten of the 17 Asian countries compared,
with it being most prominent in Sri Lanka (39%), China (36%), Thailand (33%), and Hong Kong(30%) (Figure 50).
u The composition of economic growth is shifting over time. In the past two decades, the contribu-

tion of capital input (especially of non-IT capital) has been getting progressively smaller in Asia,
falling to a share of below 50% on average, while the contribution of TFP is getting progressively
more significant, rising to a share of above 40% on average in the 2000s (Figure 52).
u The evident rise in the contribution of information technology (IT) capital is noteworthy. By the

2000s, it had risen to above 5% in most Asian countries compared, while accounting for around
one-third of economic growth in Japan and the US. The allocation shift towards IT capital started
two decades earlier in the US than in any Asian country (Figures 52 and 55).
u Widening our perspective to include other Organisation for Economic Co-operation and Develop-

ment (OECD) countries shows that Asia’s vibrant economic growth and TFP performance in the
2000s was unmatched by any other country, except Ireland (Figure 53).
u Over the past decades, it has been observable that economic growth has decelerated in the earlystarters (i.e., Japan and the Asian Tigers). Their experience lends support to the likelihood of aneventual slowdown in China; the question is more likely to be “when”, rather than “if”. TFP growthslowed from its former peaks achieved in the late 1970s or early 1980s until recent years whencountries experienced TFP resurgence (Figure 54).
Capital Deepening and Capital Productivity
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 10.2% on average a year to 7.4% in Korea between
1970–1990 and 1990–2012, whereas it doubled in China from 5.2% to 10.5% (Figure 58).

©2013 Asian Productivity Organizationu 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 over the past two decades did
not compromise its capital productivity as much as the early starters in the early period (Figure 59).
u Over a long period stretching four decades, a downward trend in labor productivity growth can beseen among the early starters, but there is 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 66).

10

Overview

Industry structure2

u Evidence supports the view that a country’s industry structure transforms with its economic devel-

opment. 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 67).
u Manufacturing is a significant sector, accounting for over 20% of total value added in most Asian

economies. It is particularly prominent in China, Thailand, Korea, Malaysia, and the ROC. 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 food industry (Figure 68).
u While Asian countries are diversifying away from agriculture, the sector still dominates employ-ment, accounting for 41% of total employment in 2009 for Asia29, down from 62% in 1980. Its
share in total value added rose from 6% to 10% over the same period, implying more labor efficiency. However, it is still the only sector that consistently has a disproportionately higher employment share than justified by its value-added share. Shifting out of agriculture into more efficient
sectors will boost economy-wide productivity (Figures 69 and 72).
u Manufacturing is a main absorption sector for workers who have been displaced from the agricul-

ture sector, especially in the initial stages of economic development. In Korea and ROC, expansions
to manufacturing output could account for the increases of employment in the 1970s and the1980s. Since the 1990s, however, the manufacturing sector has no longer been an absorption sector of employment, regardless of the sound expansion of production in this sector. (Figure 74).
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. In the past two and a half decades China has been undergoing a slight transition, with
its growth shifting away from being manufacturing-driven to being more services-driven. In the
period 2000–2010, the contributions to economic growth by manufacturing and services were
35% and 44%, respectively, compared with 46% and 29% in the first half of the 1990s (Figures
75 and 76).
u In contrast, growth in India has always been more driven by services, the contribution of whichrose from 51% in the late 1980s to 63% in the 2000s, while manufacturing usually contributes onefifth or less (Figures 75 and 77).
u A total of 29% of Asia29’s regional growth originated from the expansion of manufacturing in theu While the importance of manufacturing as a contributor to overall labor productivity growth has

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 (Table 16 and Figure 85).

11©2013 Asian Productivity Organization

2000s, two-thirds of which was accounted for by China. In other words, China’s manufacturing
alone contributed 18% to regional growth (Figure 81).

2 Overview

Real income and terms of tradeu Real GDP could systematically underestimate (or overestimate) growth in real income if terms oftrade improve (or deteriorate). It is generally observed that the trading gain effect is more significant in the short term than in the long term. Our findings confirm this observation, with the exceptions being for some oil-exporting countries such as Kuwait and Brunei, where trading gain has
always been positive and significant. Our results also reflect Australia’s recent fortune and trading
gain as the prices of their commodity exports rise and their import prices continue to fall over the
past decade or so (Table 17 and Figure 93).
u Positive net primary income from abroad also bolsters a country’s real income. In Japan and thePhilippines, net primary income from abroad has been rising steadily, albeit at different magnitudes. In Japan, it rose from 0.6% of GDP in 1990 to 3.1% in 2011, compared with 1.4% in 1990 and
32.3% in 2011 in the Philippines. Singapore’s historical margin fluctuates within a large range whencompared with other rich economies – from +1.9% in 1997 to −7.1% in 2004, but on the whole, it
has been more negative than positive (Figure 87).
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% over the long period 1970–2011; Kuwait and Brunei appear to be
the outliers (Figure 88).
u The five countries that have been enjoying a trading gain over 1% 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 a deteriorating trading gain position as a price of their own success (Figure 94).

©2013 Asian Productivity Organization

Asia is a diverse regional economy within which countries have embarked on their own journey 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. The evidence gained from our research confirms that countries’
capital accumulation is accompanied by strong productivity improvements. Through the statistics
and data presented in this report, one manages to catch a glimpse of the current unparalleledeconomic dynamics inherent in the region. China, in particular, has been rising in world economic
rankings, having overtaken Germany in 2009 as the largest exporter and Japan in 2010 as the secondlargest economy. Growth in India has also received a sudden spur in recent years. As the rich economies
lumber on, heavily laden with debt (to the point of crisis in some) and associated difficulties, this may
well prove to be an opportunity for Asia to consolidate its development achievements further.

12

3.1 Economic Scale and Growth

3 Growth of Asian Economy
In the past two decades, a consistent divergence has been observed in the growth performance between Asia and the West. 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 to 4 percentage points on average a year, respectively (Figure 1). Furthermore, this wedge has been widening
in recent years; at the height of the global financial storm (i.e., 2009), the growth differentials were 6.9
and 8.0 percentage points against the US and EU15, respectively. In 2010, major economies rebounded strongly on the back of their simultaneous large-scale fiscal stimulus package before growthslowed again in 2011. Throughout this turbulent period, the differences in growth performance havebeen sustained. It is therefore no surprise that the center of gravity in the global economy is graduallyshifting toward Asia. In 2011, the Asian economy contributed two-fifths of world output (38% for
Asia29), compared with the US and%
10
EU27, each accounting for a one8
fifth share (Figure 2). The Interna6
tional Monetary Fund (IMF) (2013)
4
projects that the Asian share in2
world output will continue to rise,0
reaching 46% (43% for Asia29) by
−2
Japan
US
2018. In contrast, the US and EU27
−4
Asia29EU15
will shrink by a similar extent to
−6
1970
1975
1980
1985
1990
1995
2000
2005
2010
18%, and 17%, respectively (14% forEU15).
Figure 1 GDP Growth of Asia, the EU, Japan, and the US,
1970–2011
With the exception of the US, which___Annual growth rate of GDP at constant market prices
has recently shown encouraging
Sources: Official national accounts in each country, including author adjustments.
signs of moving away from thepack, most of the advanced econo2011
2018
mies have been much weakened
following the recent financial crisis;
the fortune of the world economy is
ASIA
ASIA
APO20
Others
40 %
46 %
APO20
Otherstherefore increasingly tied to that of
%
21
%
20
21 %
21 %
Asia’s. To better understand the dyAsia29
Asia29
38 %
43 %
EU15
namics of the long-term economic
EU15
14 %
%
18
growth within the region, the remainOther Asia
EU27
EU27
US
US
3%
20 %
17 %
Other Asiader of this chapter looks into the
19 %
18 %
3%
details of countries’ diverse development efforts and achievements
Figure 2 Share of Asia in World GDP in 2011 and Projecsince the 1970s, through crosstion for 2018
country level comparisons of GDP___Share of GDP using constant PPP
and other related performance indiSource: IMF, World Economic Outlook Database, April 2013.
cators.5 To facilitate international

13©2013 Asian Productivity Organization

5: The database used in the Databook series includes author adjustments made to better harmonize GDP coverage across countries. GDP reported in this edition includes the final consumption of financial intermediation services indirectly measured (FISIM).
Although our database 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 1. The Databook 2013 reflects some large revisions published by national statistical offices in 2012 and in the first quarter of 2013. More specifically, at the end of 2011, Thailand officiallyswitched to the 1993 SNA, and its national accounts became compatible with the 1993 framework for the first time. To construct
the long time-series data in this report, back data based on the 1968 SNA has 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. Government capital stock and its CFC for the period 1970–1989 are estimated and the past government consumption
and GDP are adjusted accordingly.) There are also some revisions to the data, largely results of national accounts revisions including backward amendment and/or benchmark revisions.

33 Growth of Asian Economy

level comparisons, harmonized GDP for each of the individual countries6 is expressed in its equivalent
in a common currency unit (customarily in the US dollar), using a set of conversion rates between theindividual national currencies. The choices for conversion rates are exchange rates and PPPs.

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,7 for the six separate years of 1970, 1980, 1990, 2000, 2010, and 2011. By
Table 1 Cross-Country Comparison of GDP using Exchange Rate, 1970, 1980, 1990, 2000, 2010, and 2011___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

357
451
462
319
86
35
10

171.2
216.5
221.4
152.8
41.3
16.9
4.9

©2013 Asian Productivity Organization

Australia
Turkey1,038 497.9
1,194 572.6
45
25

21.6
11.8

1990

(%)

2000

(%)

Japan
3,103 100.0
China
390 12.6
India
322 10.4
Korea
270 8.7
ROC
165 5.3
Indonesia
127 4.1
Saudi Arabia 120 3.9
Iran
94 3.0Thailand
88 2.8Hong Kong77 2.5UAE
51 1.6
Philippines
49 1.6
Pakistan
48 1.5
Malaysia
45 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
5 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

Japan
4,741 100.0
China
1,198 25.3
Korea
533 11.3
India
468 9.9
ROC
326 6.9
Saudi Arabia 194 4.1
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

China
Japan
India
Korea
Indonesia
Saudi Arabia
Iran
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)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

1,745
2,059
2,299
1,526
237
198
239

160.6
189.5
211.6
140.4
21.8
18.3
22.0

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

4,481
4,880
5,094
4,006
412
366
214

144.4
157.3
164.2
129.1
13.3
11.8
6.9

(reference)

US
EU15

2,788 256.6
3,200 294.5

Australia
Turkey

173
91

15.9
8.3

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

7,091
8,302
8,686
6,969
609
613
384

149.6
175.1
183.2
147.0
12.8
12.9
8.1

(reference)

US
EU15

5,801 186.9
6,160 198.5

Australia
Turkey

323
200

10.4
6.4

US
EU15
EU27
Australia
TurkeyAPO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC
US
EU15
EU27
Australia
Turkey2011(%)

5,931 100.0
5,508 92.9
1,651 27.8
1,015 17.1
719 12.1
542 9.1
467 7.9
428 7.2
338 5.7
290 4.9
238 4.0
232 3.9
224 3.8
199 3.4
176 3.0
129 2.2
123 2.1
108 1.8
101 1.7
59 1.050 0.842 0.726 0.419 0.3
14 0.2
11 0.2
7 0.1
6 0.1
3 0.1

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

7,318 100.0
5,910 80.8
1,851 25.3
1,114 15.2
858 11.7
689 9.4
657 9.0464 6.3
365 5.0345 4.7
278 3.8
266 3.6
244 3.3
224 3.1
211 2.9
175 2.4
164 2.2
125 1.7
108 1.5
73 1.059 0.856 0.829 0.4
21 0.317 0.2
13 0.2
9 0.1
8 0.1
4 0.1

(regrouped)

11,49917,486
18,655
13,112
1,996
1,908
1,169

193.9
294.8
314.6
221.1
33.7
32.2
19.7

(reference)

9,952 209.9
9,541 201.3
10,585 223.3
407 8.6
267 5.6

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

14

2010

(%)

Japan
1,087 100.0
China
303 27.9
India
182 16.8
Saudi Arabia 148 13.6
Iran
97 8.9Indonesia
80 7.3Korea
64 5.9UAE
44 4.0ROC
42 3.9
Philippines
36 3.3Thailand
33 3.1
Kuwait30 2.7
Hong Kong
29 2.7
Pakistan
29 2.7
Malaysia
25 2.3
Bangladesh
19 1.7Singapore
12 1.1
Qatar
8 0.7
Oman
6 0.6
Myanmar
6 0.5
Brunei
5 0.5
Sri Lanka
4 0.4
Bahrain
3 0.3
Nepal
3 0.2
Fiji
1 0.1
Vietnam
1 0.1
Cambodia
1 0.1
Mongolia
0 0.0(reference)(reference)

US
EU15

1980

(%)

209 100.0
92 43.9
61 29.0
12 5.8
11 5.410 4.8
10 4.7
9 4.3
7 3.5
7 3.5
6 2.8
5 2.4
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

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

12,791
20,182
21,65815,060
2,251
2,210
1,476

174.8
275.8
295.9
205.8
30.8
30.2
20.2

(reference)

14,499 244.5
13,942 235.1
15,941 268.8
1,274 21.5
734 12.4

US
EU15
EU27
Australia
Turkey15,076 206.0
14,346 196.0
16,465 225.0
1,505 20.6
778 10.6

3.1 Economic Scale and Growth

this measure, 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
ahead strongly 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 ofJapan’s fortune came in 1990, when the country’s bubble years of the late 1980s ended and its descentbegan. 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
44% and 51% larger than the US and EU15 in 2011, respectively.

3

Comparisons based on exchange rates could appear arbitrary as movements in exchange rates can bevolatile and subject to short-term or substantial fluctuations of speculative capital flows and government intervention. Furthermore, comparisons based on exchange rates typically underestimate thesize of a developing economy and in turn the perceived welfare of its residents. The rankings of scaleof economy change dramatically when international price differences are properly accounted for. Thisis because exchange rates embody the trade sector bias
18 Japan(i.e., is more influenced by the prices of traded than nonAustralia
6
Fiji
−15
traded goods and services) and thus do not necessarily
Korea
−23
succeed in correcting the price differentials among counQatar−25
Kuwait−27
tries. As developing economies tend to have relatively
Hong Kong
−27
UAE
−34
lower wages and, in turn, lower prices for non-traded
Bahrain−34
goods and services, a unit of local currency has greater
Saudi Arabia−34
Singapore−35
purchasing power in the local economy than reflected in
Turkey−38
Oman
its exchange rate.
−40

Table 2 repeats the same snapshot level comparisons ofAsian countries as in Table 1 but is based on GDP at constant market prices using constant PPPs for Asian countries.
By correcting to allow for international price differentials,

−80

−60

−40

−20

0

20 %

Figure 3 Relative Prices of GDP, 2005___Ratio of PPP to exchange rate (reference
country=US)

Sources: Analysis of Main Aggregate rates by United
Nations Statistics Division (UNSD) and PPP by WorldBank.

6: Appendix 1 discusses the extent to which countries’ GDP data are comparable.
7: The exchange rates used in this Databook are the adjusted rates, which are called the Analysis of Main Aggregate (UNSD database) rates in the UN Statistics Division’s National Accounts Main Aggregate Database. The AMA rates coincide with the IMF rates(which are mostly the annual average of market or official exchange rates) except for some periods in countries with official fixedexchange 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.
8: 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.

15©2013 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 therelative purchasing power for all the countries covered inthis report. The underestimation is substantial for some,ranging from 15% for Fiji to 76% for Myanmar. Thus, theexchange-rate-based GDP considerably underestimatesthe economic scales in real terms for those countries. By
taking into account the international price differentials,
PPP rectifies the trade sector bias, and in turn the relative
size of economies can be more adequately measured.8

ROC
BruneiMalaysia
China
Indonesia
ThailandPhilippines
Bangladesh
Sri Lanka
Mongolia
India
Pakistan
Nepal
Cambodia
Iran
VietnamLao PDR
Myanmar

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

3 Growth of Asian Economy

Asia29 has been expanding rapidly, and was 98%, instead of 44%, larger than the US economy in 2011,
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% in 1970. In contrast, EU15 has been experiencing a gradual relative decline in economic size, from 116% of the US economy in 1970 to a low of
93% in 2011. Based on the GDP using constant PPPs, the weight of the world economy is even moretilted 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 2011 doubled to 253% that of Japan, comparedwith 124% when exchange rates are used in Table 1. Similarly, its size in 2011 increased from 49% toTable 2 Cross-Country Comparison of GDP using PPP, 1970, 1980, 1990, 2000, 2010, and 2011___GDP at constant market prices, using 2005 PPP, reference year 2010
1970

1990

(%)

2000

(%)

2010

(%)

2011

(%)

(%)

Japan
2,316 100.0
India
654 28.2
China
571 24.6
Saudi Arabia 369 15.9
Iran
299 12.9
Indonesia
225 9.7
Korea
205 8.9
ROC
148 6.4
Philippines
147 6.4
UAE
140 6.0
Thailand122 5.3
Pakistan
111 4.8
Hong Kong78 3.4
Malaysia
72 3.1
Kuwait65 2.8Bangladesh
62 2.7Singapore40 1.7
Vietnam
39 1.7
Sri Lanka
25 1.1Qatar
20 0.9Brunei18 0.8Oman
14 0.6
Myanmar13 0.6
Nepal
11 0.5Bahrain
10 0.4
Mongolia
3 0.1
Fiji
2 0.1

Japan
3,644 100.0
China
1,386 38.0
India
1,128 31.0
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
132 3.6
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
12 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
1,937 47.5
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
19 0.5
Brunei17 0.4
Cambodia
14 0.4
Lao PDR
8 0.2
Mongolia
6 0.1
Fiji
4 0.1

China
10,128 100.0Japan
4,398 43.4
India
4,045 39.9
Korea
1,468 14.5
Indonesia
1,050 10.4
Iran1,047 10.3
ROC
825 8.1
Saudi Arabia 634 6.3
Thailand632 6.2
Pakistan
468 4.6
Malaysia
417 4.1
Philippines
368 3.6
UAE
348 3.4
Hong Kong
327 3.2
Singapore295 2.9
Vietnam
281 2.8
Bangladesh
248 2.4
Qatar
152 1.5
Kuwait132 1.3
Sri Lanka
106 1.0
Myanmar
93 0.9Oman
80 0.8Nepal
41 0.4Bahrain
33 0.3
Cambodia
31 0.3
Brunei19 0.2
Lao PDR
16 0.2
Mongolia
11 0.1
Fiji
4 0.0

China
11,070 100.0Japan
4,373 39.5
India
4,275 38.6
Korea
1,522 13.8
Indonesia
1,119 10.1
Iran1,098 9.9
ROC
858 7.8
Saudi Arabia 679 6.1
Thailand635 5.7
Pakistan
481 4.3
Malaysia
439 4.0
Philippines
382 3.5
UAE
364 3.3
Hong Kong
344 3.1
Singapore310 2.8
Vietnam
297 2.7
Bangladesh
264 2.4
Qatar
172 1.6
Kuwait141 1.3
Sri Lanka
115 1.0
Myanmar
99 0.9Oman
80 0.7Nepal
42 0.4Bahrain
34 0.3
Cambodia
33 0.3
Brunei20 0.2
Lao PDR
17 0.2
Mongolia
13 0.1Fiji
4 0.0(regrouped)(regrouped)(regrouped)(regrouped)(regrouped)(regrouped)

APO20
10,753 263.8
Asia23
14,538 356.7
Asia2915,427 378.5
East Asia
9,582 235.1
South Asia 2,468 60.5
ASEAN
1,911 46.9
GCC
889 21.8

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

(reference)(reference)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

2,852
3,180
3,429
1,994
627
343
249

190.0
211.8
228.4
132.8
41.8
22.8
16.6

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

4,562
5,163
5,781
3,322
864
676
618

196.9
222.9
249.6
143.4
37.3
29.2
26.7

US
EU15

4,735 315.4
5,501 366.4

Australia
Turkey

260
196

17.3
13.0

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

7,636
9,050
9,656
6,013
1,474
1,172
606

209.5
248.4
265.0
165.0
40.5
32.2
16.6

(reference)(reference)(reference)©2013 Asian Productivity Organization

1980

(%)

Japan
1,501 100.0
India
485 32.3
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 3.8Hong Kong
33 2.2
Malaysia
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
5 0.3
Mongolia
2 0.1
Fiji
1 0.1

US
EU15

6,475 279.6
7,510 324.2

Australia
Turkey

349
291

15.1
12.6

US
EU15

8,909 244.5
9,551 262.1

Australia
Turkey

470
484

12.9
13.3

US
EU15
EU27
Australia
Turkey12,449 305.4
11,960 293.4
13,365 327.9
666 16.3
695 17.1

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

16

US
EU15
EU27
Australia
Turkey16,07826,31927,69917,158
4,907
3,203
1,379

158.7
259.9
273.5
169.4
48.4
31.6
13.6

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

16,62327,811
29,28018,180
5,178
3,351
1,469

150.2
251.2
264.5
164.2
46.8
30.3
13.3

(reference)

14,499 143.2
13,563 133.9
15,350 151.6
901 8.9
1,018 10.1

US
EU15
EU27
Australia
Turkey14,761 133.3
13,745 124.2
15,586 140.8
932 8.4
1,105 10.0

3.1 Economic Scale and Growth

US=100

US=100

180

70

160

60

140

50

200

100
80
60

EU15

40

US

30

Asia29
APO20

3

China

Japan

20
East Asia

10

India

40
1970 1975 1980 1985 1990 1995 2000 2005 201001970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 4 Regional GDP of Asia and the EU
Relative to the US, 1970–2011

Figure 5 GDP of China, India, and Japan,
1970–20112005 PPP

2005 PPP___Indices of GDP at constant market prices, using

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

75% relative to the US economy. In this measure,
China overtook Japan after 2002 to become theleading economy in Asia (Figure 5). This represents remarkable growth, considering that the
Chinese economy was only 21% that of Japanand 64% that of India in 1970. India has alsonearly caught up with Japan, with its relative size
having increased from 32% in 1970 to 98% in
2011. If India and Japan were to grow at thesame pace as they have been on average between 2000–2011, (i.e., at 7.2% and 0.6% a year,
respectively), India might already overtake Japan and become the second largest economy in
Asia and the third largest economy in the worldin 2012. Assuming that China and the US also
grow at the same pace as they have displayed
during the same period, the total GDP of thethree largest Asian countries alone will be about
50% larger than the US economy by 2014.

___Indices of GDP at constant market prices, using

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

US=100

35

30
25
20
15

South Asia

ASEAN

10
5

GCC

0
1970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 6 Regional GDP of South Asia, ASEAN,
and GCC, 1970–2011___Indices of GDP at constant market prices, using
2005 PPP

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

Figure 6 shows the rapid expansion of the relative size of the South Asia economy (consisting of Bangladesh, India, Nepal, Pakistan, and Sri Lanka), 83% of which was accounted for by India in 2011. The
catch-up effort of ASEAN has also been vigorous, but the setback caused by the Asian financial crisisof 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 flagged for two decades;
only in the past decade has it picked up slightly and brought the relative size of the country groupback to its previous peak of the early 1980s.10
9: GCC consists of Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the 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% of the world’s proven oil reserves and 25% of crude oil exports, and possess at least 17% of
the proven global natural gas reserves.

17©2013 Asian Productivity Organization

120

80

3 Growth of Asian Economy

Table 3 GDP Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2011___Average annual growth rate of GDP at constant market prices
1990–1995
China
Malaysia
KuwaitSingapore
Thailand
Vietnam
Korea
Indonesia
ROC
Cambodia
Lao PDR
Oman
MyanmarBahrain
Sri Lanka
India
Hong Kong
Nepal
Pakistan
Bangladesh
Iran
UAE
Brunei
Saudi Arabia  
Fiji
Qatar
Philippines
Japan
Mongolia

1995–2000

11.6
9.2
9.2
8.2
8.2
7.9
7.6
7.6
7.0
6.6
6.2
5.7
5.7
5.3
5.3
5.1
5.1
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
6.0
5.7
5.6
5.1
5.1
5.1
4.9
4.8
4.8
4.2
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)

4.0
5.3
5.2
5.1
5.0
7.2
3.8

(reference)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

2.5
1.6

Australia
Turkey

3.2
3.2

US
EU15
EU27
Australia
Turkey2005–2011
12.1
9.3
9.0
8.1
7.3
7.2
6.8
6.6
6.3
6.2
5.9
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
Turkey1990–2011
15.9
10.3
9.8
7.9
7.8
7.7
6.6
6.6
6.5
6.1
6.1
5.7
5.6
5.2
4.8
4.7
4.5
4.5
4.0
4.0
3.9
3.7
3.5
3.0
2.8
2.0
1.0
0.5
0.2

(regrouped)

3.9
5.4
5.4
5.2
6.2
5.1
4.8

(reference)

4.2
2.8
2.8
3.8
4.1

Qatar
China
MyanmarMongolia
Lao PDR
India
Vietnam
Cambodia
Sri Lanka
Bangladesh
Singapore
Indonesia
Oman
Iran
Bahrain
Philippines
Malaysia
Nepal
Hong Kong
ROC
Pakistan
Korea
Saudi Arabia  
Thailand
UAE
KuwaitBrunei
Fiji
Japan
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC
US
EU15
EU27
Australia
Turkey2000–2011
9.9
9.6
8.9
7.3
7.1
6.6
6.3
6.1
5.7
5.2
5.2
5.1
5.1
5.0
5.0
4.9
4.7
4.5
4.4
4.3
4.2
4.2
4.1
3.9
3.8
3.2
1.8
1.7
0.9

(regrouped)

4.0
6.3
6.2
6.3
7.2
5.1
4.4

(reference)

2.4
1.8
1.9
3.4
4.5

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

12.4
10.9
9.9
7.7
7.2
7.2
7.1
6.9
5.9
5.8
5.5
5.3
5.3
5.2
4.6
4.6
4.5
4.3
4.3
4.1
4.0
4.0
4.0
3.9
3.8
3.6
1.5
1.2
0.6

(regrouped)

3.7
5.3
5.3
5.3
6.0
5.0
4.2

(reference)

0.9
0.8
1.0
2.8
4.0

Qatar
Myanmar
China
Cambodia
India
Mongolia
Lao PDR
Vietnam
IranBangladesh
Singapore
Sri Lanka
BahrainIndonesia
Philippines
Malaysia
Oman
KuwaitPakistanThailandHong Kong
Korea
UAE
Nepal
ROC
Saudi Arabia  
Brunei
Fiji
Japan
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

4.0
5.9
5.8
5.8
6.7
5.1
4.6

(reference)

2.4
1.7
1.8
3.3
3.9

US
EU15
EU27
Australia
Turkey

1.5
1.3
1.4
3.1
4.2

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

©2013 Asian Productivity Organization

Countries’ relative performance is also transformed when economic growth is used as the yardstick.
Table 3 presents cross-country comparisons of real GDP growth in Asia, covering the 1990s and2000s.11 The rankings vary from period to period and are no longer dominated by the economic

10: In interpreting the results in this report, one 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. See Chapter 7.

18

3.1 Economic Scale and Growth

1970–1990
1990–2011
giants. In fact, small developing
Japan
China
34.7
47.1
Asian countries, like Qatar, MyanChina
India
15.5
16.1
15.4
India
Korea
mar, Cambodia, Vietnam, and
9.6
5.9
5.7
Korea
Japan
6.6
4.8
5.1
Mongolia, are equally capable ofIndonesia
Indonesia
5.0
3.8
Saudi Arabia
Iran
4.4
3.6
exhibiting exuberant growth. In
ROC
ROC
3.9
3.1
Iran
Thailand 2.2
contrast, Japan has been consis3.7
Thailand
Saudi
Arabia2.9
1.8
tently struggling at the bottom
UAE
Malaysia 1.7
2.7
Pakistan
Pakistan
2.1
1.5
over the past two decades (1990–
Hong Kong
UAE 1.3
1.92011), with average growth ofPhilippines
Vietnam 1.2
1.7
Malaysia
Singapore 1.2
1.6
0.9% per year, compared with
Singapore
Hong Kong 1.1
1.1
VietnamPhilippines 1.0
0.6
Asia29’s 5.3% and the fastest
Oman
Bangladesh 0.9
0.4
growth of 9.9% achieved by ChiSri Lanka
Qatar 0.6
0.4
Bangladesh
Kuwait 0.5
0.4
na. During this period, only three
Qatar
Myanmar 0.4
0.2
Brunei
Sri Lanka 0.4
0.2
Asian countries – Brunei, Fiji, andBahrainOman 0.3
0.1
Japan – grew slower than the US
Myanmar
Nepal 0.1
0.1
Nepal
Cambodia 0.1
0.1(2.4%), and only Japan grew slowMongolia
Bahrain 0.1
0.1
Fiji
0.0
Lao PDR 0.1
er than EU15 (1.7%). The diverLao PDR
0.0
Brunei 0.0
gence of growth performanceCambodia
0.0
Mongolia 0.0−0.5
KuwaitFiji 0.0
between the Asian countries on−10 0
10 20 30 40 %0
10 20 30 40
50 %the one hand and the US and
EU15 on the other was even more
Figure 7 Country Contributions to Regional GDP Growth,pronounced when looking at
1970–1990 and 1990–2011___Contribution share to the growth of gross regional products (growth
2000–2011 (i.e., Asia29’s 5.8%
compared with the US at 1.5%
rate of Asia29=100)
and EU15 at 1.3%). The change ofSources: Official national accounts in each country, including author adjustments.
guards in Asia is clearly illustrated
in Figure 7. While Japan were thestandard-bearers in yesteryears, China and India have emerged as the driving force propelling Asia
forward over the past two decades (1990–2011) and accounting for 47% and 15% of regional growth,
respectively. Despite being the slowest growing economy in Asia, Japan has remained the fourth largest contributor to regional growth in 1990–2011 due to its size.

3

11: Annual data maximizes the use of available information and data, and are normally published two to three years in arrears. For
more timely analysis, quarterly economic data is used as it is normally published within a month of the reference period and is
subsequently revised as more data become available. There always exists, a trade-off between data timeliness and precision. See
Box 3 (p. 48) for more details.

19©2013 Asian Productivity Organization

Looking at the four sub-periods (in Table 3), growth in the reference countries, namely the US, EU15,
and Australia, revived between 1990–2000, 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 the 2000s (2005–2011), the US managed a growthof only 0.9% whereas EU15 achieved only 0.8%. In contrast, growth in Asia has gone from strength tostrength, with a blip in the second half of the 1990s due to the Asian financial crisis. Fastest acceleration
has been achieved by South Asia, from an annual average growth rate of 5.0% in 1990–1995 to 7.2%
in 2005–2011, compared with 5.1% and 6.3% for East Asia, respectively. In contrast, ASEAN, which wasmost 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 (2005–2011),
being 2.1 percentage points lower than that in the first half of the 1990s.

3 Growth of Asian Economy

US

EU15

TUR

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 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) −0.6 −0.5 −0.3 −0.2 1.0
ROC (ROC)
0.6 0.8 0.5 0.7 −0.7 1.0
Bangladesh (BAN) −0.3 −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
0.3 0.3 0.4 0.3 −0.4 0.5 −0.2 0.1 0.4 −0.2 1.0
Pakistan (PAK)
0.3 0.3 0.0 0.1 −0.1 0.1 0.2−0.3 −0.3 0.2−0.6 1.0
Sri Lanka (SRI)
0.3 0.4 0.4 0.6 −0.2 0.6 −0.3 0.2 0.3 0.0 0.9 −0.5 1.0
Brunei (BRN)
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 0.1−0.2 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 −0.3−0.8 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)
0.2 −0.5 −0.7 −0.5 0.5 −0.5 0.4 0.7 −0.4 0.0−0.3 0.0 −0.4 −0.3 0.5 −0.4 0.4 −0.4 0.2 0.2 −0.2 −0.4 0.3 0.0 0.6 −0.2 0.4 −0.7 0.0 1.0
Australia (AUS)
0.1 0.1 0.2 −0.2 −0.2 −0.3 0.5−0.1 0.3 0.2−0.1 0.3 −0.2 −0.7−0.4 0.1 −0.2 0.1 0.0 0.2 0.1 −0.1 0.4 0.6 0.3 0.5 0.3 0.1 0.0 0.1 1.0
Turkey (TUR)−0.7 −0.2 0.0 0.0 0.7 −0.4 0.4 0.1 −0.2 −0.5−0.1 −0.1 0.0 0.5−0.2 −0.3 0.0 −0.3 0.3 0.2 −0.3 −0.5−0.3 −0.7 −0.4 −0.4 0.4 0.1 0.7 −0.1 −0.3 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 0.7−0.1 0.4 1.0
US
If greater than 0.55

If less than −0.55

Figure 8 Correlation of GDP Growth, 1990–1999___Correlation of GDP growth at constant prices

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

©2013 Asian Productivity Organization

Based on Table 3, it is easy to assume that Asia has not been even slightly affected by the global financial crisis, as Asia29’s growth rate accelerated from 5.4% to 6.2% between 2000–2005 and 2005–2011.
But, in fact, Asia29’s growth slowed significantly from a recent peak of 8.0% in 2007, to 4.5% in 2008 andfurther to 3.6% in 2009, before rebounding strongly to 7.9% in 2010. Growth moderated again in 2011
to 5.6%, partly reflecting the retreating impact of the crisis response in the form of fiscal stimulation.
Out of the 29 countries, eight Asian economies experienced negative growth in 2009, among which
Japan went through the deepest contraction of 5.7%. Of the four Asian Tigers, only Korea managed anarrow escape from recession with 0.3% growth in 2009.
It has been a subject of much debate as to whether the Asian economy has decoupled from the US
and EU15. If it has, the world economy will be substantially less volatile. Park and Shin (2009) showthat East Asia has seen a marked increase in intra-regional trade, and, at the same time, diversified its
export markets to other parts of the world resulting in an output movement that is more idiosyncratic than before, and in turn, less dependent on the US. Such increased self-subsistence is a necessary adaptation; in recent years the US has become less and less reliable as an outlet of China’s final
goods export. 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 conduit20

3.1 Economic Scale and Growth

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

1.0
0.8 1.0
0.6 0.8 1.0
0.8 0.7 0.4
0.8 0.9 0.8
0.5 0.2 −0.2
0.5 0.3 −0.1
0.4 0.5 0.6
0.1 −0.1 −0.1
0.7 0.3 0.2
0.7 0.5 0.3
0.3 0.6 0.7
0.7 0.6 0.4
0.2 0.2 0.3
0.6 0.5 0.3
0.4 0.1 0.0
0.9 0.9 0.7
0.4 0.2 0.1
0.9 0.9 0.7
0.9 0.8 0.7
0.7 0.9 0.8
0.8 0.6 0.5
0.6 0.4 0.2
0.4 0.4 0.1
0.0 −0.1 −0.2
0.5 0.3 0.3
0.6 0.5 0.0
0.5 0.4 0.1
0.3 0.5 0.4
0.9 0.8 0.7
0.8 0.9 0.7
0.9 0.9 0.8

US

EU15

TUR

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
0.5 1.0
0.5 0.2 1.0
0.3 0.4 0.6 1.0
0.2 0.5 −0.3 0.3 1.0
0.3 0.2 0.3 0.4 0.0 1.0
0.5 0.4 0.5 0.8 0.5 0.2 1.0
0.6 0.8 0.5 0.5 0.2 0.6 0.5 1.0
0.1 0.4 −0.3 0.0 0.7 −0.4 0.1 0.0 1.0
0.8 0.3 0.3 0.3 0.3 −0.1 0.6 0.2 0.3 1.0
0.3 0.0 −0.2−0.4 0.2 −0.3 0.1−0.2 0.3 0.2 1.0
0.6 0.6 0.6 0.4 −0.1 0.6 0.3 0.9−0.2 0.2−0.4 1.0
0.3 0.4 0.8 0.5 −0.3 0.4 0.2 0.7−0.2 −0.1−0.3 0.7 1.0
0.8 0.9 0.2 0.2 0.4 0.3 0.4 0.8 0.4 0.6 0.2 0.7 0.3
0.4 0.1 0.0 0.4 0.6 0.1 0.8 0.1 0.3 0.7 0.4−0.2−0.3
0.7 0.9 0.4 0.4 0.4 0.2 0.4 0.7 0.3 0.4 0.1 0.7 0.4
0.5 1.0 0.4 0.5 0.4 0.2 0.5 0.8 0.4 0.3 0.0 0.7 0.5
0.6 0.8 −0.1 0.2 0.7 0.0 0.3 0.4 0.7 0.5 0.3 0.3−0.1
0.7 0.4 0.4 0.5 0.6 0.1 0.8 0.3 0.4 0.9 0.2 0.3 0.1
0.8 0.2 0.4 0.4 0.3 0.4 0.7 0.4 0.1 0.9 0.0 0.4 0.1
0.6 0.2 0.0 0.2 0.3 0.1 0.5 0.3 0.3 0.7 0.3 0.1−0.2
0.3 −0.2 0.5−0.3 −0.8 0.0−0.4 0.1−0.5 0.0−0.2 0.5 0.5
0.5 0.5 0.8 0.3 −0.1 0.3 0.2 0.7 0.0 0.0 0.1 0.7 0.9
0.6 0.4 0.3 0.4 0.1 0.2 0.5 0.6 0.0 0.5 0.0 0.4 0.1
0.7 0.2 0.3 0.3 0.4 0.1 0.6 0.3 0.3 0.7 0.5 0.0 0.0
0.2 0.2 −0.1 0.3 0.7 −0.2 0.3−0.1 0.7 0.5 0.2−0.2−0.3
0.7 0.9 0.2 0.4 0.5 0.3 0.6 0.8 0.4 0.5 0.2 0.6 0.2
0.8 0.6 0.2 0.2 0.5 −0.2 0.4 0.2 0.6 0.8 0.3 0.3 0.0
0.7 0.8 0.1 0.3 0.6 −0.1 0.5 0.4 0.6 0.8 0.3 0.3 0.0
If greater than 0.55

1.0
0.3 1.0
0.9 0.1 1.0
0.8 0.1 0.9 1.0
0.8 0.3 0.8 0.8 1.0
0.6 0.8 0.5 0.4 0.5 1.0
0.6 0.7 0.4 0.3 0.3 0.9 1.0
0.5 0.8 0.3 0.2 0.5 0.6 0.7 1.0
0.0−0.6 0.0 −0.1 −0.4−0.1 0.0 −0.3 1.0
0.4−0.2 0.5 0.6 0.1 0.2 0.1 −0.2 0.5 1.0
0.6 0.5 0.6 0.4 0.5 0.4 0.6 0.8 −0.1 0.1 1.0
0.5 0.8 0.3 0.2 0.4 0.7 0.7 0.8 −0.2 0.2 0.6 1.0
0.2 0.6 0.3 0.2 0.6 0.6 0.4 0.4 −0.5 −0.2 0.2 0.5 1.0
0.9 0.4 0.8 0.9 0.8 0.6 0.5 0.5 −0.2 0.4 0.6 0.5 0.2 1.0
0.7 0.4 0.7 0.6 0.8 0.8 0.6 0.5 0.0 0.2 0.3 0.5 0.6 0.6 1.0
0.8 0.5 0.8 0.7 0.9 0.8 0.5 0.6 −0.3 0.2 0.6 0.6 0.6 0.8 0.9 1.0

If less than −0.55

Figure 9 Correlation of GDP Growth, 2000–2011___Correlation of GDP growth at constant prices

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

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 0.4, and China’s correlation with the US
and EU15 has moved from being negative to moderately positive. Correlation among the East Asian
countries has 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, the ties of Vietnam and the Philippines to East Asia
have become much closer. Therefore, our comparisons of the correlation coefficients of growth between the two periods lend support to an increase, not a decrease, in business cycle synchronicity.

21©2013 Asian Productivity Organization

for financial contagion, and East Asia still suffers from the flight for quality when a crisis strikes. As theimpact of the global financial crisis was filtering through, Asia seemed immune to the adverse impacts
initially. However, once global investors began to retreat from the region and the financial menace
began to inexorably spread through the real economy, Asia too started to slow.

3 Growth of Asian Economy

Box 1

National Accounts in Asian Countries

Understanding data comparability is essential for the construction of an international database, andrequires significant effort and expert knowledge. Between September and December 2012, metadata surveys on the national accounts and other statistical data required for international comparisons of productivity were conducted 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. Countries can also vary in their estimation methodology and assumptions, which may account for part of the differences observable in thedata and which can 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, the 1993 SNA is used as the standard, noting 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 is important to know in which year in thedata 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 the 2008 SNA. For example, Japan

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
Vietnam1972 1973
68
93
1979
2000
1993
68
93 N.A.(Some definitions of 1993 SNA are introduced. The main framework is still based on 1968 SNA.)
1951
1988
68
1951
2005
93
2012
08
1968
1974
68
1995
2003
93
2005 2008
08
1950
1978
68
1999
2007
93
2004
2010
08
1960
1970
68
93 N.A.(Some definitions of 1993 SNA are introduced. It will be fully implemented in 2013.)
2013
08
1959
1981
68
1991 1993
93
2013
08
1955
1978
68
1980
2000
93
2015
08
1970
1986
68
1970
2004
93
2014
08
1990
68
1997
2002
93
2015
08
1960
1975
68
2000
2007
(mixture of 1953 SNA until 1968)
93
2012
08
68 N.A.(Before 1993 SNA is introduced, Material Product System was used.)
1980
1995
93
2014
08
1974 1975
68
2000
2006
93
2015
08
1981
1988
68
2000
2004
93
2012
08
1985
68 1946
1998
2011
93
1998
2011
08
1975
68
1998 2001
93
1972 1975
68
1990
2012
93
1989
68
1986
1993
93
2015
08

©2013 Asian Productivity Organization

Introduction year

Backward estimates and implementation

Plan making backward estimates

Figure B1 Implementation of the 1968 and 1993 SNA and Plan for the 2008 SNA
Source: APO Metadata Survey 2012.
continued on next page >22

3.2 Catching Up in Per Capita GDP> continued from previous page

started to publish national accounts based on the 1993 SNA in 2000 (backward estimates based on the1993 SNA are available from 1980 at present) and will introduce the 2008 SNA progressively and switch it
in 2015–2016.
As Figure B1 suggests, countries differ in their year of introduction, the extent of implementation, andbackward estimates available. According to the survey response, most APO countries are currently 1993
SNA compliant (partly or fully), although for some countries the switchover was a relatively recent affair;and for Indonesia, the 1993 SNA an ambition for the near future. The starting year of the official 1993 SNAcompliant time series therefore varies a great deal across countries, reflecting the differences in the availability of backward estimates. Countries may have adopted the 1993 SNA as the framework for theirnational accounts, but the extent of compliance in terms of coverage may vary. The APO Productivity
Database tries to reconcile the national accounts variations and provide harmonized estimates for international comparison. See Appendix 1 for details of the adjustments.

3

3.2 Catching Up in Per Capita GDP
Performance comparisons based on whole-economy GDP do not take into account the population
size and can in turn exaggerate the wellbeing of countries with large populations. Asia is the world’s
most populous region. In 2011, it accounted for 61% of the world’s population (56% for Asia29), with
China and India alone accounting for more than one-third (Figure 10). Based on per capita GDP, which
adjusts for the differences in population size (but not income distribution), Asia’s rising economic giants (i.e., China and India) are still substantially less well-off compared than the US standard, whereas
the Asian Tigers fare exceptionally well.
Table 4 presents cross-country comparisons of per capita current-price GDP, using exchange rates asconversion 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
Kong have been moving closely with one another for three and a half decades until the mid-2000s,
when Singapore sprinted deftly ahead of Hong Kong. Hong Kong’s per capita GDP peaked in 1997, theyear when Hong Kong was returned to China, and plummeted in 2004 before picking up again. Singapore’s followed a similar path: peaking in 1996, and falling to an all time low in 2002 before the surgeof recent years. The ROC and Korea moved roughly together but at a lower level than Singapore and Hong2011
Kong. Korea’s income level similarly peaked in 1996 but
its doldrums were shorter lived than Hong Kong or Singapore’s. In Asia, Japan and Singapore are the two
Otherscountries that have income levels almost equivalent to
Asia
APO20
28 %
61 %
35 %
that of the US. However, this view is considerably revised if focusing on production or real income per capAsia29
EU15
56 %
EU27
ita (i.e., using PPPs as the conversion rates) (Table 5).
6%USIn terms of per capita GDP at constant prices using
PPPs, Japan was the first country in Asia to start catching up with the US (Figure 13). By 1970, its per capita
GDP was 62% that of the US, quite a distance ahead ofother Asian countries. It had been steadily closing the
gap with the US until 1991 (86%), but the gap widened

5 % Other Asia
4%

Figure 10 Share of Asian Population in
the World in 2011
Source: IMF, World Economic Outlook Database, April
2013

23

©2013 Asian Productivity Organization

7%

3 Growth of Asian Economy

Table 4 Cross-Country Comparison of Per Capita GDP using Exchange Rate, 1970, 1980, 1990,
2000, 2010, and 2011___GDP at current market prices per person, using annual average exchange rate
1970

1980

(%)

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

1.99 100.0
0.96 48.3
0.93 46.4
0.43 21.4
0.39 19.8
0.39 19.5
0.36 17.9
0.28 13.9
0.21 10.6
0.21 10.5
0.20 10.1
0.20 10.0
0.13 6.7
0.12 5.8
0.11 5.6
0.11 5.5
0.10 5.0
0.09 4.7
0.09 4.4
0.09 4.3
0.03 1.4

Japan
Hong Kong
Singapore
Iran
ROC
Fiji
Malaysia
Korea
Philippines
ThailandIndonesia
Pakistan
China
Sri Lanka
Mongolia
India
Bangladesh
Myanmar
Nepal
Cambodia
VietnamBahrain
KuwaitOman
Qatar
Saudi Arabia  
UAE
Brunei1.88 94.4
3.95 198.5
0.40 20.0
4.99 250.7
0.88 44.3
4.27 214.4
1.49 74.9

Bahrain
10.37
Kuwait
21.60
Oman
5.78
Qatar
35.57
Saudi Arabia   15.12
UAE
42.13
Brunei
28.25

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

111.7
232.7
62.2
383.2
162.9
453.9
304.4

(regrouped)(regrouped)

0.31
0.23
0.23
0.32
0.12
0.13
1.33

15.8
11.4
11.6
16.2
6.2
6.3
66.7

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

1.22 13.2
0.84 9.1
0.93 10.1
1.31 14.1
0.27 2.9
0.56 6.0
17.27 186.1(reference)(reference)

1990

(%)

9.28 100.0
5.69 61.3
4.99 53.8
2.50 26.9
2.36 25.5
1.92 20.7
1.78 19.1
1.69 18.2
0.74 8.0
0.74 8.0
0.54 5.8
0.35 3.8
0.31 3.3
0.30 3.2
0.27 2.9
0.26 2.9
0.22 2.4
0.18 1.9
0.18 1.9
0.12 1.3
0.02 0.2

Japan
Hong Kong
Singapore
ROC
Korea
MalaysiaFiji
IranThailandPhilippines
Indonesia
Mongolia
Sri Lanka
Pakistan
India
China
Bangladesh
Nepal
Lao PDR
Cambodia
MyanmarVietnam2000(%)

25.10 100.0
13.48 53.7
12.75 50.8
8.08 32.2
6.31 25.1
2.49 9.9
1.85 7.4
1.72 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
0.39 1.5
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
MyanmarBahrain9.27 36.9
Kuwait8.96 35.7
Oman
7.16 28.5
Qatar
17.66 70.3
Saudi Arabia   7.44 29.7
UAE
28.86 115.0
Brunei12.92 51.5

Bahrain
13.17
Kuwait
17.94
Oman
8.18
Qatar
29.20
Saudi Arabia   9.69
UAE
35.20
Brunei17.75(regrouped)(regrouped)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

2.58
1.67
1.73
2.99
0.38
0.84
9.48

10.3
6.7
6.9
11.9
1.5
3.3
37.8

(reference)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

35.3
48.0
21.9
78.2
25.9
94.2
47.5

3.45
2.46
2.55
4.73
0.46
1.19
13.32

9.2
6.6
6.8
12.7
1.2
3.2
35.7

35.27
25.24
21.91
21.26
3.94

94.4
67.6
58.7
56.9
10.5

(reference)

US
EU15

5.06 254.2
3.49 175.3

US
EU15

12.27 132.2
8.96 96.6

US
EU15

23.24
16.83

92.6
67.1

Australia
Turkey3.56 178.7
0.69 34.7

Australia
Turkey11.78 126.9
2.03 21.8

Australia
Turkey

18.92
3.54

75.4
14.1

US
EU15
EU27
Australia
Turkey2010(%)

37.35 100.0
25.38 67.9
23.41 62.7
14.64 39.2
11.35 30.4
4.00 10.7
2.10 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
0.47 1.3
0.46 1.2
0.41 1.1
0.37 1.0
0.32 0.8
0.31 0.8
0.28 0.7
0.15 0.4

SingaporeJapan
Hong Kong
Korea
ROC
Malaysia
Iran
ThailandChina
Fiji
Indonesia
Sri Lanka
Mongolia
Philippines
India
VietnamLao PDR
Pakistan
Cambodia
Nepal
MyanmarBangladesh

2011

(%)

45.64 100.0
43.01 94.2
31.91 69.9
20.54 45.0
18.49 40.5
8.34 18.3
6.28 13.8
5.13 11.2
4.42 9.7
3.74 8.2
3.03 6.6
2.41 5.3
2.25 4.9
2.16 4.7
1.40 3.1
1.24 2.7
1.10 2.4
1.01 2.2
0.83 1.8
0.73 1.6
0.71 1.6
0.68 1.5

SingaporeJapan
Hong Kong
Korea
ROC
Malaysia
Iran
ThailandChina
Fiji
Indonesia
Mongolia
Sri Lanka
Philippines
India
VietnamLao PDR
Pakistan
Cambodia
Myanmar
Nepal
Bangladesh(%)

51.24 100.0
46.25 90.3
34.46 67.2
22.39 43.7
19.98 39.0
9.60 18.7
8.74 17.1
5.50 10.7
5.43 10.6
4.47 8.7
3.57 7.0
3.13 6.1
2.85 5.6
2.39 4.7
1.53 3.0
1.42 2.8
1.31 2.5
1.19 2.3
0.94 1.8
0.92 1.8
0.81 1.6
0.72 1.4

Bahrain20.83 45.6
Kuwait41.22 90.3
Oman
21.45 47.0
Qatar
75.84 166.2
Saudi Arabia   19.76 43.3
UAE
35.09 76.9
Brunei35.60 78.0

Bahrain24.26 47.3
Kuwait53.51 104.4
Oman
22.27 43.5
Qatar
96.96 189.2
Saudi Arabia   24.54 47.9
UAE
39.80 77.7
Brunei43.46 84.8

(regrouped)(regrouped)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

4.86
4.64
4.89
8.45
1.29
3.20
26.34

10.6
10.2
10.7
18.5
2.8
7.0
57.7

(reference)

US
EU15
EU27
Australia
TurkeyAPO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

5.30
5.28
5.60
9.67
1.42
3.66
32.00

10.3
10.3
10.9
18.9
2.8
7.1
62.5

(reference)

46.87 102.7
34.99 76.7
31.81 69.7
57.74 126.5
9.95 21.8

US
EU15
EU27
Australia
Turkey48.38 94.4
35.86 70.0
32.77 64.0
67.42 131.6
10.41 20.3

©2013 Asian Productivity Organization

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

again when the impact of the long recession of the 1990s started to manifest itself.12 In recent years,
Japan’s level has stabilized to around 70–73% that of the US.
Japan’s per capita GDP was the highest among Asian countries until it was overtaken by Singapore13
in 1993. The result highlights the outcome of the dramatic development effort made by the four AsianTigers, as shown in Figure 14. Not only were they inching up to the top, they were constantly closing
the gap with the US. Starting from a level of 36% that of the US in 1970, Singapore surpassed the US243.2 Catching Up in Per Capita GDP

US=100 in each year

US=100 in each year

160

120

140

100

120
100

Japan
US

US
Singapore

80
60

3

Hong Kong

80
40

60

Austraria

ROC

Korea

40

20

20
1970 1975 1980 1985 1990 1995 2000 2005 201001970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 11 Cross-Country Comparison of Per
Capita GDP using Exchange Rate of Japanand Australia Relative to the US, 1970–2011___GDP at current market prices per person, using

Figure 12 Cross-Country Comparison of Per
Capita GDP using Exchange Rate of AsianTigers Relative to the US, 1970–2011

annual average exchange rates, relative to the US___GDP at current market prices per person, using
annual average exchange rates, relative to the US

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

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

US=100 in each year

100
90

Austraria

120
100

Singapore

US

80

80

Hong Kong
EU15

70
60

US=100 in each year

60
40

Japan

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, 1970–2011___Ratio of per capita GDP at constant market prices,

20

ROC
Korea

0
1970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 14 Per Capita GDP of Asian Tigers
Relative to the US, 1970–2011

using 2005 PPP, relative to the US___Ratio of per capita GDP at constant market prices,using 2005 PPP, relative to the US

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

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

12: 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, by 1990, the US–Japan TFP gap for the manufacturing sector had almost
disappeared.
13: 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% in 2000, the share of permanent
residents who are not Singaporean citizens was 7%, and the share of non-permanent residents was 19%.

25

©2013 Asian Productivity Organizationin 2004.14 In 2011, Singapore had a per capita GDP which was 26% above that of the US, and it became
the richest economy in Asia. This represents a remarkable achievement. Hong Kong occupies the second place, with a per capita GDP similar to that of the US. Japan’s per capita GDP, at 72% of the US or
around 60% of the group leader (Singapore), is similar to that of EU15. The ROC and Korea trail behindthe other two Asian Tigers at 78% and 65% of the US, respectively.

3 Growth of Asian Economy

US=100 in each year

Qatar

18

42.0

Japan
15
12
9
ASEAN
6
3

India
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, 1970–2011___Ratio of per capita GDP at constant market prices,

2.4
14.4

UAE

27.7

Brunei

25.3

Kuwait

23.8

24.9
20.6

Bahrain

20.6

6.2

Oman

16.4

12.4

Saudi Arabia

13.4

Malaysia

47.2

32.0

Non-mining
GDP

9.7

12.2 2.4
Thousands of US dollars (as of 2010)

Iran 11.1 3.0
0

20

40

60

80

100

Figure 16 Per Capita Non-Mining GDP in Oil-Rich
Countries, 2010

using 2005 PPP, relative to the US___GDP at constant market prices per person, using
2005 PPP, reference year 2010

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

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

The relative performance of China and India, the two most populous countries in the world, is diminished in this measure due to their population size, with their per capita GDP at 17.3% and 7.5% that of
the US in 2011, respectively (Figure 15). Even so, this should not taint the remarkable progress madeover the past decades, especially that of China, whose per capita GDP was less than 2% that of the US
in 1970; China’s relative per capita GDP has increased sevenfold in four decades. The income gap between the US and the majority of Asian countries is still sizable,15 indicating that there is still a lot ofroom to catch up.
Table 5 presents separately the figures for seven oil-rich economies (Brunei and the six GCC countries).
At first glance, figures in 1970 and to a lesser extent in 1990 suggest that these economies enjoyed anincome many times that of Japan and the US. For example, Kuwait, Qatar, and Brunei had a per capita
GDP 7.5 times, 7.4 times, and 3.9 times that of Japan, respectively, in 1970. However, the measurementof GDP as an indicator of income is misleading for these countries, as it erroneously includes proceedsfrom the liquidation of a natural resource stock as part of the income flow. In other words, GDP overestimates income from the oil-exporting economies, as it does not account for depletion of theirnatural resource assets. To give a rough indication of the extent of distortion, Figure 16 provides comparisons of per capita GDP excluding production of the mining sector (i.e., crude oil, natural gas, andso on). The non-mining 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.

©2013 Asian Productivity Organization

Catching up with the per capita GDP level of 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

14: 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% of GDP. As the US GNI never goes outside +1.7% 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 26% over the US in 2011 was large enough that theirrelative positions would be independent of whether GNI or GDP was used.
15: 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%. The Philippines is the exception where thedivergence 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 (max in 2010, 32.3 in 2011)% in 2010. Fiji had a GNI 10–16% above GDP in the early 2000s, but since then, GNI
has converged back to the GDP level.

263.2 Catching Up in Per Capita GDP

Table 5 Per Capita GDP, 1970, 1980, 1990, 2000, 2010, and 2011___GDP at constant market prices per person, using 2005 PPP, reference year 2010
1970
Japan
Hong Kong
Singapore
Iran
ROC
Malaysia
Fiji
Korea
Philippines
ThailandMongolia
Sri Lanka
Pakistan
India
Indonesia
Bangladesh
Vietnam
China
MyanmarBahrain23.3
Kuwait
107.9
Oman
7.5
Qatar
106.4
Saudi Arabia   24.2
UAE
29.2
Brunei
55.6

162.1
752.1
52.5
742.0
168.7
203.9
387.9

Japan
Singapore
Hong Kong
ROC
Iran
Korea
Malaysia
Fiji
Philippines
ThailandMongolia
Sri Lanka
Indonesia
Pakistan
India
Nepal
Bangladesh
Vietnam
China
MyanmarBahrain
29.8
Kuwait
47.4
Oman
13.1
Qatar
90.2
Saudi Arabia   37.6
UAE
133.9
Brunei94.1

2.5 17.5
1.6 11.1
1.7 12.0
2.0 14.1
0.9 6.3
1.2 8.5
32.1 223.8

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

150.5
239.6
66.0
456.1
190.3
676.8
475.8

2000

(%)

2010

(%)

2011

(%)

(%)

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
7.3 24.7
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 4.6
1.2 4.1
1.0 3.5
1.0 3.4
0.9 3.2
0.8 2.7
0.8 2.6
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 4.5
1.8 4.2
1.5 3.6
1.2 2.9
1.2 2.8
1.1 2.7
0.6 1.4

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

58.1 100.0
46.6 80.3
35.6 61.3
34.3 59.2
29.7 51.2
14.6 25.2
14.1 24.3
9.6 16.5
7.6 13.0
5.1 8.8
4.7 8.1
4.4 7.6
4.0 6.9
4.0 6.9
3.4 5.9
3.2 5.6
2.7 4.6
2.6 4.4
2.3 3.9
1.7 2.9
1.6 2.7
1.6 2.7

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

59.8 100.0
48.6 81.3
37.0 61.8
34.2 57.2
30.6 51.1
15.1 25.3
14.6 24.4
9.6 16.0
8.2 13.7
5.5 9.2
4.8 8.0
4.7 7.8
4.6 7.8
4.1 6.8
3.5 5.9
3.4 5.7
2.7 4.5
2.7 4.5
2.4 4.0
1.8 3.0
1.6 2.7
1.6 2.7

Bahrain
KuwaitOman
Qatar
Saudi Arabia  
UAE
Brunei23.7 80.4
23.3 79.0
19.4 65.8
55.0 186.7
21.5 73.0
80.7 273.7
53.3 180.9

Bahrain
KuwaitOman
Qatar
Saudi Arabia  
UAE
Brunei29.4 69.5
40.8 96.6
20.5 48.5
72.0 170.4
22.7 53.7
78.3 185.5
51.8 122.6

Bahrain
KuwaitOman
Qatar
Saudi Arabia  
UAE
Brunei26.8 46.1
44.5 76.6
28.9 49.7
89.2 153.6
23.1 39.8
42.1 72.6
50.2 86.5

Bahrain
KuwaitOman
Qatar
Saudi Arabia  
UAE
Brunei28.2 47.1
45.8 76.7
24.4 40.8
95.2 159.3
24.2 40.4
41.9 70.0
50.6 84.6(regrouped)

3.2 16.2
2.1 10.7
2.4 11.9
2.8 14.4
1.0 4.9
1.9 9.7
44.6 225.3(reference)(reference)

1990

(%)

19.8 100.0
16.8 84.8
15.5 78.2
8.3 41.8
7.7 38.9
5.4 27.2
5.2 26.4
3.6 18.1
3.1 15.5
2.7 13.8
1.9 9.8
1.7 8.7
1.5 7.7
1.3 6.8
0.9 4.8
0.7 3.8
0.7 3.7
0.7 3.6
0.6 2.9
0.4 2.0(regrouped)(regrouped)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

1980

(%)

14.3 100.0
8.3 58.2
8.2 57.3
7.6 52.8
4.0 27.6
3.0 20.9
2.7 19.1
2.7 18.8
2.3 15.8
1.9 12.9
1.4 9.9
1.2 8.6
1.1 8.0
0.9 6.3
0.9 6.0
0.8 5.5
0.7 4.8
0.4 2.6
0.3 2.3

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

(regrouped)

4.4
3.1
3.3
4.5
1.4
2.7
26.9

14.9
10.5
11.1
15.2
4.6
9.1
91.1

(reference)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

(regrouped)

5.2
4.3
4.5
6.5
1.9
3.7
30.8

12.4
10.2
10.7
15.4
4.4
8.8
73.0

(reference)

US
EU15

23.1 161.0
16.1 112.2

US
EU15

28.5 144.0
21.0 106.3

US
EU15

35.7 121.1
26.1 88.5

Australia
Turkey20.6 143.6
5.5 38.3

Australia
Turkey23.7 119.9
6.5 32.9

Australia
Turkey

27.5
8.6

93.3
29.1

US
EU15
EU27
Australia
TurkeyAPO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

(regrouped)

6.8
7.0
7.3
11.1
3.2
5.4
31.1

11.7
12.0
12.5
19.0
5.5
9.2
53.5

46.9
34.0
30.6
40.8
13.8

80.7
58.6
52.8
70.3
23.8

(reference)

44.1 104.4
31.6 74.9
27.7 65.5
34.8 82.3
10.3 24.3

US
EU15
EU27
Australia
Turkey3

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

6.9
7.3
7.6
11.7
3.3
5.6
31.9

11.5
12.2
12.7
19.5
5.5
9.3
53.3

47.4
34.4
31.0
41.7
14.8

79.2
57.5
51.9
69.8
24.7

(reference)

US
EU15
EU27
Australia
Turkeyexceptions. With the possibility of adopting successful practices and technologies from the more advanced economies, less advanced economies are poised to experience faster growth in per capita
GDP, enabling them to catch up to average income level. However, as income levels approach thoseof the more advanced countries, their economic growth rates are expected to gradually decline
over time.16
16: The OECD (2012) observes that GDP per capita has broadly converged in the OECD countries since the 1970s. However, moreadvanced economies that started with high income levels in the 1970s have had lower rates of catch-up, stagnated or recently
diverged vis-à-vis the US.

27©2013 Asian Productivity Organization

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

3 Growth of Asian Economy% Growth rate of per capita GDP during 1970–20115% Growth rate of per capita GDP during 1970–2011=1970,=1990,

8=2011=1970,

China=1990, =20117
4

Indonesia

MyanmarVietnam

6

India

ROC

Mongolia

Lao PDR

Bangladesh

Nepal

Singapore5

3 Cambodia

2

Korea

Sri Lanka

Hong Kong

Thailand
Malaysia

4

Pakistan
3
Philippines

Turkey

Fiji

Japan
EU15

2

1
1

US

Australia

Iran

Thousands of US dollars (as of 2010)

Thousands of US dollars (as of 2010)

0

0
0

1

2

3

4

5

6

Per capita GDP at constant prices

0

10

20

30

40

50

60

70

Per capita GDP at constant prices

Figure 17 Initial Level and Growth of Per Capita GDP, 1970–2011___Level and average annual growth rate of GDP at constant market prices, using 2005 PPP, reference year 2010©2013 Asian Productivity Organization

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

Figure 17 plots countries’ initial
Table 6 Country Groups Based on the Initial Economic
Level and the Pace of Catching Up
per capita GDP levels against their___Level and average annual growth rate of GDP at constant market
respective average growth rates
prices, using 2005 PPP
per year between 1970 (or the iniAnnual rate of catch-up to the US
tial year data first became availInitial GDP
level
(C2)
(C3)
(C4)
(C1)
able for the country in question)
to the US
1%<–<3%0%<–<1%<0%>3%
and 2011. If the two variables
Brunei, Bahrain,
have a correlation coefficient of
Kuwait, Qatar,(L1)
Japan, EU15
Saudi Arabia, UAE,
60%<
−0.5 (i.e., a negative relationship
Australia
of medium strength), the higher
Hong Kong,(L2)
SingaporeIran, Turkey
the initial income level, the slower
Oman
20%<–<60%
the average growth rate appears
Malaysia, Mongolia(L3)Fiji, Philippines
ROC, Korea
Sri Lanka, Thailand
5%<–<20%
per year. However, this is not always true. Low-income countries
India, Indonesia,
Bangladesh, Nepal,(L4)
Cambodia, China Lao PDR, Myanmar,
Pakistan<5%
like Nepal, Bangladesh, the PhilipVietnam
pines, and Fiji have failed to catch
Sources: Official national accounts in each country, including author adjustments.
up, while Thailand and Malaysia
Note: The annual catch-up rates are based on the difference in the growths of per
could be expected to have grown
capita GDP at constant prices between each country and the US during 1970–2011.
The starting years for some countries are different due to data availability: Camboeven faster given their initial india (1987–), the Lao PDR (1984–), and Nepal (1974–).
come levels. The Asian Tigers haveenjoyed robust 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. Relative to the Asian Tigers, China appears to be at thestart of the catch-up process. Mature economies like the US, EU15, and Japan shared similar growthexperiences (i.e., around 2% on average per year, in the past four decades).
Table 6 summarizes Figure 17 by country groups. Four levels of per capita income groups are defined:
Group-L1, with per capita GDP at or above 60% of the US; Group-L2, from 20% to under 60%; Group-L3,

28

3.3 Sources of Per Capita GDP Gap

from 5% to under 20%; and Group-L4, below 5%. Likewise, countries are also grouped according to
the speed of their catch-up with the US: Group-C1, at 3% per annum or above; Group-C2, from 1% tounder 3%; Group-C3, from 0% to under 1%; and Group-C4, under 0%. The speed of catch-up with the
US is defined as the difference in the average annual growth rate of per capita real GDP between eachcountry and the US. Table 6 shows that many Asian countries (not belonging to Group-C4) have succeeded in closing the gap in per capita real GDP against the US over the last four decades.

3

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

From Table 6 one can see that the initial economic level does not fully explain the catch-up process; if
it does, the table would have been populated diagonally from bottom left corner to top right corner.
Of the Asia29 countries, five achieved a very fast catch-up (i.e., over 3% a year on average) between
the respective starting years of their data series and 2011. 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 with low-income countries like Fiji and the Philippines
failing 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 (a distortion, as aforementioned) at the beginning of
the period. Japan was the only
1995
Asian non-oil-exporting country with a high-income level in1970. But, like EU15, it has since%
20
failed to achieve further parity
4 3
4
7
6
0
−11
−12 −11
with the US.
−24 −6 −11
−9
−33
−20
−40

−98

−7
−38−21 −17

−60
−80
−100

−2 −13 −2 −6 −1 −1 −11−10

−22

−13

−19

−10 −7 −5 −4 −4−13 −12

2011

%

20
0

9

1

2

9 10 9

1

7

−20
−40
−60

6

8

7 29

−20 −4 −3−24−20
−34
−38
−43
−2
−47
−3
−62

−77
−80 −86−80 −84−84−90−86−86−81−89−79−89−92−90−84−100−97−96 −104−96−26−22

−6

−80
−100

3

−1 −7

−14 −7−7 −5 −9 −1 −11

Employment rate

−11

−6

Labor productivity

Per capita GDP

Figure 18 Labor Productivity and Employment Rate Gap
Relative to the US, 1995 and 2011___Decomposition of per capita GDP gap at constant market prices, using
2005 PPP

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

17: 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, 2012). In Section 5.2, labor productivity measures are provided based on hours worked for some selected countries. Also, in the computation of TFP in Section 5.3,
hours worked data are used.

29©2013 Asian Productivity Organization

To understand the diverse performance in the Asian groupfurther, 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 ofworkers to population ratio, or
employment rate used in thisreport).17 Figure 18 shows thepercentage point differences inper capita GDP decomposed
into the contributions by the labor productivity gap and theemployment rate gap relative to
the US in 1995 and 2011.18 Most

−95−91−95−95

−97

−14
−41
−48
−55−56−13−75−82−74−82−84 −85−86 −85−76−90 −85−73−85−86

Nepal
MyanmarBangladesh
Cambodia
Lao PDR
PakistanSouth Asia
Vietnam
India
Philippines
Mongolia
Indonesia
Fiji
Sri Lanka
ASEAN
APO20
Asia23
Asia29China
ThailandEast Asia
Iran
TurkeyMalaysia
Korea
Japan
EU15
ROC
Australia
Hong Kong
Singapore

3.3 Sources of Per Capita
GDP Gap−85

3 Growth of Asian Economy

%

8

0.2

4

1995–2000
0.1

6

0.5
1.5

7.1
5.9

2

4.7

0.6 0.1
2.4

4.1 4.3
3.4 3.9

0.6

0.2

0.7

3.4 3.0

3.9

1.7

0

−0.1

0.3 0.3

0.8
3.1

3.7

2.6 2.6

2.3

0.6
1.2 0.9 1.7 3.4
2.0 1.4 1.7

−0.7

−0.4

2.5 1.3
0.9

0.7
−0.3
−1.1

0.5
1.4 2.2
0.3−0.6

1.0

1.9

0.1 0.4 0.4 1.3
1.2 0.6 0.6

−0.6

0.4

1.0

−0.7 −1.4−0.5−2Indonesia
ThailandJapan
Hong Kong
ASEAN
Fiji
Philippines
APO20
GCC
Pakistan
Malaysia
Mongolia
Turkey
Iran
Nepal
EU15
Australia
Asia29Asia23Singapore
US
East Asia
Lao PDRSouth Asia
India
Sri Lanka
Korea
ROC
Bangladesh
Cambodia
Vietnam
Myanmar
China
%

10

2000–20118
64

9.3 9.4

4.2 4.5 5.0

20

2.1 1.3 0.8

0.2

0.5 0.5

5.3 5.3 4.7

0.2 0.2

0.7 1.4

4.6 4.6 4.5 3.9

0.5
1.6

3.0 2.5

3.3

0.7 0.7

0.5

0.7

0.1
1.0 1.4

2.9 2.8 3.0 2.7 3.2 2.2

−0.2

0.8
1.1 0.7 0.5 1.2
1.0
0.0 1.6 0.9 0.6
1.7 1.6 2.0 2.0 1.2
1.4
1.0 0.9 0.7−1.0−0.3−0.1
−1.1

−2
GCC
Fiji
Japan
US
EU15
Australia
Pakistan
Nepal
APO20
Malaysia
Philippines
Singapore
ThailandTurkeyROC
Hong Kong
Korea
ASEAN
Indonesia
Bangladesh
Iran
Sri Lanka
Asia29Asia23
South Asia
Lao PDR
East Asia
India
Mongolia
Vietnam
Cambodia
MyanmarChinaof the Asian countries display ahuge per capita GDP gap with
the US, predominantly explained by their relative laborproductivity performance. Except for the four Asian Tigers,
Japan, and Iran, all the other
Asian countries had labor productivity gaps of more than
50% against the US in 2011.
Hong Kong and Singapore had
the smallest labor productivity
gaps of 3–4% against the US. Allowing for a margin of error of±10%, these gaps are not statistically significant. In contrast,
the labor productivity gaps ofthe other two Asian Tigers arestill sizable against the US, at
20% and 38% for the ROC andKorea, respectively.

Employment rate

Labor productivity

Per capita GDP©2013 Asian Productivity Organization

Figure 19 Sources of Per Capita GDP Growth, 1995–2000
Figure 19 focuses on explaining aand 2000–2011
country’s per capita GDP growth___Decomposition of average annual growth rate of per capita GDP atby its components: namely laconstant market prices, using 2005 PPP
bor productivity growth andSources: Official national accounts in each country, including author adjustments.
the change in the employment
rate for the periods 1995–2000
and 2000–2011, respectively.19
For most countries in Asia, the majority of per capita GDP growth can be explained by improvement
in 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% a year between 1995 and 2000,
and accelerated to 4.7% a year between 2000 and 2011. The earlier period captured the dampening
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 per capita GDP growth than employment, but the employment rate contribution relative
to labor productivity was also highly significant in, for example, Pakistan and Nepal (over 50%), thePhilippines and Bangladesh (around 40%), and Cambodia and Iran (around one-third).

18: 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.
19: 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.

30

3.3 Sources of Per Capita GDP Gap

51
50
49
48
47
47
47
46
46
45
45
45
43
43
42
42
41
39
38
36
35
33
32

3

29
26
26
21
20
19
16
14
14
11

0

10

20

30

40

50

60%

Figure 20 Share of Female Employment___Ratio of female to total employment

Sources: Population census or labor survey in each country.

2011

1990

1970

Cambodia
Singapore
Thailand
Vietnam
China
Australia
BruneiJapan
Hong Kong
Lao PDR
Korea
Nepal
US
ROC
Indonesia
EU15
Myanmar
Malaysia
Philippines
India
Bangladesh
MongoliaFiji
Sri Lanka
TurkeyPakistan
Iran

Most countries also have an employment rate shortof the US level, substantially in the case of Iran andPakistan, further reinforcing theirpoor productivity performances(Figure 18). It is no coincidence that
Iran and Pakistan are among the%countries with the lowest shares of65
female workers in employment, at
16% and 20%, respectively (Figure
6020). In contrast, a handful of coun55
tries – most notably Singapore,
Cambodia, China, and Thailand –50
had higher employment rates thanthe US, counteracting the negative45
impact of their productivity performances. In particular, the positive40
gap in employment rate plays a sig35
nificant role in nudging Singapore
ahead of the US in per capita GDP.
30
More specifically, Singapore’s laborproductivity was 3 percentage
25
points short of the US level, but its
20
employment rate was 29 percentage points higher, giving an overall per capita GDP 26% higher thanthe US.

Cambodia（2008）
Lao PDR（2005）
Vietnam（2010）
Canada（2011）
Mongolia（2010）
Hong Kong（2010）
USA（2011）
Nepal（2008）
Thailand（2011）
EU27（2011）
Australia（2008）
China（2011）
ROC（2008）
Singapore（2008）
Japan（2011）
Korea（2011）
Brunei（2001）
Philippines（2008）
Indonesia（2008）
Malaysia（2008）
Sri Lanka（2009）
Kuwait（2011）
Fiji（2007）
Turkey（2011）
Bangladesh（2010）
India（2011）
Bahrain（2001）
Pakistan（2008）
UAE（2008）
Iran（2008）
Saudi Arabia（2008）
Oman（2000）
Qatar（2008）

All other things being equal, increasing employment and improving labor productivity could present

Figure 21 Employment Rates, 1970, 1990, and 2011___Ratio of employment to total population

Sources: Employment and population data by national statistical office in eachcountry.

31©2013 Asian Productivity Organization

China’s improvement was the most impressive,
achieving per capita GDP growth of 7.4% and 9.3%
a year on average in the two periods, respectively,
with improvement in labor productivity consistently explaining almost all of that growth. According
to official statistics,20 Myanmar achieved a similar
performance to China in growth terms, with per
capita GDP growth of 5.7% and 9.2% a year on average in the two periods. However, this growth wasfrom a very low base; even in 2011, Myanmar’s per
capita GDP was only 20% that of China’s (see Table
5, p. 27). Like China, Myanmar’s per capita GDP
growth has been predominantly explained by laborproductivity. In both periods Japan had a deteriorating employment rate. 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 to counteract thenegative effect of its employment rate.

3 Growth of Asian Economy

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 thecontext of the generally high employment rate in Asia.

©2013 Asian Productivity Organization

Figure 21 shows cross-country comparisons of employment rates in 2011, based on the labor statistics of each country. Employment consists of employees, own-account workers, and contributing
family workers. Cambodia, and Singapore lead the Asian group with employment rates of over 60%,
13–15 percentage points higher than the US and 12–17 EU15, respectively, in 2011. It is clear that
employment rates have been rising in Asia.21 The fastest catch-up countries (i.e., those in Group C1)
are also countries with the largest surge in employment rates over the past four decades; Singapore,
China, Korea, and the ROC. However, China seems to have exhausted its capacity for further improvement as its employment rate was little changed between 1990 and 2011 at 57%. Some of thecountries in Group C2 also experienced significant improvements in employment rates: for example, Indonesia and Vietnam. Countries that have failed to catch up also tend to make less vigorous improvements over the period, and in turn continue to have lower employment rates. Fiji isthe only exception, where the employment rate has improved significantly, albeit from a very low,
starting base.

20: The author would caution readers as to 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 Economist Intelligence Unit (2010). Nonetheless,official statistics from Myanmar are presented in this report, as there is no comprehensive and transparent alternative data source.
21: Japan is the only exception where the employment rate in 2011 was lower than that in 1970. This reflects, among other things, its
aging population. US employment rates also shows weakening in the recent period, with levels in 2011 lower than that in 1990 (i.e.,
47% compared with 51%).

32

3.3 Sources of Per Capita GDP Gap

Population and Demographic Dividend

Box 2

According to the United Nations (UN) (2011), the world’s population is estimated to reach 6.9 billion in
2010, of which Asian countries account for 60.4%. The region is by far the most populous in the world.
China and India account for 19.5% and 17.8% of the world’s population, respectively. It has been observedthat falling fertility rates and rising living standards go hand in hand, although the direction of causality isless 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, and needs varyat different stages of life, changes in a country’s age structure can have a significant impact on its economic growth via a supply-side and demand-side impacts.

3

The world’s fertility rate is converging to the replacement level – the level at which a country’s population
stabilizes. According to the UN, the number of children a woman is expected to have in her reproductive
years has dropped by more than half, from about 6.0 to 2.5 in the last 60 years, compared to the replacement 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 six 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 five 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. Thiswidespread social revolution has been heralded 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 have all been contributing factors to this trend. Coupled with changes in themortality rate, such a trend can dramatically alter the age profile of a country’s population, and bring with
it economic implications.
The growth rate of the world’s population has slowed from its peak of around 2.0% in the 1970s to today’s
1.1% a year. With falling fertility rates, the UN projects that the world’s population growth rate will decelerate to 0.40% a year by 2050 and further to 0.05% by 2100. Even so, the world population will still increaseby one-third in the next 40 years, from 6.9 billion to 9.3 billion and a further 8% to 10.1 billion by 2100.
These estimates are based on the medium-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 in2100) or lower (8.1 billion in 2050 and 6.2 billion in 2100).
Much of this increase is expected to come from high-fertility countries, which comprise 39 out of the 55
countries in Africa, nine in Asia, six in Oceania, and four in Latin America. In contrast, low-fertility countries
include all countries in Europe except Iceland and Ireland, 19 out of the 51 in Asia, 14 out of the 39 in theAmericas, 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% to 14.1% in 2050 and 13.2% in 2100, compared with 32.1% in 1950, whereas the share of theBillionLeast developed countries
Less developed regions, excluding
least developed countries
More developed regions
1.1

8

1.7

0.2

Oceania
Northern America
Latin America and the Caribbean
Europe0.4
Africa0.7
Other Asia
0.7
ASEAN
0.3
China
0.5
1.4
India
0.7

10
8
6

0.3

4

0

2.7

0.7

6

2

2.3

4
4.3

5.6

6.3

6.3

6.1

2.7

2

1.5
0.8

1.0

1.2

1.3

1.3

1.3

1.3

1950

1975

2000

2025

2050

2075

2100

0

0.5
0.6

1950

0.3
0.7
0.4
0.5
0.3
0.9
0.6

1975

0.4
0.8

0.5
0.7

0.5
0.7

0.7

0.7

2.2

3.0

3.6

1.4

1.5

0.7

0.8

1.2

0.9
0.5

0.7

0.7

0.7

1.4

1.3

1.1

1.1

1.5

1.7

1.7

1.6

2000

2025

2050

2075

2100

1.3

1.4
0.7
0.9

Figure B2.1 Distribution of the World’s Population in Different Regions, 1950–2100
Source: UN (Department of Economic and Social Affairs), World Population Prospects: The 2010 Revision.
continued on next page >33©2013 Asian Productivity Organization

Billion10

3 Growth of Asian Economy> continued from previous page

2050

1400
1200
1000

800
600
400
350
300
250
200
150
100
50
30

scale by 5 millions©2013 Asian Productivity Organization1970

scale by 50 millions

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 happen in parallelwith economic progress, although
the direction of causation is not certain. As countries move from highto low mortality and fertility rates,
the demographic transition produces a “boom” generation that islarger than those immediately before and after it. As this boom generation gradually works through anation’s age structure, it produces ademographic dividend of economic growth as people reach theirprime.

2011

1600

25
20
15
10
5
0

BruneiFiji
Bahrein
Qatar
Mongolia
KuwaitOman
Singapore
Lao PDR
Hong Kong
UAE
Cambodia
Sri Lanka
Australia
ROC
Nepal
Saudi Arabia
Malaysia
Korea
MyanmarThailandTurkeyIranVietnamPhilippines
Japan
Bangladesh
PakistanIndonesia
US
EU27
India
China

According to the projection Asia’sshare will decline from its 60.4% today to 55.3% in 2050 and 45.4% in
2100, while Africa’s share will risefrom today’s 14.8% to 23.6% and35.3%, respectively. Figure B2.2
shows the current population sizeof individual Asian countries compared with the 1970 level and its
2050 projection. As can be seenfrom the chart, China’s population is
expected to more or less stabilize
around the current level. China hassocially engineered the changewith its one-child policy, which has
made its current population 300–
400 million lower than it would
have been otherwise. In less than adecade, India is projected to overtake China as the most populous
country in the world, and China’s
population will drop to under 1 billion by 2088.

Millionscale by 200 millions

least developed countries risingfrom today’s 12.1% to a projected18.6% in 2050 and 26.6% in 2100,
up from 7.9% in 1950.

Figure B2.2 Asian Countries’ Population Size and Projection, 1970, 2011, and 2050
Source: World Bank, World Development Indicators.

18.9
19.8

30.8

34.9

25.3
26.3

13.1

Japan
Australia
US
Hong Kong
Korea
ROC
Singapore
China
ThailandTurkeySri Lanka
MyanmarVietnam
IranIndonesia
Nepal
Fiji
India
Malaysia
Bangladesh
Philippines
Cambodia
Pakistan
Mongolia
Lao PDR
Brunei
Saudi Arabia
Oman
KuwaitBahrain
Qatar
UAE

11.6
15.6
15.1
16.8
16.5
20.2

23.2
23.4
26.7

28.9
30.2
26.7
30.7
33.6
31.7
34.8
27.4
37.3
25.9
30.0
27.0
26.8

20.9

13.6
16.8

40 %

30

Ages 0–14

20

10

0

23.3

13.8
13.3
13.3
11.4
10.9
9.4
9.1
9.1
7.3
6.3
6.0
6.0
5.7
5.6
5.3
5.0
5.0
4.8
4.6
4.4
4.4
4.3
4.0
3.7
3.7
3.0
2.7
2.5
2.2
0.8
0.4

0

5

10

15

20

25 %

Ages over 65

Figure B2.3 Proportion of the Dependent Population,
2011
Sources: Population census and official national accounts in each country.

continued on next page >34

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

Using demographic data since 1950 and UN projections up to 2100, Figure B2.4 tracks changes in the ratioof the working population (aged 15–64) to dependent population (aged under 14 and over 65) over time.
The higher the ratio, the more favorable its demography for economic growth. Japan could have capitalized the demographic dividend in the 1960s, when its GDP growth was over 10% on average per year forten years. Similarly, China, Hong Kong, Korea, Singapore, and Thailand are poised for the prospect of suchdemographic dividend in the 2000s and 2010s, whereas, based on projections, Indonesia will have to wait
for such opportunity until the 2020s and 2030s, and India till the 2040s. The reaping of this dividend, however, is far from automatic. A favorable demography can work wonders to produce a virtuous cycle of
Dependent population (aged under 14 and over 65)=1.0
wealth creation only if it is comHong Kong
3.0
bined with appropriate health, laJapanbor, financial, human capital, and
Korea
2.5
Singapore
growth-enhancing economic poliUS
2.0
cies. The presence of these complementary factors cannot be taken for
1.5
granted, but needs to be cultivated
1.0
in order to earn the demographic
1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
dividend. As the analysis of the
Databook show, the contribution of
Dependent population (aged under 14 and over 65)=1.0
labor to economic growth has been
China
3.0
India
smaller than those of capital andIndonesia
2.5
TFP for most countries (Figure 52,
ThailandAustralia
p. 72). This means that countries
2.0
should not be afraid of ageing too
1.5
much as long as fairly high growth
rates of capital and TFP are main1.0
tained. Nevertheless, understand1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
ing the demographic shift and its
implications is highly relevant for
Figure B2.4 Demographic Dividend, 1950–2100
economic projections and in turnprovides valuable foresight for ecoSource: UN (Department of Economic and Social Affairs), World Population Prospects: The 2010 Revision.
nomic policy making.

©2013 Asian Productivity Organization

35

3

4.1 Composition of Final Demand

4 Expenditure
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 only
accounting identities, but in reality, they differ by statistical discrepancies.22 Decompositions of GDP
are valuable in understanding the structure, and in turn the behavior, of an economy. In this chapter,the economic composition of countries’ expenditure experience is critiqued. The decomposition of
output growth into input growth and the TFP growth (the supply side) is analyzed in Chapter 5, while
countries’ industry structure are presented and analyzed in Chapter 6.

4

4.1 Composition of Final Demand
From Table 7, one 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 capitalformation (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 in the present day.
Table 7 Final Demand Shares in GDP, 1970, 1980, 1990, 2000, and 2011___Share of final demands with respect to GDP at current market prices

APO20

Household consumption
Government consumption
Investment
Net exports
1970 1980 1990 2000 2011 1970 1980 1990 2000 2011 1970 1980 1990 2000 2011 1970 1980 1990 2000 201151.8 56.1 54.9 58.7 61.0 10.8 13.7 12.8 13.9 12.6 36.6 31.6 31.8 25.1 27.6
0.9 −1.4
0.6
2.4 −1.2

Asia23

52.1

55.8

54.1

55.7

51.2

10.8

13.7

12.9

14.3

12.9

36.2

31.8

32.2

27.5

35.5

0.8

−1.4

0.8

2.4

0.3

Asia29

51.7

52.5

53.8

55.1

50.1

10.9

13.7

13.6

14.6

13.0

35.8

30.6

31.3

27.1

35.0

1.6

3.2

1.3

3.2

1.9

East Asia

50.3

54.5

52.3

53.1

43.3

10.9

14.1

13.4

15.6

14.8

37.8

32.5

32.9

29.2

39.9

1.1

−1.1

1.4

2.0

2.0

South Asia

76.2

76.1

68.3

67.2

67.2

8.6

9.2

11.0

11.7

11.0

15.5

19.3

23.2

22.6

28.9

−0.3

−4.6

−2.5

−1.5

−7.1

ASEAN

65.3

58.5

56.2

56.7

57.7

13.4

12.5

10.5

10.1

10.4

26.3

31.6

34.7

24.0

28.3

−4.9

−2.6

−1.4

9.2

3.7

GCC

36.0

29.7

50.1

42.9

32.0

14.0

13.4

24.6

19.8

14.7

19.5

22.3

15.8

18.2

26.4

30.5

34.6

9.5

19.1

26.9

China

55.6

50.2

47.0

46.7

36.4

11.2

14.9

14.1

15.8

13.5

33.1

35.2

36.1

35.1

47.6

0.1

−0.3

2.7

2.4

2.6

India

74.8

74.2

65.2

64.9

63.5

9.4

10.1

11.7

12.7

11.7

15.9

18.9

24.5

23.3

31.7

−0.1

−3.2

−1.4

−0.9

−6.9
−0.9

Japan

49.3

54.6

53.0

56.4

59.8

10.7

14.1

13.3

16.9

20.7

38.8

32.3

32.8

25.3

20.4

1.2

−0.9

0.9

1.4

Australia

54.7

55.9

58.4

59.5

54.1

13.9

17.7

18.1

17.7

18.1

31.7

28.3

23.7

22.6

27.5

−0.3

−1.9

−0.2

0.2

0.3

US

62.4

63.0

66.1

68.6

71.2

18.3

16.7

16.7

14.3

17.1

18.9

20.8

18.6

20.9

15.5

0.4

−0.5

−1.3

−3.8

−3.8

EU15

58.1

58.2

58.1

58.7

58.2

16.3

20.1

20.0

19.8

21.9

26.1

24.1

22.6

21.2

18.8

−0.5

−2.4

−0.8

0.3

1.1

22: Countries follow an international framework, called the 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 upon the 1993 SNA. For further details, seeBox 1 (p. 22).

37

©2013 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 GFCF plus changes in inventories.

4 Expenditure

China’s household consumption has been trending downward as a share of GDP. It fell from 55.6% in
1970 to 46.7% in 2000. This compares with the early Communist era, when household consumption
was more volatile and at a higher level of over 60% of GDP (Figure 22); China was less well off then.
Figure 22 shows how household consumption share and investment share mirror each other. As thedecline in household consumption share accelerated in the 2000s, plummeting to 36.4% in 2011, theinvestment share rose rapidly to 47.6% of GDP from 35.1% in 2000. There is also a notably rapid rise inexports as a share of GDP since the 1980s when China began to open its economy, from around 5.0%
or below in the 1950s and 1960s to its peak of 37.0% in 2006 before softening to 26.5% in 2011.
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 areflection of consumer behavior or preference, but a manifestation of an array of underlying distortions in the economy: an undervalued currency with a wide range of factor price distortions whichfavors the production of tradables over non-tradables, may result in an unusually low consumption
ratio and a heavy reliance on exports; lax corporate governance of state-owned enterprises is notconducive to distribution of dividends and therefore, in effect, may act to subsidize investment; andin the absence of a social safety net, well-developed domestic financial markets may provide a strong
incentive for precautionary saving on the part of households (Eichengreen, Park, and Shin, 2011).
All of these factors suggest that there are policy levers available to the government to impede or rebalance the economy.
In recent years, even labor-abundant China faced a tightened supply of surplus labor at its coasts, putting an upward pressure on wages.24 This could be good news for the world, as a higher labor share of
GDP will enable higher household consumption, helping the domestic market to fulfill its potential.
This will make China less dependent on foreign demand on the one hand and generate demand forforeign products on the other. Signs that the Chinese economy may have started moving in the right
direction were evident when the decline in the consumption ratio halted (even turning up slightly
since its recent trough in 2009) and external imbalances narrowed to 2.6% in 2011 – the lowest since2004. Since the peak of 8.8% in 2007, net exports have been shrinking. Only time will tell if this is thestart of a more persistent trend that reflects fundamental adjustments to the underlying economy.
India, another fast-emerging economy, has seen its household consumption share declining rapidly in the past four decades, from 74.8% in 1970 to 63.5% in 2011 (Table 7). In contrast, the share ofhousehold consumption was relatively stable in the US at around 62–63% for the 1970s and 1980s
before edging up to 71.2% of GDP in 2011. From a historical perspective, the current level is below thatexperienced during the Great Depression in the US when the consumption share was over 75% andeven as high as 83% in 1932, and above its all-time low of below 50% in 1944 during World War II(Figure 23).

©2013 Asian Productivity Organization

The share of household consumption in EU15, which is at around 58%, has stayed fairly stable over the
past four decades. The Asian average, meanwhile, has hovered in the lower 50% range until recently

23: Based on the metadata survey on national accounts in Asian countries, Japan is an exceptional country that estimates GDP fromits expenditure side. In other countries, GDP is estimated from the production side (value added in industries), and some countries
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 is 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% of GDP in 1990 in theThailand SNA published as of the end of 2011.
24: See Box 4.

38

4.1 Composition of Final Demand

%

%

80

70

70

Household Consumption
consumption

60
50
40

50
Investment

4

40

30

Exports

20

30

Investment

20
Imports (−)

10
0
1952

consumption
Household Consumption

60

1962

1972

1982

1992

2002

Imports (−)

10
0
1929

Exports
1939

1949

1959

1969

1979

1989

1999

2009

Figure 22 Final Demand Shares in GDP of
China, 1952–2011

Figure 23 Final Demand Shares in GDP of theUS, 1929–2011

current market prices

current market prices_ Share of final demands with respect to GDP at

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

_ Share of final demands with respect to GDP at
Sources: National accounts by Bureau of Economic Analysis, US.

when the gap with EU15 widened, largely reflecting the trend in China (Table 7). Australia’s consumption ratio has never exceeded 60% of GDP and has dipped significantly in the past decade to 54.1%,
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 ratios. South Asia maintains thehighest share, despite its fall from 76.2% in 1970 down to 67.2% in 2011. In contrast, GCC economies
are unusually skewed towards net exports because of their oil production.

Compared to other components of final demand, the contribution of net exports to the Asian economy has always been more volatile. Having increased in Asia23 between 1990 and 2000 from 0.8% to
2.4%, the contribution of net exports has been ebbing away once again to 0.3% in 2011. In contrast,
the net export share in China has been steady at a rate of 2.4–2.7% over the past two decades. This
compares with the oil-exporting GCC countries at 9.5% in 1990, rising to 19.1% in 2000 and further to
26.9% in 2011. Including the GCC countries, the contribution of net exports to the GDP of Asia29 was
1.9% in 2011, compared to 1.6% in 1970 when net exports accounted for nearly a third of final demand39©2013 Asian Productivity Organization

Overall, Asian countries invest significantly more than the US and EU15. Historically, the wedge in theinvestment share of GDP between Asia29 and EU15 never exceeded 10 percentage points, but since
the beginning of the 1990s, it has started to widen (except for the period of the Asian Financial Crisis).
In 2011, the portion represented over 16 percentage points. In the 1970s, EU15 was investing on average 4% more of their GDP than the US. Thereafter, the EU15 investment share converged to the US
level and they were out of synch with each other temporarily in the late 1980s and early 1990s. For the
past five years, a divergence has opened up with the US investment share of GDP declining faster thanthat of EU15 (Figure 31.3). In 2011, investment accounted for 15.5% and 18.8% of final demand in the
US and EU15, respectively, compared with 35.5% for Asia23. Australia’s investment level has beencloser to the level of the APO20 than that of the US/EU15 and in 2011 it accounted for over a quarterof final demand. The share of investment in China is the biggest final demand component of GDP
since 2004 and, at 47.6% in 2011, it is probably unsustainable in the long term. East Asia has the highest investment ratio among the Asian regions; South Asia caught up with them in 2007, but sincethen, the paths of the two regions diverged in the opposite directions. Now South Asia is converging
with ASEAN countries, the investment intensity of which has not recovered since the Asian financial
crisis of the late 1990s.

4 Expenditurein GCC countries. In the US, there is an observable trend of persistent deficit between exports andimports, which has considerably expanded from 0.5% of GDP in 1980 to nearly 4.0% in the mid-2000s
before narrowing to 3.8% in 2011. South Asia is the only Asian region that consistently runs a trade
deficit with fluctuating sizes over the years. Lately, it has become historically sizable at 7.1% of GDP in
2011. In EU15, net exports have turned into a positive component in the past two decades, accounting for 1.1% in 2011.
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 during 1995 and 2011;
countries are arranged in descending order of their household consumption shares. Although mostcountries fall to the right of the US, there are a handful of Asian countries that have a higher consumption ratio than the US; Bangladesh, Cambodia, Nepal, Pakistan, and the Philippines fell to the left of
the US in both years of comparisons, 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 countries clustered on the left of Figure 24 tend to be those in the bottom income
groups25 among the countries studied in this report (see Table 14, p. 88). Countries with a high

1995

%

125
100

15
6 19 27 14 27 24
5

75
50

95

8

8

83 81 78

25
0
−25

−6
−15

4 1
0 1
4
0
2
1
1 2 0
1
8
8
10 5 1011
16
25 27 27 25 17 34 23 24 20 27 29
43
28
37
36
37 33 21 43 20 21 15
14 32 3235 35
8 11 9 1442
9 15 10 11 11
8 13 8 16 18 20 15 13
33
21 13 1415
10
7
11 11 14 21 12 23 28 32
14 8 25 31
20

24

24

19

74 74 73 71 68 67

66 64 63 63 62 62 61−1 −9 −9 −2 −9 0 −1 −2 −1 −159 58 57 57 57 55 55 54 54 54 52 52 52

0

−4

0

−2

−15

−7

−1

50 49 47 45

43 43 42 36

33

−4

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

2011

%

125
100

75
50
25
0
−25

33
1 4 1 2 2 0 2
0
3
2
4
0 2
7
23
13 18
15 24 30
25 22
12
63 16
20 19
20 29
32 28
8 6 1028 27 26
27
23 33
28
27
30
21
31
33
28 33
36 35
6 10 15 17 14 1540
48 50 41
10 11
48
22
28
8 6 12 13 12 21 22
22 18
10 9 9 16 18 15
23 26 27
7 13 13 12 1415
10 13 13
16 13 3184 82 80 78
16 15 1974 73 71 71 70 70 67
65 65 63 61 60 60 58 58
15 17
57 56 56 54 53 52 51 50 5048 43
1040 38 36 33
32 27
22 20 18
−9

−5 −5

−5

−12

−4

−9
−14

−7

−4

−7

−1

−1

−22

−24

Qatar
Brunei
KuwaitSaudi Arabia
GCC
Oman
China
Bahrain
Singapore
East Asia
Malaysia
Mongolia
Asia29Asia23
UAE
Korea
Australia
ThailandIranIndonesia
ASEAN
EU15
Japan
ROC
APO20
India
VietnamHong Kong
South Asia
Myanmar
Sri Lanka
TurkeyUS
FijiPhilippines
Bangladesh
Nepal
Cambodia
Pakistan©2013 Asian Productivity Organization

Household consumption

Government consumption

Investment

Net exports

Figure 24 Final Demand Shares in GDP, 1995 and 2011___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 GFCF plus changes in inventories.

40

4.1 Composition of Final Demand

proportion of dependent population (under15s and over-65s) also tend to have a highhousehold consumption share in their GDP(see Figure 25).
At the other end of the spectrum, GCC andother oil-exporting countries tend to cluster at
the low end of household consumption shareof GDP in both years of comparison. The average household consumption share for GCC
countries has been squeezed by net exports(which in turn are dominated by erratic oil revenues), from 50.3% in 1995 to 32.0% in 2011.26
Given that a large part of GCC countries’ GDP isnot sustainable income, it may in fact be prudent for oil-exporting countries not to overconsume beyond their sustainable levels andrather, purposefully invest much to generate a
steady income stream in the eventuality of oil
depletion – no matter how distant this may
seem now. Among the non-oil-exporting
Asian countries, it was Singapore that had thesmallest household consumption share, butsince 2002 China has replaced Singapore inpole position, with a share of 36.4% in 2011.

Household consumption share in GDP%

90

Pakistan

Cambodia80

Nepal

Bangladesh
FijiTurkey70

US

Sri Lanka
Hong Kong

60

VietnamPhilippines

4

Myanmar
India

ROC
UAE

50

Japan
Thailand Indonesia
Iran
Australia
Korea
Mongolia
Malaysia

Singapore

40

Bahrain
China

Oman

30
Saudi Arabia

Kuwait20

10Brunei

Qatar

10

15

20

25

30

35

40

45 %

Dependent population ratio

Figure 25 Ratio of Dependent Population andConsumption Share in GDP at Current Prices,
2011_ Shares of dependent population (under-15s andover-65s) to total population and consumption share toGDP

Sources: Population data by national statistical office in each coun-

Net exports are particularly important in atry; World Bank, World Development Indicators; official national accounts in each country with author estimates.
handful of economies; in 2011 in Singapore
export shares were at 27.6%, in Malaysia it was
16.5%, and in Hong Kong it was 3.9% reflecting their entrepôt function in Asia. This explains why the total values of exports and imports are exceptionally high, relative to the size of GDP in these economies (Figure 26). Once the 2008 SNA is implemented, however, these values will be adjusted to reflect a change in the ownership of goods
rather than accounting for goods moved for processing without incurring actual transactions.

25: The Lao PDR is also in the bottom income bracket; 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 any real change in the underlying behavior in the economies. For example, Qatar has the smallest share of household consumption, which shrank from 32.9% in 1995 to 18.9% in 2010, while over the same period, net exports swung from 1.0%
to 26.1%. Similarly, net exports for GCC countries as a whole swung from 7.8% to 18.2%, squeezing household consumption from
50.3% in 1995 to 32.0% in 2011.

41©2013 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 consistent high performers, and come at the top for most of
the level indicators presented in Chapter 3. As seen in Figure 27.1, Singapore and Korea showed themost rapid relative retrenchment in household consumption as a share of GDP in their initial stage ofdevelopment. While the downward trend continues in Singapore, it has halted and been mildly reversed in Korea since the late 1980s. Between 1970 and 2011, the household consumption share of
GDP fell from 69.1% of GDP to 40.0% and from 74.1% to 53.1% in Singapore and Korea, respectively.

4 Expenditure

1995

%

100

91 143

182
78

80
60

37

40

59

57

52
35
22

20

47

44

44
29

20

25
9

18 19

1
−2

0
−8

−20

−14
−18
−27
−28 −29
−41
−42
−45
−53

−40
−60
−80
−100

−18
−25 −19
−29

11

−12
−12 −16

−17

−36

−43

33 34 31

22

31

−38
−42 −41−46−48 −43

−59

−67

−148
−95

%

78

70

60

79
61

95

207
59

2011
85

230

86

76

71
56

56
27

20

21

26

31

22

15 14

14

−16
−18

−19

0
0

0
−22

−19
−24

−25

−21

62

54

54

42

40

−20

11 11 14

−166

100
80

42

35

28

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

In contrast, household consumption as a share of GDP, at 64.9% in
2011, has held steady in Hong
Kong over the past four decadeswith no established long-term
downward trend. The household
consumption share did fall from
64.8% in 1970 to nearly 55% in
the late 1980s, but it was subsequently reversed. Only time willtell if the recent pickup in consumption share is the start of amore persistent upward trend towards record levels. Similarly, relative household consumption fellin the ROC, from 56.6% in 1970 tounder 50% in the mid-1980s.
Since then, it has been on an upward climb until the 2000s when
it stabilized at around 60%.

26 23 24

23
10©2013 Asian Productivity Organization

Mongolia
Nepal
Sri Lanka
Fiji
TurkeyBangladesh
India
Cambodia
Pakistan
Philippines
Vietnam
USJapan
Myanmar
Australia
EU15
Indonesia
Thailand
Korea
Iran
China
Hong Kong
ROC
UAE
Malaysia
Saudi Arabia
Singapore
Oman
Bahrain
Qatar
KuwaitBrunei−27 −20 −31 −29−32−32 −33
Figure 27.2 plots the trends of
−40
−36
−37
−31
−41
−48
−54
household consumption in the
−60
−59
−66
−69
−70
−73
−80
three largest Asian economies by
−78
−87
−90
−226
−180
−100
size. The downward long-term
trend in India and China is unmistakable.27 The falling share ofhousehold consumption may
Exports
Imports
Net exports
partially reflect the falling labor
income share of GDP and/or an
Figure 26 Export and Import Shares in GDP, 1995 and 2011
uneven distribution of economic___Share of exports and imports with respect to GDP at current market
gain between the rich and thepricespoor in these countries. FurtherSources: Official national accounts in each country, including author adjustments.
more, the fact that India has a dependent population (under-15s
and over-65s) of 35.2%, compared with 25.6% in China, may help to explain why India has had to sustain a relatively high share of household consumption despite its falling trend over time, whereas
China’s share has fallen below the norm of country’s experience (Figure 25). In contrast, the household
consumption share in Japan has been rising slowly since 1970, from just under 50% in 1970 to almost
60% in 2011. With a rapidly aging population, this rising trend can be expected to continue. Japan’sshare of dependent population stood at 36.4% in 2011, nearly 60% of which was accounted for by theover-65 age group (Figure 28). To a lesser extent, all the Asian Tigers, China, Australia, and the US havea high proportion of over-65s relative to other countries.

27: The Chinese official statistics on household consumption could be misleading. Zhang and Tian (2013), for example, point out
three potential sources of a significant downward bias in Chinese consumption data. Firstly, the method used to impute rents forowner-occupiers does not take into account land costs, and in turn greatly underestimates the market values of housing. Secondly, private consumption on company accounts is misclassified as business costs (i.e., intermediate consumption) or investment
expenditure. Thirdly, sample selection bias (under-representation of high income households) and reporting errors also contributeto the underestimation of household consumption. The authors suggest that taking into account these factors could add 10–15
percentage points to China’s consumption, which would bring it to a level more comparable with other East Asian countries.

424.1 Composition of Final Demand

%

%

80

ROC
Hong Kong
Korea
Singapore

70

80

70

China
India
Japan

60

60

50

50

40

40

30
1970 1975 1980 1985 1990 1995 2000 2005 201030
1970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 27.1

Figure 27.2

%

80
70

4

%

APO20
US
Australia

Asia29
EU15

80

70

East Asia
South Asia
ASEAN

60

60

50

50

40

40

30
1970 1975 1980 1985 1990 1995 2000 2005 201030
1970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 27.3

Figure 27.4

Figure 27 Long-Term Trend of Household Consumption Share in GDP, 1970–2011___Share of household consumption with respect to GDP at current market prices

Figure 27.3 illustrates 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 71% of GDP in 2011, from a level of around 62%. Today the US level is more than 10% higher
than that of EU15 and the APO20,28 both of which have been fluctuating between 57% and 60% since
the mid-1990s. In 1970, household consumption accounted for around 50% of GDP in APO countries.
It rose to a peak of 57.1% in 1983 before falling back and hovering around 55%. Since the early 1990s,
however, it has been trending upwards and went over the 60% mark in 2011. The pattern in APO
closely follows that of Japan. After the bubble burst and its economy floundered, the investment
share of GDP shrank – with household consumption and government consumption both inflating
their shares to sustain final demand (see Figure 24). In contrast, the consumption share for Asia29
declined rapidly from 55.7% to around 50% over the past decade. This largely reflects China’s recent
household consumption behavior as it gained gravity in the regional economy. Australia’s levels havebeen fluctuating between that of EU15 and Asia29 in the 1970s and 1980s, and inclined towards
EU15’s level in the 1990s, but its trend in the past decade has diverged again and become similar tothat of Asia29, albeit at different levels. The trends of South Asia and East Asia are dominated by thoseof India and China, respectively (Figure 27.4).

28: 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.

43©2013 Asian Productivity Organization

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

4 Expenditure©2013 Asian Productivity Organization

37
4
Lao PDR
The decomposition of household consumption reveals a
5
35
Nepal
huge diversity of consumption patterns among individu4
35
Pakistan
434
Philippines
al countries, partly reflecting their income levels and
631
Myanmar23
13
Japan
partly the idiosyncratic characteristics of the society. Fig4
32
Cambodiaure 29 strongly illustrates the cross-country version of
31
5South Asia
5
31
Bangladesh
Engel’s Law, which says that basic necessities will account
5
30
India
6
28
APO20
for a high proportion of household consumption for a
29
5
Fiji
lower per capita income group and vice versa. More spe20
13
US
27
6
ASEAN
cifically, countries where food and non-alcoholic bever330
Saudi Arabia
14
19
Australia
ages account for a large proportion of consumption tend
25
7Turkeyto have low income (i.e., in groups L3 or L4 in Table 14).
6
26
Sri Lanka
627
Indonesia
Figure 30 traces the decreasing long-term path of Japan’s
5
27
Malaysia
Engel’s Curve for the period 1949–2011 and the coun27
4
Mongolia
24
7
Asia23tries’ levels in 2010 are mapped against Japan’s experi24
7
Asia293
27
Oman
ence (as circle). Among the selected countries, it is426
Bruneistaggering to note that in 2010, 52.7% of Bangladesh’s
20
9Thailand27
2
Kuwaithousehold consumption was spent on food and non6
23
Vietnam23
6
Iranalcoholic beverages at one end of the spectrum, com2
26
GCC
pared with only 6.6% in the US at the other end. This trans11
16
Korea
10
16
East Asia
lates into the fact that low-income countries spend 30–
17
9Singapore
15
11ROC
50% of their GDP on food and non-alcoholic beverages,
9
16
China
which corresponds to Japan’s experience in the 1950s
12
13
Hong Kong
21
2
Bahrain
Age 0–14
and the 1960s. Eating out, recreation and culture are
0
17
UAE
Age over 65
luxuries that the least well-off countries cannot afford in
14
1
Qatar
0 5 10 15 20 25 30 35 40 45 %contrast to their richer counterparts. Besides food andnon-alcoholic beverages, housing/utilities and transport
Figure 28 Share of Dependent Popuare the other two large spending categories. In rich eco­lation, 2011
nomies, these two categories account for bigger sharesin household consumption than food and non-alcoholic
Sources: Population data by national statistical officein each country; World Bank, World Development
beverages. Idiosyncratic spending, such as education in
Indicators.
Indonesia and Korea accounting for 7.5% and 7.2% ofhousehold consumption, respectively, and health in theUS, accounting for one-fifth of consumption, are unreflected in other countries.

Figure 31 looks at the long-term trend of investment share in GDP across countries. Historically, aninvestment share in the region of 40% or above seems to be unsustainable in the long run. We see thatJapan’s investment share of GDP steadily declined over the past decades from 38.8% in 1970 to 20.4%
in 2011 (Figure 31.2). In the initial period, Singapore also sustained an investment share of 40% orabove. Since the mid-1980s, however, it has seen a downward trend, in spite of its fluctuations. In
2011, the investment ratio was 22.2%. The investment share hit 40% in the ROC and Korea at different
times but these were no more than temporary spikes (Figure 31.1). In contrast, the investment sharein China and India has been rising. India in particular has been investing very aggressively since 2000,
coming as close as 5.2 percentage points to China’s 41.7% share in 2007. Since then, the gap has widened to 15.9% in 2011 as investment in India softened (Figure 31.2). 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%, but it fell sharply to around 25% during the Asian financial crisis in thelate 1990s and is slowly inching up, reaching 28.3% in 2011. In the past two and a half decades, theinvestment share in GCC countries has fluctuated between 20–30% of GDP (Figure 31.4).

44

4.1 Composition of Final Demand

Figure 33.3 illustrates the external
imbalance of the world’s major
economies. Both the US and EU15
faced a trade deficit at the beginning

90
80
70
60
50
40
30
20
10
0

4 5 4 322
4 2 5 754443
3 24 3 54
7
10 3 1214 13 12 15 16 15
2 15
2
3
20
3
2
3
3 2 12
6 8 7
10
6
7
3
9
9
9 2
2 2
4
3
2
1
4
8
7
7
5
5
3
10
9
9
8
14
3
15
2
17
11
12
8 9 3 8
2 5
13 2
4
5
5 4 2
2
2 20 4 16
310
5 11 4
2 6
11
2
4
13
11
10
10
2
10 4 12174
14
3
13 4 31 2
10 6
4
10
10
5
21
7
4 11
5
9
18
7
3
4 7
3 5
16
25
6 4
4 5
16 18 23
57
4 5
53
3
2 14
18 19
40 37
36 36
3 5 5
30
3 2 2 3
27 25
4 3
22
2 4
15 14 13 13
10
7 7
8
2
1
6
2
5

Miscellaneous goods andservices
Restaurants and hotels
Education
Recreation and culture

4

Communication
Transport
HealthFurnishings, household
equipment, and routine
household maintenance
Housing, water, electricity,
gas and other fuels
Clothing and footwear
Alcoholic beverages,
tobacco and narcotics
Food and non-alcoholic
beverages

US
Singapore
Australia
ROC
Korea
Japan
Hong Kong
Malaysia
Iran
ThailandIndia
Mongolia
Indonesia
Cambodia
Sri Lanka
Bangladesh
Fiji

Figure 33 plots the long-term trendof net export share in GDP from1970 to 2011. Among the selected
countries, India can be identified asprone to running a trade deficit,
which deteriorated rapidly from themid-2000s to 6.9% of GDP in 2011
(Figure 33.2). In contrast, net exports, which used to be a huge dragon the Asian Tigers, Singapore, andKorea in the 1970s, have rapidly improved their position. In recent
years, net exports are making a positive contribution to GDP for all the
Asian Tigers. The share of net exports in Singapore is particularly
large, at 27.6% in 2011, comparedwith 2.0%, 6.6%, and 3.9% for Korea,
the ROC, and Hong Kong, respectively (Figure 33.1). China is anothercountry that has turned around its
net export position to transform it
into a significant positive contribution to final demand. The net exports share of GDP peaked at 8.8%
in 2007; since then, it has slackened
at 2.6% in 2011, reflecting, among
other factors, weaker foreign demand as a consequence of the global financial crisis (Figure 33.2).

%

100

Figure 29 Household Consumption by Purpose, 2010
Note: For data of Hong Kong, transportation includes communication; recreationand culture includes hotels; miscellaneous goods and services include restaurants.
For data of Sri Lanka, transportation includes communication; food and nonalcoholic beverages includes alcoholic beverages, tobacco and narcotics. For Fijiand Indonesia, the observation period is 2009.
Sources: Official national accounts in each country.
Food consumption share in 2010
relative to Japan

0.7

0.6

Japan (1949–2010)

Fiji
Bangladesh

0.5

Indonesia
Sri Lanka

0.4

Mongolia

Cambodia
India
Thailand

0.3

Iran
Malaysia

0.2

Japan
Korea
ROC HongKong

0.1

US
1940

1950

1960

1970

1980

1990

2000

Singapore

2010

2020

Figure 30 Engel Curve of Japan during 1949–2010 andLevels of Asian Countries in 2010___Share of food in household consumption

Note: Food is defined as sum of food and non-alcoholic beverages and alcoholic
beverages, tobacco and narcotics. For Fiji and Indonesia, the observation period is2009.
Sources: Official national accounts in each country. The historical data of Japan isbased on JSNA by ESRI, Cabinet Office of Japan.

45©2013 Asian Productivity Organization

Figure 32 shows the nominal investment share of six types of assets forsome selected countries.29 For mostcountries, investment is still verymuch construction-based (i.e., in
dwellings, non-residential buildings, and other structures). However, the expansion of IT capital in thepast four decades is significant in
the US, Japan, Asian Tigers, and Malaysia even at the current price comparisons. The real-term comparisonsare conducted at the flow and stocklevels in Chapter 5.

4 Expenditure

%

%

50

50

ROC
Hong Kong
Korea
Singapore

40

China
India
Japan

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 31.1

Figure 31.2

%

%

50

50

APO20
Asia29US
EU15Australia

40

East Asia
South Asia
ASEAN
GCC

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 31.3

Figure 31.4

Figure 31 Long-Term Trend of Investment Share in GDP, 1970–2011___Share of investment with respect to GDP at current market prices
Sources: Official national accounts in each country, including author adjustments.

1970

%

100
80
60
40
20

Dwellings
Transport equipment

100

19

80
60
40
20
0

Non-residential buildings
IT capital

16

28 23 26 25

85

31 25 38 26
5
4
8
15
9
13
9 15
7 12 4322
10 7 9
12
8
7 12
16
9
13
9 11
14
17
20 9
16
27 24
6
8
14
28
26
7 23
21 19
23 18
15 14
23
28
13
14
15
25
4 11
32 33
10
14
22
12 12 1319 20
18 20 18
28 25 24 24
7
20 18 15 15 13
11 11 11 10 9 9 8 5 5

13

32

25

7

39

27

37 32 32

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

China
Philippines
Sri Lanka
ROC
ThailandMongolia
Malaysia
PakistanIndonesia
Singapore
Japan
US
Fiji
Hong Kong
Korea
Vietnam
Iran
India

0

2011

%

11
17
18
26 30 24
27 26
28 4
30
32
35
35 30 42
4
42
43
8
12
13
4
7
10
8
5
4
11 12
12 10 1355 12 30 21 4 11 16 5
23 13
16
5
17 20 11 32
8
24 22
15 21
18
8
22
34
18
9
26
21
21
14
8 15
17 18
29
13 13 13 18
17 15 2539
19 27
27 23 23 23 22 22 20
19 18 16 16 15
11 9 8 5
16

Other structures
Other non-IT capital©2013 Asian Productivity Organization

Figure 32 Investment Share by Type of Asset, 1970 and 2011
Sources: Official national accounts in each country, including author estimates based on input–output tables and trade data.

29: The investment data by type of assets includes our own estimates for the countries where data is not available. Although our estimates are constructed based on ten classifications of assets, they have been aggregated into six assets for the purposes of thistable. The IT capital is defined as IT hardware, communications equipment, and computer software.

46

4.1 Composition of Final Demand

%

32
24

%

10

ROC
Hong Kong
Korea
Singapore

8

China
India
Japan

6

16

4
8

4

2

0

0

−8

−2

−16

−4

−24
1970 1975 1980 1985 1990 1995 2000 2005 2010

−61970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 33.1

Figure 33.2

%

%

12

6
4

8

East Asia
South Asia
ASEAN

2
4
0
0
−2
−4

APO20
US
Australia

Asia29EU15−4−61970 1975 1980 1985 1990 1995 2000 2005 2010−81970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 33.3

Figure 33.4

Figure 33 Long-Term Trend of Net Export Share in GDP, 1970–2011___Share of net exports with respect to GDP at current market prices
Sources: Official national accounts in each country, including author adjustments.

47©2013 Asian Productivity Organizationof this period. While EU15 managed to revert and has been in surplus since the early 1990s (within arange of 0–2% of GDP), the US position has significantly deteriorated since the middle of the 1990s,
despite a tremendous effort in restoring its trade balance in the late 1980s. In 2011, the size of the US
trade deficit stood at 3.8% of its GDP, compared to its recent dip to 5.8% of GDP in 2006. Australia has
been running a trade deficit for most of this 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-imageof the US. Asia29’s net exports share of GDP was 1.9%, compared to the recent peak of 5.3% in 2011.
Addressing this external imbalance has been highlighted as a necessary step to healthy and sustained
growth in the world economy.

4 Expenditure

Box 3

Quarterly Economic GrowthTimely analysis of the current economic situation is beyond the scope of this Databook, which presents
results based on annual data, with the latest year covered as 2011. In the meantime, for an insight into, forexample, the current economic growth, one has to rely on countries’ quarterly national accounts (QNA).
Although they are timelier, the QNA are often less precise, and subject to frequent revisions as more reliable data become available in their normal estimation cycle. With this trade-off between timeliness anddata quality in mind, the APO sees the complementary benefits of collating and presenting countries’ QNA
alongside its database of annual data. As a result, the APO 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).
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 analysesof the current economic situation. The first two measures are presented in the AQGM (with year-on-year
growth displayed as a default).

©2013 Asian Productivity Organization

The current version includes 21 Asian countries that publish QNA: China, Hong Kong, India, Indonesia, Iran,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 comparisons, the current
version includes 50 non-Asian countries, based on data available from the OECD.Stat and independent
publications by the respective statistical offices in those countries. The AQGM is updated at least once amonth, to reflect revisions and capture newly available data. Based on the AQGM, Figure B3.2 presents
year-on-year quarterly GDP growth and available quarter-on-quarter GDP growth for Asian countries, theUS, and EU15 from 2011Q4 to 2012Q4.

Figure B3.1 Views of Quarterly Economic Growth in Asian Countries by the AQGM
Source: Asian Quarterly Growth Map, January 2013.

continued on next page >

48

8

8

8

8

8
6

6

6

6

6
4

4

4

4

4
2

2

2

2

2
0

0

0

0

0
−2

−2

−2

−2

−2

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4−1−8

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

20

6
4

4

4

15

4
2

2

2

10

2
0

0

0

5

0
−2

−2

−2

0

−2

2

2

2

1

1

1

1

0

0

0

0

0

−2

−1

−1

−1

−1

2

2

2

2

2

1

1

1

1

1

0

0

0

0

0

−1

−1

−1

−1

−1

−2

−2

−2

−2

−2

−3

−3

−3

−3

−3

−4

−4

−4

−4

−4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4Compared to previous quarter
Compared to the same quarter in previous year

20

United Kingdom
%
3

Spain
%
3

Portugal
%
3

Italy
%
3

Ireland%3

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q43
2

2

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q443

42012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q44

3

6

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4438

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4410

48

Canada%5Germany%
5France%5US%5Turkey
%
12

−2
0
−12
0

1

0

3
−4
3

3
6
4
6

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4
6

Australia%
5

Vietnam%
9

Thailand%
12

Sri Lanka%
9Singapore
%
14
12
10
8
6
4
2
0
−2

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q4

2012Q4
2012Q3
2012Q2
2012Q1
2011Q4
2011Q3
2011Q2
2011Q1
2010Q46

46

Philippines%
8

Mongolia%
25

Malaysia
%
8

Korea
%
8

Japan
%
8

Indonesia
%
10

India
%
10

Hong Kong
%
10

ROC
%
10

China
%
10

Figure 34 shows the decomposition of the average annual economic growth by final demand for theperiods 1995–2000 and 2000–2011, respectively with Asia29 growing faster in the latter period than
the former (at 5.8% on average per annum compared with 4.1% as presented in Table 3, p. 18).30 The
earlier period was atypical in that it embodied the impact of the Asian financial crisis, and there weresome erratic contributions by the final demand components observed. On one hand, investment has

49©2013 Asian Productivity Organization
4.2 Demand-Side Growth Decomposition> continued from previous page

Figure B3.2 Quarterly Economic Growth in Asian Countries, 2010Q4 – 2012Q4

Source: Asian Quarterly Growth Map, January 2013.

4.2 Demand-Side Growth Decomposition

4 Expenditure

Indonesia
ThailandJapan
KuwaitBruneiHong Kong
Saudi Arabia
Philippines
Iran
EU15
Oman
PakistanBahrain
Australia
Bangladesh
US
TurkeyMyanmarKorea
Sri Lanka
Malaysia
Cambodia
India
ROC
Singapore
UAE
Vietnam
China
Qatar

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, for example, 6.7 and 4.8 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 the countries studied, averaging 8.9% per year, three-quarters of which was driven by net exports. Unlike thenature of growth in Qatar, China’s growth was more even, with all components making their fair sharesof positive contribution. Out of its average annual growth of 7.7%, 40.4% was contributed by household consumption, 17.7% by government consumption, 26.2% by
1995–2000%
investment, and 15.7% by net
10exports. This compares with av­
8
1.2
0.2 0.5
0.6
erage annual growths of 4.2% in
6 6.7 2.0
0.4 0.2
1.1
2.6 0.6 2.4
0.1
0.9 1.2
1.8
1.3
0.2
the US and 2.9% in EU15. The con1.5
4
0.9 0.6 4.8
1.6
0.6 0.1
1.4
2.7 1.6 1.0
0.0
0.4
0.6
0.9
0.8
0.2
0.4 0.0 0.4
1.1
0.3
4.0 1.5
0.5
0.2 2.0 0.5 0.2 0.1 1.4
0.1
0.9
tribution from household con4.6
0.4
0.3
0.4
0.8 1.5 3.4
2 1.8 3.1 3.5
3.4 3.5 3.7
0.4
3.1 3.0 0.1 2.3
0.2
2.5
3.0 0.0 0.3 2.9 3.2
2.3
2.9 1.9 2.5
2.0
1.7
1.5
1.6 0.2 0.5 2.4 0.4 0.5
1.0
1.3 1.7
1.1
sumption was 72.2% and 59.9%
0.4
0 −0.70.0
0.0−0.6 −0.2 −0.4 0.2 −0.6 −0.2 0.4 −0.1
−0.1
−0.1 −1.3−0.3 −0.7
−0.5
−0.4
−2.0
−2.4
−3.4
in the US and EU15, respectively,−2−4.8
whereas investment growth ac−4
counted for 38.2% and 32.7%−6of overall growth in the US and
EU15, respectively.

©2013 Asian Productivity Organization

2000–2011

%

12
10

1.4

2.5

8
6
4
2
0
−2

0.0 0.5

0.9

6.1

1.8
5.9 0.5

3.1 3.3

2.0

0.6 0.5 2.7

1.1

2.7

1.8

3.4 0.2

3.0

2.0
2.1 2.0
1.8
1.3 1.1 2.6
0.5
0.8 0.5
0.3
4.6 4.6
0.2 0.1
0.4 1.2 0.6 0.0 0.2 0.8
4.0 3.6 0.4
0.9 3.0 0.6
3.1
0.7 0.3
3.2
2.9
3.3 2.6 2.9 3.3 2.9
2.7 2.2 2.3
1.8
2.3 1.8 1.9 0.3 0.4 1.1
1.4
1.5
1.5
1.4 0.7
0.5 0.3−0.5−0.1−0.1−0.2−1.2−0.4−1.1−0.1 −1.8
−0.3−0.4−0.3−1.9 −1.1−1.4−1.2 −0.1 −1.7−0.4
−0.7
−2.8

7.5 1.3

6.8

1.0

0.9

0.4 3.2

0.3
1.8 0.8 1.1 0.5

1.2 1.0

0.3 0.6 1.0 0.3 0.7 2.2 0.5 0.8 1.3

−4
Japan
BruneiEU15
USAustralia
Saudi Arabia
UAE
Nepal
ROC
Hong Kong
ThailandOman
Korea
TurkeyKuwaitPakistan
Philippines
Malaysia
Indonesia
IranSingapore
Bangladesh
Sri Lanka
Bahrain
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 inthe fast-growing economies. For
example, investment contributed
5.9 percentage points in China,
2.5 percentage points in Myanmar, 3.1 percentage points in India, and 3.3 percentage points
in Vietnam. The role played byinvestment in China has strengthened, with its contribution to economic growth doubling between
1995–2000 and 2000–2011 from
26.2% to 54.9%, whereas the contribution of net exports dwindled from 15.7% to 4.2%. However,for Singapore and the ROC, theHousehold consumption
Investment

Government consumption
Net exports

Real GDP

Figure 34 Final Demand Contributions to Economic Growth,
1995–2000 and 2000–2011_ Decomposition: Average annual growth rate of GDP at constantmarket prices

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

30: The Törnqvist quantity index is adopted for calculating the growth of real GDP. Using this index, the growth of real GDP into the
products of contributions by final demands can be decomposed:
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 (p. 18).

50

4.2 Demand-Side Growth Decomposition

strength of net exports was the real economic story, accounting for 58.7% and 69.2% of their economic growth on average per year between 2000 and 2011, respectively (Figure 35). The reverse wastrue in India, where net exports swung away from making a positive contribution of 2.8% in the earlier period to being a drag on economic growth with a negative contribution of –9.9% in the period
2000–2011. In some of these economies, the contribution of household consumption to economic
growth was really squeezed; for example, from 40.4% in 1995–2000 to 28.9% in 2000–2011 in China,
from 39.2% to 27.2% in Singapore, and from 61.8% to 36.0% in the ROC. Also, in the latter period net
exports made negative contributions in countries such as Vietnam, Nepal, Cambodia, India, and mostof the oil-exporting countries.

4

In the 2000s, economic growth slowed in both the US and EU15 – from 4.2% on average per year in
1995–2000 to 1.5% in 2000–2011, and from 2.8% to 1.3%, respectively. In terms of contributions,household consumption increased from 72.2% to 88.6% and government spending from 5.9% to17.8% in the US over the two periods. Investment in the US took a plunge, however, from a contribution of 38.2% to –8.0% over the two periods although its net exports improved from –16.2% to 1.7%.
EU15 had a similar pattern, where the contribution of government spending nearly tripled over thetwo periods from 12.0% to 28.6%, squeezing out the contribution of investment by nine-tenths, whilehousehold consumption remained more or less stable. Its net exports also improved from –4.6%
to 12.6%.

51©2013 Asian Productivity Organization

Korea

Hong Kong

Singapore

ROC

Figure 38 shows how the contribution of economic growth by final demand varies across countries
and over time for the period 1970–2011. The immediate impact of the global financial crisis of 2007–2008 is represented in the data, although its far-reaching effects would have stretched well beyond
2011. Most countries felt an adverse impact in 2008 and 2009, with the exception of India where
growth rebounded strongly in 2009 from a slowdown in the previous year. The impact on the Asian
countries varied both in magnitude and in nature. Japan’s recession was particularly deep with theeconomy contracting by 1.1% and 5.6% in 2008 and 2009, respectively, compared with 2.0% growthin 2007, as shown in Figure 36. 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 10.9% in 2007 to 0.7% and –0.5%
in 2008 and 2009, respectively. Similarly,
growth in Hong Kong slowed from 6.2% in%2007 to 2.3% 2008 before moving into the120
negative zone of –2.8% in 2009. The correHousehold consumption
100
sponding real GDP growth figures for the80
ROC were 5.8% in 2007, 0.9% in 2008, andGovernment consumption
60–1.5% in 2009. India’s growth slowed from
Investment
10.2% in 2007 to 3.9% in 2008 before bounc40
ing back to 7.3% in 2009. In contrast, the20
Net exports
slowdown in China was more gradual but
0lasted longer – from 13.1% in 2007, growth
decelerated to 10.5% in 2010, and further
dipped to 9.4% in 2011. Most countries experienced a rebound (strongly in some cases) in
2010, but it was largely due to some tempoFigure 35 Final Demand Contribution Shares torary effects, which wore off and resulted in a
Economic Growth of the Asian Tigers, 2000–2011___Shares of final demand contributions to growth rate ofmore subdued growth trajectory in 2011. For
example, growth in Japan swung from 4.5%
GDP at constant market prices
in 2010 to –0.6% in 2011, and similarly from
Sources: Official national accounts in each country, including author
adjustments.
10.3% to 5.9% in India, from 13.3% to 5.2% in

4 Expenditure%15

2007–2008%15

2008–20092009–2010

%

14
12

10

10

5

5

2010–2011

%

10
8

10

6

8

4

6
0

0

−5

−5

−10

0

2

−10

−2

−2

−4

Investment

Net exports

EU15
US
Japan
India
China
Hong Kong
ROC
Korea
Singapore

Government consumption

0
EU15
US
Japan
India
China
Hong Kong
ROC
Korea
Singapore

EU15
US
Japan
India
China
Hong Kong
ROC
Korea
Singapore

EU15
US
Japan
India
China
Hong Kong
ROC
Korea
Singapore
Household consumption

2

4

GDP

Figure 36 Impacts of Global Financial Crisis and Recoveries, 2007–2011___Annual growth rates of GDP at constant market prices and contributions of final demands
Sources: Official national accounts in each country, including author adjustments.

Singapore, from 9.5% to 4.0% in the ROC, from 2.3% to 1.8% in the US and from 2.1% to 1.3% in EU15.
For Asia29, the figures were 8.0% in 2010 and 6.0% in 2011.

©2013 Asian Productivity Organization

The channels through which the adverse impact filtered through also varied across countries. Japan’srecession in 2009 was largely accounted for by a sharp fall in investment (3.9 percentage points) and,to a lesser extent, a fall in net exports (1.7 percentage points), while the 0.4% growth of government
spending canceled out the 0.4% fall in household consumption. Similarly, in the ROC, investment fell
by 4.9% in 2009, while the other components of final demand grew, albeit more slowly than it had
previously enjoyed. In Singapore, net exports and investment accounted for –7.7 percentage points
and 6.5 percentage points of the final demand growth, respectively, in 2008. The reverse was true in2009 with net exports accounting for 5.6 percentage points and investment –6.4 percentage points offinal 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. In the subsequent
years, investment growth softened and contributed to a slowdown in growth. Hong Kong also took ahard hit in terms of net exports in 2009, falling by 3.4 percentage points, while household consumption growth slowed considerably over two years before bouncing back to its normal range of 4–5%. In
the US and EU15, the vulnerability in 2009 was in investment and household consumption. Consumers were cautious with their spending as households repaired their balance sheets and job prospects
became insecure. Household consumption fell by 1.4 percentage points and 0.8 percentage points,
whereas investment fell by 3.6 percentage points and 3.9 percentage points in the US and EU15, respectively. In the subsequent years, there was no further retrenchment in these activities, which, however, still struggled to grow.
Japan was the only Asian country in which the global financial storm of 2007–2008 caused a deeper
retrenchment in its economy than the Asian financial crisis of 1997–1998 (Figure 37). 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 and consumption alsofell, 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 suffered52

4.2 Demand-Side Growth Decomposition

adversely in 2001 following the
burst of the dot.com bubble.

%

20
15
10

Economic restructuring is a grad5
ual process and can take a long0
time to establish. Some shifting in−5
the relative weight of the key driv−10
ers of growth may be emerging in−15
some countries, and is discernible−20
in data covering almost four dec­
ades. For example, in the ROC−25
and Hong Kong, the significant
role played by investment in theearly development stage has reHousehold consumption
Government consumption
treated and besides household
Investment
Net exports
GDP
consumption, net exports haveemerged as an important driver
Figure 37 Impacts of Asian Financial Crisis, 1997–1998
of economic growth in the 2000s.
___Annual growth rates of GDP at constant market prices and contribuIn contrast, investment has betions of final demands
come increasingly prominent in
Sources: Official national accounts in each country, including author adjustments.
determining economic growth inChina and India in the past two
decades as they undergo rapid development. In Japan, investment has faded as a key driver of economic growth since the beginning of the 1900s. In the US and EU15, economic growth is largely driven
by household consumption, followed by investment, over the economic cycle, while the contribution
from net exports tends to fluctuate. Government consumption, also, has been expanding proportionately more in some countries (such as EU15, Australia, China, and India) than others (Hong Kong,
Vietnam, and the ROC in recent years). Growth of government consumption in the US appears to be
more cyclical than in other countries.

4

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

53©2013 Asian Productivity Organization

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

It is difficult to understand the oil-exporting economies fully without analyzing the oil market in parallel. Its volatility can be clearly observed from Figure 38, with huge peaks and troughs, particularly inthe 1970s. The oil booms of the 1970s brought benefits, but the downturn hurt. Net exports remain
erratic, but overall volatility seems to have reduced in the past two decades. Qatar experienced thefastest GDP growth among the oil-exporting countries in recent years with very strong investment
growth, but its economy is still very dependent on oil and gas and related industries, which accounted
for 51% of its GDP in 2010 (Figure 67, p. 89) – roughly 80% of its export earnings, and 70% of government revenues in the 2000s.31 In contrast, Bahrain has diversified into a regional banking and financial
center and benefited from the regional boom in recent years. Even so, petroleum production andprocessing still accounted for 21.9% of its GDP in 2010 (Figure 67) – about 60% of export earnings,
and 75% of government revenues in the 2000s.32 The economic fortunes of these countries are therefore intimately tied with the rest of the world via their dependence 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 wellthey can diversify away from oil and gas while the stock of natural resources remains.

4 Expenditure%
60

Bahrain

%
20

50

15

40

10

30

20
10

0

10

0

−5

0

−10

−10

−10

−15

−20

%
15

−20
1971 1976 1981 1986 1991 1996 2001 2006 2011

Cambodia1971 1976 1981 1986 1991 1996 2001 2006 2011
%
20

China

−20

16

12

9

12

8

6

8

4

3

4

0

0

0

−4

−3

−4

−8

−6

−8

−12
1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

Hong Kong

%
12

India

1971 1976 1981 1986 1991 1996 2001 2006 2011

Indonesia

12
6

6

5

ROC

%
18

9

10

1971 1976 1981 1986 1991 1996 2001 2006 2011

%
16

12

%
15

Brunei

%
30

5

20

−30

Bangladesh

0
3
−6

0

0

−5
−10

−24

Iran

1971 1976 1981 1986 1991 1996 2001 2006 2011
%
10

18

8

12

6

6

Japan

12
6
0
−6

0

−12
−18

−2

−24

−4

−30

−6

−12
−18
−24

1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

KuwaitMalaysia

150
100
50

%
18

1971 1976 1981 1986 1991 1996 2001 2006 2011

12

75

6

50

0

25

−6

0

−12

−25

−150

−18

−50

−200

−24

−50
−100

Myanmar

%
12

12

10

8

8

4

6

0

4

−4

2

−8

0

−12

−2

−16

−4
1971 1976 1981 1986 1991 1996 2001 2006 2011

Household consumption

54−75
1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

Mongolia

%
100

0

%
16

Korea

2

−6

©2013 Asian Productivity Organization

1971 1976 1981 1986 1991 1996 2001 2006 2011
%
18

4

0

%
200

−18

−6
1971 1976 1981 1986 1991 1996 2001 2006 2011

%
24

−12

−3

Nepal

1971 1976 1981 1986 1991 1996 2001 2006 2011

Oman

%
40
30
20
10
0
−10
−20
−30

1971 1976 1981 1986 1991 1996 2001 2006 2011

Government consumption

Investment

1971 1976 1981 1986 1991 1996 2001 2006 2011

Net exports

Real GDP

4.2 Demand-Side Growth Decomposition%
12

Pakistan%
12

Philippines

9
8

20

6
10

3

4

0
0

0

−3

−10

−6

−4

−20

−9
−8

−12
1971 1976 1981 1986 1991 1996 2001 2006 2011%250

Saudi Arabia

200

−30

%
20

Singapore

Sri Lanka

%
18

15

4

12

10

100

1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

150

6

5

50
0

0

0

−50

−6

−5

−100
−150

−10

Thailand10−121971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

%
20

Qatar

%
30

%
90

UAE

1971 1976 1981 1986 1991 1996 2001 2006 2011

Vietnam

%
30
20

60

10

0
30

0

−10
0

−20

−30

−30

US

8

−20
1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

%
10

−10

%
6

EU15

Australia

%
8
6

4

6

4
2

4
2

2
0

0

0

−2
−2

−2
−4

−4
−6

−4
1971 1976 1981 1986 1991 1996 2001 2006 2011%151971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

Turkey

10
5
0
−5
−10
−15
1971 1976 1981 1986 1991 1996 2001 2006 2011

Household consumption

Government consumption

Investment

Net exports

Real GDP

Figure 38 Final Demand Decomposition of Real GDP Growth, 1970–201155©2013 Asian Productivity Organization

Sources: Official national accounts in each country, including author adjustments.
Note: Myanmar’s household consumption includes government consumption due to data limitations.

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 sustainable 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.

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, one quickly realizes the complexity in operationalizing
this notion to suit different purposes, especially in a world with data limitations. Consequently, there
are different measures of productivity for different purposes, and different estimation approaches anddefinitions subject to the data used. In the Databook, national accounts are the basis for productivity
estimates, and, in turn, growth accounting with the appropriate choice of index numbers is adopted
as estimation approach.33 Two productivity measures are presented in this chapter, namely labor productivity and TFP.
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 to allow for different work patterns across countries and across time.34 However, total actual
hours worked cannot be collated for all countries. In order to include all countries and define the Asian
country groups, the labor productivity measure in terms of GDP per worker is used in Section 5.1. As
workers in high-performing Asian countries tend to work longer hours on average than those in theUS, the worker-based labor productivity gaps, in this instance, probably cast the Asian countries in aparticularly favorable light. 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, andits direct link to per capita GDP performance. Section 3.2 looks at how the per capita GDP gap, between the US and 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 basedon a companionable definition, namely GDP per worker. Section 5.2 sees the focus shift to alternative
estimates of labor productivity measure, namely GDP per hour worked for some selected Asian countries. In Section 5.3, capital input is included as another key factor of production and the TFP estimates
are presented for 17 Asian countries and the US, based on the estimates of capital services (seeAppendix 3).

5.1 Per-Worker Measure of Labor Productivity

33: 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.
34: 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 official estimates for GDP atbasic prices in their national accounts, they are calculated based on available tax data. See Appendix 1 for the methods employedfor our calculations.
35: 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 precise ranking.

57©2013 Asian Productivity Organization

Figure 39 presents the cross-country comparisons of labor productivity levels in 2011, measured as
GDP per worker in US dollars. 35 The countries naturally bundle into groups. On this measure, the US isthe leading economy with Asia, Singapore and Hong Kong as close forerunners. The other two Asian5 Productivity

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, p.
31). Singapore and Hong Kong both achieved a laborproductivity level within −5% of the US in 2011. Given
data uncertainty, this difference is not deemed statistically significant. The ROC and Japan took the third andfourth places among the Asian group, with productivity levels at 19% and 31% below that of the US, respectively. Korea followed, with a gap of 35%. Iran, Turkey,
and Malaysia achieved productivity levels that were48%, 46%, and 36% of the US level, respectively. Thereafter, a number of countries from among the Asiagroup followed with labor productivity levels at lessthan 20% of the US, pulling down the average performance of the group to 17% for the APO20, 16% for
Asia29, and 11% for ASEAN. Bringing up the rear were
China and India, with productivity levels that were
14% and 9% of the US level, respectively.

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

93.8
92.0
90.2
76.6
74.6
70.5
63.3
58.7
44.8
42.7
33.3
19.5
15.6
15.4
15.1
14.5
14.4
13.5
12.3
11.7
10.7
9.5
9.2
8.5
8.3
8.1
5.5
5.0
4.4
3.6
3.4
3.0

Thousands of US dollars (as of 2010)

In the past decade, the APO20 as a group has achieved
0
20
40
60
80
100
little change in its labor productivity relative to that of
the US, stagnating at around 16%, while Asia23’s has
Figure 39 Labor Productivity Level byrisen from 11% to 15% (Table 8). Having been the
Per-Worker GDP, 2011___GDP at constant basic prices per worker,
leader in Asia, Japan started to fall behind the Asianusing 2005 PPP, reference year 2010
Tigers, when Hong Kong and Singapore caught up
and overtook it in labor productivity in 1991 and 1992,
Source: APO Productivity Database 2013.01.
respectively. In 2000, Hong Kong sustained a productivity gap of 18% with the US, but by 2011 the gap had
narrowed to around 4%. In contrast, the relative productivity level of Singapore against the US has
been slightly improved over the last ten years.

©2013 Asian Productivity Organization

In the past decade, the top eight countries have maintained their relative positions, although countries have been closing in on the region’s leader up to 2011 when Singapore’s labor productivity grewfaster than the rest. China and India are the two giant and fast-emerging economies in Asia. Chinabegan with one-third of India’s productivity levels in 1970; but four decades later it showed signs ofpulling ahead of India (Figure 40). China’s relative performance against the US moved up from 2%
in 1970 to 6% in 2000 and 14% in 2011, compared with the corresponding figures of 5%, 6%, and 9%
for India.36
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; in addition,

36: 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.

585.1 Per-Worker Measure of Labor Productivity

Table 8 Per-Worker Labor Productivity Levels, 1970, 1980, 1990, 2000, 2010, and 2011___GDP at constant basic prices per worker, using 2005 PPP, reference year 2010
1970

1980

(%)

26.7 100.0
25.4 95.1
24.3 90.9
19.8 74.2
11.9 44.5
11.0 41.2
9.1 34.0
8.9 33.5
6.8 25.4
4.0 14.9
3.8 14.4
3.6 13.6
3.6 13.5
2.5 9.5
2.5 9.5
0.8 3.2

Japan
Singapore
Hong Kong
Iran
ROC
Korea
Malaysia
Fiji
Philippines
Mongolia
Sri Lanka
Thailand
PakistanIndonesia
India
Bangladesh
Nepal
China
Myanmar36.4 100.0
34.3 94.3
32.9 90.3
28.8 79.0
21.0 57.8
14.4 39.5
13.9 38.3
10.5 28.7
8.0 22.0
5.8 15.9
5.8 15.9
5.0 13.9
4.3 11.8
4.1 11.1
2.9 7.9
2.3 6.3
1.5 4.2
1.3 3.4
0.8 2.1

Bahrain
KuwaitOman

78.8 294.8
320.4 1198.6
53.7 201.0

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei

72.0
125.2
73.1
156.7
113.5
234.8
255.8

Saudi Arabia 113.0 422.7
UAE
63.8 238.5

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

197.9
344.1
200.9
430.5
311.9
645.2
702.8

(regrouped)(regrouped)

7.2 26.8
4.1 15.4
4.4 16.6
4.5 16.8
2.9 10.7
3.4 12.7
130.5 488.0

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

8.7 24.0
5.2 14.2
5.8 15.9
6.1 16.8
3.0 8.1
4.4 12.1
128.1 351.8(reference)(reference)

1990

(%)

Iran
Japan
Singapore
Hong Kong
ROC
Fiji
Malaysia
Korea
Philippines
Sri Lanka
Mongolia
PakistanThailandIndonesia
India
China

Japan
Hong Kong
Singapore
ROC
Iran
Korea
Malaysia
Fiji
ThailandPhilippines
Sri Lanka
Mongolia
PakistanIndonesia
India
Bangladesh
Nepal
Lao PDR
Vietnam
China
Myanmar2000(%)

52.3 100.0
51.9 99.4
51.2 98.0
34.7 66.3
28.8 55.1
27.1 51.8
18.4 35.1
11.0 21.1
7.8 15.0
7.2 13.7
7.0 13.5
6.4 12.3
6.2 11.8
5.1 9.7
3.5 6.7
2.4 4.6
2.2 4.2
2.1 4.0
2.0 3.9
2.0 3.8
0.8 1.5

Singapore
Hong Kong
Japan
ROC
Korea
Iran
Malaysia
ThailandFiji
Sri Lanka
Philippines
Pakistan
Mongolia
Indonesia
China
India
VietnamBangladesh
Lao PDR
Nepal
Cambodia
Myanmar2010(%)

75.6 100.0
64.5 85.3
57.6 76.1
55.4 73.2
42.9 56.7
32.0 42.3
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
4.7 6.2
3.4 4.5
3.4 4.4
3.0 4.0
2.7 3.6
2.3 3.0
1.2 1.6

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

2011

(%)

90.2 100.0
88.5 98.1
73.2 81.1
63.5 70.4
57.7 64.0
44.0 48.8
32.7 36.2
15.5 17.2
13.6 15.1
12.4 13.7
12.1 13.5
10.0 11.1
9.4 10.4
9.0 10.0
8.4 9.3
8.2 9.1
5.3 5.9
4.8 5.3
4.3 4.7
3.4 3.8
3.2 3.6
3.0 3.3

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

92.0 100.0
90.2 98.1
74.6 81.1
63.3 68.8
58.7 63.8
44.8 48.7
33.3 36.2
15.4 16.7
14.4 15.6
13.5 14.7
12.3 13.4
11.7 12.7
9.5 10.3
9.2 10.0
8.5 9.3
8.3 9.1
5.5 6.0
5.0 5.5
4.4 4.8
3.6 3.9
3.4 3.6
3.0 3.3

Bahrain
53.4 102.1
Kuwait50.9 97.3
Oman
78.2 149.6
Qatar
99.9 191.1
Saudi Arabia 62.7 119.9
UAE
146.2 279.8
Brunei123.5 236.3

Bahrain63.1 83.5
Kuwait99.0 130.9
Oman
65.7 86.9
Qatar
133.5 176.5
Saudi Arabia 70.0 92.6
UAE
126.1 166.7
Brunei111.2 147.0

Bahrain
43.8 48.5
Kuwait74.4 82.5
Oman
65.4 72.5
Qatar
111.1 123.2
Saudi Arabia 66.8 74.1
UAE
97.6 108.2
Brunei93.6 103.8

Bahrain
42.1 45.8
Kuwait75.4 82.0
Oman
55.3 60.1
Qatar
126.2 137.2
Saudi Arabia 63.6 69.2
UAE
96.8 105.2
Brunei92.3 100.4(regrouped)(regrouped)(regrouped)(regrouped)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

10.9 20.8
6.4 12.2
6.8 12.9
7.6 14.4
3.6 6.9
5.8 11.0
72.6 139.0(reference)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

12.5 16.6
8.8 11.6
9.2 12.2
10.9 14.4
4.8 6.4
7.7 10.2
83.7 110.7(reference)

US
EU15

50.8 189.9
36.0 134.5

US
EU15

56.3 154.8
46.4 127.6

US
EU15

65.3 124.9
55.2 105.7

Australia

44.0 164.8

Australia

50.5 138.8

Australia
Turkey55.9 106.9
23.7 45.3

US
EU15
EU27
Australia
TurkeyAPO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

15.4
13.9
14.5
18.5
7.8
10.4
75.9

17.1
15.4
16.1
20.5
8.7
11.6
84.1

(reference)

78.6 103.9
65.2 86.3
58.9 77.9
68.8 91.0
30.0 39.7

US
EU15
EU27
Australia
TurkeyAPO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

15.6
14.5
15.1
19.5
8.1
10.7
73.8

5

17.0
15.8
16.5
21.2
8.8
11.6
80.3

(reference)

93.0 103.0
69.8 77.4
64.4 71.4
75.5 83.7
42.0 46.5

US
EU15
EU27
Australia
Turkey93.8 102.0
70.5 76.7
65.3 71.0
76.6 83.3
42.7 46.4

Qatar has become the fourth-largest exporter of liquefied natural gas. In contrast, Bahrain has thesmallest 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, p. 104). 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 3.0% a year, except in the UAE andQatar where the population grew at 7.6% and 6.9%, respectively. The working-age population has
been expanding accordingly. Employment is erratic from one year to another, and this will be reflected in the labor productivity figures.

59©2013 Asian Productivity Organization

Unit: Thousands of US dollars (as of 2010).
Source: APO Productivity Database 2013.01.

5 Productivity

Box 4

Turning Point in China

The Lewis model (Lewis, 1954) or the Fei-Ranis model (Fei and Ranis, 1964), which established development economics as a respectable academic discipline in the late 1950s and 1960s, proposed the conceptof a turning point where a developing economy transforms itself from an unskilled-labor-abundant economy with seemingly unlimited supply of labor to a labor-scarce industrial economy. The Chinese economy
seems to pass by its turning point in the latter half of the 2000s.
Figure B4.1 presents the price of labor relative to capital in China, Japan, and the Asian Tigers. Price of labor
is defined as the average wage (total labor compensation, including our estimates of wages for selfemployed and family workers, over total hours worked) and price of capital is estimated by the ex-post
approach for measuring user cost of capital in APO Productivity Database 2013 (see Appendix 3). The relative price index of labor/capital is normalized as 1.0 in 1970 in each country.
In Japan the prices of labor increased at the beginning of the 1970s, and for Korea and ROC the late1980s and the beginning of the 1990s, respectively. In these periods, China’s low price of labor could
be a main source of superior price competitiveness in labor-intensive manufacturing. The turning
point is found at around 2008, in which the price oflabor started to increase sharply relative to capital.

©2013 Asian Productivity Organization

Such a turning point emerges when a country
makes effective movements of labor from agricultural/rural/informal sectors to industrial/urban/
formal sectors. Although it is claimed that the aggravation of income disparity is a serious concern,
the alleviation of poverty in China are certainly
great achievements. The Chinese economy has
overcome its first-round of economic development issues and now faces new challenges tomove beyond the upper middle-income plateau.

When labor productivity growth is comparedhowever, the ranking of countries is substantiallyreshuffled (Table 9). In the 2000s there was aspurt in labor productivity growth among lowincome countries. While they were scatteredaround the table in the earlier periods, by 2000–
2005 the seven countries with the fastest laborproductivity growth were all from Group-L4 (asdefined in Table 6, p. 28); and in the latest period
2005–2011, five out of the top seven were fromGroup-L4 and two from Group-L3. Among them,
China has been sustaining rapid productivity
growth in the past two decades; its growth accelerated to an average of 10.2% a year in 2005–2011 from 7.1% a year in 1995–2000 and 8.6% a
year in 2000–2005. This compares with India’s at
7.7%, 3.4%, and 3.5% over the same periods. Labor productivity growth amongst the Asian Tigers was steady, ranging from 2.6% to 3.3% on

60

1970=1.0
35
30
25
20

China
ROC
Hong Kong
Korea
Singapore
Japan

15
10
5
0
1970 1975 1980 1985 1990 1995 2000 2005 2010

Figure B4.1 Price of Labor Relative to Capital in China, Japan, and the Asian Tigers,
1970–2011
Sources: APO Productivity Database 2013.01.

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 40 Labor Productivity Trends of China
and India, 1970–2011___GDP at constant basic prices per worker, using
2005 PPP, reference year 2010
Source: APO Productivity Database 2013.01.

5.1 Per-Worker Measure of Labor Productivity

Table 9 Labor Productivity Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2011___Average annual growth rate of GDP at constant basic prices per worker, using 2005 PPP
1990–1995
KuwaitChina
Thailand
Malaysia
Indonesia
Vietnam
ROC
Korea
Cambodia
Singapore
Sri Lanka
Hong Kong
Pakistan
MyanmarLao PDR
Bahrain
Bangladesh
India
Nepal
Iran
Saudi Arabia
Japan
Qatar
BruneiFiji
Philippines
Mongolia
UAE
Oman

1995–2000

13.1
10.6
8.2
6.6
6.5
5.2
5.2
5.0
4.3
4.1
4.1
3.7
3.5
3.3
3.3
3.0
2.9
2.6
2.4
1.4
0.6
0.6
0.3
−0.2
−0.4
−0.4
−1.3
−3.7
−9.3

(regrouped)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

China
Oman
Myanmar
Qatar
Vietnam
Korea
ROC
Lao PDR
Bangladesh
Singapore
Cambodia
India
Mongolia
Philippines
Nepal
Sri Lanka
Saudi Arabia
Japan
Fiji
Malaysia
Iran
UAE
Hong Kong
ThailandBahrainPakistan
KuwaitIndonesia
Brunei

2000–2005

7.1
5.8
5.6
5.5
4.7
4.2
4.1
3.9
3.9
3.7
3.4
3.4
2.5
1.9
1.7
1.7
1.6
1.3
1.2
0.9
0.7
0.7
0.6
0.4
0.4
0.3
0.2
−1.4
−1.9

(regrouped)

1.9
3.8
3.7
4.1
2.7
5.2
0.7

(reference)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

1.5
2.0

Australia
Turkey

2.1
1.3

US
EU15
EU27
Australia
Turkey2005–2011

10.6
8.6
4.8
4.1
3.6
3.6
3.5
3.5
3.3
3.2
3.1
3.0
3.0
2.9
2.7
2.6
2.5
2.0
1.9
1.5
1.3
1.1
0.9
0.5
−0.2
−0.7
−1.2
−1.8
−4.8

(regrouped)

1.0
2.6
2.6
3.2
3.0
0.6
2.2

(reference)

US
EU15

Myanmar
China
VietnamLao PDR
Cambodia
Indonesia
Iran
India
Hong Kong
Oman
Singapore
Malaysia
Thailand
Korea
MongoliaROC
Sri Lanka
Pakistan
Bangladesh
Fiji
Japan
Philippines
KuwaitNepal
Saudi Arabia
Qatar
BruneiUAE
Bahrain
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC
US
EU15
EU27
Australia
Turkey1990–2000

10.2
9.2
7.7
5.1
5.0
4.9
4.6
4.2
3.1
3.0
3.0
3.0
2.9
2.8
2.7
2.1
1.3
1.0
0.6
0.4
0.4
−0.4
−0.7
−2.2
−2.6
−3.0
−3.3
−3.3
−6.6

(regrouped)

1.4
3.8
3.7
4.6
3.1
3.2
−0.1

(reference)

2.3
1.4
1.6
2.1
3.4

China
MyanmarIndia
Lao PDR
Mongolia
Sri Lanka
Cambodia
VietnamHong Kong
Korea
ROC
Bangladesh
IranIndonesia
Philippines
Thailand
Nepal
Malaysia
Japan
Singapore
PakistanFiji
Saudi Arabia
BruneiBahrain
Qatar
UAE
Oman
KuwaitAPO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC
US
EU15
EU27
Australia
Turkey2000–2011

8.9
6.7
5.0
4.7
4.6
4.5
4.3
3.9
3.7
3.7
3.6
3.4
3.0
2.9
2.9
2.6
2.2
2.0
1.9
1.7
1.1
1.1
1.0
0.8
0.6
0.4
−1.0
−1.5
−1.7

(regrouped)

2.8
5.5
5.3
6.1
6.5
2.8
−1.9

(reference)

2.1
0.9
1.2
1.3
5.9

China
KuwaitVietnam
ROC
Korea
MyanmarThailandSingapore
Malaysia
Cambodia
Lao PDR
Bangladesh
India
Qatar
Sri Lanka
Indonesia
Hong Kong
Nepal
PakistanBahrainSaudi Arabia
Iran
Japan
Philippines
Mongolia
Fiji
Brunei
UAE
Oman
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC
US
EU15
EU27
Australia
Turkey

9.9
9.4
5.6
4.6
4.5
4.1
3.8
3.7
3.2
3.2
3.2
3.0
2.8
2.5
2.4
2.0
1.9
1.8
1.2
1.0
0.9
0.6
−0.1
−0.5
−1.7
−1.8
−2.6
−2.9
−3.7

5

(regrouped)

1.4
3.2
3.1
3.6
2.9
2.9
1.4

(reference)

1.3
0.5
0.6
0.6
0.8

Myanmar
China
India
Lao PDR
Vietnam
Cambodia
Mongolia
Sri Lanka
IranIndonesia
Hong Kong
Korea
ROC
ThailandBangladesh
Malaysia
Philippines
Singapore
Pakistan
Japan
Nepal
Fiji
Oman
Saudi Arabia
Brunei
Qatar
UAE
KuwaitBahrain
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC

2.1
4.6
4.5
5.3
4.8
3.0
−1.0

(reference)

1.9
1.7
1.6
2.1
2.4

US
EU15
EU27
Australia
Turkey

1.7
0.7
0.9
0.9
3.4

average a year in 2000–2005. This performance was sustained in 2005–2011, except for in Singapore.
While Singapore’s average annual productivity growth slowed significantly to 0.4%, the others enjoyed growth of about 3.0% in 2005–2011. The 2000s were an era when labor productivity deteriorated in GCC countries. The decline accelerated from −0.1% to −1.9% between the two halves of the
2000s.
As a group, Asia23 achieved the highest labor productivity growth in recent years, reaching 5.5% on
average a year in 2005–2011, up from 3.8% in 2000–2005. Within Asia, labor productivity growth has
been accelerating in both South Asia and East Asia, to 6.5% and 6.1% in 2005–2011, respectively.
South Asia displayed a newfound vigor in recent years considering that, to date, labor productivity

61©2013 Asian Productivity Organization

Unit: Percentage.
Source: APO Productivity Database 2013.01.

5 Productivity

US=100
100
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 41.1: Group-C1 Countries

Figure 41.2: 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
20

Fiji
Iran
Philippines
Australia
Turkey101001970 1975 1980 1985 1990 1995 2000 2005 201001970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 41.3: Group-C3 Countries

Figure 41.4: Group-C4 Countries

Figure 41 Labor Productivity Level Relative to the US, 1970–2011___Indices of GDP at constant basic prices per worker, using 2005 PPP
Source: APO Productivity Database 2013.01.

©2013 Asian Productivity Organization

growth had been traditionally faster in East Asia. In contrast, average annual productivity growth in
the US slowed rapidly to 1.3% between 2005 and 2011, after a decade of over 2.0% growth a year. The
EU15 shows signs of weakening as well, slowing in every successive period from 2.0% in the first halfof the 1990s to 0.5% in the most recent period 2005–2011. Japan’s labor productivity growth behaved
closer to that of other mature economies. Having managed to grow at 1.3% on average a year for a
decade in 1995–2005, labor productivity growth in Japan has slowed to 0.6% per year on average
since 2005.
Figure 41 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 faster with the US in per capita GDP (Group-C1) arealso faster catching up in labor productivity (Figure 41.1). Similarly, countries with deteriorating relative per capita GDP (Group-C4) also present signs of deterioration or of little change against the US in
terms of labor productivity (Figure 41.4).
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% in 1970 to

62

5.2 Per-Hour Measure of Labor Productivity

within 5% in 2011 (Figure 41.1 and Figure 41.2). Similarly, the ROC and Korea have reduced a gap ofaround 80% initially to 20% and 40% by 2011, respectively (Figure 41.1). Malaysia has been making
steady progress, raising its relative productivity level from 18% that of the US in 1970 to 35% in 2011
(Figure 41.2). The rest of the countries in these two groups all display an initial relative labor productivity level of below 10%, but have shown signs of a strong and promising start in their catch-up process
in the past decade.37

5Countries that have managed modest catch-up with the US (Group-C3) or have a declining per capita
GDP against the US (Group-C4) are also those with stagnant or deteriorating relative labor productivity. Japan is the only high-income Asian country in this group, while the rest (except Iran) are all lowincome countries with per capita GDP less than 20% that of the US. Japan showed strong catch-up
behaviors in the earlier period, with relative labor productivity peaking at 81% that of the US in 1991,
and since then the gap has widened again to over 30% in 2011. Similarly EU15, a reference economy
with high income, has seen its productivity gap double against the US since 1995, from 13% to 25% in
2011, whereas the low-income countries have managed little catch-up (Figure 41.3) or a declining
relative productivity level (Figure 41.4). Iran (a Group-L2 country) experienced a drastic decline in its
relative labor productivity from its former peak of 77% in 1976 to 38% in 1988, before recovering to
48% in 2011.

5.2 Per-Hour Measure of Labor Productivity
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 17 Asian countries, although the quality of the estimates may vary considerably across countries.38
Figure 42 shows how the productivity gap against the US in 2011 varies depending on which measureof 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 eleven of these countries, theadjustments 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 16–27 percentage points for the four Asian Tigers (Korea, theROC, Singapore, and Hong Kong). Europeans generally work fewer hours. This is reflected in comparisons on hourly labor productivity showing EU15 in a more favorable light against the US, albeit
only marginally.

37: Among these countries, the impact of the Asian financial crisis of 1997–1998 in temporarily stalling the progress of Thailand andIndonesia can be clearly seen. They are slowly recovering lost ground.
38: Cross-country comparisons of hours worked are notoriously difficult, not least because harmonized data is 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 the publications may have been constructed based on different methodologies. Some countries only
published 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 estimated 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 Appendix 4 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 42.

63©2013 Asian Productivity Organization

Based on GDP at constant basic prices per hour worked, US labor productivity has been able to sustain
a big lead over even the Asian high performers (Table 10). In 1970, the US productivity level was

−20
−40

−38

−50

−52

−60

−65

−65

−70

−55
−60

−38

−31

−32
−35

Australia

−2

EU15

−4

−21

−30

−19
−21 −20−27 −25

−54

−74

−80
−90
−100

Singapore−10

Hong Kong

Japan

ROC

Turkey

Korea

Iran

Malaysia

ThailandSri Lanka

China

Philippines

Indonesia

India

Pakistan0Vietnam%Bangladesh

nearly 2.5 times that of the Asianleader, Japan. This gap was reduced to around 33% in 1990.
Since 1990, Japan’s pace in closing the gap has slowed. By 2011, asizable gap of 35% still remained.
The gap between the US and the
Asian leader of the past decade(i.e., Singapore) has been persistent at around 30%. This is in contrast with the picture painted by
the per-worker productivity measure, based on which the Asianleaders (Singapore and HongKong) have almost closed the gap
with the US (Figure 41, p. 62).40
EU15’s lead over the Asian leader

Cambodia

5 Productivity−96−98 −95−97 −94−96−91 −91 −90−93 −90−92−94 −93

Per worker GDP−83 −85−86−90 −88 −88

Per hour GDP

Figure 42 Labor Productivity Gap by Per-Worker and PerHour GDP Relative to the US, 2011___GDP at constant basic prices per worker and hour, using 2005 PPP
Source: APO Productivity Database 2013.01.

Table 10 Per-Hour Labor Productivity Levels, 1970, 1980, 1990, 2000, 2010, and 2011___GDP at constant basic prices per hour, using 2005 PPP, reference year 2010
1970
Japan
Singapore
IranHong Kong
ROC
Malaysia
Korea
Philippines
Sri Lanka
Thailand
PakistanIndonesia
India
China

Japan
Singapore
Hong Kong
Iran
ROC  
Malaysia
Korea
Philippines
Sri Lanka
ThailandIndonesia
Pakistan
India
Bangladesh  China28.6 238.0

1990

(%)

17.6 100.0
16.1 91.8
13.1 74.8
11.8 67.4
8.8 49.9
6.3 35.8
5.2 29.7
3.6 20.3
2.9 16.6
2.3 13.1
2.0 11.5
1.9 10.6
1.3 7.4
1.1 6.1
0.6 3.2(reference)(reference)

US

1980

(%)

12.0 100.0
11.0 91.6
11.0 91.6
7.7 64.1
4.9 41.0
4.1 34.2
3.2 26.9
2.9 24.2
2.5 21.0
1.6 13.7
1.5 12.8
1.3 10.6
1.2 9.7
0.4 3.2

Japan
Singapore
Hong Kong
ROC  
Iran
Korea
Malaysia
Sri Lanka
ThailandPhilippines
PakistanIndonesia
India
Bangladesh  
ChinaVietnam2000(%)

25.9 100.0
22.9 88.4
22.2 85.8
15.1 58.2
11.8 45.7
9.9 38.3
8.2 31.6
3.6 13.9
3.6 13.8
3.3 12.7
2.6 10.2
2.5 9.8
1.6 6.1
1.2 4.6
0.9 3.5
0.8 3.2(reference)

SingaporeJapan
Hong Kong
ROC  
Korea
Iran
Malaysia
ThailandSri Lanka
Philippines
Indonesia
Pakistan
China
India
Bangladesh  Vietnam
Cambodia(reference)US

33.1 188.3

US38.6 149.1

Australia

27.5 156.8

Australia
Turkey31.3 120.9
12.7 49.1

US
EU15
Australia
Turkey2010(%)

33.2 100.0
31.6 95.2
28.2 85.0
24.8 74.6
16.7 50.3
13.2 39.7
11.4 34.3
5.3 15.9
4.8 14.4
3.6 11.0
3.3 10.1
3.2 9.5
2.2 6.6
2.1 6.5
1.7 5.0
1.4 4.1
0.9 2.8

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

46.5 139.9
39.8 119.7
38.6 116.3
15.5 46.6

US
EU15
Australia
Turkey2011(%)

40.4 100.0
37.1 92.0
36.6 90.8
34.8 86.1
25.3 62.7
19.7 48.8
14.2 35.2
6.8 16.8
6.8 16.8
5.6 14.0
4.5 11.0
4.0 9.9
3.8 9.4
3.6 9.0
2.3 5.6
1.8 4.5
1.4 3.4

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

42.0 100.0
40.4 96.2
36.6 87.3
35.5 84.6
26.5 63.0
20.1 48.0
14.5 34.5
7.2 17.1
6.7 16.0
6.1 14.6
4.4 10.4
4.2 10.0
3.9 9.4
3.6 8.7
2.3 5.6
1.9 4.4
1.4 3.2(reference)

56.1 139.1
44.1 109.2
44.6 110.5
22.4 55.4

US
EU15
Australia
Turkey56.3 134.2
44.6 106.4
45.1 107.6
22.7 54.2©2013 Asian Productivity Organization

Unit: US dollar (as of 2010).
Source: APO Productivity Database 2013.01.

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% 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% of the labor productivity gap in 2004, while non-IT-capital deepening (defined by capital input per unit of labor input) accounts for 37.3%. In the next section, the gap in labor productivity “growth” among countries is analyzed, without the levelcomparisons of capital deepening and TFP due to lack of data.

645.2 Per-Hour Measure of Labor Productivity

was around 20% in 2000, but rapidly eroded
to around 10% by 2011.

Thousands of US dollars (as of 2010)

The levels of labor productivity for the top fivecountries – Japan and the four Asian Tigers –maintained their relative positions for almost
four decades. The progress of labor productivity
in these countries during 1970–2011 is shown in
Figure 43. Within four decades, GDP per hour has
roughly tripled for the top three economies,
namely Japan, Singapore, and Hong Kong, andthe gap among them has literally disappeared.
They were ahead of the ROC and Korea by 10.0%
and 30.0%, respectively, in 2011, despite the
duo’s effort in catching up with Japan by 2.1%
and 2.4% a year on average, respectively, over30

1970−2011

%

10

40
ROC
Hong Kong
Japan
Korea
Singapore

20

5

10

0
1970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 43 Labor Productivity Trends in Japanand the Four Asian Tigers, 1970–2011___GDP at constant basic prices per hour, using 2005
PPP, reference year 2010
Source: APO Productivity Database 2013.01.

1970−1990

1990−2011
9.1

8
6.8

6

5.1

5.6 5.6
4.8

4

4.5

3.4 3.3 3.2

3.1 3.0 2.9

2.72.6 2.62

3.9 3.8 3.7

4.9 4.7
4.3
3.5 3.5
2.7

2.1
1.7 1.5 1.5 1.5

1.0

4.1
3.3 3.2

2.2

1.8 1.5

1.5

1.1

0.7 0.6

3.0 2.9 2.8

2.8 2.7 2.5

2.4

2.1

1.8 1.7 1.7 1.6

1.3

0.4 0.3

Philippines
PakistanJapan
Australia
US
BangladeshIndonesia
Iran
Malaysia
TurkeyHong Kong
Singapore
ThailandCambodia
Sri Lanka
ROC
India
Korea
Vietnam
China

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

Philippines
Bangladesh
Iran
Australia
US
Pakistan
Sri Lanka
TurkeyJapan
Indonesia
India
Malaysia
Cambodia
Singapore
ThailandHong Kong
Vietnam
ROC
Korea
China

0

5.3
4.3

4.0

Figure 44 Labor Productivity Growth, 1970–2010, 1970–1990, and 1990–2011___Average annual growth rate of GDP at constant basic prices per hour
Source: APO Productivity Database 2013.01.

1970−2011
4 3.8

2
1
0

3.6
3.2

3.0

2.7 2.6

2.5 2.4

2.3 2.3 2.3

2.2 2.2

1.9

3.5 3.4

3.2 3.1 3.1 3.1

1.7 1.7 1.7

3.0

1990−2011
3.3

2.7 2.7 2.7 2.6

2.6 2.5

2.9
2.6

2.3

2.4 2.4 2.3

1.7

2.2

2.1 2.0
1.3 1.2 1.2

1.1
0.6

1.1

0.8 0.8

0.6

0.4

−0.1
−0.8

−1

Japan
Korea
US
China
ROC
Hong Kong
Fiji
ThailandMongolia
Sri Lanka
India
VietnamIndonesia
Philippines
Iran
Pakistan
Malaysia
SingaporeJapan
US
Hong Kong
Vietnam
IranPakistan
India
ROC
Sri Lanka
Mongolia
Philippines
Korea
ThailandChina
Fiji
Malaysia
Indonesia
SingaporeJapan
US
Hong Kong
Korea
ROC
China
Mongolia
Thailand
VietnamFiji
Sri Lanka
India
Iran
Pakistan
Philippines
Indonesia
Malaysia
Singapore

Figure 45 Labor Input Growth, 1970–2010, 1970–1990, and 1990–2011___Average annual growth rate of total hours worked
Source: APO Productivity Database 2013.01.

65©2013 Asian Productivity Organization

3

1970−1990

4.4%

5 Productivity

Table 11 Labor Productivity Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2011___Average annual growth rate of GDP at constant basic prices per hour, using 2005 PPP
1990–1995
China
ThailandIndonesia
Malaysia
Korea
Cambodia
ROC
VietnamHong Kong
Sri Lanka
Singapore
India
Pakistan
Bangladesh
Japan
Iran
Philippines

1995–2000
10.6
7.4
6.5
6.0
5.5
5.5
5.4
5.2
4.6
4.2
3.8
3.6
3.2
2.5
2.0
1.4
0.0

(reference)

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

2000–2005
7.1
4.9
4.8
4.5
4.1
3.7
2.5
2.0
2.0
1.6
1.4
0.7
0.7
0.6
0.4
0.2
-1.1

(reference)

US

1.4

Australia
Turkey

2.0
1.2

US
EU15
Australia
TurkeyChina
Vietnam
Cambodia
Korea
Iran
India
Indonesia
Hong Kong
ROC
Malaysia
ThailandSingapore
PakistanJapan
Sri Lanka
Philippines
Bangladesh

2005–2011
8.6
6.7
4.0
4.0
3.7
3.6
3.2
3.1
3.0
3.0
2.9
2.7
2.3
1.8
1.7
1.3
-0.5

(reference)

2.3
1.8
2.3
2.8

US
EU15
Australia
TurkeyChina
India
Sri Lanka
Korea
Iran
ROC
Hong Kong
Cambodia
VietnamBangladesh
Philippines
Singapore
Thailand
Malaysia
Indonesia
Japan
Pakistan

1990–2000
9.9
7.1
5.3
4.4
4.0
3.5
3.4
3.2
3.2
2.2
1.9
1.6
1.6
1.5
1.1
0.9
0.4

(reference)

2.4
1.3
1.9
5.9

US
EU15
Australia
TurkeyChina
Korea
Vietnam
ROC
ThailandSingapore
Malaysia
Bangladesh
India
Sri Lanka
Cambodia
Indonesia
Hong KongJapan
Pakistan
IranPhilippines

2000–2011
8.9
5.2
5.0
5.0
3.9
3.7
3.3
3.3
3.0
2.8
2.7
2.7
2.4
2.0
1.9
1.1
1.0

(reference)

1.2
0.9
1.0
1.5

US
EU15
Australia
TurkeyChina
India
Vietnam
Korea
Iran
Sri Lanka
Cambodia
ROC
Hong Kong
Thailand
Malaysia
Singapore
Indonesia
Philippines
Japan
Pakistan
Bangladesh

9.3
5.5
4.8
4.2
3.9
3.7
3.6
3.3
3.3
2.2
2.2
2.1
2.1
1.6
1.3
1.3
1.0

(reference)

1.9
1.8
2.1
2.0

US
EU15
Australia
Turkey

1.7
1.1
1.4
3.5

Unit: Percentage.
Source: APO Productivity Database 2013.01.
Note: The annual average growth rates for Cambodia and Vietnam during 1990–1995 replicate their annual average
growth rates of 1993–1995 due to absent data.

the past four decades. If they could maintain this effort at the same pace, it would take the ROC two
years, and Korea 14 years to finally draw level with Japan.

©2013 Asian Productivity Organization

Over the past four decades, hourly labor productivity growth ranged from 1.0% (the Philippines) to
6.8% (China) on average per year, compared with that of the US at 1.7% and Australia at 1.5% (Figure44). Among the 16 Asian countries compared, only Bangladesh, Iran, and the Philippines grew slower
than the US. Between the two sub-periods (i.e., 1970–1990 and 1990–2011), there is a notable deceleration in the hourly productivity growth for nine out of 16 Asian countries: for example, 2.5 percentage points and 2.1 percentage points were shaved off productivity growth in the earlier period inHong Kong and Japan, respectively. Seven countries managed to accelerate their productivity improvement after 1990. Among these, China’s performance is the most outstanding, with productivity
growth more than doubling from 4.3% to 9.1% between the two sub-periods.
The deceleration of labor productivity growth in most countries between the two sub-periods, reflect
weaknesses in output growth. Figure 45 shows that all countries except Pakistan experienced a slowdown in hours-worked growth between the sub-periods, which should have worked to boost laborproductivity growth, all other things being equal.41 This implies that output growth must have been
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% a year on average in thelatter period, from 3.2% in the previous period. Japan was the only economy to experience an
41: By definition, positive labor productivity growth occurs when output grows faster than labor input. Figures 44 and 45 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.

665.2 Per-Hour Measure of Labor Productivity

actual fall in labor input in the
period 1990–2011. This served tocompensate for a sluggish output growth during said period,
and to sustain a positive labor productivity growth of 1.7% a year
on average.

Labor productivity gap in 2011 relative to Japan(Japan's level in 2011=1.0)

Singapore
Hong Kong

1.1
Japan (1885−2011)
1.0

ROC

0.9

5

0.8
0.7

Korea

One can identify where countries are today in terms of their hourly productivity performance against
a backdrop of Japan’s historical experience.43 Figure 46 traces the long-term path of Japan’s per-hourlabor productivity for the period 1885–2011 along the red line, expressed as relative to Japan’s 2011
level (set equal to 1.0). A structural break is observed during World War II when output collapsed.
Countries’ relative hourly productivity levels against Japan in 2011 are then mapped against Japan’s
growth experience (as circles). By so doing, a corresponding year can be located when Japan’s hourly
productivity level was the closest to that of the country in question. The two countries (i.e., Cambodia
and Bangladesh) with the lowest hourly productivity in 2011 see levels corresponding to Japan’s in
the 1900s. This means that even if they manage Japan’s long-term productivity growth of 2.9% on
average per year, it will still take them over a century to catch up with the Asian leader’s current

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 mindful that level comparisons of productivity among countries and over periods, are subject to a great degree of data uncertainty, they should provide a rough sketch of the productivity divergence in Asia.

67©2013 Asian Productivity Organization

Table 11 looks more closely at the
0.6
latter sub-period and provides
Iranthe growth rates of per hour0.5
based labor productivity since
Malaysia
0.4
1990. The growth patterns of individual countries generally follow
0.3
their counterparts closely in perPhilippines
0.2
Thailand
India
China
worker productivity growth as ilSri Lanka
Indonesia
lustrated in Table 9, but in some
0.1
Bangladesh
pakistan
Cambodia
Vietnamcountries the two measures diverge greatly and are not at all
1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
consistent through the periods
Figure 46 Labor Productivity Trends of Japan during 1885–
compared.42 This contrast was
2011 and Levels of Asian Countries in 2011
particularly stark in the first half of___GDP at constant basic prices per hour, using 2005 PPP
the 1990s, when Japan’s hourly
Sources: For historical data of Japan, the sources of GDP are Long-Term Economic
productivity growth was 2.0%
Statistics by K. Ohkawa et al. (1974) during 1885–1954 and the JSNA by ESRI, Cabinet
compared with 0.6% in per-worker
Office of Japan, during 1955–2011 (including author adjustments). Hours worked data
is based on KEO Database (Kuroda et al., 1997), Keio University, during 1955–2011.
productivity growth. However,During 1885–1954, the average hours worked per person are assumed to be constant.
the divergence has been narrowFor the labor productivity level of Asian countries in 2011, it is based on the APO Productivity Database 2013.01. The estimates for Fiji, Iran, the Lao PDR, and Mongolia are
ing to 0.3 percentage points indefined by per-worker labor productivity due to data constraints.
the 2000s. Korea is another country 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 at a slower rate than number of workers, but the portion ranged from 0.4 to
0.5 percentage points.

5 Productivity

position (i.e., Singapore, Hong
Kong, and Japan). Most Asian
countries are clustered around
Japan’s level as achieved in the
1950s and early 1960s. Amongthem, China has been leading
the catch-up effort, with productivity growing three times fasterthan Japan’s long-term average(Table 11), followed by India andVietnam.

1965

1975

1985

1995

1969

2005
Japan (21)

1990

1970
1977

1993

Singapore (23)1993

Hong Kong (16)1986

ROC (16)

2002
1992

2011

Korea (19)Figure 47 Time Durations Taken to Improve Labor Productivity by Japan and the Asian Tigers
Sources: See Figure 46.

In pole position are the Asian Tigers, of whom Singapore and Hong Kong have already surpassed Japan. Figure 47 compares the time periods taken by each country to raise its labor productivity from
30% to 70% of Japan’s level today (i.e., unit of measurement on the y-axis of Figure 46). What Japanand Singapore had achieved in the 21 years from 1969 to 1990, and the 23 years from 1970 to 1993,
respectively, Hong Kong, the ROC, and Korea managed to achieve in less than two decades (Figure47). Although the speed of catch-up for latecomers is somewhat increasing, most Asian countries will
still take a long time to catch up with the leaders, currently clustered at around Japan’s 1960 levels.

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 reflect different capital intensities in thechosen production method under the relative labor–capital price faced by the economy concerned.
By observing 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-skilled labor, production lines may
be deliberately organized in a way to utilize this abundant, and hence relatively cheap, resource. It
follows that the chosen production method is most likely to be (low-skilled) labor-intensive and withlittle capital, manifested in low labor productivity. This is why economists analyze TFP, which is GDP
per unit of combined inputs, to arrive at a more complete picture of a country’s production efficiency.44©2013 Asian Productivity Organization

Capital 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 SNA.45 The required basis for estimating
capital services is the appropriate measures of capital stock. The SNA recommends constructing thenational balance sheet accounts for official national accounts, but this is still not common practice inthe national accounts of many Asian countries.46 Even where estimates of net capital stocks are available for the whole economy, assumptions and methodologies can differ 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

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 of capi­
tal 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).

685.3 Total Factor Productivity

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 IT-related assets (seeAppendix 2).
The current APO Productivity Database estimates capital services and TFP for 17 Asian countries48 forwhich long-time investment data by type of asset are available or estimated.49 Their economic growthis decomposed into sources from factor inputs and TFP based on the methodology developed byJorgenson and Griliches (1967). This report defines output as GDP at constant basic prices, and factors
inputs as labor, IT capital, and non-IT capital.50 Labor input is measured by total hours worked (except
for Fiji and Mongolia), without adjustments for changes in labor quality.51

5

Cross-country comparisons of TFP growth for the 17 Asian countries and the US are shown in Figure
48 for the period 1970–2011, and the two sub-periods 1970–1990 and 1990–2011. The average annual growth rate of TFP during the entire observation period ranges from almost 0% to 2%, with the
exception of China who has achieved considerably high growth of TFP over 3%. Taking the US as thereference economy, with TFP growth of 0.9% on average a year, ten Asian countries achieved higher
TFP growth than the US.

47: The Department of Statistics Malaysia developed a new set of comprehensive capital stock statistics in April 2011 following theOECD Capital Manual (2009). The correlations between these official estimates (Department of Statistics Malaysia, 2012) and ourestimates for the period of 1970–2011 are high; they are 88.7% and 93.6% 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 ensure that the same methodology and same asset classification are applied for the 17 Asian countries compared.
48: In APO Productivity Database 2013, the TFP estimates for Pakistan and Sri Lanka were newly developed.
49: 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,
except China, where labor remuneration in the national accounts includes labor income for the self-employed (Holz, 2006). In the
Databook, it is assumed that the per-worker wages for self-employed and family workers are 20%–80% of the per worker wage for
employees in the countries where the appropriate wage data is not available, in order to measure total labor compensation. For
sensitivity of our TFP results to our assumptions, see Box 5 (p. 86).
50: IT capital is defined as a composite asset of IT hardware (computers and copying machines), communications equipment, andcomputer software.
51: 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. The estimate of quality adjusted labor input for Singapore was newly developed last year. See Nomura and Amano (2012).
52: In Mongolia, subsoil assets may have a significant role in economic growth, although they are omitted in our measures of capital
inputs.
53: Warr (2006) shows that the average annual TFP growths of Thailand were 2.0% in the period of economic boom (1987–1996),−9.0% during the Asian financial crisis (1996–98), and 1.6% in the period of recovery (1998–2002). These compare with our estimates of 2.7%, −8.7%, and 2.5%, respectively.

69©2013 Asian Productivity Organization

Looking at the sub-periods (i.e., 1970–1990 and 1990–2011), one 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. Ten of the 17 Asian countries experienced acceleration in TFP growth.
China and Iran accelerated the most between the two sub-periods: from 1.7% to 4.5%, and from
−1.4% to 2.2%, respectively. More modestly, Mongolia’s productivity growth, for example, improved
from −0.03% on average a year in the earlier period to 1.9% since 1990.52 Four countries saw theirproductivity growth more than halved: Thailand,53 Hong Kong, Indonesia, and Japan, all of which had
a TFP growth of under 1% on average a year in the period 1990–2011. TFP growth in the ROC, Malaysia, and the US was little changed.

5 Productivity

1970−2011

1970−1990

1990−2011

%

4.5

4.5

3.0

3.2
2.8
2.1

1.5

0.0

1.9 1.8

1.7 1.7 1.6

2.6

2.6
1.7 1.6 1.6

1.4 1.4
1.0 0.9

0.8

0.6 0.6 0.5

0.4
0.0 0.0

1.5 1.4

2.3 2.3 2.2

1.9 1.9
1.5

1.1 1.1

0.9 0.8

0.6

0.4

1.3 1.2

0.9 0.9 0.8

0.5 0.5 0.4

0.0

0.3 0.3

−0.1
−0.3
−0.5

−1.5

−1.4

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

Iran
PhilippinesFiji
Singapore
Mongolia
India
Malaysia
US
Japan
Indonesia
Sri Lanka
Vietnam
Korea
ROC
Pakistan
China
Hong Kong
ThailandPhilippines
Fiji
Iran
Malaysia
Japan
Singapore
Indonesia
US
Mongolia
India
Pakistan
ROC
Hong Kong
Korea
ThailandSri Lanka
Vietnam
China

Figure 48 TFP Growth, 1970–2011, 1970–1990, and 1990–2011
Source: APO Productivity Database 2013.01.
Note: The starting period for Vietnam is 1986. The labor inputs for Fiji and Mongolia are defined by numbers of employment.

In terms of its contribution to economic growth, TFP has played a significant role in Asian fast-growing
economies over the past decades. During the period of 1970–2011, China achieved the fastest output
growth of 8.7% on average a year. This is followed by Singapore and Korea, growing at 7.1% and 6.8%
on average a year, respectively (Figure 49). From these GDP growths, the TFP contribution accounted
for over 30% of economic growth in six of the 17 Asian countries compared (Figure 50). Among them,
the TFP contribution was the largest in Sri Lanka (39%), China (36%), Thailand (33%), and was 30% in
Hong Kong and Pakistan. This compares with 31% in the US.
China’s productivity performance has been outstanding in this period. The average TFP growth was
3.2% per year during 1970–2010 (Figure 49). This compares with the long-run estimates of 3.8% during 1978–2005 in Holz (2006) and also 3.8% during 1978–2004 in Bosworth and Collins (2008). The
Chinese experience of long-term TFP growth of about 3.0% is not unprecedented in Asia. According
to Jorgenson and Nomura (2005), Japan achieved an annual TFP growth of 3.1% during 1960–1973,
even after improvements in labor quality had been taken into account in the estimation of labor
growth (and, as such, eliminating overestimation in TFP).54 Both the ROC and Korea55 also achieved a
TFP growth of 2.4% and 2.2%, respectively, during the period 1985–2000,56 as shown in the second
chart of Figure 51, whereas in the last decade, TFP growth was 2.9% in India.

©2013 Asian Productivity Organization

In the long run, TFP growth has no impact on economic growth for the Philippines and Fiji, while labor
input growth explained 60% and 40% of their economic growth, respectively (Figure 50). Looking at
the breakdown of the period in Figure 51, one can see that the Philippines and Fiji were running an
overall negative TFP growth only in the period 1970–1985, at −1.5% and −1.2% on average per annum, respectively.57 Negative TFP growth can be caused by many things, including a rapid, temporary

54: In the same period 1960–1973, the average annual contribution rate of labor quality improvement to growth is measured as 0.54%
in Jorgenson and Nomura (2005). As a measure of the TFP contribution that is comparable with the estimates in this Databook,their estimate can be recognized as 3.6% per year during the same period.
55: 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% to 8.6% on average in the 1970s, from 8.4% to 9.3% in the 1980s,
and from 5.9% to 6.3% in the 1990s.
56: 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% (1985–1999).

70

5.3 Total Factor Productivity

%

%

9

TFP
Non-IT Capital
Output

8
7

3.2

2
1
0

2.1 1.6

80

0.5

8
31

14
30 33

20

26
39

Labor
11

4.1

1
22

30

31

1
36

54
1.7

3.8 2.9 3.6

36

24

IT Capital

0.8

4.1
4.3

Non-IT Capital

8
25

1.7

1.8 1.4

1.0
1.9

3.3

57

60
1.4

0.4 0.0

65 55
55 43 540.0
2.0
2.7 2.2 2.5
2.8 1.7
0.9 0.6 0.9
2.5
1.6
0.6
0.1
0.2
0.1
0.1
0.7
0.1 0.1
0.3
0.3
0.3
0.2
0.2
0.1
0.4
0.4
1.8
0.4
0.4
1.8
1.5
1.5
1.5
1.5
1.4 1.7
1.3 1.4 1.3
1.0
1.0
1.0
0.9
0.9
0.7
1.0
0.3
−0.1

40

48 39

9

3
5

4

20
3

25

6

6
15

12

22

15

21

29

3

62

5

47
32
2

16
2

4

24 26 27 19

32

5

68

6
1

2

7
16

26

57 37

49

60

40
27

25

12

0

−2
Fiji

Japan
US

Philippines

Iran
Pakistan
Mongolia

Sri Lanka

India

ThailandHong Kong

Indonesia
Malaysia
ROC

Vietnam
Korea

Singapore

China

Fiji

Japan
US

Philippines

Iran
Pakistan
Mongolia

Sri Lanka

India

ThailandHong Kong

Indonesia
Malaysia
ROC

Vietnam
Korea

Singapore

China

−1

TFP
100

5

3

120

Labor

0.6

6

4

IT Capital

Figure 49 Sources of Economic Growth,
1970–2011

Figure 50 Contribution Shares of Economic
Growth, 1970–2011

Source: APO Productivity Database 2013.01.
Note: The starting period for Vietnam is 1986. The labor input
for Fiji is defined by numbers of employment.

Source: APO Productivity Database 2013.01.
Note: The starting period for Vietnam is 1986. The labor input
for Fiji is defined by numbers of employment.

decline in demand or the inefficient use of resources by political interventions to the economy. This isunlikely to be sustainable in the long run. As shown in the year-on-year changes of growth decomposition in each country (Figure 57), the Philippine’s TFP fell severely in the beginning of the 1980s, inwhich the economy shrank by 15.2% for two years from 1983 to 1985 under the regime of Ferdinand
Marcos. In Mongolia, negative TFP growths are observed before the transition to market economy
in 1992.

One prevalent characteristic of Asian countries is their investment intensity as a share of GDP (Figure
31, p. 46), and in turn its contribution to economic growth (Figures 50 and 52). 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 than by capital assimilation, the Asian model may prove to
be too expensive for many less well-off countries to emulate. According to our findings (Figures 51
and 52), it is true that, historically, capital accumulation has played a much more significant role in the
Asian countries than in the US. However, the relative contribution shares are not constant across

57: Negative TFP growth for both countries is also observed in other studies. Baier, Dwyer, and Tamura (2006) estimate the averageannual growth rate of TFP of Fiji at −0.75% during 1960–2000. Cororaton (2002) shows that the average annual TFP growth of thePhilippines was −1.09% during 1970–2000.

71©2013 Asian Productivity Organization

It is clear from Figure 50 that economic growth was predominantly explained by the contribution ofcapital input in most of the Asian countries, which ranged from 39% in Fiji to 80% in Japan. Among the
Asian Tigers, the contribution of capital services ranged from 55% in Hong Kong to 67% in Singapore,
whereas in China and India, it accounted for 52% and 58% of economic growth, respectively. This
compares with 43% in the US, of which 16 percentage points were contributed by IT capital, a shareunmatched by Asian countries. Japan has been leading Asian countries in terms of contribution fromIT capital (12% of economic growth) whereas in other Asian countries it has been 1–10%, with China
and India trailing behind.

5 Productivity

1985−2000

1970−1985%

2000−2011

10

8

3.9

0.9 0.8

3.5

0.1 0.8

1.5

2.3 2.26

5.2 4.1
3.5

1.8 1.7 2.2 1.5

0

0.1

0.1

2.2
0.1 2.5 0.1

4.1

1.9

3.2

2.2

3.4

2.7 1.7
0.1
0.1

4.1
0.9

0.0 0.1
0.0
2.8 0.3
0.0
0.1
2.2
1.8
1.4
1.3 1.7 2.0 0.8 1.7 1.1
1.2
0.3
1.0
0.3

−1.0

4.8
3.6

1.2
3.2 1.9
0.2

0.9
0.8

3.4

2.2 3.1 3.1

2.7

0.7

1.0

1.9

TFP

1.2 1.0

5.0

0.7

1.8
1.6 0.6
0.7 0.6
0.8 0.1
0.2 0.6 0.1 0.1 1.6 0.1
0.1

0.1 0.2
0.1
0.3
0.4
0.5
0.5 1.8
1.6 1.4 0.5
1.3 0.9 1.1 1.1 1.2
1.3 1.6 1.0 1.4
1.2
0.8
0.6 1.0
0.4 0.9

2.4 1.5
4.2

3.2

1.9

2.0
2.6

2.3

1.1
1.3 1.1

1.4

2.2

1.6 1.9 0.5
0.1
1.8 0.2

2.1 1.9 2.1 1.4−0.2 −0.9

0.9
0.5
0.4 0.7
0.2
1.1 1.7 0.7 0.5 0.6
0.2 0.4 0.4
2.4 1.7 0.3
0.2
0.2
1.5 1.1 1.7 1.3 1.0
0.6 1.0 1.2 1.0
0.1
1.0 0.4 0.3 0.6
0.7
0.4 0.3 0.4 0.1 0.3
0.3
0.3
−0.1
−0.1 0.3−0.4−1.2−1.8−1.5

US
Fiji
Philippines
Iran
India
Japan
Sri Lanka
PakistanThailandMongolia
Indonesia
Malaysia
China
Hong Kong
Singapore
ROC
Korea

−2

4.4

0.0

3.7

1.6 0.6 0.8

0.5

1.3

2.9

1.3

Japan
Fiji
US
ROC
Hong Kong
Thailand
Korea
Pakistan
Malaysia
Philippines
Indonesia
Sri Lanka
Singapore
Iran
VietnamMongolia
India
China

0.2

3.9

1.6 0.8

2.8

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

0.5

0.3 0.4

0.5
2.4

2.3

5.4 5.3

4

2

2.2

0.8

6.3

Non-IT Capital

IT Capital

Labor

OutputFigure 51 Sources of Economic Growth, 1970–1985, 1985–2000, and 2000–2011
Source: APO Productivity Database 2013.01.

1970−1985

%

120
100

1
11 10

2000−2011

11 13

17
38

2 27
60

72

47 52
3

7
5

3

22 21 27 20

0

1
17

1

2
13

0
28

21

39

1

1

84 10

2
63

38

37
7
8

30

35

21

11
29

16

27

28

20

30

42

40 39

46

34

54 40
46

45
11

33

68
50

28

61

43

19

47

18
2 3

3
5

59

6

17 2 6
2

21
7
24 3
66
2

42
2
11
7
7 27
33 35
29 27
22 29 2819
15 22 14 20 12
15
12

33
51 47 52

43 35 41

36

51

26

44

2 5 6 36 14 17 15 12

1555 42 8

21

23

4
28

20

3

32 28

45

21

2

37 20

22
4 8

43

11

34
10

38

8

28

46

5
42

10

9

28 30

11 7

−1

−8
−62

Japan
Fiji
US
ROC
Hong Kong
Thailand
Korea
Pakistan
Malaysia
Philippines
Indonesia
Sri Lanka
Singapore
Iran
VietnamMongolia
India
China

US

Philippines
Pakistan
Sri Lanka
Hong Kong
Indonesia
India
Thailand
Vietnam
ROC
Malaysia
Korea
Singapore
China

US
Fiji
Philippines
Iran
India
Japan
Sri Lanka
PakistanThailandMongolia
Indonesia
Malaysia
China
Hong Kong
Singapore
ROC
Korea

−48

Mongolia
Japan
Fiji
Iran

−53 −45 −37

Non-IT Capital

42

60

44

46

−9

TFP

22 28 24

27
41

52

−12

−20

19

39 34

59
30

75

2

1

24 28

32 47

21

4

45

74 59

64 64

40

7

11

31

78

60

99

95

0

30 30

80

20

1985−2000
118 78 52

IT Capital

Labor

Figure 52 Contribution Shares of Economic Growth, 1970–1985, 1985–2000, and 2000–2011
Source: APO Productivity Database 2013.01.

©2013 Asian Productivity Organization

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.
Looking at Figure 52, capital accumulation was the dominant factor in the early period 1970–1985,
typically explaining two-thirds to three-quarters of economic growth achieved. In Thailand, Pakistan,
China, and Hong Kong, however, the contribution of TFP growth was still significant, accounting for
30–38% of their respective economic growth. In the subsequent periods, the contribution of capital
input became progressively smaller, falling to a share of below 50% on average, while the contribution of TFP became progressively more significant, rising to a share of above 40% on average in the
2000s. The evident rise in the contribution of IT capital is also noteworthy. In 1970–1985, IT capital72

5.3 Total Factor Productivity

TFP

%

9

CapitalLabor

Output

4.1
4.4

6

3.2

1.5
2.8 2.5 1.4
1.0

3

5.6

1.1

2.1 1.5 1.0
1.5

4.5
3.3

2.5 2.3
2.1

2.6
2.0 2.0

2.8

3.2

0

1.6 1.8
1.0 1.0 1.3 0.7
1.0 1.2 0.9

0.6

0.4
2.2 2.0 1.3
1.7 1.4

5

0.1
1.3 0.4 1.1
0.1
0.3
1.0
1.4 1.1
0.2 0.4
1.1 1.0
0.8 0.7 0.4
0.7
0.9
1.0 0.9
0.6
1.6
0.6
1.5
0.7
1.1
0.7 0.3
0.5 0.6 0.8 0.8
1.2
1.0
0.5
0.7
0.7
0.5
0.5
0.5 0.6
0.4 0.5 0.3
0.0
0.2
0.3 0.3
0.0
0.2 0.1
0.2−0.2−0.4 −0.9
1.1

2.4

0.3

1.2

1.6 2.2

2.1

Japan

Italy

Fiji

FranceSwitzerland

Belgium

US

SwedenFinlandDenmark

Germany

Spain

Netherlands

Austria

United Kingdom

New ZealandAustralia

ROC

Hong Kong

CanadaKorea

Thailand

Pakistan

Malaysia

Philippines

Sri Lanka

Indonesia

Singapore

Iran

Mongolia

VietnamIndia

IrelandChina

Figure 53 Comparison of Sources of Economic Growth with OECD Countries, 2000–2010
Sources: APO Productivity Database 2013.01 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.

accounted for below 5% of economic growth in all Asian countries, except Japan and Singapore. By
the 2000s, the IT capital share rose to above 5% in most countries, with the exceptions being India,
Iran, Pakistan, Sri Lanka, and Indonesia. Between 1985–2000 and 2000–2010, the contribution of IT
capital more than doubled in Malaysia and Japan, from 5% to 14%, and from 15% to 36%, respectively. Hong Kong sustained an IT share of 10% in the same period. This yearly accumulation of IT investment may have paved the way for countries to capitalize on 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 towhy this is so are beyond the scope of this report.

58: The multi-factor productivity in the OECD Productivity Database (OECD, 2012), 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 thewhole economy with ours, there are mainly two differences in assumptions. Firstly, capital services of residential buildings areincluded in our estimates of capital input in order to be consistent with output that includes the imputed cost of owner-occupied
housing. Secondly, 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 in measuring capital services are designed to be largely consistent with the OECD methodology, and the impact of thedifferences in assumptions on the volume estimates of capital services is judged to be limited.

73©2013 Asian Productivity Organization

Figure 53 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 in Europe. Asian countries are also among those that experienced the fastest TFP growth in the 2000s: 4.1% in China, 3.2% in India, 2.8% in Mongolia, and 2.0%
in Korea, and 1.7% in Hong Kong. Their performance was only beaten by Ireland, with TFP growth at
4.4%. Though growing at a more subdued pace, the contribution made by TFP in the slower-growing,5 Productivity

mature economies should not be underestimated: TFP accounted for half or more of economic growthin, for example, Austria, the Netherlands, Finland, Germany, and the US.
Figure 54 and Table 12 show the growth accounting decomposition for individual countries in fiveyear intervals covering the period 1970–2011. 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 is driven by input growth while TFP growth becomes more prominent andmakes a steady contribution in the later periods. Hong Kong’s TFP growth peaked at 5.2% in 1975–
1980, and was robust at 3.5% in 1985–1990, when TFP growth also peaked in the ROC, Korea, Japan,
and Singapore, at 4.0%, 3.3%, 2.0%, and 2.5%, 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 a negative standing following the Asian financial crisis of the late 1990s, but has lapsed again since 2005. In contrast, the US experienced a surge in
TFP growth in the second half of the 1990s, which was sustained into the early 2000s before the adverse cyclical effect hit in 2005–2010. Over the whole period of estimation, TFP accounted for a quarter or more of economic growth in Hong Kong (30%), the ROC (24%), and Korea (25%), while it was
22% in Japan. In contrast, TFP performance has been erratic in Singapore, resulting in its relatively
small contribution of only 8% to economic growth over the same period. Among the less developed
economies, TFP has been contributing 33% to economic growth in Thailand, 14% in Indonesia, and
8% in Malaysia.
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 explained largely 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% on average per annum in the previous period to 3.1%. Thereafter, output growth
has accelerated to reflect the pickup in TFP growth in the 2000s. In India, TFP growth was insignificant
in the 1970s; since then, it has been accelerating and has increasingly accounting for a greater
proportion of economic growth. In the second half of the 2000s, India achieved TFP growth of 3.9%
– its highest in the past four decades. Through trials and error, China and India invested first and thenlearned how to combine inputs efficiently. Both have reaped the benefits of their efforts in robust TFP
growth, while the contribution from labor input growth dwindles in the two countries over time.

©2013 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 have traditionally struggled with slow productivity growth). Given the share of the service sector in the economy (Figure 69, p. 90), its potential
and implications for economic development and productivity gains could therefore be immense. A

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% during 1995–2000 to 1.7% during 2000–2007 in Indonesia. Warr (2006) also finds that TFP growth increased
from −8.4% during 1996–1998 to 1.5% during 1998–2002.
60: Bosworth (2005) shows that annual average TFP growth increased from −4.6% during 1996–1999 to 2.1% during 1999–2004 in
Thailand. Warr (2006) also finds that TFP growth increased from −9.0% during 1996–1998 to 1.6% during 1998–2002.

74

5.3 Total Factor Productivity

%

10

10

8

8

4.9

0.4

4.0

7.1

3.9

2005–2011

2000–2005

1995–2000

2005–2011

2000–2005

2.7

1

2.7

2000–2005

2005–2011
2005–2011

1995–2000

1990–1995

1985–1990

0.9
0.7
1.1
0.3

1980–1985

0
–2

1.9

1970–1975

2

1.9

2.4 0.6

5.0 0.2 3.2
1.0
2.7
1.3
2.4
2.0 1.9 1.9 0.3
0.5 0.3
0.2 0.2
0.6
0.3
–0.2
–2.5

1970–1975

Thailand
4.1
1.0

2.3
0.3

3.6 4.4 2.3 3.0–4
2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

0.8
0.2 0.2 0.2
2005–2011

0.6
0.3

2000–2005

1980–1985

1.1

1995–2000

2.0

1985–1990

1.6

1990–1995

0.8

0.4

–0.1
1975–1980

2005–2011

2000–2005

2.1

0.2

1.4

0.7

0.1 0.1 0.9 0.4 0.5

6
4

0.7

1.5

2.7 2.2
2.2 2.6 2.6

%

1.8

1.7

1.2
1.4 0.9 1.1

10

3.5

2.0
2.8

1995–2000

2.3

2
0

1995–2000

1990–1995

2.0

1990–1995

3

–1

4.3

2
1.9

1990–1995

2.4 2.0
0.5
0.5 0.6 0.4
0.2 0.3

–2.6

2.0
1.4

1985–1990

1980–1985

1975–1980

1970–1975

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

2.0

1985–1990

1980–1985

1975–1980

1970–1975

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

1.0

5

1.5
1.2
0.9

0.6
1.3

0.8 1.2

1.2

0.7 0.7
0.7 0.3
1.1 1.0 0.7 0.7 0.5
0.5
0.8 0.6
0.3
0.2 0.3 0.4 0.5 0.5–0.1 –0.2–1
2005–2011

2000–2005

Non–IT capital

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

TFP

–0.5

1980–1985

0.8 1.70

1985–1990

2

0.6

3

1970–1975

0.2 0.1 0.3 0.3

3.0

2.1

1975–1980

1.6 1.20

4.9

2.8 3.3

2005–2011

1.7 2.3

2

2000–2005

0.6

1

1995–2000

1.4 0.3

1990–1995

3

0.5
1.4

1985–1990

1.7

Pakistan

8

0.3

1

0.2
2.0
0.9
2.0
1.8
0.9 0.3 0.5
0.2 0.2 0.4
0.4
0.3 0.3 0.4–0.4–0.4 –0.4
–0.3
–0.7
–0.7
–0.3

4
0.5

0.1

4

0.4

2.7

US

4

4.3 2.3 3.4

4

1980–1985

1970–1975

6

4.0
3.4

Sri Lanka

0%8

1980–1985

0.6 0.4 0.6
0.8 0.9 0.7
–1.2

1.1
0.9 2.0
2.1 1.9
0.6 0.5–1.9

1975–1980

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

Vietnam%

0.2 0.2

1975–1980

3.0 3.3 3.9

1.8

0.4

2.0

6

3.9

2.9 3.3

0

5.0

7

2.3
3.0 1.1
0.9 7.0
0.6

1970–1975

5.2 5.7

0.1
2.0 0.95

0.5
0.9 1.6%

Mongolia

5

–3

10

0

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990–8

1980–1985

7.8

0

–6

1

6

2.0

3

–1

7

2.4 1.5 2.5 1.9

Japan

4

–9

%

0.2

1.8

6

–12

3

3.5 1.0
1.9 0.2
0.9 0.4 0.2 1.2
1.8 2.3
3.7 4.2 3.1 3.4 2.8 0.5
2.8
0.4
0.7
1.3
0.4
0.4
1.0
0.2 0.2 0.3
0.5 0.3
–2.1

1.4

%

–9.9

–1.6 –2.5

2.6

–3

5.2

5

1975–1980–2.5

Singapore

6

0

1.5

–3

3

–5.9

–4

9

–2.1

3

2

1970–1975

–2.5

%

1.2

0

6

1.3 0.9
6.0 5.3 0.6 1.3
5.9
4.7 4.8
2.1 1.7
3.0
0.2 0.3 0.5 0.7 0.6

1975–1980

2.8

3

–0.4

1.0

1.6

12

0.9 1.6
0.7 1.4
1.3
2.0 3.3 2.7 1.0 1.7 2.4 1.7 1.5
0.4
0.7
0.6 0.2
–0.8
1.8

0.7
0.7 1.2
0.3
1.3 1.0 1.0
0.2 0.7 0.4 0.4

3.1
0.4
1.9
1.9 1.8 1.1 0.4
4.6 5.5 1.1
1.2
2.4 2.7
2.2 1.2 0.8
1.1
0.9

0.9

9

1.8
1.2 1.6 1.5
1.1 1.4
2.2
1.8 1.7

1970–1975

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

3.0 1.7

6

1.9

Iran

%

–4

Philippines

9

2005–2011

Malaysia

–2

–1.1

6

3.9

–6

2000–2005

1995–2000

0

1990–1995

3.9 4.0 4.1 2.8
1.9 1.6
0.4
0.3
0.4
0.2
0.6
0.5 0.5 0.2
–0.3
–1.4

2

–3

–0.5

1.5

%

–3.6

1985–1990

1.7
0.3 2.4

1980–1985

1.6

0

1975–1980–1.6

1975–1980

6.5

4

1.9 2.0

2.6

–3

–3

6

2.8

1970–1975

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

0

9

12

1.6
2.3 2.2
3.2
2.1 1.6
0.6
2.5 0.7 1.1
1.8 2.4
3.2 0.8
3.5
3.8 4.5 4.0
2.7
1.9 2.5

1970–1975

1.7
1.9 1.2
1.4

4

–2

3

8

3.0

0.5 0.8

0

4.0

2.3

%

3.3

1.8

6

2

0.9
1.2 1.0 0.3

Indonesia

10

–2

%

6

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975
5.7

2.3

–6

Korea

2.3

3

Hong Kong

%

12

4.1
0.8
1.1

1980–1985

4.0–0.4 –0.3

4

0

0.4

2.2 2.2 2.2 2.2 2.2 2.3 2.3
0.1 0.1 0.2

%

2

1.3

4.0

Fiji

6

–2

2.4

1.9
0.7
1.9 1.7
2.0 2.1
1.1 1.1
0.9

10

6

0

%

0.6 2.2
0.3
3.1
2.1 0.3
3.1 3.4
1.5
0.5 0.4 0.4 0.3 0.3
0.8 0.6 0.1
–0.7
5.3

1975–1980

1.5

8

2

6.6

9

3.3

1.1

4

%

6

0

1.9

6

1970–197582

2005–2011

India

%

4

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

0.1 0.1 0.2 0.7 0.6
1975–1980

04

1970–1975

2

3.1
0.2
2.8
0.5 1.2
0.7 0.4
1.0 1.1
1.8
0.6
5.6
4.3
4.3 3.8 4.3
4.2 4.0
3.4

6

2.0

ROC
2.5

IT capital

Labor

OutputFigure 54 Individual Countries’ Growth Accounting Decomposition, 1970–2011
Source: APO Productivity Database 2013.01.

75©2013 Asian Productivity Organization

China

%

12

5 Productivity

ROC

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

8.5
10.1
6.2
8.5
7.0
5.1
3.5
4.0
4.0
6.6

2.0
1.9
1.1
1.2
1.0
0.3
0.3
0.2
1.0
1.0

(24)
(19)
(18)
(14)
(14)
(6)
(7)
(4)
(24)
(15)

0.5
0.4
0.4
0.3
0.3
0.8
0.6
0.1
0.1
0.4

CapitalTFP
Non-IT(6) 6.6 (78) −0.7 (−8)(4) 5.3 (52) 2.5 (24)(6) 4.0 (64) 0.8 (12)(4) 3.1 (36) 4.0 (47)(5) 3.4 (49) 2.3 (33)(15) 3.1 (61) 0.9 (18)(18) 2.1 (59) 0.6 (16)(2) 1.5 (38) 2.3 (56)(3) 1.2 (29) 1.7 (43)(6) 3.6 (54) 1.6 (24)Hong Kong

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

6.2
11.0
5.6
7.4
5.1
2.6
4.1
3.9
4.9
5.7

1.8
(30)
1.9
(17)
0.9
(16)
0.4
(5)
0.2
(5)
1.2
(48)
0.5
(12)
0.8
(21)
−1.9 (−40)
0.9
(16)

0.2
0.2
0.3
0.4
0.4
0.7
0.5
0.3
0.2
0.4

(3)
(2)
(5)
(6)
(9)
(27)
(13)
(8)
(4)
(7)

2.8
3.7
4.2
3.1
3.4
2.8
1.3
1.1
0.8
2.7

(44) 1.4 (23)(33) 5.2 (47)(75) 0.2(3)(41) 3.5 (48)(67) 1.0 (19)(107) −2.1 (−81)(31) 1.8 (44)(28) 1.7 (43)(17) 5.8 (119)(48) 1.7 (30)Indonesia

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

8.3
7.8
4.8
7.5
7.6
0.8
4.6
5.6
6.3
5.9

2.1
1.6
2.3
2.5
0.7
1.1
0.8
2.8
0.5
1.7

(25)
(20)
(47)
(33)
(9)
(132)
(17)
(50)
(8)
(29)

0.0
0.1
0.1
0.1
0.2
0.2
0.2
0.2
0.2
0.1

(1)
(2)
(3)
(2)
(3)
(19)
(3)
(4)
(4)
(3)

3.8
4.5
4.0
2.7
3.5
3.2
1.9
2.4
2.7
3.3

(46) 2.3 (28)(58) 1.6 (20)(85) −1.6 (−34)(36) 2.2 (29)(46) 3.2 (42)(397) −3.6 (−447)(42) 1.8 (39)(43) 0.2(3)(43) 2.8 (45)(55) 0.8 (14)1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

4.4
4.3
4.2
4.9
1.4
0.8
1.2
0.3
−0.6
2.6

−0.3 (−6)
0.9
(22)
0.4
(9)
0.4
(8)
−0.4 (−26)−0.7 (−80)−0.4 (−32)−0.4 (−134)
−0.3
(48)
−0.1 (−2)

0.4
0.2
0.2
0.4
0.3
0.3
0.4
0.2
0.0
0.3

(8) 5.0(5) 2.7(6) 2.0(9) 2.0(23) 1.8(39) 0.9(33) 0.3(56) 0.0(−9) −0.3(12) 1.8(114) −0.7 (−16)(62) 0.5 (11)(47) 1.6 (39)(41) 2.0 (42)(125) −0.3 (−23)(111) 0.2 (29)(26) 0.9 (72)(11) 0.6 (167)(48) −0.1 (13)(68) 0.6 (22)1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

7.7
8.2
5.1
6.9
9.2
4.8
4.6
4.4
5.0
6.3

1.8
1.7
1.5
1.6
1.1
1.4
0.6
1.3
1.2
1.4

0.1
0.1
0.1
0.2
0.3
0.5
0.7
0.7
0.5
0.3

(1)
(1)
(2)
(2)
(3)
(11)
(16)
(15)
(9)
(5)

(61) 1.2 (15)(59) 1.6 (19)(117) −2.5 (−49)(44) 2.2 (31)(65) 1.8 (20)(111) −2.5 (−52)(45) 1.3 (27)(38) 0.8 (17)(32) 1.7 (34)(65) 0.5
(8)

China

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

5.7
6.3
10.2
7.6
11.6
8.3
9.3
10.6
8.9
8.7

1.0
1.1
1.8
2.8
0.6
0.7
0.4
0.2
0.2
1.0

(18)
(17)
(18)
(37)
(5)
(8)
(4)
(2)
(3)
(12)

Fiji

TFP

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

5.6
3.7
0.7
3.8
2.7
2.1
2.0
0.2
1.9
2.6

4.1
2.8
1.5
1.0
1.9
0.7
0.3
0.4
0.2
1.5

(73) 0.1(76) 0.1(204) 0.0(27) 0.1(70) 0.2(32) 0.0(15) 0.1(209) 0.1
(13) −0.1(60) 0.1

(2)
(2)
(6)
(3)
(7)
(−1)
(3)
(37)
(−4)
(3)

1.9
2.0
1.3
0.0
1.0
0.7
0.4
0.1
0.0
0.9

(35) −0.5 (−9)(53) −1.1 (−31)(181) −2.1 (−291)(1) 2.6 (69)(38) −0.4 (−15)(35) 0.7 (34)(21) 1.2 (60)(44) −0.4 (−190)(1) 1.7 (90)(36) 0.0
(1)

India

0.0
0.0
0.0
0.1
0.1
0.2
0.7
0.6
0.5
0.2

CapitalNon-IT(1) 4.2 (73)(1) 4.0 (64)(0) 3.4 (33)(1) 4.3 (57)(1) 3.8 (33)(3) 4.3 (52)(7) 4.3 (46)(5) 5.7 (53)(5) 5.5 (62)(3) 4.3 (49)

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

2.9
3.1
5.0
5.9
5.1
5.7
6.6
8.4
5.5
5.3

1.1
1.1
2.0
2.1
0.9
1.9
1.7
0.3
1.0
1.4

(36)
(37)
(40)
(36)
(18)
(33)
(26)
(4)
(17)
(26)

0.0
0.0
0.0
0.1
0.1
0.1
0.1
0.2
0.2
0.1

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

2.2
2.2
2.2
2.2
2.2
2.3
2.3
4.0
4.2
2.5

(75) −0.4 (−12)(72) −0.3 (−10)(44) 0.7 (14)(37) 1.5 (26)(43) 1.9 (38)(41) 1.3 (24)(35) 2.4 (36)(47) 3.9 (46)(75) 0.2(4)(47) 1.4 (26)

Iran

IT

Japan

Labor

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

9.4
−2.9
3.8
1.4
3.7
4.1
6.8
5.2
4.7
4.0

0.9
(9)
1.5 (−52)
1.1
(30)
1.2
(88)
0.8
(22)
1.2
(28)
1.1
(16)
0.3
(5)
0.9
(20)
1.0
(25)

0.0
0.1
0.0
0.1
0.1
0.1
0.2
0.1
0.1
0.1

(0)
(−2)
(1)
(4)
(2)
(2)
(3)
(3)
(2)
(2)

4.6 (48) 3.9
5.5 (−191) −9.9
2.2 (57) 0.4
0.2 (17) −0.1
0.9 (24) 1.9
1.1 (26) 1.8
2.4 (36) 3.1
2.9 (55) 1.9
2.1 (44) 1.6
2.5 (62) 0.4

Korea

OutputMalaysia

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

0.5
1.2
4.9
0.4
7.1
3.1
3.9
4.2
2.7
3.2

(9)
(19)
(48)
(5)
(61)
(38)
(42)
(40)
(30)
(36)

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

9.3
7.3
8.5
9.7
7.4
4.9
4.5
3.9
3.4
6.8

2.3
(24)
1.8
(25)
1.4
(16)
1.9
(20)
1.2
(16)
0.0
(0)
0.3
(6)
−0.3 (−7)−0.6 (−18)
1.0
(15)

0.2
0.4
0.3
0.6
0.4
0.5
0.5
0.2
0.1
0.4

(2)
(5)
(4)
(6)
(5)
(11)
(12)
(5)
(3)
(6)

5.7
6.5
3.9
4.0
4.1
2.8
1.9
1.6
1.5
3.8

(42)
(345)
(12)
(−9)
(52)
(43)
(46)
(37)
(34)
(11)

(61) 1.1 (12)(90) −1.4 (−19)(45) 3.0 (35)(41) 3.3 (34)(56) 1.7 (23)(58) 1.6 (32)(43) 1.7 (38)(41) 2.4 (62)(44) 2.4 (70)(55) 1.7 (25)Output

Labor

(23)
(21)
(29)
(23)
(12)
(30)
(12)
(29)
(25)
(21)

IT

4.7
4.8
5.9
3.0
6.0
5.3
2.1
1.7
1.6
4.1

©2013 Asian Productivity Organization

frequent question asked by policymakers and researchers is how best to capitalize on the productivity potential invited by this IT revolution. As with non-IT capital, it involves a process of accumulation
and assimilation. IT capability becomes a factor which determines an economy’s long-term growthprospects. The 2008 SNA formally acknowledges the IT sector’s importance to the modern economy
and has made it more easily identifiable and separable in industry classification and asset type.
Japan has been leading Asian countries in terms of IT capital contribution to economic growth (Figures 50 and 52). 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% in 1995 to a peak of 65% in 2005
(Figure 55).61 It took place in a period when Japan’s overall investment growth slowed significantly
after the economic collapse of the early 1990s (Figure 38, p. 54); after years of excesses, Japan shiftedaway from non-IT to IT capital as a profitable investment. In contrast, the US had started its shift toward IT capital much earlier than any Asian economy and over a longer period of time. For two decades

76

5.6
5.9
−1.3
4.6
2.2
3.5
4.5
4.8
3.8
3.7

3.0
(53)
1.7
(29)
1.8 (−141)
1.0
(21)
1.2
(55)
0.7
(19)
1.4
(30)
1.0
(20)
2.8
(73)
1.5
(40)

0.1
(2)
0.1
(2)
0.1 (−11)
0.1
(3)
0.1
(3)
0.4 (12)0.6 (13)
0.2
(5)
0.1
(4)
0.2
(6)

2.0 (36) 0.5(9)3.3 (56) 0.8 (14)2.7 (−211) −5.9 (463)
0.7 (15) 2.8 (61)
1.7 (77) −0.8 (−35)
2.4 (69) 0.0(0)1.7 (38) 0.9 (19)
1.5 (31) 2.1 (44)
1.8 (48) −0.9 (−25)
2.0 (54) 0.0(1)

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

4.2
5.6
5.0
3.3
5.3
4.9
4.0
6.2
8.0
4.9

2.0
1.4
2.0
0.2
0.6
2.1
1.4
0.6
1.5
1.3

0.0
0.0
0.1
0.0
0.1
0.2
0.2
0.3
0.1
0.1

1.9
2.0
2.8
1.1
0.3
0.8
1.6
1.9
2.3
1.6

4.8
7.9
6.7
7.3
6.8
5.8
6.8

1.7
2.3
1.4
0.3
1.7
1.3
1.5

(35)
(29)
(21)
(4)
(25)
(23)
(22)

0.2
0.1
0.3
0.3
0.6
0.5
0.3

(1)
(1)
(2)
(1)
(1)
(4)
(6)
(4)
(1)
(2)

(4)
(2)
(4)
(4)
(9)
(8)
(4)

1.6
1.2
2.8
3.3
4.8
5.1
2.9

(45)
(36)
(56)
(34)
(6)
(16)
(40)
(31)
(29)
(32)

0.3
2.1
0.1
2.0
4.3
1.8
0.7
3.4
4.0
1.9

(7)
(38)
(2)
(59)
(81)
(37)
(18)
(55)
(51)
(39)

(33) 1.4 (29)(15) 4.3 (55)(41) 2.3 (34)(45) 3.4 (47)(71) −0.3 (−5)(88) −1.1 (−20)(43) 2.1 (31)Pakistan

Philippines

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

3.6
5.8
6.4
5.6
4.6
3.2
4.9
4.1
2.9
4.7

1.4
0.9
1.1
1.2
0.7
1.9
1.9
2.8
2.2
1.5

(39)
(15)
(17)
(22)
(16)
(59)
(40)
(69)
(77)
(32)

0.0
0.0
0.0
0.1
0.1
0.0
0.1
0.1
0.1
0.1

CapitalTFP
Non-IT(1) 2.2 (62) −0.1 (−2)(0) 2.6 (45) 2.3 (40)(0) 2.6 (41) 2.7 (42)(1) 2.7 (47) 1.7 (30)(2) 2.2 (48) 1.5 (34)(1) 0.9 (28) 0.4 (12)(1) 0.4(9) 2.4 (50)(2) 0.5 (13) 0.6 (16)(2) 0.3 (10) 0.3 (11)(1) 1.7 (37) 1.4 (30)Singapore

Mongolia

0.6
0.9
1.0
2.3
−0.2
0.5
2.0
0.6
0.2
0.9

Vietnam

6.5
5.4
6.6
3.8
−1.8
3.6
6.3
6.3
16.1
4.9

(48)
(26)
(41)
(6)
(12)
(43)
(36)
(10)
(19)
(27)

0.0
0.1
0.2
0.2
0.1
0.2
0.3
0.5
0.3
0.2

CapitalTFP
Non-IT(1) 2.9 (45) 3.0 (45)(1) 3.3 (61) 1.1 (20)(4) 7.0 (106) −1.6 (−24)(4) 3.9 (101) −2.5 (−66)(−5) 1.0 (−55) −2.6 (148)(5) 0.5 (14) 2.4 (68)(4) 0.6(9) 3.4 (55)(7) 3.0 (48) 2.2 (35)(2) 2.9 (18) 12.8 (79)(4) 2.8 (57) 1.0 (20)1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

1985−1990
1990−1995
1995−2000
2000−2005
2005−20102010−2011
1970−2011

(9)
(17)
(15)
(61)
(12)
(14)
(32)
(10)
(1)
(19)

IT

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

9.1
8.2
6.6
8.3
8.2
5.6
4.7
6.4
5.2
7.1

2.6
2.4
1.5
2.0
2.0
0.9
0.9
2.3
0.6
1.8

(28)
(29)
(22)
(24)
(25)
(16)
(20)
(36)
(12)
(25)

0.6
0.4
0.6
0.8
0.9
0.7
0.6
0.5
0.3
0.6

(6)
(5)
(9)
(10)
(11)
(12)
(13)
(8)
(6)
(9)

7.8
5.2
5.7
3.0
3.3
3.9
2.1
1.9
1.9
4.1

(86) −1.9 (−21)(63) 0.2(3)(86) −1.2 (−17)(36) 2.5 (30)(41) 1.9 (24)(70) 0.1(2)(44) 1.1 (23)(29) 1.7 (26)(36) 2.4 (46)(57) 0.6(8)

ThailandLabor

Sri Lanka

Output1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

5.5
7.4
5.3
9.8
8.2
0.7
5.3
3.6
0.3
5.6

−0.2
4.4
1.0
3.0
0.3
0.2
1.3
0.7
0.6
1.3

(−4)
(59)
(19)
(31)
(4)
(25)
(24)
(21)
(163)
(24)

0.1
0.2
0.2
0.3
0.5
0.3
0.3
0.4
0.3
0.3

(1)
(2)
(3)
(3)
(7)
(44)
(6)
(10)
(74)
(5)

2.0
1.9
1.9
2.4
5.0
2.7
0.6
1.2
1.0
2.2

(37) 3.6 (66)(25) 1.0 (14)(35) 2.3 (43)(24) 4.1 (42)(61) 2.3 (28)(378) −2.5 (−347)(11) 3.2 (59)(32) 1.3 (37)(291) −1.5 (−429)(39) 1.8 (33)US

5.3 Total Factor Productivity

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

2.7
3.6
3.2
3.2
2.5
4.2
2.4
0.7
1.8
2.8

0.5
(19)
1.7
(48)
0.9
(27)
1.3
(41)
0.7
(28)
1.2
(29)
−0.1 (−3)−0.4 (−60)
0.9
(52)
0.7
(27)

0.2
0.3
0.4
0.5
0.5
0.8
0.6
0.3
0.2
0.4

(8)
(7)
(14)
(16)
(18)
(18)
(25)
(49)
(12)
(16)

1.1
1.0
0.7
0.7
0.5
0.7
0.7
0.6
0.1
0.7

(42)
(28)
(22)
(22)
(19)
(17)
(29)
(81)
(3)
(26)

Output

Labor

IT

0.8
0.6
1.2
0.6
0.8
1.5
1.2
0.2
0.6
0.9

5

(30)
(17)
(37)
(20)
(34)
(35)
(49)
(29)
(33)
(31)

Unit: Average annual growth rate (percentage), contribution share in parentheses.
Source: APO Productivity Database 2013.01.

(i.e., between 1983 and 2003), IT capital accounted for over 40% of the US’ capital input growth, reaching height of over 50% at the turn of the millennium. In recent years, the slowdown in total capital
growth has concentrated more on non-IT capital, resulting in spikes in the contribution of IT capital inboth Japan and the US. The findings here are in accordance with Jorgenson, Ho, and Stiroh (2005).
Based on their measurement, IT capital in the 1980s contributed 31.9% of the growth of total capital
inputs in the US, but only 13.5% in Japan.62 Since 1995, the Japanese economy had been rapidly shifting its capital allocation from non-IT to IT capital. In 2002, the contribution of IT capital in Japan rose
to 53.7%, which is higher than the US’ 49.8%.

61: Japan’s capital services recorded negative growth in 2009–2011, for the first time after World War II, although IT capital services
increased. This period has been omitted from our calculations of the IT capital contribution share in total capital input in Figure 55
62: Based on our estimates, IT capital contributes 38.5% in the US and 18.5% 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 55 are very similar to Figure 3 in Jorgenson and Nomura (ibid.).

77©2013 Asian Productivity Organization

A similar allocation shift to IT capital is also found in the Asian Tigers (Figure 56).63 In Korea, the ROC,
and Hong Kong, the contribution of IT capital to total capital input peaked in excess of 30% at the turn

5 Productivity

Japan

%

%

80

70

7.0

70

60

6.0

50

5.0

40

4.0

30

3.0

20

2.0

10

1.0

20

0

0.0

10

−1.0

0
1971

–10
1971

1976

1981

1986

1991

1996

2001

Non-IT capital (right-axis)

2006

2011

US

%

8.0

80

%

3.0
2.5

60
2.0

50

1.5

40
30

IT capital (right-axis)

1.0
0.5
0.0
1976

1981

1986

1991

1996

2001

2006

2011

IT capital contribution to capital input growth

Figure 55 IT Capital Contribution to Capital Input Growth of Japan and the US, 1970–2011
Source: APO Productivity Database 2013.01.

%

40

30

%

40

ROC
Hong Kong
Korea
Singapore

30

20

20

10

10

0
1971

1976

1981

China
India

1986

1991

1996

2001

2006

2011

0
1971

1976

1981

1986

1991

1996

2001

2006

2011

Figure 56 IT Capital Contribution to Capital Input Growth of Asian Tigers, China, and India, 1970–
2011
Source: APO Productivity Database 2013.01.

©2013 Asian Productivity Organizationof the millennium, from a share of 10% or below before 1995. In contrast, Singapore had two local
peaks. The first at the end of 1980s when the contribution of IT capital reached 29%, and the secondin 2005–2006 when it peaked at 29% again. China was a latecomer in terms of investing in IT capitalwith a surge in its contributions only taking off around 2000 and peaking at 16% in the early 2000s.
There has not been as big a drive in IT pickups in India as in other Asian countries. Rather, the process
has been gradual with a clear step-up in effort from a minimal level in the early 1990s. The share of IT
capital reached 7% in the early 2000s before lessening recently.

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. Thus, data inconsistency could pose a problem. Where software is excluded from the GFCF definition compliant to the 1968 SNA, software investment is estimated as described in Appendix 1. In addition, the constant-quality prices for IT capital are hardly available for mostAsian countries. If they are not available, the prices for IT capital are estimated by harmonizing Japan’s price indices, as describedin Appendix 2. Thus, readers are cautioned about data uncertainty and should expect that the decompositions of contributionsof capital services into IT and non-IT capital may be considerably revised for some countries, when more reliable data sources for
estimation become available.

785.3 Total Factor Productivity

China

12
9
6
3
0
–3
–6
–9

Hong Kong

9

6

6

3

3
0

0

–3

–3

–6

6
3
0
–3
–6
–9
–12

India

–12

Iran

3

–6
–9
–12
–15
–18

Japan

%
10

1971 1976 1981 1986 1991 1996 2001 2006 2011

12

6

9
6

2

3

0

0

–2
–4

–3

–6

–6
–9

–8
1971 1976 1981 1986 1991 1996 2001 2006 2011

Mongolia%
18

1971 1976 1981 1986 1991 1996 2001 2006 2011

15

6

12

3

9

0

6

4

–3

3

2

–6

0

–9

–3

6

0
–2
–4

–9
1971 1976 1981 1986 1991 1996 2001 2006 2011

%
12

8

–6

–15

Philippines1971 1976 1981 1986 1991 1996 2001 2006 2011

Singapore%
15

1971 1976 1981 1986 1991 1996 2001 2006 2011

12

8

6

9

6

6

4

3

0

2

0

–3

0

–3
–6

–2

–9

–9

–4

–12

–12

–6

1971 1976 1981 1986 1991 1996 2001 2006 2011%16

Thailand–6
1971 1976 1981 1986 1991 1996 2001 2006 2011

Vietnam

%
12
10

12

4

0

2

2
0

0

–4

–2

–8

–2

–4

–12

–4

–6

1971 1976 1981 1986 1991 1996 2001 2006 2011

TFP

US

%
8

4

6

4

1971 1976 1981 1986 1991 1996 2001 2006 2011

6

8

8

Sri Lanka

%
10

9

3

Pakistan

%
10

9

–12

Korea

%
15

8
4

Malaysia50–31971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

Indonesia

%
12
6

–9
1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

9

–6

–9

%
12

9

9

12

%
18
15
12
9
6
3
0
–3
–6
–9
–12
–15
–18

12

%
12

15

Fiji

%
15

1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

%
18

ROC

%
14
12
10
8
6
4
2
0
–2
–4
–6
–8

1971 1976 1981 1986 1991 1996 2001 2006 2011

Non–IT capital

IT capital

1971 1976 1981 1986 1991 1996 2001 2006 2011

Labor

OutputFigure 57 Individual Countries’ Growth Accounting Decomposition (year-on-year), 1970–2011
Source: APO Productivity Database 2013.01.

79©2013 Asian Productivity Organization%15

5 Productivity

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 broken down into effects of capital deepening (as measured by capital input per hour worked),which reflect the capital–labor substitution, and of TFP. In other words, these factors are key in fostering labor productivity.
Capital deepening has been taking place in all of the countries compared, albeit to various degrees(Figure 58). 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
more rapid capital deepening than other countries compared, and in the earlier rather than the latter
period. The reverse is true for the emerging Asian economies where concerted efforts were made toincrease capital intensity in the latter period. In 1990–2011, China, Vietnam, India, Indonesia, andThailand moved up to occupy the top spots among the Asian Tigers, while Singapore and Japan
stepped down in the rankings. In 1970–1990, the capital–labor ratio was rising by 10.2% and 9.5% on
1970−2011%12

1970−1990
10.2

10
8.7

8

10.5
9.5

7.9 7.7

7.6
6.8

6

5.3 5.1

7.6 7.4

7.1
5.7 5.5 5.5

5.0 4.9 4.7
3.8 3.7

4

1990−2011

6.0

5.2

4.6 4.4 4.4

4.2
3.0

2

3.4
2.3 2.1

2.0 1.7

1.2

3.0 2.8

2.6 2.4

2.1 1.9

0.8

1.6

4.1 4.0

3.2 3.1

2.5

1.0

1.9 1.8 1.6
0.7 0.6 0.6

0Pakistan
Iran
Fiji
Philippines
Mongolia
Sri Lanka
USSingaporeJapan
Malaysia
Hong Kong
ThailandIndonesia
India
ROC
Korea
Vietnam
China

Fiji
Sri Lanka
PakistanUS
VietnamPhilippines
India
ThailandIranMongolia
China
Malaysia
Indonesia
Hong Kong
Japan
Singapore
ROC
Korea

Fiji
Pakistan
Sri Lanka
IranPhilippines
US
Mongolia
ThailandIndia
Malaysia
Hong Kong
Indonesia
Japan
Singapore
Vietnam
ROC
China
Korea

Figure 58 Capital Deepening, 1970–2011, 1970–1990, and 1990–2011
Source: APO Productivity Database 2013.01.
Note: The starting period for Vietnam is 1986. The labor input for Fiji is defined by numbers of employment.

1970−2011%

1970−1990

1

1.4
0.9 0.8

0.9 0.8–0.3 –0.3

–2
–3
–4

–0.5 –0.6–0.2–0.7 –0.8–0.9–1.1 –1.2–1.5–2.0 –2.0–2.3 –2.4
–2.9

–0.4

–0.6

–0.1 –0.2 –0.3 –0.3
–0.9 –1.0

–0.7
–1.3

–1.6

–1.1 –1.3–2.7 –2.7–3.3–3.9 –4.0–4.6

Vietnam
Korea
Indonesia
ROC
Japan
China
ThailandHong Kong
Malaysia
US
Philippines
India
Singapore
FijiPakistan
Mongolia
Sri Lanka
Iran

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

Korea
ROC
Japan
VietnamIndonesia
Singapore
Malaysia
China
Philippines
Hong Kong
India
US
Fiji
Iran
Mongolia
ThailandSri Lanka
Pakistan

Figure 59 Capital Productivity Growth, 1970–2011, 1970–1990, and 1990–2011
Source: APO Productivity Database 2013.01.
Note: The starting period for Vietnam is 1986.

80–1.4 –1.4 –1.5
–1.9 –2.0–2.0 –2.0 –2.0
–3.0

–3.6

–5

©2013 Asian Productivity Organization

1.0 1.0

0.2

0–1

1990−20112.0

2

5.4 Enhancement of Labor Productivity

1970=1.0
1.2

1970=1.0
1.2

1.0

1.0

0.8

0.8

0.6

0.6
ROC
Hong Kong
Korea
Singapore
Japan

0.4
0.2

5

0.4
China
India

0.2

0.0
1970 1975 1980 1985 1990 1995 2000 2005 2010

0.0
1970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 60 Capital Productivity Trends inJapan and the Four Asian Tigers, 1970–2011

Figure 61 Capital Productivity Trends in
China and India, 1970–2011

Source: APO Productivity Database 2013.01.

Source: APO Productivity Database 2013.01.

%

%

7

TFP
IT capital deepening

6
5

80
1.7

33 33
47

47

42

28

2.1

52
74

60
1.7

0.6 0.5
1.4 0.8 0.6

3.4 3.1 2.9

2.2 2.4

2.1 2.0

1

1.4

1.5

2.0 1.8

40
1.9

1.6

60 59
47

50
1.4 0.9 0.4
0.0

9

12

31

25

17 16

2

5

3

4

6

Fiji

Thailand

4

Philippines
Iran
US

7

15

Pakistan

6

Hong Kong

7

9

Sri Lanka
Mongolia
Japan
Indonesia
India
Malaysia
Singapore83Vietnam
ROC
Korea

Fiji

Philippines

Iran

US

Pakistan

Sri Lanka

Mongolia

Japan

Indonesia

India

Malaysia

Singapore

ThailandHong Kong

Vietnam

ROC

China

Korea

−20

22

China

0

23 67

58

51

40

20

0.8
0.6 0.7 0.4 1.0
0.2 0.1 0.0 0.4 0.1 0.2 0.0
0.2
0.2 0.4 0.4 0.3 0.4 0.2 0.5 0.3 0.1 0.1 0.3
0.0

81

67
68

50

67
70

67 75
1.0

28

36

46

53

14

21

1.6

1.8

−1

IT capital deepening
2

18 16

3.2

3

0

Non-IT capital deepening

TFP
100

4

2

120

Non-IT capital deepening
Labor productivity

Figure 62 Sources of Labor Productivity
Growth, 1970–2011

Figure 63 Contribution Shares of Labor
Productivity Growth, 1970–2011

Source: APO Productivity Database 2013.01.

Source: APO Productivity Database 2013.01.

While labor productivity steadily improved for all countries (Figure 44, p. 65), the growth rate of capital
productivity as the other measure of partial productivity remains negative for almost all countries
during 1970–2011 (Figure 59). Although rates of capital deepening in Korea and the ROC were outstanding, at 8.7% and 7.9% per year, their capital productivity experienced the sharpest decline of 3.6
and 2.9% per year, respectively, on average during this period (Figure 60). In contrast, the deterioration of capital productivity (by 1.2%) was relatively mild in China as shown in Figure 59, despite its fast
capital deepening of 7.9% (Figure 58). Looking at the two sub-periods, overall the rate of deteriorationin 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

81©2013 Asian Productivity Organization

average a year in Korea and the ROC, respectively; over the subsequent two decades it slowed to 7.4%
and 6.0% respectively. Meanwhile, China’s pace doubled between the two periods, from 5.2% to10.5% on average a year. In Vietnam, it more than tripled from 2.4% to 7.6%. In the US the pace ofcapital deepening also hastened from 2.1% to 2.5% between the two sub-periods.

5 Productivity

1970−1985%

1985−2000

2000−2011

10

8

3.9

6
0.9 0.84

3.5
2.2 2.3 0.8

4.1 4.1

2

0

4.2 2.3

3.3

2.6

0.8
2.8

1.6
0.9 0.8

3.0

0.0 2.8

1.1
1.3
1.2
0.9 0.5
0.5
0.0 0.1 0.5
0.3
0.3 0.4 0.1 0.1 0.1
0.0
0.0
0.0 0.0
−1.0
−1.2
−1.5
−1.8

Fiji
Philippines
Iran
India
Sri Lanka
USPakistanIndonesia
Malaysia
ThailandSingaporeJapan
Mongolia
Hong Kong
China
ROC
Korea

−2

0.4

0.0 0.2 0.1

1.3
0.8

TFP

3.0 2.7

2.6

2.6

1.5

0.6
2.9

1.3

2.9

0.5

2.7

1.6

0.7
1.2

2.1

3.7

4.8

2.4 2.3 1.4

3.1

2.1

0.7 1.0
1.1
1.3
1.0 0.8 0.1
1.0 1.2 0.6
0.1 0.5 0.4 0.3 0.2 0.5 0.6 0.3 0.1 0.1 0.1 0.4 0.1 0.2 0.5 0.1 0.0 0.1
0.0 −0.9
0.1−1.0

1.1 1.1 0.7
1.9 1.5
1.3 0.6
1.3 1.2 1.5 0.8
1.4 0.5
0.8 0.4 0.6
0.9
0.3
0.4
0.0
0.6 0.2 0.3 0.4 0.3 0.1 0.2 0.3 0.4 0.3 0.4 0.1 0.6 0.4 0.1
0.3 0.3 0.1 0.1−0.2 0.0

FijiPakistanJapan
Philippines
US
Malaysia
Indonesia
Singapore
ThailandHong KongROC
Sri Lanka
Iran
Korea
VietnamMongolia
India
China

0.2

2.4

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

2.7 2.3

3.1 3.0

2.2

0.1

0.5

1.6

2.3

1.7

2.5

IT capital deepening

Non-IT capital deepening

1.8

Labor productivity

Figure 64 Sources of Labor Productivity Growth, 1970–1985, 1985–2000, and 2000–2011
Source: APO Productivity Database 2013.01.

1970−1985%

120

1985−2000

17 16

80

20

12

480382

1

3

100

2000−2011

2871016168

114

22

45 47
63

65

54

53

60

39 43

13

21

31

19

27

24

41

42

41
53

57

66

61

40

80

78 77

97

77

20
0

32

37

36

12
2 2 0
5 7 1 4 3 7
3

45

17

3 2

5
−3

61

43

49

40

8

3 14 2 11
5 4
2

20
6
−1
−400−46

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

TFP

Non-IT capital deepening

112 813633 33

6 3 6 8 8 4 6 10

30

18
14 39

25
1

11 12 17

28 26
6

5
17

11

22

5 7
−16

Fiji
PakistanJapan
Philippines
US
Malaysia
Indonesia
Singapore
ThailandHong KongROC
Sri Lanka
Iran
Korea
VietnamMongolia
India
China

−192−49 −65

−26

18

78

54

46

42

45

44
32

13 17

87

51

39

69

65
49 8

31

2 8 8 8 4

62

76

48

55

64

94

94

Fiji
Philippines
Iran
India
Sri Lanka
USPakistanIndonesia
Malaysia
ThailandSingaporeJapan
Mongolia
Hong Kong
China
ROC
Korea

−20

53

29

55 48

79

66

75

44
63 61

76

60
95

50

52

IT capital deepening

Figure 65 Contribution Shares of Labor Productivity Growth, 1970–1985, 1985–2000, and 2000–
2011
Source: APO Productivity Database 2013.01.

©2013 Asian Productivity Organization

its capital productivity as much as the early starters (Figure 61). In 1990–2011, China’s capital–laborratio rose by 10.5% whereas its capital productivity fell by 1.4%. This compares with Korea’s performance in 1970–1990 when its capital–labor ratio rose by 10.2% while capital productivity fell by 4.6%.
Labor productivity growth can be decomposed into contributions from capital deepening and TFP
growth. Capital deepening should raise labor productivity, all other things being equal, and it remains
the prime motor of labor productivity growth, generally explaining 50% of it; Sri Lanka, Pakistan,Thailand, and the US are the exceptions to this observation (Figure 63). Within this long period, thecomposition of labor productivity growth has seen substantial shifts (Figures 64 and 65). In the earlier825.4 Enhancement of Labor Productivity

China

%

12

ROC

%

7

4.0
7.1

6

2

3.9

0.5 1.2
3.2 3.00

0.4
1.9 1.9

3.4

3.8

4.0

5.5

0.2 0.7 0.5

1
0
–1

3.9

0.9

3.2

2.3

2.8

2.9

0.6

2.2

2005–2011

2000–2005

1995–2000

2005–2011

2000–2005

1995–2000

6

2.3

2005–2011

2000–2005

Thailand

1995–2000%

2.3 4.1 4.6

0–2

1985–1990–4

2005–2011

2.6 3.2
0.9
0.2 0.5
0.3
0.3
–0.5
–2.5

2000–2005

0.5

1.0

1.4

1980–1985

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

0.6–0.3 0.2 0.2

1995–2000

2.2

1970–1975

–0.4

3.6

1990–1995

4.3

0.7
1.6
1.8
0.8
0.7 1.2 1.0
0.1
0.2
0.2
–0.1 –0.6

0.3

4
2

0.1

1980–1985

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

Vietnam

2.0

2.1

1

–1

–2

US

%

7

2

0

0.6
0.1 0.1–0.2 –0.2

1990–1995

1.2 1.8
0.7
0.5 0.3 0.5 0.6 0.7 0.6 0.5 0.3
–0.4
–1.2
–1.9

1990–1995

1.2

0.4
0.1 0.1 0.2

1975–1980

–8

3.5

3

3.0 1.1

1975–1980

0
–6

2.7

1.9

1970–1975–4

3.9 2.5

1980–1985

–5.9

0.2

–1

0.2
–0.1

1975–1980

5.9

2

1990–1995

0

1.4 1.2 1.3 1.5

8

4

0.1

2.4

1

1970–19756

1.5

1985–1990

0.4

Sri Lanka

%

1.7

2.4

2005–2011

2000–2005

4

1985–1990

0.1 0.2

5
1.6
0.9 1.6
0.8 0.4 0.5 0.2
–0.8

–2

%

2.4

1995–2000

2.8

3
2

–2.5 –2.6

1990–1995

1.3

–1.6

1.2

3.4

–0.9

1985–1990

2.1

0.2 0.6

1980–1985

0.5
0.5

2.1 2.0

1975–1980

6

Pakistan

2.3 2.7
1.1 5.3

1970–1975

Singapore

%

0.8

2

3.0

0

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

4

0.9
1.3
0.6 0.5
0.2 0.4
0.2
0.4
0.3 0.4 0.4 0.3
0.2
–0.7
–0.3

4

–3
1970–1975

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

Philippines

%

2.0
0.2

1980–1985–4

1.6

2.1 1.7 1.7 2.0%
4.0

4.3 2.2 4.5 3.0 1.3
2.8 2.9
1.1 0.9
1.3
0.4
0.7 0.5
0.1 0.3
–0.2
–2.5
–2.5

0.5

1975–1980–2–2

Mongolia

5.2

1970–1975–1.4

2005–2011

1.8

2000–2005

3.0 2.7 3.5 2.8

1995–2000

0

0

1.8
0.1 0.3 0.3 0.5 0.4 0.5 0.5 0.2

1.7

5.2

1990–1995

4.1

1985–1990

2

2

0
–1

3

0.8
0.6 0.5 0.3

5

2

–8
1980–1985

2.4

3

1

1.8
1.2 1.6

2.3

0.9

4

–10
1975–1980

4

1.6

1.9
3.1
2.0
1.9 1.8
0.4–0.6 –1.1–9.9

1970–1975

3.0 3.3 1.7

1.8

Japan

6

6

6
1.1

–1.3
–0.1

%

8

6

–2

2005–2011

2000–2005

1995–2000

1990–1995

Malaysia%

8

1985–1990

1980–1985

1975–1980

1970–1975

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

Korea

%

1.7

5

0.4
3.5 3.8 0.9–4–3

1985–1990–3.6

0.2 0.3 0.4 0.4

%

3.9

–6

–4

0.2

1980–1985

0.6
0.4

2.1

1975–1980

–2

Iran

0

–1.6

1.0

3.3 2.8 3.2

1.6

1970–1975–0.4 –0.3–20

2005–2011

3.6
0.2

2000–2005

1.1

1.8
3.1 2.4
1.4
1.3
0.2 0.1

1995–2000

1.3
1.0

2

1990–1995

0.7 1.5 1.6
0.8 0.84

2.2
3.1 2.5

2.1

1.4

–2.1
1985–1990

6

2.3

1980–1985

1.4 1.4

2

1975–1980

2

2.4

0

–2
1970–1975

1.9

–0.2
–0.4

8

1.6

3

0.2

–2.1

%

3.2

3.5

5.2

0.1 0.2 0.5 0.3
–0.4

–1.1

–1

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

4

4

0.6 0.8
–0.5

6
3.3

6
0.7 1.20

1.9Indonesia

8

9

2.6

1

1.2
0.4 0.4 0.3 0.3 0.3 0.7 0.6 0.1
–0.7

%

6

0

2.3

5.1

1970–1975

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

India

8

4

0.8

2

4.9

%

0

4
3

3.1

4.0

Hong Kong

%

2

2.5

5
8

4

3

6

10

Fiji

%

3

6
5

2

3.4

4
3

1

4.3

2

1.4

1

2.3

3.0

3.2

0.7 0.7 0.2 0.3 0.5
0.1 0.1
–0.5

0

1.2
0.8

2.3

–1

0

1.5

1.2

0.7 0.3
0.6 0.8
0.1
0.9 0.6 0.3 0.1
0.6
0.1
0.7 0.6
0.2
0.3
0.2 0.2 0.4 0.5 0.4

2005–2011

Non-IT capital deepening

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

2005–2011

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

TFP

IT capital deepening

Labor productivity

Figure 66 Decomposition of Labor Productivity Growth, 1970–2011
Source: APO Productivity Database 2013.01.

83©2013 Asian Productivity Organization–1

5 Productivity

0.0
0.6
0.8
−0.4
−0.2
0.5
0.3
−0.1
−0.1
0.2

(−5)
(−112)
(−67)
(−16)
(39)
(44)
(18)
(22)
(−6)
(70)

−0.5
−1.1
−2.1
2.6
−0.4
0.7
1.2
−0.4
1.7
0.0

(110)
(216)
(170)
(113)
(98)
(59)
(79)
(94)
(111)
(14)

India

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

1.1
1.1
1.6
2.3
3.6
2.5
3.6
7.8
3.7
3.0

0.0
0.0
0.0
0.0
0.1
0.1
0.1
0.2
0.1
0.1

(2)
(2)
(2)
(2)
(2)
(5)
(3)
(3)
(4)
(3)

1.4
1.4
0.8
0.8
1.6
1.0
1.1
3.7
3.3
1.5

(131)
(125)
(52)
(33)
(44)
(42)
(31)
(47)
(90)
(51)

−0.4
−0.3
0.7
1.5
1.9
1.3
2.4
3.9
0.2
1.4

(−33)
(−28)
(46)
(65)
(54)
(53)
(66)
(50)
(6)
(46)

Iran

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

7.5
−6.0
1.4
−1.4
1.4
0.7
3.7
4.3
2.3
1.5

0.1
0.0
0.0
0.0
0.0
0.1
0.2
0.1
0.1
0.1

(1)
(−1)
(2)
(−3)
(3)
(9)
(4)
(3)
(4)
(5)

3.5
3.8
0.9
−1.3
−0.6
−1.1
0.4
2.2
0.6
1.0

(47)
(−63)
(66)
(94)
(−39)
(−150)
(12)
(52)
(26)
(67)

3.9
−9.9
0.4
−0.1
1.9
1.8
3.1
1.9
1.6
0.4

(52)
(164)
(32)
(9)
(136)
(241)
(84)
(45)
(70)
(28)

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

5.4
4.2
6.4
6.5
5.5
4.9
4.0
4.3
4.4
5.1

0.1
0.3
0.3
0.5
0.4
0.5
0.5
0.2
0.2
0.4

(3)
(8)
(4)
(8)
(6)
(11)
(13)
(5)
(3)
(7)

4.1
5.2
3.0
2.7
3.5
2.8
1.8
1.7
1.9
3.1

(76)
(126)
(48)
(42)
(63)
(57)
(44)
(40)
(43)
(60)

1.1
−1.4
3.0
3.3
1.7
1.6
1.7
2.4
2.4
1.7

(21)
(−33)
(48)
(50)
(31)
(32)
(43)
(55)
(54)
(33)

©2013 Asian Productivity Organization

ROC

0.0 (−5)0.0 (−3)0.0 (−2)0.1(3)0.2 (−38)
0.0 (−3)0.1(4)0.1 (−15)−0.1 (−5)0.0(16)

Hong Kong

−0.5
−0.5
−1.2
2.3
−0.4
1.2
1.5
−0.4
1.5
0.3

4.8
6.7
4.3
6.5
5.4
4.5
3.0
3.7
2.1
4.8

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

3.2
7.5
3.8
6.7
4.6
0.2
3.1
2.3
8.4
4.0

0.2
0.2
0.3
0.4
0.4
0.6
0.5
0.2
0.3
0.4

(5)
(3)
(7)
(6)
(9)
(292)
(15)
(10)
(4)
(9)

1.6
2.1
3.3
2.8
3.2
1.7
0.9
0.4
2.3
2.0

(51)
(28)
(88)
(41)
(69)
(819)
(28)
(19)
(27)
(50)

1.4
(45)
5.2
(70)
0.2
(5)
3.5
(53)
1.0
(21)
−2.1 (−1011)
1.8
(57)
1.7
(71)
5.8
(69)
1.7
(42)

IndonesiaFiji

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

Capital deepeningIT
Non-IT
0.4
(9)
5.1
(105)
0.4
(5)
3.9
(58)
0.3
(8)
3.2
(75)
0.3
(4)
2.3
(35)
0.3
(6)
2.8
(52)
0.7
(16)
2.9
(64)
0.6
(20)
1.9
(62)
0.1
(2)
1.4
(37)
0.1
(3)
0.3
(14)
0.4
(8)
2.9
(59)

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

4.4
4.8
0.9
3.6
6.5
−1.1
3.2
0.3
5.3
2.9

0.0
(1)
0.1
(2)
0.1
(10)
0.1
(3)
0.2
(3)
0.1 (−12)
0.1
(4)
0.1
(38)
0.2
(4)
0.1
(4)

2.1
3.1
2.5
1.4
3.1
2.4
1.3
0.0
2.2
2.0

(47)
(65)
(264)
(37)
(47)
(−230)
(41)
(4)
(42)
(68)

2.3
1.6
−1.6
2.2
3.2
−3.6
1.8
0.2
2.8
0.8

(53)
(33)
(−175)
(60)
(49)
(342)
(55)
(58)
(54)
(28)

Japan

3.7
4.2
6.9
2.4
10.6
7.1
8.6
10.2
8.5
6.8

Labor
Productivity

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

4.8
2.8
3.6
4.2
2.0
2.0
1.8
1.1
−0.1
2.7

0.4
(8)
0.2
(7)
0.2
(7)
0.4
(10)
0.3
(17)
0.4
(19)
0.4
(23)
0.2
(20)
0.1 (−80)
0.3
(12)

5.2
2.1
1.7
1.7
2.0
1.3
0.6
0.3
−0.1
1.8

(107)
(76)
(48)
(41)
(98)
(69)
(30)
(31)
(93)
(67)

−0.7
0.5
1.6
2.0
−0.3
0.2
0.9
0.6
−0.1
0.6

(−15)
(17)
(45)
(49)
(−16)
(13)
(47)
(50)
(87)
(21)

Malaysia

China

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

Capital deepeningIT
Non-IT
0.0
(1)
3.2
(86)
0.0
(1)
3.0
(71)
0.0
(1)
1.9
(28)
0.1
(3)
1.9
(82)
0.1
(1)
3.4
(32)
0.2
(3)
3.8
(54)
0.7
(8)
4.0
(47)
0.6
(5)
5.5
(53)
0.4
(5)
5.4
(63)
0.2
(3)
3.4
(50)

Korea

Table 13 Role of TFP and Capital Deepening in Labor Productivity Growth, 1970–2011

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

4.0
4.5
1.9
3.6
6.6
0.9
3.0
1.0
1.8
3.2

0.1
0.1
0.1
0.1
0.3
0.4
0.7
0.5
0.3
0.3

2.8
2.9
4.3
1.3
4.5
3.0
1.1
−0.3
−0.2
2.4

(70)
(63)
(224)
(36)
(68)
(324)
(36)
(−25)
(−12)
(75)

1.2
1.6
−2.5
2.2
1.8
−2.5
1.3
0.8
1.7
0.5

(29)
(35)
(−128)(60)(28)(−273)
(42)
(75)
(95)
(16)

Labor
Productivity

TFP
0.5
1.2
4.9
0.4
7.1
3.1
3.9
4.2
2.7
3.2

(13)
(28)
(71)
(15)
(67)
(44)
(46)
(41)
(32)
(47)

(1)
(2)
(4)
(4)
(4)
(49)
(22)
(50)
(17)
(9)

TFP
−0.7
2.5
0.8
4.0
2.3
0.9
0.6
2.3
1.7
1.6

(−14)
(37)
(17)
(61)
(42)
(20)
(19)
(61)
(83)
(33)

period of 1970–1985, TFP growth was enjoyed by eleven out of the 16 Asian countries compared, andit was a significant 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 TFP growth to bolster labor productivity growth. By 2000–2011, TFP growth had become thedominant driver of labor productivity growth in 13 out of the 17 countries compared. At the sametime, the contribution from IT capital deepening was also strengthening, from a range of 1–12% in
1970–1985, to 2–20% in 1985–2000, and 3–28% in 2000–2011. This may have accounted for a boost of
countries’ TFP performance. In the mid period of 1985–2000, the contribution of IT capital deepening
in the US was ahead of Asian countries accounting for 32% of labor productivity growth. Coincidentally, this was also the period when the share of TFP growth was the largest, at 61%.
Figure 66 and Table 13 show the decomposition of labor productivity growth for individual countries
in five-year intervals covering the period 1970–2011. Productivity is procyclical in nature, and, in turn,

84

0.0
0.1
0.1
0.1
0.0
0.4
0.5
0.2
−0.1
0.2

(5)
(2)
(−2)
(3)
(173)
(20)
(35)
(6)
(3)
(17)

0.5
2.1
1.3
0.0
0.8
1.6
0.0
0.4
−1.1
0.8

(46)
(70)
(−30)
(1)
(3619)
(80)
(−2)
(16)
(53)
(81)

0.5
(49)
0.8
(27)
−5.9
(132)
2.8
(95)
−0.8 (−3691)
0.0
(0)
0.9
(67)
2.1
(78)
−0.9
(44)
0.0
(2)

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

−0.1
2.9
1.4
3.0
4.2
1.4
1.7
5.3
5.7
2.6

0.0 (−35)
0.0
(2)
0.1
(5)
0.0
(1)
0.0
(1)
0.1
(9)
0.2
(12)
0.3
(5)
0.1
(1)
0.1
(4)

−0.4
0.7
1.2
1.0
−0.1
−0.6
0.8
1.6
1.6
0.6

(612)
(25)
(87)
(33)
(−2)
(−40)
(47)
(30)
(28)
(22)

0.3
2.1
0.1
2.0
4.3
1.8
0.7
3.4
4.0
1.9

Vietnam

1985−1990
1990−1995
1995−2000
2000−2005
2005−20102010−2011
1970−2011

2.2
5.2
4.8
6.7
3.3
2.7
4.5

0.1
0.1
0.2
0.3
0.5
0.4
0.3

(7)
(2)
(5)
(4)
(15)
(14)
(6)

0.7
0.7
2.3
3.0
3.1
3.4
2.1

(32)
(14)
(47)
(45)
(95)
(128)
(47)

Pakistan

1.0
3.0
−4.5
2.9
0.0
2.0
1.3
2.7
−2.1
1.0

0.2
3.7
3.9
3.0
3.2
0.6
2.3
0.5
0.0
2.1

Singapore

Philippines

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

Capital deepeningIT
Non-IT
0.0
(10)
0.2
(129)
0.0
(0)
1.4
(37)
0.0
(0)
1.2
(32)
0.1
(2)
1.3
(43)
0.1
(2)
1.5
(49)
0.0
(5)
0.2
(28)
0.1
(2)
−0.2
(−8)
0.1
(13)
−0.2 (−42)
0.0 (137)−0.3 (−1259)
0.0
(2)
0.7
(31)

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

4.5
3.2
3.2
3.8
3.8
3.7
2.7
1.2
3.9
3.3

0.5
0.3
0.5
0.6
0.7
0.6
0.5
0.2
0.3
0.5

(11)
(9)
(16)
(17)
(18)
(15)
(18)
(21)
(7)
(15)

5.9
2.7
3.9
0.7
1.2
3.0
1.2
−0.7
1.2
2.2

(132)
(84)
(120)
(18)
(31)
(81)
(42)
(−62)
(31)
(67)

−1.9
0.2
−1.2
2.5
1.9
0.1
1.1
1.7
2.4
0.6

(−43)
(7)
(−36)
(66)
(52)
(4)
(40)
(141)
(62)
(18)

Thailand

5.1
3.1
3.9
−1.9
−1.3
2.5
2.7
5.0
15.8
2.7

Labor
Productivity

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

5.9
0.8
3.8
5.0
7.4
0.4
2.9
2.1
−0.8
3.4

0.1
(1)
0.1
(11)
0.2
(4)
0.2
(4)
0.5
(7)
0.3
(79)
0.2
(8)
0.3
(15)
0.2 (−28)
0.2
(7)

2.2
−0.3
1.4
0.6
4.6
2.6
−0.5
0.5
0.5
1.4

(37)
(−36)
(37)
(13)
(62)
(669)
(−17)
(22)
(−61)
(40)

3.6
1.0
2.3
4.1
2.3
−2.5
3.2
1.3
−1.5
1.8

(61)
(125)
(59)
(83)
(31)
(−649)
(109)
(64)
(189)
(53)

US

Mongolia

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

Capital deepeningIT
Non-IT
0.0
(1)
2.1
(41)
0.1
(2)
2.0
(63)
0.2
(5)
5.3
(136)
0.1 (−4)
0.6 (−30)
0.1 (−7)
1.2 (−86)
0.1
(6)
−0.1
(−2)
0.2
(8)
−0.9 (−35)
0.4
(9)
2.3
(47)
0.3
(2)
2.7
(17)
0.2
(6)
1.6
(58)

Sri Lanka

5.4 Enhancement of Labor Productivity

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2011
1970–2011

1.9
1.0
1.9
1.2
1.4
2.3
2.4
1.3
0.3
1.7

0.2
0.2
0.4
0.5
0.4
0.7
0.6
0.4
0.1
0.4

0.9
0.2
0.3
0.1
0.1
0.1
0.7
0.8
−0.4
0.4

(47)
(19)
(15)
(9)
(11)
(6)
(29)
(57)
(−144)
(23)

0.8
0.6
1.2
0.6
0.8
1.5
1.2
0.2
0.6
0.9

(42)
(60)
(63)
(53)
(60)
(64)
(47)
(15)
(197)
(52)

Labor
Productivity

TFP
3.0
1.1
−1.6
−2.5
−2.6
2.4
3.4
2.2
12.8
1.0

1.4
4.3
2.3
3.4
−0.3
−1.1
2.1

(58)
(35)
(−41)
(135)
(194)
(96)
(128)
(45)
(81)
(36)

(−477)
(74)
(8)
(66)
(101)
(131)
(42)
(65)
(71)
(74)

(61)
(84)
(48)
(50)
(−10)
(−42)
(47)

(10)
(21)
(22)
(38)
(29)
(30)
(24)
(28)
(47)
(25)

TFP
−0.1
2.3
2.7
1.7
1.5
0.4
2.4
0.6
0.3
1.4

(−39)
(62)
(68)
(55)
(49)
(68)
(105)
(129)
(1222)(67)

5

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 has clearly leapt from a growth rateof around 4% in the 1970s to a rate of 8–10% in the 2000s, with its transition period in the early 1990s.
India’s passage to accelerating labor productivity growth is more gradual than China’s, from around
1.0% in the 1970s to 7.8% in the second half of the 2000s. Both TFP growth and capital deepening took
a leap in 2005–2011 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 heights of
the late 1980s. In both Hong Kong and Korea labor productivity growth appeared to have stabilized in
the 2000s, but at a lower rate than previously. Singapore’s productivity performance, albeit robust
compared with other mature economies like the US, has been very modest against its Asian counterparts. A recent peak of 3.7–3.8% in the 1990s, compared with over 6% in Hong Kong, the ROC, andKorea in the late 1980s. The US clearly enjoyed a labor productivity growth spurt in the late 1990s(2.3%) and early 2000s (2.4%), the origin of which attracted a lot of research attention at the time. In
recent years, it has returned to its long-term average of under 2%.

85©2013 Asian Productivity Organization

Unit: Average annual growth rate (percentage), contribution share in parentheses.
Source: APO Productivity Database 2013.01

5 Productivity

Box 5

Sensitivity of TFP Estimates

TFP computations based on the growth accounting framework depends on data that is sometimes difficult
to observe. One such task is calculating the wages for the self-employed and unpaid family workers. As acrude approximation in this report, it is assumed that per-worker wages for the self-employed and contributing family workers are 20–80% of the per-worker wage for employee in the countries where the appropriate wage data is not available, 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 measureof capital services.
The right-hand chart of Figure B5.1 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 17 Asian countries and the US in 2011 and the left chart provides theemployee share to total employment. There is a large divergence in labor income share for employees
among the Asian countries.
Roughly, this divides into twogroups: countries with ap100 %
80
60
40
20
0
0
20
40
60 %
proximately a 50% share and
59
94
US
57
54
Sri Lanka
countries with an approxi56
Chinamately a 30% share of com55
86
Japan
pensation for employees. This
94
53
Hong Kong
50
72
Korea
does not necessarily reflect
49
43
Fiji
differences in the number of
78
48
ROC
44
94
Singapore
employees in total employ40
36
Pakistanment. Although Malaysia has
34
55
Philippines
33
44
a high employee share ofThailand32
78
Malaysia
78%, the labor income share
32
20
India
is only 32%.
48
31
Indonesia
Mongolia
Vietnam
Iran

51

28
28
22

Share of employees to total

Labor income share for employees

Figure B5.1 Labor Income Share for Employees, 2011
Sources: Official national accounts in each country, including author adjustments.

%

4

3.9

3

3.2

2

2.4

2.8
2.1

2.6
1.7
0.8

2.2
1.7
1.2

2.3
1.6
0.8

1.5
1.4
1.3

1.7
1.4
1.0

0

1.1
0.6
0.1

1.0
0.5
0.0

0.6
0.4
0.2

0.1
0.0
0.0

0.2
0.0
−0.2

Philippines

Fiji

Iran

India

Pakistan

ROC

Hong Kong

Korea

ThailandSri Lanka

−1

1.1
0.6
0.1

Malaysia

1.3
0.8
0.3

Japan

1.1
0.9
0.6

Singapore

1.3
1.0
0.7

Indonesia

2.2
1.8
1.5

US

1

2.1
1.9
1.7

TFP(vL+10)
TFP
TFP(vL−10)

Mongolia

1.4

Vietnam

86

38

China

©2013 Asian Productivity Organization

59

Figure B5.2 illustrates the sensitivity of TFP estimates bychanging the factor income
share during the period 1970–
2011. In general, the growthrate of capital input is higher
than that of labor input, so
the higher income share of labor results in higher estimatesof 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 44 and 59). The TFP estimate reflects the improvement of labor productivity
more when the labor income
share increases. In Malaysia,
with TFP growth of 0.5% on
average during the period
1970–2011, the true estimate
could be 1.1% if the current
labor income share is underestimated by 10%.

Figure B5.2 Sensitivity of TFP Estimates by the Change ofIncome Share, 1970–2011
Source: APO Productivity Database 2013.01.
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 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, reliance on a narrow industry-base leaves economies more vulnerable to shocks and 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 otherend the agriculture sector is negligible and the service sector is the dominant economic base. The
middle realm is occupied by manufacturing as the main driver of economic growth. As an economy
matures, its depth and sophistication increases and its resilience to economic shocks should beaccordingly strengthened. Furthermore, the different composition of economic activities among
countries is also 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, one canclearly trace the path of economic development and identify countries’ respective stages based on
their characteristics.64

6

6.1 Output and Employment
Table 6 (p. 28) in Section 3.2 introduces a country grouping according to stages of development (asmeasured by per capita GDP relative to the US). Table 14 regroups countries based on the same set ofcriteria as in Table 6, but applies it to countries’ 2011 income levels. The difference in countries’ relative
per capita GDP between the two tables reflects the impact of their catch-up efforts since 1970 or theyear of first recorded data.
Comparing Table 14 with Table 6, it is notable that 13 of the 29 Asian economies have moved up in
income group, whereas 14 have stagnated. Among them, the most upwardly mobile countries are the
ROC and Korea, both in the fast catch-up group, which have moved up two income levels during thepast 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 in different catch-up groups. Indonesia, theLao PDR, and Vietnam (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 three(Myanmar, Bangladesh, and Nepal) as of 2011. As expected, there were few movements in countrygroups with little or no catch-up. Only Pakistan moved up one level (as it marginally crossed theboundary of income groups from 5.0% to 5.7% 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.

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 toresearchers in this field. The industry data in this chapter is mainly based on official national accounts. Where back data is not available, 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 although levels of breakdown are deliberately chosen to minimize the potential
impact of these data inconsistencies. In this sense, the industry data in APO Productivity Database should be treated as a workin progress and it is difficult to advise on data uncertainty. These data will be further developed and examined in the near future.
Readers should bear these caveats in mind in interpreting the results.

87©2013 Asian Productivity Organization

Countries at the lower rungs of the development ladder tend to have a bigger agriculture sector as ashare of value added.65 Figure 67 shows the industry composition66 of the Asian economies in 2010,
and indicates a broad, negative correlation between the share of the agriculture sector and the relative6 Industry Perspective

per capita GDP against the US.
Table 14 Country Groups Based on the Current Economic
Level and the Pace of Catching Up
Half of the Asian countries com___Level and average annual growth rate of GDP at constant market
pared have an agriculture sector
prices, using 2005 PPP
accounting for over 10% of total
Annual rate to catch-up to the US
value added, and they all have a
Per capita
GDP level to
(C2)
(C3)
(C4)
(C1)
relative per capita GDP that is
the US in 2011
1% <–< 3%
0% <–< 1%<0%>3%
20% below that of the US. Among
Brunei, Kuwait,
ROC, Korea,(L1)
them, the three countries with the
Qatar, UAE,
Hong KongJapan, EU15
Singapore
60% <Australia
biggest agricultural share are allin the lowest income group (i.e.,
Malaysia,
Bahrain,(L2)
Iran, Turkey
Thailand, Oman
Saudi Arabia
20% <–< 60%with a per capita GDP less than
5% that of the US). In contrast, theIndia, Indonesia,(L3)
Cambodia, China Lao PDR, Mongolia,
PakistanFiji, Philippines
agriculture sector is 10% or less of
5% <–< 20%
Sri Lanka, Vietnam
the total value added for GroupBangladesh,(L4)
L2 countries, compared with 3%
Myanmar
Nepal< 5%or less for Group-L1 economies. In
particular, agriculture accounts
Sources: Official national accounts in each country, including author adjustments.
Note: The annual catch-up rates are based on the data during 1970–2011. The startingfor less than 1% in the US, while it
years for some countries are different due to data availability: Cambodia (1987–), theis negligible in Hong Kong and
Lao PDR (1984–), and Nepal (1974–).
Singapore. Note also how finance,
real estate, and business activities
grow in importance as one moves up income levels. The finance sector is especially prominent in Hong Kong (38%), Singapore (29%), and the US (33%). Mining appears to be what defines oilexporting countries, typically accounting for over 40% of total value added, except in Bahrain (22%),
Iran (15%), and the UAE (28%) – countries which have managed to diversify away from the dominanceof mining. Finance is the biggest sector in Bahrain, accounting for 27% of total value added, whereas
it is the second largest sector (17%) in the UAE, following mining.
Manufacturing is a key sector in propelling countries to make a leap in economic development. It accounts for around 20% of total value added or more in eight of the 29 Asian countries compared.
Among these, manufacturing is the largest sector in China, Korea, and Thailand, at equivalent toaround 30% of total value added, while in the ROC, Malaysia, and Indonesia it accounts for a quarteror more. At the other end of the spectrum are five countries where manufacturing accounts for lessthan 10%. Among these, two are oil-exporting countries and the other three are Hong Kong (2%),
Mongolia (7%), and Nepal (6%). These compare with the values for the US at 11% and Australia at 8%.

©2013 Asian Productivity Organization

Figure 68 shows the breakdown of the manufacturing sector, comprising nine sub-industries, for 17
selected Asian countries and the US.67 The dominance of machinery and equipment in Asian
manufacturing can be clearly seen, particularly in the ROC and Singapore (close to 60% of

65: 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, Iran, the Lao PDR, Mongolia, Nepal,
and Singapore; at producers’ prices for the ROC, and the Philippines; and at market prices for Bangladesh, Indonesia, Japan, Malaysia, Sri Lanka, Thailand, and Vietnam.
66: 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 6 for the concordance with the ISIC, Revision 3.
67: 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 3 for the concordance with ISIC, Revision 3.

88

6.1 Output and Employment

manufacturing’s total value added), and Korea (50%) and Japan(45%). These compare with 40%
in the US. At the other end arecountries dominated by lightmanufacturing (e.g., the foodproducts, beverages, and tobacco
products sector in the Philippines,
Sri Lanka, Fiji, and Mongolia, andthe textiles, wearing apparel, andleather products sector in Cambodia and Bangladesh). Coke, refined
petroleum products, chemicals,
rubber, and plastic products arealso a prominent subsector, notleast in Kuwait, where they account for two-thirds of the country’s manufacturing value added.

11.9
12.5
8.0
15.9
6.2 6.9
36.9
Nepal
4.0 Myanmar
13.8
19.7
4.6
19.6
36.4
10.7 Cambodia
8.1 7.4
14.5
6.4
15.6
36.1
4.8 6.4 10.0 Lao PDR
20.2
10.1 4.0 5.3
9.6
29.7
16.0
6.8
13.1
17.6
2.32.3
17.7
3.1
21.2
Pakistan
4.4 5.6 9.3 Vietnam
18.4
4.2 7.0
19.6
10.9
20.6
17.9
8.6
15.7
10.7
8.3
17.9
18.6
Bangladesh
14.0
16.0
7.3
17.2
8.2
2.7 14.9
18.0
India
13.5
10.7
12.0
7.3 3.0 10.0
25.8
16.2
Mongolia
10.2 Indonesia
6.6 7.2
13.7
10.3
24.8
11.2
15.3
11.2 Sri Lanka
13.7
12.7
20.2
2.3 7.6
18.0
12.8
13.4
17.8
6.5
17.4
3.6 6.1
21.4
12.3
Philippines
14.8
18.1
15.4
18.8
2.9
15.3
11.7
Fiji
13.1
11.8
6.9
17.6
2.82.831.4
10.5 3.2
Thailand
12.3
12.9
6.5
2.5 3.2 14.2
25.6
12.3
10.4
Malaysia
14.4
10.9
7.0
2.4 6.6 10.9
32.5
10.1 5.2
China
12.4
22.1
14.7
14.9
17.6 2.6 4.7
9.5
Turkey
14.8
16.3
7.5
14.0
13.2 2.3 6.4
16.7
8.7
Iran
27.9
21.3
8.8
11.4
8.3 2.4 7.7
9.5
Australia
20.1
19.3
8.2
6.3 10.9
30.3
Korea
16.1
4.6 8.8 5.1 9.2
11.0
41.5
Saudi Arabia
21.3
19.1
5.0
20.9
2.9
27.2
ROC
14.0
5.7 8.3 5.0 8.5
10.5
45.5
Oman
29.7
16.8
10.3
13.8
2.9 5.5
19.7
Japan
28.6
33.0
7.1
3.6 11.6
11.2
US
7.3 UAE
17.5
8.3
14.6
8.5 2.1 11.1
29.8
19.3
12.1 3.13.73.4 6.1
50.8
Brunei16.1
24.0
7.5 7.4 6.8
14.6
21.9
Bahrain
5.4 4.3 6.7 12.9
15.5
51.5
Kuwait8.9 Qatar
10.5 5.1 6.9 3.9 13.2
51.0
17.0
37.8
11.1
27.0
3.3
Hong Kong
21.6
10.6 Singapore
28.8
12.3
20.8
4.2

0

10

20

30

40

50

60

70

1. Agriculture
3. Manufacturing
5. Construction
7. Transport, storage, and communications
9. Community, social, and personal services

80

90Group-L3(except for
Bangladesh)

6

Group-L2(except for
China)

Group-L1(except for
Bahrain,Oman, andSaudi Arabia)

100 %2. Mining
4. Electricity, gas, and water supply
6. Wholesale and retail trade, hotels, and restaurants
8. Finance, real estate, and business activities

Figure 67 Industry Shares of Value Added, 2010
Sources: Official national accounts in each country, including author adjustments.

50.8
50.7
46.6
34.6
29.1
24.8
22.3
21.6
15.5

7.8

8.0
5.0 4.1

8.6
8.2

30.0
21.5

2.3

63.7

20

40

9.5
2.0 2.6
10.7
3.2 2.8
6.7
69.8

Sri Lanka
Mongolia
Philippines
Fiji
Indonesia
4.8 Hong Kong
4.8 Thailand
6.3 2.5 Bangladesh
3.9 3.8 8.1 4.1 7.7
2.3 3.2 3.61.8 8.3
Cambodia
44.8
4.9 Japan
40.6
5.1 US
Iran
29.7
10.0
Malaysia
42.6
India
30.9
11.3
Kuwait9.8
5.9
58.5
4.3 ROC
51.1
Korea
62.4
3.4 Singapore

2.9
18.0
18.0
15.4
13.3
4.5 3.4
6.1
21.3
14.5
2.7 3.4
11.2
8.9
4.8
15.4
24.4
24.4
2.8
21.2
7.0 2.8
34.1
3.9 2.0

41.9

13.9
15.8
3.1
5.4
13.4
26.3
2.9 5.2
12.7
4.6 2.8
27.0
11.8
30.7
3.3 3.1
9.5
15.1
21.8
2.02.7
5.9 3.0 3.5
4.6 3.0 2.3
19.0
6.3
4.1 4.2 2.6
15.7
3.3
17.2
3.2 2.8
26.7

0

5.9
9.8

60

80

7.6
2.3 2.5
3.1
6.2

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

Figure 68 Industry Shares of Value Added in Manufacturing, 2010
Sources: Official national accounts in each country, including author adjustments.

89©2013 Asian Productivity Organization

Figure 69 shows the industry
shares of value added and employment by the four countrygroups based on 2011 income
levels, compared with the Asia29
average and the US for the years
1980, 1990, 2000, and 2010.68 The
first thing to note is that in 2010,
the service sector accounted forthe largest share of total value
added in all country groups, independent of their economic development.69 That said, Group-L1 has
always had the biggest service
sector among all Asian countries,
and this has become much more
distinctive as the bulk of theeconomy in this group continues
to shift heavily toward services
over time. By 2010, the service
sector accounted for 69% of total
value added in Group-L1, compared to 80% in the US and 51%
in Group-L2.70 The weight of theservice sector is similar in GroupL3 and Group-L4 at 46–48%. This
reflects the relative importance of
manufacturing to the former, andagriculture for the latter, at their
particular stages of development.

Group-L4

6 Industry Perspective

The second noteworthy point is that 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% in 1980 to 40% in 2010, while its share in total value addedrose from 6% in 1980 to 10% in 2010, implying that agriculture is becoming more labor-efficient. In
the past three decades, the value-added share of agriculture in Group-L3 has more than halved from
31% in 1980 to 13% in 2010, with the most rapid shift taking place in the 1990s; employment in the
sector was also cut by one-third over the same period. The least well-off countries, in contrast, havenot been as successful in diversifying away from agriculture, which accounted for 26% of total value
added and 53% of employment in 2010, compared with 34% and 69%, respectively, in 1980. In themeantime, the richest economies continued to squeeze agriculture even though it had a share of only
3% in total value added and 17% in total employment in 1980. By 2010, the figures had fallen to 1%
and 5%, respectively.
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.71 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

%

100

1990

1980

2000

2010

90
80
70
60
50
40
30
20
10
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.

Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.

Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.

Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.
Emp.
V.A.

0

Group Group Group Group Asia29
L-1
L-2
L-3
L-4

Group Group Group Group Asia29 US
L-1
L-2
L-3
L-4

Group Group Group Group Asia29
L-1
L-2
L-3
L-4

Group Group Group Group Asia29
L-1
L-2
L-3
L-4

US

1. Agriculture
4. Electricity, gas, and water supply
7. Transport, storage, and communications

2. Mining
5. Construction
8. Finance, real estate, and business activities

USUS

3. Manufacturing
6. Wholesale and retail trade, hotels, and restaurants
9. Community, social, and personal services

Figure 69 Industry Shares of Value Added and Employment by Country Group, 1980,
1990, 2000, and 2010©2013 Asian Productivity Organization

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

68: 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.
69: 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.
70: If Figure 67 was to rank by the size of the service sector, Hong Kong would top the table at 92.9%, followed by the US (80.4%), andother Group-L1 countries, namely the ROC (66.4%), Japan (70.7%), and Singapore (72.5%). Fiji is an exception, with a large service
sector share (67.1%) relative to its per capita GDP level.

906.1 Output and Employment

value-added share and employment share are similar, suggesting that labor productivity in this sector
is higher than that experienced in Asian countries. The reverse is true for the sector of finance, realestate, and business activities, which often generate a much bigger value-added share than suggested by its employment share. In 2010, the sector accounted for 33% of total value added generated by
19% of employment in the US, and 13% and 3%, respectively, in Asia29. While the value-added shareof the sector has grown by 11 percentage points in the US over the past three decades, it has onlygrown by 1 percentage point in Asia29.

6

The third point to note is that the industry structure in Asian countries differ from that in the US as
regards the relative importance of manufacturing, even in Group-L1 countries, where manufacturingaccounts for 22% of the economies’ value added, compared with 11% in the US in 2010. The US economy is highly skewed toward the service sector, accounting for 80% of the total value added, compared with an average of 69% in Group-L1 countries. Certainly, its share of finance, real estate, andbusiness activities at 33% was much larger than the share in Group-L1 countries, at 19%. This suggeststhat 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 the size of acountry’s manufacturing sector.72 In Asia, the manufacturing employment share is typically smaller
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 in Group-L3 countries it has been relatively stable, and slowly expanding in Group-L4, reflecting their different developmental stage.
Figure 70 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 broad 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 aroundthe 30–50% band in the 1970s, trending down to the 10–20% band by 2010. Vietnam and Mongolia
are two countries where the agriculture sector experienced similar declines but within a much shorter
period (from the late 1980s and mid-1990s, respectively). The relative decline of agriculture was most
rapid in Korea, from 29% of total value added in 1970 to 2.6% in 2010. In many countries, the share of
the agriculture sector more than halved between 1970 and 2010: for example, from 44% to 15% inIndonesia, from 42% to 18% in India, and from 39% in 1972 to 19% in Bangladesh. In China, the shareof this sector also significantly declined, from 36% in 1970 to 10% in 2010.

71: 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.
72: If Figure 67 was to rank by the size of the manufacturing sector, China would lead with a share of 32.5%, followed by Thailand andKorea at 31.4% and 30.3%, respectively.
73: Data for the Lao PDR and Myanmar are unavailable for Figure 71.

91©2013 Asian Productivity Organization

Despite the relative decline of agriculture’s share in total value added, employment in the sector for
Asia as a whole still accounted for 40% of total employment in 2010. Figure 71 shows countries’ industry shares in total employment, and ranks them by size of employment in the agriculture sector.73
Group-L4 and Group-L3 countries and Thailand cluster at the top in Figure 71, with the share of
agricultural employment ranging from 33% (Sri Lanka) to 76% (Nepal). Figure 72 traces the historical6 Industry Perspective

%

%

30

Brunei
ROC
Hong Kong
Japan
Korea
Kuwait
Qatar
Singapore
UAE
Australia

25
20
15
10
5

1970 1975 1980 1985 1990 1995 2000 2005 2010

Group-L1

50

25
20
15
10

0
1970 1975 1980 1985 1990 1995 2000 2005 2010

Group-L2%

60

Bahrain
Iran
Malaysia
Oman
Saudi Arabia
ThailandTurkey

5

0

70

30

%

Cambodia
India
Mongolia
Pakistan
Philippines
Sri Lanka
Vietnam

China
Indonesia

Fiji
Lao PDR

70
60
50

40

40

30

30

20

20

10
1970 1975 1980 1985 1990 1995 2000 2005 2010

Group-L3

Bangladesh
Myanmar
Nepal

101970 1975 1980 1985 1990 1995 2000 2005 2010

Group-L4

Figure 70 Long-Term Trends of Value-added Share in the Agriculture Sector, 1970–2010
Sources: Official national accounts in each country, including author adjustments.

trajectory of Japan’s employment share of agriculture for the period 1885–2011 and the countries’
levels in 2010, mapped against Japan’s experience (as circle). Large shares of agriculture employment
over 30% in twelve countries correspond to Japan’s level at the end of the 1950s and the onset of higheconomic growth. This may indicate there is much room for improving labor productivity and per
capita income.

©2013 Asian Productivity Organization

The trend of employment share over time (Figure 73) suggests that the relative decline in the share of
agriculture in total value added has been accompanied by a downward trend in its share in total employment.74 This trend is unmistakable in most of the countries plotted in Figure 73.75 Between 1970
and 2010, the employment share in agriculture shrank from 50% to 7% in Korea and from 20% to 5%

74: Nepal’s employment-by-industry figures are constructed by interpolating benchmark data taken from its labor force survey as wellas its population census. Figure 73 indicates that its share of agriculture has increased since 1999. This reflects the employment
share of agriculture at 66% in the population census of 2001 and its share of 74% in the labor force survey of 2008.
75: However, the decline in a share does not always reflect an actual fall in employment for the agriculture sector; rather, it could
reflect total employment rising faster than employment in agriculture. Countries that have been experiencing a consistent fall in
actual employment in the agriculture sector are, for example, the ROC, Hong Kong, Japan, and Korea, whereas in Cambodia, India,
Iran, Nepal, and Pakistan, actual employment has been rising. Other countries such as Thailand, Indonesia, Singapore, Malaysia,
and Vietnam have no established trend in employment growth. China, however, has seen actual employment in agriculture fallingsince the turn of the millennium.

926.1 Output and Employment

It is the manufacturing sector thatlargely absorbs workers who havebeen displaced from the agriculture sector, especially in the initialstages of economic development.
Figure 74 traces the trajectory ofgrowth rates of GDP and employment in combination with
manufacturing for several Asian
countries and the US over the
past four decades. Each dot represents the average annual growthrate in the 1970s, 1980s, 1990s,
and 2000s. The growth rate in the
2000s is described by a white dot.
If manufacturing GDP and employment grow at the same rate, adot will be on a 45° line throughthe origin running from the lower
left to upper right quadrants. Despite positive gains in manufacturing GDP, for the US and Japan,
the overall ‘growth’ in manufacturing employment was negative,
except for during the US’s 1970s
and Japan’s 1980s,. In Korea andthe ROC, expansions of manufacturing output could allow for increases of employment in the
1970s and the 1980s but since the1990s manufacturing has no long­er been an absorption sector of
employment, regardless of thesound expansion of production inthis sector. The experiences ofSingapore, Indonesia, and Thailand are closer to the 45° line
through the origin, which implies the well-balanced growth of
output and employment in manufacturing sector. In China and
Sri Lanka, the job creation roleof manufacturing still seems effective. In India, Pakistan, and

Nepal
Cambodia
India
14
6
15
Vietnam12
515Bangladesh
45
13
7
16
5
11
Pakistan
38
13
5
21
5 2
15
Indonesia
38
14
6
23
3 3
12
Thailand
37
18
9
10
4
19
China
34
3 6
5
17
9 2
23
Mongolia
34
8
5
23
7 5
17
Philippines
33
18
6
16
6 4
17
Sri Lanka
25
18
6
21
5 6
18
Turkey
19
17
14
17
10
4
17
Iran
13
17
Malaysia
9
24
6
9
21
Fiji
10
4 6
18
22
13
3
23
7
17
7
Korea
23
8
14
24
5
27
8
24
5
9
22
ROC
5 2 8
33
12
4 3
33
Oman
5
Japan
16
8
18
9
5
39
4
7
12
21
5 5
45
Saudi Arabia
32 7
12
UAE
18
9
9
38
32 9
Australia
9
21
7
5
42
6
9
16
3 6
57
Kuwait
8
5
US
15
5
19
46
3 9 2 814
3 6Brunei
55
7
8
40
11
6 3
24
Qatar
12
23
16
9
4
35
Bahrain
17
12
21
10
8
32
Singapore
4
8
32
12
18
25
Hong Kong
0
10
20
30
40
50
60
70
80
90 100 %
76

57

11

53
49
48

6 3 7 2 4
15
3 10

3

22

1. Agriculture
3. Manufacturing
5. Construction
7. Transport, storage, and communications
9. Community, social, and personal services

28Group-L4

3 5 6
3
10
7 2 10Group-L3(except for
Bangladesh, andThailand)Group-L2(except for Fiji)

6

Group-L1(except for
Bahrain,Oman, andSaudi Arabia)

2. Minig
4. Electricity, gas, and water supply
6. Wholesale and retail trade, hotels, and restaurants
8. Finance, real estate, and business activities

Figure 71 Industry Shares of Employment, 2010
Sources: Official national accounts in each country, including author adjustments.

Agriculture Share in Total Employment

0.8

Nepal
Japan (1885–2011)

0.7
0.6

Cambodia
India

0.5
0.4
0.3

VietnamBangladesh
PakistanIndonesia
China
Mongolia
ThailandPhilippines

Sri Lanka

0.2
Iran
0.1

Malaysia
Fiji

Korea
ROC

BruneiSingapore
Hong Kong
1881 1891 1901 1911 1921 1931 1941 1951 1961 1971 1981 1991 2001 2011

Figure 72 Employment Share of Agriculture in Japan during 1885–2011 and Levels of Asian Countries in 2010
Sources: Official national accounts in each country, including author adjustments. The
sources of historical data of Japan are Long-Term Economic Statistics by K. Ohkawa etal. (1974) during 1885–1954 and Population Censuses since 1920.

93©2013 Asian Productivity Organizationin Japan. Employment in agriculture also fell rapidly in the ROC,
from 25% in 1978 to 5% in 2010.
In China, the share has declined
from 71% in 1978 to 37% in 2010.

6 Industry Perspective

%

%

60

Brunei
ROC
Hong Kong
Japan
Korea
Kuwait
Qatar
Singapore
UAE
Australia

50
40
30

90
80
70
60
50

Bahrain
Iran
Malaysia
Oman
Saudi Arabia
ThailandTurkey

40
30

20

20
10

10
0

0

1970 1975 1980 1985 1990 1995 2000 2005 2010

1970 1975 1980 1985 1990 1995 2000 2005 2010

Group-L1

Group-L2

%

%

80

100

70

90

Bangladesh
Myanmar
Nepal

60
80

50
40

70

30
Cambodia
China

20
10
0

Fiji
Indonesia
Philippines

India
Mongolia
Sri Lanka

50
Pakistan
Vietnam1970 1975 1980 1985 1990 1995 2000 2005 2010

Group-L360

401970 1975 1980 1985 1990 1995 2000 2005 2010

Group-L4

Figure 73 Long-Term Trends of Employment Share in the Agriculture Sector, 1970–2010
Sources: Official national accounts in each country, including author adjustments.

Iran, this role is becoming more important, and at times, output growth and employment
growth diverge.

©2013 Asian Productivity Organization

6.2 Industry Growth
In Section 3.1, it can be seen that, as a region, growth in Asia29 accelerated in the most recent period
2005–2011, averaging 6.2% per annum, up from 5.4% in 2000–2005. China and India have been thetwo main drivers among the Asian economies, accounting for 47% and 15% of the region’s growthduring 1990–2011, respectively (Figure 7, p. 19). 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,76 whereas for India economic growth has been led by service sector expansion. Although the findings broadly support their conclusion, it also discerns that the nature of growth inChina may have started shifting more toward services in recent years.

76: The industry sector in Bosworth and Collins (2008) is equivalent to the industry groups 2–5 in this report.

946.2 Industry Growth

%

%

2

Growth of
Employment in Mnf

1

0
−1

8

1980−1990

24
1970−1980

1970
4 −1980 6 %2Growth of
GDP in Mnf

0

1990
−2000

−2

Growth of
Employment in Mnf

6Growth of
GDP in Mnf

0
−2

10

−8

−4

−2

2000−2010

4

8

16 %

12

1980−1990

6

−4

−3

−6

1990
−2000

Japan
US
Australia

−4

−8

ROC
Hong Kong
Korea

2000−2010 −10

−12

−5
%

%

10

8

Growth of
Employment in Mnf

1970
−1980

Growth of
Employment in Mnf

7

8
China
Indonesia
Singapore
Thailand

6

6

India
Iran
Pakistan
Sri Lanka

5

1990−2000

4
4

3
1980
−1990

2

2
2000−2010
Growth of
GDP in Mnf

1990−2000

0
0

5

1980
−1990

10

15

20 %

2000−2010
1970
−1980

1

Growth of GDP in Mnf

0
0

2

4

6

8

10 %

Figure 74 Job Creation in Manufacturing, 1970–2010___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. The white dots indicate the rate in the latest decade.

77: The Törnqvist quantity index is adopted for calculating the growth of real GDP. Using this index, the growth of real GDP into the
products of contributions by industries can be decomposed:
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.

95©2013 Asian Productivity Organization

The effect of extending the latest period to include 2010 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, rendering 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 75).77 The gap between contributions of manufacturing and services was the widest in the early 1990s; narrowing in the late 1990s until a redressin the 2000s, with manufacturing and services accounting for 35% (Figure 76) and 44% (Figure 77)
of economic growth, respectively. In contrast, economic growth in India has always been dominatedby services and its growth has only become more pronounced over time. The contribution of

6 Industry Perspective%

1985–1990

1990–1995

Myanmar
KuwaitIranBahrainBruneiUAE
Oman
Lao PDR
Sri Lanka
Saudi Arabia
US
Qatar
Australia
Bangladesh
Fiji
Mongolia
Japan
Philippines
Nepal
VietnamTurkeyPakistan
India
Indonesia
China
ROC
Singapore
Malaysia
Korea
ThailandMongolia
Japan
Philippines
US
Fiji
Qatar
Saudi Arabia
TurkeyBrunei
Australia
Bangladesh
Pakistan
Nepal
Bahrain
MyanmarIndia
Oman
Sri Lanka
Iran
Lao PDR
ROC
Cambodia
Indonesia
Korea
VietnamThailand
UAE
Singapore
KuwaitMalaysia
China

12

1995–2000

2000–2010

10
8
6
4
2
0
−2
−4

%

12
10
8
6
4
2
0
−2

Brunei
Japan
Fiji
US
Australia
Nepal
ROC
Hong Kong
Saudi Arabia
TurkeyKuwait
Korea
Malaysia
Oman
UAE
Thailand
Pakistan
Philippines
Indonesia
Sri Lanka
Singapore
Iran
Mongolia
Bangladesh
Bahrain
Vietnam
India
Cambodia
Lao PDR
China
Myanmar
Qatar

ThailandIndonesia
Japan
Mongolia
BruneiFiji
KuwaitSaudi Arabia
Hong Kong
Oman
Philippines
TurkeyAustralia
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 75 Industry Origins of Economic Growth, 1985–1990, 1990–1995, 1995–2000, and 2000–2010___Industry decomposition: Average annual growth rate of GDP at constant prices
Sources: Official national accounts in each country, including author adjustments.

manufacturing and services to economic growth were 17% (Figure 76) versus 63% (Figure 77) in
2000–2010, compared with 18% and 51% in 1985–1990. The increased prominence of the service sector has weakened, not so much manufacturing’s hold, but agriculture’s – the contribution of whichshrank from 18% in the late 1980s to 8% in the latest period of comparisons.

©2013 Asian Productivity Organization

Manufacturing has sustained its prominence in Thailand, Korea, and the ROC, contributing 36%, 41%,
and 49% to economic growth in 2000–2010, respectively, while its importance is modest in Singapore
as 26% in 2000–2010 (Figure 76). 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, andthe sectors which bore the brunt were construction, wholesale and retail trade, hotels, and restaurants, and finance, real estate, and business activities. In contrast, manufacturing played a significant
role in bolstering the economy at the time (Figure 76).
The service sector plays an equal, if not more important, role in Asian economic growth. Services
made the biggest contribution to economic growth in all Asian countries except Qatar (Figure 77).
The story behind India’s recent growth has been one of services. Modern information and communication technology have allowed India to take an unusual path in its economic development, bypassing a stage when manufacturing steers growth.78 Within the service sector, contribution is quite
evenly spread among the sub-sectors, more recently the iron/steel and motor vehicle sectors havebeen intensively developed.79 For further improvement in per capita GDP and to capitalize on the96

6.2 Industry Growth

1995−2000
4.0

3.0

2.0

1.0

3.4
2.5
2.3
2.2
1.8
1.6
1.6
1.4
1.2
1.1
1.1
1.0
0.8
0.8
0.8
0.7
0.7
0.7
0.6
0.6
0.6
0.5
0.5
0.5
0.5
0.3
0.3
0.2
0.2

Contribution

2000−2010

0.0 −1.0 %China
Cambodia
Korea
Malaysia
VietnamSingapore
UAE
ROC
Sri Lanka
TurkeyIran
Lao PDR
Bangladesh
US
Philippines
Indonesia
India
MyanmarSaudi Arabia
Thailand
Qatar
Oman
Fiji
Pakistan
Nepal
BruneiBahrain
Australia
Japan
Kuwait0.0−0.4
Hong Kong−0.8 Mongolia

0

20

40

60

80 %

40

4.0

3.0

2.0

0.0 −1.0 %

3.5

36

2.5
2.0

47

1.9

40
26

1.9

27

1.7

25
26

1.6
1.4

25

1.2

29

1.2

27

1.2

17
17

1.2

18

1.0

20

1.0

1.1

116

1.0

12

0.9

9

0.9
22

0.8
110

0.8

6

0.8
17

0.8
31

0.6

13

0.4

10

0.4
24

0.3

6

0.1

6

0.1
25

0.1

−2

0.0

−14
−67

1.0

0.0

Contribution share

Contribution

−0.1

China
MyanmarVietnam
Cambodia
ROC
Korea
ThailandSingapore
India
BangladeshIndonesia
Pakistan
Iran
Oman
Bahrain
Malaysia
Qatar
Philippines
TurkeySaudi Arabia
Lao PDR
Sri Lanka
Mongolia
Kuwait
Japan
UAE
US
Fiji
Australia
Nepal
BruneiHong Kong

0

30

60 %
35

22
30
25
49
41
36
26
17
21

6

24
26
21
24
17
23
8
18
19
19
10
15
11
10
49
8
10
6
3
1
0
−3

Contribution share

Figure 76 Contribution of Manufacturing to Economic Growth, 1995–2000 and 2000–2010
Sources: Official national accounts in each country, including author adjustments.

demographic dividend (see Box 2, p. 33), expansion of labor-intensive manufacturing may be requiredin India for greater job creation.
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 50% of growth in the ROC for the period 2000–2010, 52% in Korea,
71% in Singapore, and 104% in Hong Kong (to counterbalance the negative contribution of 3% by
manufacturing and 2% by construction) (Figure 77). These compare with 99% in the US (to counterbalance the negative contribution of 12% by construction). In the 2000s, growth in Hong Kong was
highly skewed toward wholesale and retail trade, hotels, and restaurants, accounting for 44% of
growth. This compares with 23% in Singapore and 18% in the ROC. In contrast, the sector contributed
only 7% to Korea’s growth over the same period (Figure 78). Finance, real estate, and business activities also played an important part, contributing 40% to growth in Hong Kong, 28% in Singapore, and
14% in the ROC.

78: The computer software industry in India depends considerably on export demands. According to India’s Input–Output Table 2006–
2007, 82% of the output in computer and related activities is exported. This export is equivalent to 14.8% of total exports in Indiaand is the second-largest export product (among 130 products in this table).
79: 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.

97©2013 Asian Productivity Organization

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 its

6 Industry Perspective

1995−2000
5.0 4.0 3.0 2.0 1.0 0.0 −1.0 %
4.0
4.0
3.7
3.5
3.4
3.2
3.1
3.0
2.8
2.8
2.8
2.7
2.5
2.5
2.3
2.3
2.3
2.3
2.2
2.2
2.0
1.9
1.8
1.8
1.6
1.6
1.4
1.1
0.9
0.8
0.3
−0.3

Contribution

ROC
Singapore
India
China
UAE
US
Hong Kong
Australia
Sri Lanka
Cambodia
Malaysia
Iran
Myanmar
Korea
Bahrain
Nepal
VietnamBangladesh
Philippines
TurkeyQatar
KuwaitPakistan
Mongolia
Lao PDR
Saudi Arabia
Oman
Fiji
BruneiJapan
ThailandIndonesia

2000−2010
−30

0

30

60

90 %
74

6.0 5.0 4.0 3.0 2.0 1.0 0.0 %
4.7

65

4.5

63

4.5

41

4.4
55

4.4
77

4.0

103

3.8

79

3.7

58

3.7

41

3.4
3.3

51

3.2

69

3.2

33

3.1

53

2.9

60

2.9

50

2.8

34

2.7

45
60

2.7

58

2.7
2.6

20

2.5

97

2.5

48

2.3

144

2.2

29

2.2

59

2.1

43

1.9

68

1.4

65

1.3

80

1.2

55

0.5

−39

Contribution share

Contribution

India
Qatar
Bahrain
China
MyanmarHong Kong
Lao PDR
Singapore
Mongolia
Cambodia
Iran
Sri Lanka
UAE
Bangladesh
Philippines
TurkeyKuwaitMalaysia
Indonesia
Vietnam
Oman
Pakistan
Saudi Arabia
Australia
Thailand
Nepal
Korea
ROC
US
Brunei
Fiji
Japan

0

30

60

90 %
63

38
73
44
38
104
51
71
65
45
63
63
73
54
63
70
70
65
53
40
60
56
61
74
51
58
52
50
99
193
91
72

Contribution share

Figure 77 Contribution of Service Sector to Economic Growth, 1995–2000 and 2000–2010
Sources: Official national accounts in each country, including author adjustments.

economies from one period to another. In 2000–2010, mining accounted for almost half of economic
growth in Qatar, 10% in Kuwait, 7% in Saudi Arabia, and only 1% in Iran, reflecting a drop in the
demand toward the end of 2008 and 2009 (Figure 75). Still, it has been a drain on growth, in somecases a significant one; its contribution was −5% in Bahrain and Oman, and −124% in Brunei, reflecting a reduction in oil or gas production. These countries would do well to learn to diversify. Bahrain
has been successful in branching into finance, real estate, and business activities, which accounted for
34% of the 6.1% overall growth over the same period. Oman also sustained growth of 4.4% on averagea year, 60% of which originated from the service sector. Brunei has not managed as well, with dismal
growth of 0.7% on average a year between 2000 and 2010. Oil and gas production activities are also
reflected in Mongolia and the Lao PDR, where mining accounted for 18% and 20% of overall economic
growth, respectively, in the 2000s.

©2013 Asian Productivity Organization

For some Asian countries, agriculture is still the biggest sector. The four countries in which theagriculture sector has the largest share in total value added are Myanmar, Cambodia, Nepal, and theLao PDR (Figure 67, p. 89). For the period 2000–2010, agriculture in Myanmar, Nepal, and Cambodia
had the highest contribution to economic growth among all Asian countries, accounting for 33%,
30%, and 22% of growth, respectively.80 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 70, p. 92)

80: In Myanmar, agriculture accounted for over 36.4% of GDP in 2010. Since 1988, the government has continued its modest steps toliberalize 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 33.1% of GDP growth in 2000–2010.

98

6.2 Industry Growth

1995−2000
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
0.8
0.7
0.7
0.6
0.6
0.6
0.6
0.5
0.5
0.5
0.4
0.4
0.3
0.2
0.0
0.0
−0.1
−0.1

Contribution−0.2

2000−2010−20

MyanmarUAE
Sri Lanka
Iran
ROC
Vietnam
India
US
Nepal
Lao PDR
Philippines
China
Bangladesh
Cambodia
Mongolia
Hong Kong
TurkeySingapore
Malaysia
Australia
Korea
Fiji
Qatar
Saudi Arabia
Pakistan
Oman
Bahrain
Kuwait−2
Indonesia−8
Brunei
−14
Japan
−46
Thailand

0

20

40

60 %

23

2.4

23

2.0

26

1.7

31

1.4

22

1.3

16

1.2

17

1.2
23

1.1

18

1.1

15

1.0
22

1.0

10

1.0
15

0.9

11

0.9
57

0.8

23

0.8

17

0.8

10

0.8

11

0.7

15

0.7

11

0.6
32

0.6
0.5

5

0.5

17
10

0.4

9

0.4
0.3

5

0.3

2

0.2
0.2
0.1

Contribution share−20

3.0 2.5 2.0 1.5 1.0 0.5 0.0−0.5%

Contribution−0.1

MyanmarLao PDR
Hong Kong
India
Vietnam
China
Singapore
Sri Lanka
Cambodia
UAE
Qatar
BangladeshIndonesia
Mongolia
Philippines
Malaysia
Iran
Pakistan
Saudi Arabia
ROC
ThailandOman
TurkeyBahrainFiji
Australia
Korea
KuwaitBrunei
US
Nepal
Japan

0

20

40

60%

21
26
44
19
20
12
23
22
15
23

6

8
17
18
15
18
19
15
17
18
18
15
14
13
8
29
12
7
6
26
12
4
−9

Contribution share

Figure 78 Contribution of Wholesale and Retail to Economic Growth, 1995–2000 and 2000–2010
Sources: Official national accounts in each country, including author adjustments.

over the recent period is more a result of rapid growth in other sectors than any actual contractionof the sector.
Comparisons across the country groups in Table 15 reveal that Asia enjoyed more vibrant growth thanthe US in all sectors, it is notable that the US was more directly affected by the global financial crisis of
2008–2009 than Asia. Overall construction retrenched in the US in the 2000s, while growth has beenstrongest in South Asia and the GCC countries, at 8.7% and 9.2% a year on average respectively. Apartfrom construction, the other fast-growing sectors in GCC countries and South Asia were transport,
storage, and communications (at over 10% a year on average), presumably reflecting their effort inbuilding and upgrading infrastructure for their development needs. Finance, real estate, and businessactivities also enjoyed robust expansion at 9.0% and 7.4% a year on average in South Asia and GCC
countries, respectively, compared with 2.0% in the US and 3.7% in Australia. For East Asia, manufacturing has been growing at 7.4% a year on average in Asia23 and 6.6% in GCC countries, compared with
1.0% in the US and 0.7% in Australia.

81: The Törnqvist quantity index is adopted for calculating the growth of real GDP of manufacturing. Using this index, the growth ofreal GDP of manufacturing into the products of contributions by sub-industries of manufacturing can be decomposed:
In (GDPt / GDPt−1)= ∑ i (1/2) (sjt + sjt−1) In (Qjt / Qjt−1)
where Qjt is real GDP of a sub-industry j in period t and sjt is the nomReal GDP growth of manufacturing

Contribution of a sub-industry jinal GDP share of a sub-industry j in period t.

99©2013 Asian Productivity Organization

Figure 79 presents the sub-industry origins of average annual growth of manufacturing GDP for selected Asian countries for the periods 1995–2000 and 2000–2010.81 Manufacturing in Asia has been

6 Industry Perspective©2013 Asian Productivity Organization

Table 15 Output Growth by Industry, 2000–2010
4. Electricity, gas,
and water supply

5. Construction

−1.7
3.4
2.2
5.0
4.1
0.1
−1.3
−2.7
3.1
3.4
3.6
−1.1
1.3
7.8
2.8
2.9
0.7
7.9
3.2
2.6
2.6
2.8
6.0
1.2
−0.2
2.8
2.0
−2.4
3.5

−1.5
7.9
−1.3
17.5
10.7
−4.2
2.6
−6.9
4.6
1.1
0.2
−7.7
−1.1
1.4
42.9
0.4
5.3
13.2
3.7
−0.5
5.5
10.7
9.8
0.8
0.0
12.1
5.0
−0.4
1.7

8.2
7.2
−0.2
10.1
10.7
6.9
0.6
−3.8
8.1
4.4
8.3
1.8
6.1
5.3
8.5
3.4
7.8
19.8
0.7
11.4
7.0
3.7
10.6
7.7
5.5
4.0
5.4
3.0
9.9

13.9
6.8
3.1
11.9
10.7
2.8
2.4
1.6
5.8
7.7
7.9
1.0
5.4
14.0
4.2
4.6
3.6
12.0
5.1
11.5
0.4
4.4
6.6
11.2
4.0
6.3
5.6
7.6
12.2

9.5
7.2
4.7
7.1
11.9
−0.4
2.0
−2.2
9.1
6.7
3.9
−2.7
2.0
4.7
6.8
2.7
5.2
18.6
3.7
19.6
4.1
4.7
21.5
6.0
2.5
6.2
3.8
9.5
9.3

6. Wholesale andretail trade, hotels,
and restaurants
7. Transport,
storage, andcommunications
8. Finance, realestate, andbusiness activities
9. Community,social, andpersonal services

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

2. Mining___Average annual growth rate of industry GDP at constant prices
1. Agriculture

dominated by 3-8.machinery andequipment, accounting for 40%
or more of overall manufacturing
growth in half of the Asian countries compared. In Korea and theROC, it was over 80%. The subsector 3-1.food products, beverages, and tobacco products is thelargest contributor in the Philippines for both periods, accountingfor 55% of manufacturing output
growth in both periods. In Bangladesh and Cambodia, manufacturing growth has been dominatedby the sub-sector of 3-2.textiles,
wearing apparel, and leather
products, whereas in Kuwait, andto a lesser extent in Singapore
and Malaysia, it is 3-5.coke, petroleum, chemicals, rubber, and plastic products.

6.3
6.5
5.0
7.5
12.1
3.3
2.3
6.2
8.8
5.8
5.1
−0.5
2.4
3.3
10.2
6.3
8.6
10.8
1.0
7.1
4.4
5.2
16.5
10.2
6.4
4.8
3.5
5.5
7.5

9.8
7.3
4.1
7.5
8.7
3.0
1.8
4.1
12.2
12.1
9.7
1.2
5.0
12.9
8.7
5.9
13.6
16.7
6.1
11.1
3.5
6.7
22.9
12.0
3.9
8.3
5.7
8.3
8.8

8.0
4.4
4.5
8.2
11.4
2.6
1.5
4.5
9.5
6.5
8.2
0.6
3.6
5.1
8.4
6.9
6.4
22.5
4.7
6.4
5.7
6.2
16.2
7.2
5.4
5.6
5.7
6.8
5.4

8.3
5.5
3.9
9.9
10.5
2.6
1.5
1.6
6.3
5.2
4.3
1.3
3.6
6.3
10.3
5.3
3.7
12.0
7.5
5.4
6.2
4.4
10.2
3.3
5.0
4.3
3.4
7.0
6.3

Figure 80 contrasts industry contributions to economic growth forthe periods of 1995–2000 and
2000–2010, as well as between
the US and Asian averages.82 Even
within such a short period, one
can see that the industry struc(regrouped)ture of growth is changing. The
APO20
2.8
1.6
4.8
3.7
3.1
4.1
5.5
4.4
3.0
Asia23
3.4
5.5
7.4
6.7
6.0
6.2
6.5
5.8
4.9
first striking feature is the domiAsia29
3.4
4.0
7.3
6.8
6.1
6.3
6.7
5.9
4.9
nance of manufacturing in Asian
East Asia
3.6
10.3
7.7
7.0
5.3
5.8
5.1
4.8
4.7
countries. Between 1995 and
5.0
8.7
10.3
6.2
South Asia
3.1
4.9
7.8
8.0
9.0
ASEAN
3.5
1.5
5.0
5.6
6.1
6.3
5.8
8.0
4.8
2000, its contribution to economic
GCC
0.7
1.4
6.6
10.2
9.2
8.0
11.1
7.4
4.7
growth in Asia23 was 32% com(regrouped)
pared with 18% in the US. AlUS
3.1
0.1
1.1
0.1
−3.7
1.3
3.4
2.0
1.2
though its significance has fallen
Australia
1.9
2.4
0.7
1.5
6.6
2.8
3.7
3.7
3.0
Turkey
1.2
1.6
4.1
4.7
3.7
3.1
5.5
6.3
2.3
in recent years, it still accounted
for 30% of economic growth in
Unit: Percentage.
Sources: Official national accounts in each country, including author adjustments.
Asia23 between 2000 and 2010,
compared with 10% in the US.
This, however, masks a divergencewithin Asia. In the earlier period, manufacturing accounted for 35% of growth in East Asia but only
13% in South Asia. The corresponding figures were 35% and 17% in the 2000s, so the differential
is narrowing.
The country group most dominated by manufacturing in the late 1990s was ASEAN, with a contribution of 40%. Yet, in recent years manufacturing’s contribution was reduced to 26%, while wholesale
and retail trade, hotels, and restaurants increased from 10% to 18%. The latter also increased its weightin the APO20, from 12% to 16% between the two periods compared. In the US, the finance, real estate,1006.2 Industry Growth

1995–2000%

20

2000–2010

%

10
0.5

16
12

8

0.8

2.0

6

15.7

8.5
0.7

8
4
0

1.2

1.8

0.6
0.9 1.4

0.7
0.4

1.9 1.2

1.3
1.3 5.9
4.9
4.0
0.8
2.6
1.6

3.5 1.0
1.3 1.8
1.2

1.6 2.3 1.5 1.5

2
1.8
−2.2

0

3.5
0.4
0.4

1.0

1.8

0.8 0.5 3.3
0.7

4

2.7 0.8
0.8

5.6

3.0 0.7
0.4

0.9
0.5

4.8
3.2 3.0

2.2

0.5
1.4

1.9

6

0.3 1.6

1.3 1.2 0.5

1.8
−0.3

Japan
KuwaitPhilippines
Malaysia
Indonesia
ThailandSingapore
Korea
ROC
Bangladesh
India
Iran
Cambodia

Indonesia
Japan
ThailandUS
Philippines
India
Bangladesh
ROC
Iran
Korea
Malaysia
Cambodia

and business activities sub-sector
made the biggest contribution inboth periods, accounting for 33%
of economic growth in 1995–2000
and rising to 45% in 2000–2010.
In contrast, its contribution in Asia
was 14% in the period 2000–2010.
Mining in GCC countries took a hit
in 2008–2009 due to the downturn in the world economy. Consequently, the contribution ofmining fell from 14% to 11% between the two periods while construction’s share increased from
5% to 11%. Finance, real estate,and business activities became
the biggest contributors of economic growth in GCC countries,
with its share rising from 16% to
20% between the two periods.

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

Construction was hit hard in the
Figure 79 Industry Origins of Output Growth in ManufacASEAN countries during the Asianturing, 1995–2000 and 2000–2010
financial crisis, dragging down___Sub-industry decomposition: Average annual growth rate of GDP at
economic growth by 8% in theconstant prices of manufacturing
latter half of the 1990s. It bounced
Sources: Official national accounts in each country, including author adjustments.
back subsequently and contributed 6% to growth in the 2000s.
The corresponding figures for
Asia23 were 1% and 6%. The reverse was true in the US, where the contribution of construction was
4% in the earlier period but fell to −12% in the later period in the 2000s. The contribution of wholesale
and retail trade, hotels, and restaurants was also high in the US. In 1995–2000, it accounted for 23% of
US economic growth compared with 11% in Asia23. Though in 2000–2010 its contribution was reduced to 12% in the US, its significance to economic growth rose to 14% in Asia23.

82: 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.
83: The average growth rate of the Asian economy for 2000–2009 is set at 100%. Asian economic growth is calculated as the sum 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% are shown in Figure 81.

101©2013 Asian Productivity Organization

Figure 81 presents industry contributions to regional economic growth in Asia29 during 2000–2010,
decomposing Figure 7 (p. 19) in Section 3.1 into countries’ industry origins.83 In each industry contribution, the top eight countries are presented. The top four industries in terms of contributions to regional growth were manufacturing (29%), wholesale and retail trade (15%), finance, real estate, andbusiness activities (13%), and community, social, and personal services (14%). A total of 29% of Asian
economic growth originated from the expansion of its manufacturing sector, two-thirds of which was

6 Industry Perspective

accounted for by China. In other words, China’s
manufacturing sector alone accounted fornearly 18% of the region’s economic growth.
This was followed by China’s community, social,
and personal services (7.4%) and wholesale
and retail trade, hotels, and restaurants (6.9%).

%

1995―2000

100

16

120

25

20

20

21

19

5
14

80
12

12

11

2000―2010

23
14

12

16

15

15

18

15

14

16

13

14

11

12

18

33

11

13

14
20

US

GCC

ASEAN

South Asia

East Asia

Asia29Asia23©2013 Asian Productivity Organization

12

APO20

US

GCC

ASEAN

South Asia

East Asia

Asia29APO20

102

Asia238Over a period of four decades there has been a
10
45
9 10
9
13
12 12 12 10 5
1212noticeable shift in the industry origins of eco60
12
14
14 14
18
16 8
nomic growth (Figure 82). For the ROC and Ko8
11 11 0
5
16
17
19
16
1
1
4
4
6
rea, manufacturing has been a clear driving
6
12 4
6
4
5
3
3
40
2
3
force behind economic growth on the whole.
5
23
6 40
4
9
11 19
2
3
In the decade between the mid-1980s and the
20
1
35 13
35
31
26 3
32
30 29
4
mid-1990s, however, the importance of manu25
20 25
12
17
0
1
13
5
0
facturing retreated in the ROC temporarily
14
18
2
2
0
10
2
2
1
4
4
3 16 13511
while the economy developed its service sec9
9
1
7
7
7
6
6
5
5
4
4
2
2
0
0
−1
tor. Since the mid-1990s, the role of manufac−2−8−12turing in the ROC has increased again, althoughcompared to its heydays of the 1970s and−20
1980s its impact in terms of percentage points
is much reduced. In Singapore, finance, real estate, and business activities, as well as whole2. Minig
1. Agriculture
sale and retail trade, hotels, and restaurants are
3. Manufacturing
4. Electricity, gas, andwatersupply
5. Construction
important drivers alongside the manufacturing
6. Wholesale and retail trade,
7. Transport, storage, andhotels, and restaurants
sector. Working within the data constraints,
communications
9. Community, social, and
8. Finance, real estate, andHong Kong appears a clear service-driven
personal services
business activities
economy in recent years. While the lack of diFigure 80 Industry Origins of Regional Ecoversification of the oil-exporting countries cannomic Growth, 1995–2000 and 2000–2010
not be missed; historically, the dominance of___Contribution sharethe mining sector influenced the economic
Sources: Official national accounts in each country, including auvolatility of these countries, yet, in recent years
thor adjustments.
the GCC countries have been making efforts indiversifying, especially into the service sector,
with different degrees of success – Bahrain andOman are leading 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 thePhilippines, construction was driving economic growth in the first half of the period, but it never recovered its dominance after its crash in the mid-1980s. In the second half, economic growth was better balanced, with the development of finance, real estate, and business activities in particular.
146.2 Industry Growth

3. Manufacturing
18.0

0

5

2.8

10

China

15

India

Korea

1.5 1.2 1.0

4.6

20

25

30

Japan

ROC

Rest of the Asia

35 %9. Community, social, and personal services
7.4

0

2

1.9

4

China

6

India

1.4

8

Japan

0.6 0.4

10

2.6

12

6

14 %

Iran

Korea

Rest of the Asia

6. Wholesale and retail trade, hotels, and restaurants
6.9

0

2

3.2

4

China

India

0.6 0.5 0.4

6

8

10

Indonesia

IranHong Kong

2.9

12

14 %
Rest of the Asia

8. Finance, real estate, and business activities
5.4

0

3.2

2

4

China

0.8

6

India

8

Iran

0.7 0.4

3.2

10

12

14 %

Japan

Korea

Rest of the Asia

7. Transport, storage, and communications
3.7

0

2.2

2

0.6

4

China

India

0.5 0.4

2.2

6

Indonesia

8

10

Japan

Iran

12 %

Rest of the Asia

5. Construction
3.7

0

1

1.5

2

China

3

India

0.3

4

Indonesia

0.2 0.2 0.3

5

UAE

6%

Korea

Rest of the Asia

1. Agriculture
2.5

0

1
China

2
India

1.3

0.3

Iran

Pakistan

3

Indonesia

0.2 0.2

0.7

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 0.3

4

Saudi Arabia

5%

KuwaitRest of the Asia

4. Electricity, gas, and water supply

0

0.5
China

0.3

1
India

1.5
Japan

2
Iran

0.1 0.1 0.1

0.5

2.5
Korea

3

3.5 %

Rest of the Asia

Figure 81 Industry Origins of Asian Economic Growth, 2000–2010___Contribution to regional growth of GDP at constant prices, using 2005 PPP
Sources: Official national accounts in each country, including author adjustments.

103©2013 Asian Productivity Organization

2.0

6 Industry Perspective

Bahrain%50
40

Bangladesh

%
12
9

30

10

6

0

20
3

10

−20

−3

−10
1971 1976 1981 1986 1991 1996 2001 2006

Cambodia

%
12

9
6
3
0
−3

−10

0

0

−20

Brunei%20

1971 1976 1981 1986 1991 1996 2001 2006

Hong Kong

%
16
12
8

−6

1971 1976 1981 1986 1991 1996 2001 2006

China

%
15

−30

12

9

9

6

6

3

3

0

0

−3

−3

India

%
9

ROC

%
15

12

1971 1976 1981 1986 1991 1996 2001 2006

1971 1976 1981 1986 1991 1996 2001 2006

1971 1976 1981 1986 1991 1996 2001 2006

Indonesia

%
10

6

5

3

0

0

−5

−3

−10

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
8

10

2

6

0

3

−2

0

−4

−20

−3

−6
−30

1971 1976 1981 1986 1991 1996 2001 2006

Kuwait%60−81971 1976 1981 1986 1991 1996 2001 2006

Lao PDR%
15

40

1971 1976 1981 1986 1991 1996 2001 2006

Malaysia

%
12

4
5

0

0

−20
0

−4

−40

1971 1976 1981 1986 1991 1996 2001 2006

Mongollia

%
9
6
3
0

©2013 Asian Productivity Organization

−6

8

10
20

−60

Korea

%
15

9

4

−10

1971 1976 1981 1986 1991 1996 2001 2006

12

6

0

−15

−5

1971 1976 1981 1986 1991 1996 2001 2006

Myanmar%15−81971 1976 1981 1986 1991 1996 2001 2006

Nepal

%
8

10

6

5

4

0

2

−3
−6
−9
−12

1971 1976 1981 1986 1991 1996 2001 2006

−5

0

−10

−2

−15

1971 1976 1981 1986 1991 1996 2001 2006

1. Agriculture
2. Mining
5. Construction
6. Wholesale and retail trade, hotels, and restaurants
9. Community, social, and personal services

104

−4

1971 1976 1981 1986 1991 1996 2001 2006

3. Manufacturing
7. Transport, storage, and communications
Real GDP

4. Electricity, gas, and water supply
8. Finance6.2 Industry Growth

%
30

Oman

Pakistan

%
10
8

20

6

6
10

4

0

2

3
0
−3

0
−10
−20

%
45

−6

−2
1971 1976 1981 1986 1991 1996 2001 2006

Qatar

−4

Philippines%
91971 1976 1981 1986 1991 1996 2001 2006

Saudi Arabia

%
20

−9

1971 1976 1981 1986 1991 1996 2001 2006

Singapore

%
15

15
10

30

10

5
0

15

5

−5

6

−10
0

0

−15
−20

−15

%
9

1971 1976 1981 1986 1991 1996 2001 2006

Sri Lanka−25

1971 1976 1981 1986 1991 1996 2001 2006

Thailand

%
16
12

6

−5

1971 1976 1981 1986 1991 1996 2001 2006

UAE

%
100
80

8

60

4
3

%
9

20

−4

0

−3

40

0

1971 1976 1981 1986 1991 1996 2001 2006

Vietnam

6

3

0

−8

0

−12

−20

1971 1976 1981 1986 1991 1996 2001 2006

US

%
7

%
10

1971 1976 1981 1986 1991 1996 2001 2006

6

5

5

4

4

3

3

2

2

1

1

0

0

−1

−1

−3

Australia

%
7

6

−2
−3

1971 1976 1981 1986 1991 1996 2001 2006

−2
1971 1976 1981 1986 1991 1996 2001 2006

−3

1971 1976 1981 1986 1991 1996 2001 2006

Turkey

8
6
4
2
0
−2
−4
−6
−8

1971 1976 1981 1986 1991 1996 2001 2006

1. Agriculture
2. Mining
5. Construction
6. Wholesale and retail trade, hotels, and restaurants
9. Community, social, and personal services

3. Manufacturing
7. Transport, storage, and communications
Real GDP

4. Electricity, gas, and water supply
8. Finance

Figure 82 Industry Origins of Economic Growth, 1970–2010
Sources: Official national accounts in each country, including author adjustments.

105©2013 Asian Productivity Organization___Industry decomposition: Average annual growth rate of GDP at constant prices

6 Industry Perspective©2013 Asian Productivity Organization

5. Construction

6. Wholesale andretail trade, hotels,
and restaurants
7. Transport,
storage, andcommunications
8. Finance, realestate, andbusiness activities
9. Community,social, andpersonal services

4. Electricity, gas,
and water supply

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

3. Manufacturing

Table 16 presents cross-country
comparisons in labor productivity
growth by industry84 for the period 2000–2010.85 Positive laborproductivity growth was achieved
across all sectors for Asia23. If one
focuses on the regional economy,___Average annual growth rate of industry labor productivity
2. Mining

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
2011, Hong Kong and Singapore
were the countries that had laborproductivity levels comparable
to that of the US. Besides thesetwo, the best performers in Asia
achieved productivity levels thatwere at least 40% that of the US;
yet, Asia collectively was dragged
down by a long tail of countries
with labor productivity of lessthan 20% of the US level, pulling
down the average performance
to 17% that of the US for the
APO20 and 15% for Asia23. In
growth terms, however, Asia’s
performance far exceeded that of
the US, allowing the countries toclose the gap with the US gradually over time. Labor productivity
growth in Asia23 was 5.5% per annum on average between 2005
and 2011, compared to 1.3% in
the US (Table 9, p. 61).

Table 16 Labor Productivity Growth by Industry, 2000–2010
1. Agriculture

6.3 Labor Productivity by
Industry

−7.0
0.8
−0.5
3.8
6.7
3.0
0.3
−1.8
2.5
3.1
1.8
0.9
4.9
0.4
0.0
2.7
1.9
0.0
0.0
1.6
0.1
1.2
−2.3
1.2
−6.9
2.8
1.5
−0.1
3.7

3.3
7.4
−3.7
12.1
9.0
5.9
6.4
0.0
1.5
−3.0
1.2
−1.1
−3.3
1.7
0.0
−7.2
−0.8
0.0
−6.4
−1.8
−1.0
4.5
−9.4
1.3
0.0
11.2
5.9
−5.7
1.1

2.2
1.3
−4.1
2.5
8.0
6.1
1.7
5.3
3.4
2.5
6.0
3.7
6.8
−0.4
0.0
4.2
6.0
0.0
0.0
4.8
2.3
2.8
0.4
5.2
3.9
2.4
4.0
1.2
3.7

21.5
7.8
0.1
−4.7
8.1
3.1
2.0
3.0
3.1
4.0
6.0
1.0
3.4
7.4
0.0
−4.4
7.2
0.0
0.4
2.2
−4.1
1.0
6.2
9.4
1.2
13.6
6.1
2.4
1.4

−8.7
−1.2
2.0
−6.1
7.6
0.0
−9.5
−1.1
6.4
1.9
−1.1
−0.5
1.0
−0.8
0.0
−0.9
−2.2
0.0
1.5
0.4
−0.7
1.6
0.1
−1.0
0.1
4.7
−0.7
7.6
−1.5

−2.6
3.3
2.0
−0.5
8.3
2.1
−0.3
5.0
6.1
3.7
0.9
−0.6
2.9
−2.8
0.0
1.8
2.7
0.0
−0.9
3.4
−0.8
−0.7
4.3
5.5
2.4
1.7
0.0
−1.6
3.0

−5.0
2.1
1.4
0.9
7.1
2.8
2.5
2.3
9.5
9.9
3.9
0.8
0.7
6.6
0.0
0.6
3.7
0.0
2.5
4.0
−0.2
3.8
3.2
7.3
0.5
4.5
4.3
−0.9
5.3

6.6
−6.0
1.3
0.2
8.9
−0.2
−3.8
1.0
6.8
−0.4
1.0
0.7
−0.6
−4.8
0.0
−0.8
5.2
0.0
−1.0
2.0
−3.5
−2.7
2.3
−0.5
−0.4
−0.8
1.6
−8.4
−8.3

0.3
5.0
0.7
0.8
8.0
0.2
1.6
0.1
3.6
0.0
4.3
0.3
−0.5
−1.3
0.0
3.2
−0.6
0.0
10.3
2.1
5.3
3.4
1.4
0.2
−0.1
3.3
−0.2
−1.8
−1.4

2.0
4.1
4.0
6.2
2.1
3.1
0.6

−1.4
3.3
1.8
8.6
1.9
−2.2
−2.8

1.4
4.3
4.2
5.5
3.0
2.7
3.0

1.1
4.1
4.2
4.7
2.2
1.1
7.6

−0.1
2.1
2.2
1.8
4.9
0.4
0.1

1.4
3.1
3.1
2.9
4.9
2.1
2.4

2.7
4.2
4.3
3.6
7.0
5.3
3.7

0.8
2.5
2.4
2.5
5.9
−1.2
−2.2

0.6
2.5
2.4
2.4
4.2
0.5
−0.1

4.1
3.9
4.6

−2.2
−6.6
−0.8

5.1
1.4
2.9

0.9
−4.4
2.0

−2.3
2.3
3.5

1.9
1.1
1.0

4.9
2.4
4.2

2.0
1.4
−0.6

0.0
−0.2
−0.3

(regrouped)

APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
GCC
(reference)

US
Australia
TurkeyUnit: Percentage.
Source: APO Productivity Database 2013.01.

84: 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 real per-worker GDP by industry to its industry average. Thus, the industry
contribution (wjvj*) is emphasized more in industries in which the per-worker GDP is higher than the industry average, in comparison with the impact (wjvj) of using the non-adjusted measure of labor productivity.
85: The data presented in this chapter is subject to bigger uncertainty than those in previous chapters and the quality across countries is also more varied. Employment data of the less developed countries often lacks 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 compromised. Furthermore, estimates of the manufacturing sector
should be of better quality than those of the service sector as many countries have occasional manufacturing censuses, but do
not have a similar census covering the service sector.

1066.3 Labor Productivity by Industry%

12

1985–1990

9

1990–1995

6
3
0
−3

6

Mongolia
Philippines
Fiji
Japan
TurkeyUS
Nepal
Australia
Bangladesh
India
MyanmarCambodia
Pakistan
Iran
Sri Lanka
Singapore
Korea
ROC
VietnamIndonesia
Malaysia
Thailand
China

Myanmar
IranMongolia
Australia
Bangladesh
Turkey
US
China
India
Fiji
Indonesia
Philippines
Sri Lanka
Pakistan
Japan
Nepal
Singapore
Malaysia
Thailand
ROC
Korea

−6

%

10

1995–2000

8

2000–2010

6
4
2
0
−2
Australia
Fiji
Japan
Nepal
Pakistan
Singapore
US
Malaysia
Philippines
Iran
Bangladesh
Thailand
ROC
Korea
Hong Kong
Indonesia
Mongolia
TurkeySri Lanka
Cambodia
Vietnam
India
China

Indonesia
Mongolia
ThailandIran
FijiPakistan
Hong Kong
Japan
Nepal
Malaysia
Sri Lanka
Australia
Philippines
US
MyanmarTurkeyCambodia
India
Bangladesh
Korea
Singapore
ROC
VietnamChina−4

3. Manufacturing

1. Agriculture

2. Mining

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 83 Industry Origins of Labor Productivity Growth, 1985–1990, 1990–1995,
1995–2000, and 2000–2010___Industry decomposition: Average annual growth rate of GDP at constant prices
Source: APO Productivity Database 2013.01.

Figure 83 shows the industry origins of average labor productivity growth per annum in four periods:
1985–1990, 1990–1995, 1995–2000, and 2000–2010.86 In the past two and a half decades, the role
played by agriculture (both positive and negative) has been diminishing in Asian countries. While theimportance of manufacturing has never waned in some countries (e.g., Korea, the ROC, China, and

86: Not all Asian countries are included, as employment by industry sector is not available for some countries.

107©2013 Asian Productivity Organization

the findings highlight the fact that service industries no longer hamper an economy’s productivity
performance but are as capable as manufacturing in achieving productivity growth. In fact, there areno significant differences between manufacturing and some services in Asia23; i.e., manufacturing (at4.3% on average a year), transport, storage, and communications (4.2%), agriculture and electricity(4.1%). Construction was the sector with the slowest productivity growth at 2.1%. 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. When excluding China, the labor productivity growth in manufacturing remains much higher than that of the highest service sector inJapan, Korea, and the ROC.

6 Industry Perspective

1995−2000
4.0 3.0 2.0 1.0 0.0 −1.0 %
China
Korea
Singapore
Cambodia
Vietnam
Malaysia
ROC
Hong Kong
Bangladesh
US
Japan
Philippines
ThailandTurkeyIndonesia
Sri Lanka
Australia
Iran
FijiPakistan
Myanmar
India
Nepal
Mongolia

3.4
2.8
1.7
1.5
1.3
1.3
1.0
0.9
0.8
0.7
0.6
0.6
0.5
0.5
0.4
0.4
0.2
0.2
0.0
0.0
−0.2
−0.4
−0.4
−0.5

2000−2010

−30

0

30

60 %
47

2.0

1.0

0.0 %

0
China
Korea
ROC
Thailand
Vietnam
Malaysia
Cambodia
Singapore
Indonesia
Philippines
Iran
Japan
Pakistan
Bangladesh
TurkeyUS
Mongolia
Hong Kong
Sri Lanka
India
Fiji
Australia
Nepal

3.0
68

1.8

41

1.7

47

1.4

28

1.3
78

1.2

22

1.2

87

1.0

21

1.0

32

0.8

45

0.7

28

0.7

283

0.6

17

0.6

−28

0.5

24

0.5

12

0.5

50

0.5

3
−4

0.5

−6

0.3

−11

0.3

−29

0.2

−276

0.0

Contribution share toaggrergate labor productivity

Contribution
contribution

3.0

20

40

60

80 %

32
61
60
55
32
68
30
70
31
40
30
73
46
23
15
34
16
15
12
6
35
19
−2

Contribution share toaggrergate labor productivity

Contribution
contribution

Figure 84 Contribution of Manufacturing to Labor Productivity Growth, 1995–2000 and
2000–2010
Source: APO Productivity Database 2013.01.

1995−2000
4.0 3.0 2.0 1.0 0.0 −1.0−2.0 %
3.1
2.6
2.6
2.4
2.3
2.2
1.5
1.5
1.4
1.3
1.1
1.1
1.0
0.9
0.8
0.8
0.6
0.4
0.3
0.3
0.2
0.0
−0.9
−1.0

©2013 Asian Productivity Organization

contribution
Contribution

2000−2010
0

India
ROC
China
Singapore
Bangladesh
CambodiaUS
Sri Lanka
Australia
Nepal
Mongolia
Vietnam
Pakistan
Myanmar
Korea
TurkeyIranJapan
Philippines
Malaysia
Hong Kong
1
Fiji
Thailand −471
Indonesia

30

60

90 %
90

59

5.0 4.0 3.0 2.0 1.0 0.0 %
4.1
3.6

36

2.5
57

2.2

59

2.0
67

2.0

67

1.8

90

1.6

70

1.5

91

1.4

647

1.3

22

1.3

104

1.2

36

1.1

20

1.1

24

1.0

130

0.9

27
16

0.7

18

0.6

23

0.6
0.5
0.4
0.1

64

Contribution share toaggrergate labor productivity

contribution
Contribution

India
China
Hong Kong
Sri Lanka
Nepal
Bangladesh
Iran
TurkeyCambodia
Indonesia
Mongolia
Pakistan
VietnamPhilippines
US
Thailand
ROC
Fiji
Korea
Singapore
Malaysia
Australia
Japan

0

20

40

60

80

100 %

74
38
82
60
191
83
77
44
38
44
41
102
30
56
68
39
31
80
21
39
29
49
10

Contribution share toaggrergate labor productivity

Figure 85 Contribution of Service Sector to Labor Productivity Growth, 1995–2000 and
2000–2010
Source: APO Productivity Database 2013.01.

108

6.3 Labor Productivity by Industry

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 Figure 84. In the late 1990s, manufacturing accounted for a significant part oflabor productivity growth in Korea (68%), Malaysia (78%), and China (47%). Nevertheless, its role haslessened in the 2000s to 61%, 68%, and 32%, respectively. In contrast, contributions from manufacturing strengthened from 22% to 60% in the ROC and from 45% to 73% in Japan between the two
periods. In other economies, however, like India, Hong Kong, Sri Lanka, and Nepal in the 2000s, manufacturing played a negligible role.

6

Traditionally, it has been difficult for the service sector to realize productivity growth, but modern advancements in information and communication technology have changed all this. A lot of IT-intensive
users are located in this sector, which is capable of capturing the productivity benefits arising from IT
utilization. The growing importance of these services has been observed in explaining the productivity growth in Western economies of recent decades. In Asia, the contribution from services matches
that of manufacturing. Among the four industries in the service sector, three are potentially ITemploying industries: wholesale and retail trade, hotels, and restaurants; transport, storage, and communications; and finance, real estate, and business activities. Figure 85 presents the contribution ofservices in labor productivity growth by country. In the 2000s, services were contributing at least onethird or more to labor productivity growth in most Asian countries. The contribution was predominantin Hong Kong and India, accounting for 82% and 74% of labor productivity growth, respectively. It
also accounted for around two-thirds or more of labor productivity growth in the US, Sri Lanka, andSingapore. Korea had the lowest share from the service sector, accounting for less than one-fifth oflabor productivity growth. There is a slight expansion of the role played by services in China between
these two periods, from 36% to 38%. The contribution of services was also highly significant in South

1.0
0.8
0.8
0.7
0.7
0.6
0.6
0.4
0.3
0.2
0.2
0.2
0.2
0.2
0.0
0.0
0.0
0.0
−0.3
−0.3
−0.3
−0.4

Contribution
contribution

Myanmar
Sri Lanka
India
Bangladesh
US
ROC
China
Iran
CambodiaFiji
Mongolia
Australia
Philippines
Pakistan
Nepal
Korea
Japan
VietnamSingapore
Hong Kong
TurkeyMalaysia−1.0 Indonesia−1.1 Thailand

2000−2010

−30

0

30

60 %
37

2.0 1.5 1.0 0.5 0.0 −0.5 %
1.3

49
23

1.2
0.9

19

0.7
31

0.7

15

0.5

9

0.5

77

0.4

10

0.4

29

0.4

127

0.3

11

0.1

9

0.1

17

0.1

3

0.0

1
−2

0.0

−1

0.0
0.0

−7

−0.1

−32
−11

−0.1

−26

−0.1
−0.2

69
−570

Contribution share toaggrergate labor productivity−0.3

contribution
Contribution

Hong Kong
India
China
Vietnam
Sri Lanka
Indonesia
Bangladesh
Korea
ROC
Singapore
US
Iran
TurkeyCambodia
Pakistan
Australia
Mongolia
Nepal
Japan
ThailandFiji
Malaysia
Philippines

−20

0

20

40 %
43
22

10
17
18
15
19
13
14
25
17
5
2
2
0
−1
−1
−4
−10
−4
−15
−11
−17

Contribution share toaggrergate labor productivity

Figure 86 Contribution of Wholesale and Retail Sector to Labor Productivity Growth, 1995–
2000 and 2000–2010
Source: APO Productivity Database 2013.01.

109©2013 Asian Productivity Organization

1995−2000
1.2 0.8 0.4 0 −0.4 −0.8 −1.2 %6 Industry Perspective©2013 Asian Productivity Organization

Asian countries like Bangladesh, India, Nepal, and Pakistan over the same term. Finance, real estate,and business activities made the largest contribution of 1.3 percentage points in India and 1.0 percentage point in Singapore, respectively, while transport, storage, and communications made thelargest contribution of 1.1 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 2000–2010, while the contribution of manufacturing was negative for the period 1995–
2000 and 6% in 2000–2010.

110

7 Real Income
The standard GDP concept does not adequately measure welfare, as discussed in Section 3. Among its
shortcomings is the 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.87 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.88 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, as many Asian economies are (see Figure 26, p. 42). For example, real income
growth for oil-exporting countries was more than double that of real GDP growth in recent years (asin Saudi Arabia and Brunei), while there has been no significant difference between real income
growth and real GDP growth in Myanmar, which is a relatively closed economy (Figure 93, p. 118). In
the recent decade, the trading gain has also driven a significant wedge between real income and real
GDP in Australia. That is partly due to a fall in import prices, but owes more to the rising prices of its
commodity exports.
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,89 while real income is calculated fromthe prices of domestic expenditure, consisting of household consumption, government consumption, and investment. Therefore, real income can be understood as how much domestic expenditure
can be purchased with the current income flow.90 As such, real income captures the purchasing powerof the income flow. Furthermore, the Databook adopts the concept of gross national income (GNI)
instead of GDP in its estimation of real income, to take into account net income transfer from abroad.
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),91 and the effectof net income transfer.92

87: See Diewert and Morrison (1986) and Kohli (2004).
88: Kohli (2004) elaborates: “if real GDP is measured by a Laspeyres quantity index, as it is still the case in most countries, an improvement in the terms of trade will actually lead to a fall in real GDP.”
89: The weight for import price changes is negative. Thus, if import prices decrease, this tends to raise the GDP deflator.
90: 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).
91: The term “trading gain” is used by some authors (Kohli, 2006). This term is adopted in this report.
92: 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/GDP t

D

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.

111©2013 Asian Productivity Organization

GNIt

7 Real Income

A general observation is that over a long period of time the trading gain effect is, on average, small,but over a shorter period it could be very significant.93 The findings presented in Table 17 confirm thisobservation. Excluding the oil-exporting countries, the trading gain effect in 17 out of 22 the economies compared, fell within the margin of ±10% of real GDP growth on average for the long period of
1970–2011. Movements in terms of trade have been consistently unfavorable to Japan and the ROC.
In the short 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 and, as such, its
Table 17 Real Income and Terms of Trade, 1970–2011, 1995–2000, 2000–2005, and 2005–2011___Average annual growth rate of real income, real GDP, trading gain, and net primary income transfer from abroad

Bahrain5.88 4.88
Kuwait5.70 0.72
Oman
7.93 6.31
Qatar
6.55 5.92
Saudi Arabia 6.50 4.21
UAE
10.51 10.15

1.34 −0.38
4.56
0.43
1.48
0.14
0.78 −0.14
1.27
0.84
0.00
0.35

©2013 Asian Productivity Organization(reference)(reference)

US
EU15

2.71 2.76 −0.07
0.03
2.17 2.21 −0.04 −0.01

Australia
Turkey3.57 3.33 0.30 −0.05
4.19 4.35 −0.14 −0.03

US
EU15
EU27
Australia
Turkey

6.52
7.59
3.45
8.75
4.28
4.69
2.85

1.33
4.63
4.17
5.69
4.91
1.74
5.15

−0.02
−1.18
0.21
−2.32
−0.07
0.05
0.00

(reference)

4.27
2.86
2.75
3.96
3.98

4.19 0.08
0.00
2.86 −0.07
0.06
2.80 −0.11
0.06
3.69 0.12
0.15
4.37 −0.31 −0.08

US
EU15
EU27
Australia
TurkeyTrading gain

Net primary income
from abroad

Bahrain
7.84
Kuwait
11.04
Oman
7.83
Qatar
12.12
Saudi Arabia 9.13
UAE
6.48
Brunei
8.00

2.87
4.42
4.09
5.83
2.02
1.87
3.59

Real GDP

−0.35
−0.06
−0.38
−0.97
−0.21
−0.27
0.00

3.51
1.68
3.12
8.91
2.64
6.57
1.81

11.84 11.83 0.00
0.00
10.95 10.24 0.61
0.10
10.11 10.37 0.00 −0.26
9.90 7.13 3.08 −0.32
8.80 7.14 1.97 −0.30
7.51 7.57 0.05 −0.11
6.79 7.04 −0.32
0.07
6.75 4.76 1.24
0.75
5.50 4.67 0.72
0.11
5.40 4.25 −0.28
1.44
5.23 5.41 −0.45
0.27
4.64 5.17 −0.01 −0.52
4.63 4.77 −0.80
0.65
3.96 4.55 −0.96
0.37
3.71 4.47 −0.84
0.08
3.52 4.68 0.09 −1.25
2.89 4.01 −1.01 −0.11
2.64 3.11 −0.55
0.07
2.36 3.60 −1.47
0.22
1.59 1.75 0.36 −0.52
1.04 1.18 −0.34
0.21Real income

Bahrain
6.04
Kuwait
6.04
Oman
6.82
Qatar
13.78
Saudi Arabia 4.45
UAE
8.18
Brunei
5.39

Trading gain

Myanmar
China
Cambodia
Mongolia
Iran
Vietnam
India
Malaysia
Sri Lanka
Philippines
Bangladesh
Thailand
PakistanIndonesia
Korea
Singapore
Hong Kong
Nepal
ROC
Fiji
Japan

2005–2011
Net primary income
from abroad

0.08
−0.27
−0.27
1.69
0.01
−0.03
0.15
−0.31
−0.77
−0.15
−0.61
0.12
1.00
−0.02
−0.37
−0.04
0.09
−0.81
−0.01

Real GDP

China
6.96 7.74 −0.85
Vietnam
6.84 6.90 0.21
Singapore
6.43 6.46 0.23
Philippines
5.52 2.69 1.15
India
5.42 5.59 −0.18
ROC
5.34 5.47 −0.11
Iran
5.19 2.72 2.32
Cambodia5.15 5.42 0.04
Malaysia
5.02 5.37 0.41
Sri Lanka
4.82 5.04 −0.07
Myanmar4.10 4.67 0.04
Bangladesh 4.07 4.15 −0.20
Fiji
3.57 3.68 −1.13
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
Thailand−0.90 0.31 −1.20

Real income

Net primary income
from abroad

−0.01
−0.14
−0.04
−0.03
−0.03
0.07
−0.03
0.08
0.10
−0.01
−0.08
−0.20
−0.07
0.11
0.72
0.05
0.20
0.08

2000–2005
Trading gain

Net primary income
from abroad

8.61 −0.03
6.73 0.10
7.30 −0.06
6.40 0.49
7.09 −0.49
7.04 −0.92
5.41 0.67
5.76 −0.07
3.64 1.81
5.46 0.00
5.71 −0.43
5.34 0.01
5.34 −0.27
4.59 −0.26
3.49 −0.02
2.57 0.59
3.12 −0.31
2.70 −0.32

Real GDP

Trading gain

8.58
7.24
7.19
6.86
6.58
6.19
6.06
5.76
5.56
5.45
5.20
5.15
5.00
4.44
4.19
3.22
3.01
2.46

Real income

Real GDP

China
VietnamSingapore
Malaysia
Korea
ROC
Indonesia
Hong Kong
Iran
India
ThailandMyanmar
Sri Lanka
Pakistan
Philippines
Fiji
BangladeshJapan

1995–2000

Real income

1970–2011

China
11.05 11.35 −0.38
0.09
Myanmar10.10 10.10 0.01
0.00
Mongolia
8.80 9.13 1.01 −1.35
India
8.52 8.35 0.20 −0.03
Cambodia7.78 7.16 0.80 −0.18
Vietnam
7.02 6.70 0.79 −0.46
Sri Lanka
6.46 6.75 −0.31
0.02
Bangladesh 5.99 6.02 −0.64
0.62Singapore
5.88 6.16 −1.29
1.02
Malaysia
5.50 4.49 0.66
0.34
Indonesia
5.28 5.66 −0.72
0.34
Philippines
5.21 4.75 −0.36
0.82
Nepal
4.86 4.24 0.59
0.03
Iran
4.77 3.59 1.06
0.12
Hong Kong
3.74 4.03 −0.76
0.47
Pakistan
3.61 3.97 −0.76
0.40
Thailand2.93 3.10 −0.42
0.24
Korea
2.89 3.94 −1.10
0.06
ROC
1.39 4.00 −2.67
0.06
Fiji
0.65 0.32 0.51 −0.18
Japan−0.05 0.40 −0.57
0.13
Bahrain8.10 5.72
Kuwait6.06 1.53
Oman
9.70 4.75
Qatar
14.44 13.34
Saudi Arabia 5.83 2.91
UAE
4.47 2.85
Brunei6.37 −0.65

4.23
5.13
5.14
0.59
3.18
1.78
6.95

−1.85
−0.61
−0.19
0.50
−0.27
−0.16
0.09

(reference)

2.39
2.04
2.06
4.31
4.67

2.36 −0.04
0.08
1.80 0.08
0.16
1.85 0.07
0.14
3.38 1.18 −0.24
4.59 0.27 −0.19

US
EU15
EU27
Australia
Turkey

0.89
0.60
0.73
4.21
3.27

0.86 −0.12
0.15
0.82 −0.20 −0.02
0.95 −0.19 −0.03
2.85 1.20
0.16
3.89 −0.63
0.01

Unit: Percentage.
Sources: Official national accounts in each country, including author adjustments.
Note: See footnote 92 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 1970–2011: Brunei (1989–), Cambodia (1993–), Mongolia (2000–), and Nepal (2000–).

93: 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.

1127.1 Real Income and Terms of Tradeterms of trade have been turning strongly in its favor. The trading gain effect in Australia has therefore
been rising from 3% on average a year in 1995–2000, to 35% in 2000–2005, and 42% in 2005–2011 of
its real GDP growth. (In terms of percentage points, the trading gain added 0.12, 1.18, and 1.20 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, making it possible to sustain a rise in purchasing power with little real GDP growth in countries such as in Kuwait, Saudi Arabia and Brunei in the second halfof the 2000s.
Over the past four decades, net primary income from abroad has not moved outside the margin of±10% of real GDP growth on average for all 29 countries compared, except for 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 large number of overseas workers.
When its real GDP growth slowed (such as during the late 1990s), net primary income from abroadplayed 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 2.9% and 0.9% on average a year in Japan and the US, respectively and has grown to be more significant (i.e., 32% and 17%, respectively) inboth countries as real GDP growth slowed (2005–2011).

7

Figure 87 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 held positive in the ROC, oscillating around +2% of GDP, since1980. Singapore’s net primary income from abroad displayed the largest fluctuations, ranging from
+1.9% in 1997 to −7.1% in 2004, but on the whole, it has been more negative than positive. In Japanand the Philippines, net primary income from abroad has risen strongly, albeit at different magnitudes. In Japan, it rose from 0.6% of GDP in 1990 to 3.1% in 2011, compared with 1.4% in 1990 and
32.3% in 2011 in the Philippines. In the US, it has always been a positive, fluctuating within +1.7% ofGDP, whereas in the EU15 it was marginally negative for the three decades between 1975 and 2005
before turning mildly positive.
Combining both the trading gain effect and net primary income from abroad, real income growth formost of the countries compared fell within the margin of ±20% of real GDP growth (Figure 88); Kuwait
%

6
4

%

ROC
Korea

Hong Kong
Singapore

4

3

2

%

China
Japan
US

India
EU15

40

30

2

20

1

10

0

0

−1

−10

Bangladesh
Fiji
Malaysia
Pakistan

Cambodia
Indonesia
Mongolia
Philippines

0

−4
−6
−8

1970 1975 1980 1985 1990 1995 2000 2005 2010−21970 1975 1980 1985 1990 1995 2000 2005 2010−20

1970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 87 Effect of Net Income Transfer on GDP, 1970–2011
Sources: Official national accounts in each country, including author adjustments.

113©2013 Asian Productivity Organization−2

7 Real Income

%

6.9

12

(+20%)

Real income
growth

5.1
5.1
4.2

UAE

3.2

10

1.8
1.2

(−20%)

China
8

Vietnam

1.1
1.0
0.8

Oman

0.8

Singapore
Indonesia
Malaysia
Saudi Arabia
Korea
Qatar
Bahrain
ROC
Kuwait
Iran
India
Hong Kong
ThailandMyanmarBrunei
Sri Lanka
Pakistan
Philippines
TurkeyAustralia
Fiji

6

4

EU15
2

0.7
0.6
0.6
0.5
0.2
0.0
−0.1
−0.2
−0.3

Bangladesh
US
Japan

−0.4
−0.4
−0.4
−0.6
−0.6

Real GDP
growth

0

0

2

4

6

8

10

−0.6
−0.7

12 %

−0.8
−0.8
−1.1

Figure 88 Real Income and Real GDP Growth, 1970–2011___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 1970–2011: Brunei (1989–), Cambodia (1993–), Mongolia (2000–), and Nepal(2000–).

−1.3
−2.7

−3

0

3

BruneiOman
KuwaitBahrainSaudi Arabia
UAE
Australia
Iran
Mongolia
Cambodia
Vietnam
Malaysia
Qatar
Nepal
Fiji
India
MyanmarUS
EU15
Sri Lanka
Philippines
China
ThailandJapan
TurkeyBangladeshIndonesia
Pakistan
Hong Kong
Korea
Singapore
ROC

6%

Figure 89 Trading Gain Effect, 2005–
2011___Average percentage points

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

©2013 Asian Productivity Organization

and Brunei appear to be the outliers, with real income growth being 6.9 times and 3.0 times their respective long-term dismal real GDP growth of 0.7% and 1.6%.94
Unlike the oil-exporting countries, at any one time roughly half of the Asian countries compared sustained a negative trading gain effect, albeit to variable extents, whereas the impact from net primary
income from abroad was relatively less pronounced. The period of 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%), giving rise to a marginal fall in real income of −0.9%.
In Korea, the negative trading gain also shaved 38% off real GDP growth of 5.0%, producing real income growth of 3.1%. At the start of the 2000s, the Asian economy recovered from the financial crisis,
but the trading gain effect ran counter to welfare for some countries, with a negative impact that only
intensified after 2005. For example, in the ROC, the trading gain effect caused real income growth tobe 41% lower than real GDP growth in the period 2000–2005, but in the period 2005–2011 it wipedout 67% of the handsome 4.0% real GDP growth on average a year, leaving real income to grow at
1.4%. Similarly, in Korea the trading gain effect caused real GDP growth to overestimate real income
growth by 19% in the first half of the 2000s, which increased to 28% in the years 2005–2011 (Table 17

94: According to Kohli (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% (−30.9% of real income growth) per year in Norway to thelargest of 0.63% (29.4% of real income growth) per year in Switzerland.

114

7.1 Real Income and Terms of Trade

Dollars per barrel

150

145.31113.39125109.39

100

77.05

75
41.07

50

75.40 77.91

250
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

7

Figure 90 Price of Crude Oil, 1986–2013
Source: US Energy Information Administration, WTI spot prices FOB (Cushing, Oklahoma).

and Figure 89). In Japan, the negative trading gain effect more than wiped out the 0.6 percentage
points of real GDP growth, leaving real income to actually fall by 0.1% a year on average in the period
2005–2011.
In contrast, the trading gain worked to counterbalance falling real GDP in Brunei, leaving it with a robust, real income growth of 6.4%, despite its contracting real GDP of 0.7% in the latest period (Table
17). In Saudi Arabia, real income growth was more than 200% faster than its real GDP growth. Thistakes place against the backdrop of strong oil prices, which spiked in mid-July 2008 to USD 147 a barrel; after dropping sharply to USD 40 per barrel by the end of 2008 (reflecting the fall in demand after
the collapse of Lehman Brothers), it has steadily risen to, and held at, over USD 100 a barrel since 2010
(Figure 90). In the US, the trading gain effect has been unfavorable more often than not, but its positive net primary income from abroad has worked to counterbalance it and the difference between
real GDP and real income growth is reduced. For example, in the latest period 2005–2011, the trading
gain effect shaved 14.1% off real GDP growth but it was counterbalanced by the positive effect fromnet primary income from abroad, which added 17.2% to real GDP growth, leaving real income growthslightly higher than real GDP.

95: 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 effect115©2013 Asian Productivity Organization

Figure 91 provides the results of further decomposition of the trading gain into the terms-of-tradeeffect and the real exchange rate effect in Asian countries for the period 1970–2011.95 The terms-oftrade effect is the part of real income growth attributed to the change in the relative price between
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 first chart in Figure 91 applies thisbreak-down to Asian countries for the period 1970–2011. It shows that the real exchange rate effect is7 Real Income

1970–2011

%

12

9
6

1.2

0.8 0.8

10.2
8.6

3

7.3

6.4 7.1 5.9

1.8 1.5
7.0

4.2

0
−3

1.1

1.1
6.3 6.7

5.4 4.9 5.8

12

−0.8

2.6 3.1 2.8 2.7 2.2

2.3

1.8
11.3

10.8

2.6

−0.9

0.8

3.8

3.7
10.9 8.2

8.6
4.2

−0.8

1.1

1.0

7.8
4.3

7.1

6.1

−0.9−1.1

1.7 1.6

3.2

4.4

3.5
0.9

1.1

5.2 4.6 5.8 5.7

1.7
3.7 4.5

5.5 5.2

1.2
3.1

4.3 4.2 3.7 4.0 4.0 4.2
−0.8

3.8

−1.0 −0.9−2.1

1.5 1.3 1.0

Japan
Fiji
EU15
US
ROC
Korea
Hong Kong
Thailand
Nepal
TurkeyPakistan
Australia
Indonesia
Singapore
Philippines
UAE
Bangladesh
Sri Lanka
Malaysia
Iran
BruneiVietnam
Saudi Arabia
India
Bahrain
KuwaitCambodia
Oman
Mongolia
Myanmar
China
Qatar

−3

3.5 4.4 3.3

0.6

3
0

0.7

2000–2011

9
6

1.6

0.7

%

15

2.8 3.6

0.9
5.5 5.7 5.3 5.3 2.4
4.6

EU15
Japan
US
Bangladesh
Fiji
Australia
TurkeyPhilippines
Pakistan
Brunei
Sri Lanka
MyanmarThailandIndia
Iran
KuwaitHong Kong
BahrainIndonesia
ROC
Saudi Arabia
Qatar
Korea
Malaysia
Singapore
Vietnam
Oman
China
UAE

generally much smaller than theterms-of-trade effect, implyingthat the relative prices of tradedversus domestically consumed
goods have been largely stable inmost countries. The exceptions
are Kuwait and Brunei where thereal exchange rate effect accounted for 31% and 18% of real income growth. This might havereflected the weight of oil in thecomposition of their traded
goods. The second chart shows
the decomposition for the mostrecent period 2000–2011. 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 suchas Hong Kong, the ROC, Korea,
and Pakistan.

©2013 Asian Productivity Organization

Figure 92 shows the decomposiReal exchange rate effectTerms-of-trade effect
Real GDPNet primary income from abroad
Real incometion of average annual real income growth covering two periods
Figure 91 Decomposition of Real Income Growth, 1970–of major economic shocks faced
2011 and 2000–2011by the Asian economies: during
Sources: Official national accounts in each country, including author adjustments.
1973–1979, which includes thetwo oil price hikes in 1974 and1979, and 1996–1998 to capture
the impact of the Asian financial crisis. High oil prices improved the terms for oil-exporting countries,
such as Iran and Indonesia, and worsened the terms of trade for oil-importing countries. During the
Asian financial crisis, the terms-of-trade effect was still the predominant factor in determining the difference between real income growth and real GDP growth. In Brunei, the terms-of-trade effect further
reinforced the negative real GDP growth of −6.3%, reducing its real income growth a further 8.1
percentage points. In Iran, the negative terms-of-trade effect counteracted the 0.9% real GDP growth,
giving real income growth of −1.5%. In Indonesia, the trading gain effect worked to counterbalance thecontraction in real GDP, whereas in Thailand, it reinforced the negative real GDP growth. In the Philippines, although the strong favorable terms-of-trade effect was moderated by the negative real exchange rate effect, the resulting real income growth more than quadrupled the real GDP growth.96
Figure 93 shows this decomposition of real income in each Asian country, along with the US, EU15,
Australia, and Turkey97 from 1970, or the year of first data collection for the country in question. The
trading gain can be positive or negative, depending on the direction of change in the terms of trade.
Its impact is modest for most countries, adding less than ±1 percentage point to annual real GDP
growth, except for some oil-rich countries. In the short term, one sees extreme spikes in trading gain.
For instance, as a consequence of the first oil price shock, the improvement in the terms of trade was
responsible for around 80% of the 40.6% increase in real income in Iran in 1974. The opposite was true116

7.1 Real Income and Terms of Trade

1973–1979

%

10
3.2

1.1

1.2

5
2.3 0.9

9.8

5
6.9

8.9 8.0
7.5 5.2
7.1

7.3

1.5
−0.8

1.4
3.3
5.1

0.9

4.3 4.60

1996–1998%

10

6.9 5.3 7.4 6.3

0
5.8

4.4

5.4

4.7 4.1 3.6 3.8 3.9

2.9 2.9
2.3

1.2
1.4 2.9
4.6 4.3 6.0 4.3 3.5 4.6 5.0 3.0
1.0
2.9 1.4
1.3
1.2
0.8
−1.0
−1.6 −1.7
−1.1

0.9
−2.6

1.2
1.9
−1.5

−5

−1.1

Terms-of-trade effect−6.3

BruneiIndonesia
Thailand
Korea
Iran
Japan
Malaysia
Fiji
Hong Kong
Pakistan
EU15
Philippines
Myanmar
Australia
Singapore
US
Cambodia
India
ROC
Bangladesh
China
TurkeyVietnam
Sri Lanka

Bangladesh
EU15
US
Japan
Australia
India
Philippines
TurkeySri Lanka
Myanmar
China
Thailand
PakistanFiji
Singapore
Hong Kong
ROC
Iran
Malaysia
Korea
Indonesia
Real exchange rate effect

−15

−8.5

−1.4 −8.1

−10
−5

−5.0

−0.9

Real GDPNet primary income from abroad

7

Real income

Figure 92 Decomposition of Real Income Growth, 1973–1979 and 1996–1998___Decomposition: Average annual growth rate of real income

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

96: 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%. This is small by the standard of Asian economies. However, the trading gain later became significant, especially for the three years 2002–2005. Over these years, the average trading gainis 1.6% per year. This effect is decomposed into a terms-of-trade effect of 1.4% and a real exchange rate effect of −0.1%.
97: 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.

117©2013 Asian Productivity Organizationin EU15, where the negative trading gain effect counterbalanced real GDP growth, leaving virtually no
growth to real income in the period 1974–1975. The effect of the second oil spike can be seen in theearly 1980s. Sri Lanka, Malaysia, and Indonesia also experienced volatile variations in trading gains in
the 1970s. The trading gain has been working against Singapore and the ROC’s welfare for most of theperiod covered.

7 Real Income

Bahrain%60

Bangladesh

%
15

%
25
20

40

10

20

5

0

0

−20

−5

−40

−10

−5

−60

−15

−10

−80

−20

1971 1976 1981 1986 1991 1996 2001 2006 2011

Cambodia

%
14
12

10
5
0

1971 1976 1981 1986 1991 1996

2001

2006

2011

China

%
15

6
3

0

2

0

−3

0
1971 1976 1981 1986 1991 1996 2001 2006 2011

Hong Kong

%
16

−6

−3
1971 1976 1981 1986 1991 1996 2001 2006 2011

India

%
12

12

9

8

6

4

3

0

0

−4

−3

−8

−6

ROC

9

3

4

%
18

1971 1976 1981 1986 1991 1996 2001 2006 2011

12

6

6

−15

15

9

8

−2

15

12

10

Brunei−6%201971 1976 1981 1986 1991 1996 2001 2006 2011

Indonesia

15
10
5
0

1971 1976 1981 1986 1991 1996 2001 2006 2011

Iran

%
45

−5
−10
1971 1976 1981 1986 1991 1996 2001 2006 2011

Japan

%
8

36

−15

%
16

6

12

4

8

2

4

0

0

−2

−4

1971 1976 1981 1986 1991 1996 2001 2006 2011

Korea

27
18
9
0
−9
−18
−27

1971 1976 1981 1986 1991 1996 2001 2006 2011

Kuwait%90−41971 1976 1981 1986 1991 1996 2001 2006 2011

Malaysia

%
20
15

60

%
75

1971 1976 1981 1986 1991 1996 2001 2006 2011

Mongolia

50

10

30

−8

25

5
0
−30
−60

0

0

−25

−5

1971 1976 1981 1986 1991 1996 2001 2006 2011

Myanmar%15−101971 1976 1981 1986 1991 1996 2001 2006 2011

Nepal

%
8

−50

%
45

1971 1976 1981 1986 1991 1996 2001 2006 2011

Oman

12
9
6
3

©2013 Asian Productivity Organization

0
−3
−6

6

30

4

15

2

0

0

−15

−9
−12

1971 1976 1981 1986 1991 1996 2001 2006 2011

Real GDP118−21971 1976 1981 1986 1991 1996 2001 2006 2011

Trading gain

Net primary income from abroad−30

1971 1976 1981 1986 1991 1996 2001 2006 2011

Real income

7.1 Real Income and Terms of Trade%
10

Pakistan

12

8

10

0

2

0

−4

0

−8

−2

−12

−4

−16

1971 1976 1981 1986 1991 1996 2001 2006 2011

Saudi Arabia

40
30
20
10

−10
−20
1971 1976 1981 1986 1991 1996 2001 2006 2011

Singapore

%
20

−30

%
20

16

15

12

10

8

5

4

0

0

−5

−20

−4

−10

−30

−8

0
−10

%
15

1971 1976 1981 1986 1991 1996 2001 2006 2011

Thailand1971 1976 1981 1986 1991 1996 2001 2006 2011

UAE

%
100

−15

%
12

40

4

0

20

2

%
8

−2

−20

US

−40

−4
1971 1976 1981 1986 1991 1996 2001 2006 2011

EU15

%
8

−6

%
8

6

6

6

4

4

4

2

2

2

0

0

0

−2

−2

−2

−4

−4

%
12

1971 1976 1981 1986 1991 1996 2001 2006 2011

Vietnam001971 1976 1981 1986 1991 1996 2001 2006 201171971 1976 1981 1986 1991 1996 2001 2006 2011

6

5

−10

Sri Lanka

8

60

−5

1971 1976 1981 1986 1991 1996 2001 2006 2011

10

80

10

Qatar

20

4

4

%
40
30

8

6

%
50

Philippines%
161971 1976 1981 1986 1991 1996 2001 2006 2011−41971 1976 1981 1986 1991 1996 2001 2006 2011

Australia

1971 1976 1981 1986 1991 1996 2001 2006 2011

Turkey

10
8
6
4
2
0
−2
−4
−6

1971 1976 1981 1986 1991 1996 2001 2006 2011

Real GDP

Trading gain

Net primary income from abroad

Real income

Figure 93 Sources of Real Income Growth, 1970–2011

119©2013 Asian Productivity Organization

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

7 Real Income

7.2 Terms of Trade andProductivity Growth%5

Terms-of-trade effectKuwait4©2013 Asian Productivity Organization

When the trading gain is highly
favorable, it can breed a sense ofBrunei3
complacency, and productivity
performances can suffer as a re2
Iransult. Resource-rich economies are
Oman
Singapore
Bahrainsusceptible to this pitfall because
Indonesia
Australia
they are poised to reap some ex1
Malaysia
EU15
Fiji
Qatar
tremely positive trading gains when
Cambodia
Vietnam
Nepal
UAE
Myanmarcommodity prices turn in their faIndia
0
Hong
Kong
China
Philippines US
vor over a sustained period of
Saudi Arabia
Korea
TurkeyThailandBangladesh
time. While commodity prices can
ROC−1
Sri Lanka
Pakistan Japan
rise, they can also fall. This is whencountries’ real income growth−2
could suffer if fundamentals for
−4.5
−3.0
−1.5
0.0
1.5
3.0
4.5
6.0
7.5 %
Labor productivity growth
real GDP growth are weak. Overthe past four decades, only five
Figure 94 Terms-of-Trade Effect and Labor Productivity
countries have enjoyed a favorGrowth, 1970–2011able trading gain effect of over
Sources: Official national accounts in each country, including author adjustments.
1% per annum. They are Kuwait,
Note: The starting years for some countries are different due to data availability during 1970–2011: Brunei (1989–), Cambodia (1993–), Mongolia (2000–), Nepal (2000–),
Brunei, Iran, Oman, and Bahrain
and Vietnam (1986–).
(all oil-exporting countries), andonly Iran among them could
achieve a significant positive growth in labor productivity (Figure 94). Australia is a rising economy
that has benefited from 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 TFP
in the 1990s stopped around the end of the century before turning negative about five years ago,98
just at the stage when they were enjoying an all-time-high positive trading gain effect, with real income growth faster than real GDP growth by 48% during 2005–2011 (Table 17, p. 112). A resource-richcountry can suffer from “Dutch disease,” which describes a 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 the country’s dependence on natural resources. This is how resource abundance caneasily lead to resource dependence. A way to counteract Dutch disease is broad-based robust productivity growth and industry diversification, in which Bahrain and Oman have shown some success (seeSection 6.2 and Figure 75, p. 96).
Figure 94 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. These countries are
typically resource importers whose voracious demand for commodities pushes up their import prices,while export prices tend to fall as a result of their achievement in productivity improvement resulting
in unfavorable movements in terms of trade. This is particularly the case in countries where economic
growth is highly dependent on export promotion. In such instances, a negative trading gain is partly
a side-effect of 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.

98: The Economist, 28 May 2011, “Special Report on Australia: No worries?”120

7.2 Terms of Trade and Productivity Growth

Box 6

Resource-Rich Countries and the Possible Dutch Disease

Resource price hikes are certainly blessings for resource-exporting economies when prices are increasing.
Figure B6.1 illustrates trading gain effects (average annual growth rates due to trading gains in 1970–2010)and value-added shares of the mining sector in 1970 and 2010 in selected Asian economies. It indicatesthat large trade gainers typically have dominant mining sectors, petroleum and natural gas in particular.
Providing resource prices continuously go up, these countries continue to gain from the positive terms-oftrade effects.
However, what would happen if resource prices came down, or their natural reserves were depleted? Thenthe story of the Dutch disease might come in. Richness in natural resources may become a curse if they do
not have competitive industries other than mining. Figure B6.1 shows that some of the trading gainers
actively reduced their share of the mining sector over time, which could reflect the intention of developing
industries other than mining.
However, Figure 94 shows
Trading gain effect, 1970−2010that labor productivity growth%5
rates in these countries after
Kuwait1990 remained low, or evennegative. Even if they wanted
4
to start industrialization, theirhigh income and strong local
Bruneicurrency would not easily
3
allow them to develop a manufacturing sector or an internationally competitive service2
Iranindustry. Another concern is
Oman
Bahraintheir heavy dependence on
1
Qatar
foreign workers, both skilled
Indonesia
and unskilled.
Malaysia
Australia

UAE

Vietnam
Saudi Arabia

−1

0

10

20

30

40

50

60

70

80

90 %

Value-added shares in Mining, 1970 and 2010

Figure B6.1 Trading Gain Effects and Value-added Share in
Mining Sector, 1970–2010
Note: The starting years for some countries are different due to data availability during
1970–2010: Brunei (1989–) and Vietnam (1986–) for trading gain effect, Brunei (1974–),
UAE (1972–), Bahrain (1975–), Malaysia (1987–), and Vietnam (1986–) for value-added
share of mining sector.
Sources: Official national accounts in each country, including author adjustments.

121©2013 Asian Productivity Organization

On the other side of coin are
the resource/energy-importing
economies. Most of these suffered from negative trading
gain effects, losing a part oftheir economic growth due toresource price hikes, particularly after 2000 (Table 17, p.
112). However, it has actuallystrengthened their competitiveness in manufacturing andother productive activities forthe future.

07Appendix
A.1

GDP Harmonization

This edition incorporates some significant revisions to the national accounts. Observing new developments for upgrading of statistics systems in Asian economies, Malaysia and Hong Kong newly published their national accounts based on the 2008 SNA in May and September 2012, respectively. In
May 2011, the Philippines published its new national accounts based on the 1993 SNA, incorporating
elements of the 2008 SNA. While there are movements towards upgrading the SNA, some countries,
such as Cambodia and Indonesia, have still not fully introduced the 1993 SNA. The different statusesof SNA adaptions among member economies are responsible for the huge variations of data definitions and coverage in national accounts, calling for data harmonization to better perform comparative productivity analyses. This Databook project tries to reconcile the national accounts variations
that are based on the different concepts and definitions to provide harmonized estimates for international comparison. The APO Productivity Database 2013 largely follows the concepts and definitionsof the 1993 SNA, thus its GDP includes software investment and final consumption of financial intermediation services indirectly measured (FISIM) and excludes the expenditures for research and development. In addition to these adjustments, some extra adjustments are necessary to harmonize theestimates of GDP. Procedures for all these adjustments are explained below.

App.

1) FISIMFISIM 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 part of the income of the finance sector. The 1993 SNA recommends that FISIM should be allocated to users (to individual 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 negative value 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).

Figure 96 plots per capita GDP levels in 2011 and the FISIM share in GDP in the 2000–2011 (including
both of the original estimates in the official national accounts and our estimates). In countries where
GDPs are adjusted, the proportions by which author adjustments for FISIM increases GDP stand at
0.9–1.4% for Brunei, Indonesia, Nepal, and Pakistan and less than 0.5% GDP in others.

123©2013 Asian Productivity Organization

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 in these countries are smaller than others by definition. In addition, even in the countries
whose national accounts follow the 1993 SNA’s recommendation on FISIM, the available data sometimes does not cover the whole periods of our observations. 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 instances where IBSC data is not available). The ratios of value added of
IBSC or financial intermediation on FISIM allocated to final demand are assumed to be identical withthe average ratios observed in the countries in which data is available. Figure 95 describes the countries and methods to adjust FISIM. As described, in instances where both value added data are notavailable, the trend of the FISM share on GDP is applied to extrapolate past estimates (although theimpacts on GDP are minor).

Appendix

2) Software©2013 Asian Productivity Organization

The 1993 SNA also recommends thecapitalization of intangible assets,
which changes not only the sizeof GDP 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 typesof software. Another three countries exclude own-account software in theircapitalization, 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.

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
Turkey

1970
1970
1970
1970

1950
1951

1980
1993
1977

1960
1959

1955
1953

1970

1955

1970

1981 1985
1960
1974

1964
1960
1946

1967
1959
1951

1972
1970

1955

1986
1970 1974

1958

1990
1970

1975
1982

1962
1970
1970
1970
1970

1975
1975

1960

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 95 Adjustment of FISIM

Among the countries studied, the% FISIM share in GDP (average in the 2000−2011)
3.5
data for software investment isHong Kong
available for the ROC, Japan, Korea,
3.0
Mongolia, the Philippines, Singapore, Thailand, and China. To harmo2.5
nize data, a country’s GDP is adjusted
to include software investment(through its software industry) by
2.0
India
Philippines
using the ratio between software inJapan
US
Singaporevestment and GDP (software ratio)
Fiji
Korea
1.5
Thailandand the tangible GFCF to GDP ratio
ROC
Malaysia
Pakistan
China
Australia(GFCF ratio). Data from the OECD
Indonesia Turkey
1.0 Nepal Mongolia
Iran
Brunei
Productivity Database (Schreyer,
Bignon, and Dupont, 2003) and theLao PDR
0.5
Vietnam
APO Productivity Database suggest
Bangladesh
Cambodiaan inverse relationship between
Sri Lanka
Thousands of US dollars (as of 2010)
Myanmarthese two ratios (Figure 97). Coun0.0
0
10
20
30
40
50
60
tries with a low GFCF ratio tend to
Per capita GDP in 2011(using 2005 PPP, reference year 2010)
be those with high per capita GDP,
Offical national accounts in each country, including author adjustments
and the observed data suggest that
Our estimates using value added in financial intermediation
Our estimates using value added in imputed bank service charge
IT tends to play a more importantrole in these countries than in lessFigure 96 FISIM Share in GDP in the 2000–2011
developed countries. Furthermore,
Sources: Official national accounts in each country and author estimates.
it is observed from the OECD and
APO software data that the software
ratio has been gradually increasing over the past 25 years.
The Databook applies the inverse relationship between these two ratios observed from the OECD
countries and national accounts in Asian non-OECD countries to estimate the software ratio in 2006124

A.1 GDP Harmonization

for those APO member economies
that do not capitalize software investment. The estimated ratios forindividual countries in 2006 gradually taper off as one move back intime. However, there is an exception. Countries at the very earlystage of economic growth arefound 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, Cambodia, theLao PDR, and Nepal are regarded ascountries at the very early stage of
economic development, and are assigned Vietnam’s software ratio accordingly, which is the lowest of all
APO member economies.

%

2.5

Software investment/GDP

Sweden2.0

1.5

Denmark

US

Japan

Finland
Korea
Hong Kong
FranceNew ZealandUnited Kingdom
Netherlands

ROC
CanadaSwitzerland
1.0
Germany

Singapore
Austria
Italy

Australia
Spain

App.

Indonesia
Cambodia
Bangladesh
FijiVietnam
Sri Lanka
Philippines Malaysia
IrelandPakistan
India
Thailand
Nepal
Mongolia
Iran Portugal

0.5

0.0
13

18

23

28

33

China

38

43 %

Tangible GFCF/GDPCountries in which software is included
Countries in which software is excluded
Countries in which own account is excluded
Countries in which custom and own account software are excluded
Countries in which pre-package and own account software are excluded

Figure 97 Software Investment Ratio and GFCF Ratio toGDP, 2005
Source: OECD Productivity Database and author estimates.

Another problem arises from partial
software capitalization. There arethree types of software: pre-packaged software, custom software, and own-account software. Countries may have capitalized one or two types of software, but software investment data is often notavailable separately. The Databook attempt’s to adjust for the varied level of capitalization acrosscountries by adding the type of software not capitalized to countries’ GDP. In the case of Japan’s ownaccount software and ownership transfer cost, it used estimates by Nomura (2004) and added theseto the GDP of Japan’s software industry and GFCF.

3) Valuables

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 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

125©2013 Asian Productivity Organization

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 longrun. Valuables consist of precious stones and metals such as diamonds; art-works such as paintingsand sculptures; and other valuables such as jewelry made from stones and metals. In a small numberof countries, such as, India, Iran, Mongolia, Pakistan, and Vietnam, net acquisitions of valuables arerecorded as a part of gross capital formation. For example, the SNA in India has included it since
1999, accounting for 1.2% of GDP for India on average during 1999–2011. The current decision is toharmonize the data by excluding net acquisition of valuables from GDP in the APO Productivity
Database 2013.

Appendix

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 forinternational comparisons of TFP and industry performance as it is a measure from the producers’
perspective. Hence, Chapter 5 on whole-economy productivity performance is based on GDP at basic
prices, including our estimates.
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, Mongolia, Nepal, Singapore, and Sri
Lanka, a GDP at basic prices, needs to be constructed for all other countries. In order to obtain GDP atbasic prices, “taxes on products” and “duties on imports” are subtracted from GDP at market prices,which is available for all the countries studied, and “subsidies on products” is added. The main data
sources for estimating “taxes on products” and “subsidies on products” are tax data in national accounts, the IMF’s Government Finance Statistics, and the input-output tables in each country.

©2013 Asian Productivity Organization

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, Iran, Korea, the Lao PDR, Mongolia, Nepal, and Singapore, at producers’ prices for the ROC and the Philippines, and at market prices for Bangladesh, Indonesia, Japan, Malaysia, Sri Lanka, Thailand, and Vietnam. In this sense, APO industry data
should be treated as a work in progress as it is difficult to advise on data uncertainty. These issues will
be developed and examined in the future.

126

A.2 Capital Stock

A.2

Capital StockAt present, half the APO member economies publish estimates of capital stocks in their systemsof national accounts. Even where estimates are available, users must be mindful of differences 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 2013,a harmonized methodology has been applied in estimating capital stock and capital services, covering 17 Asian economies: China, the ROC, Fiji, Hong Kong, India, Indonesia, Iran, Japan, Korea, Malaysia,
Mongolia, Pakistan, the Philippines, Singapore, Sri Lanka, Thailand, and Vietnam, and the US as areference country.

App.

Quality changes in the aggregate measure of capital input can originate from two kinds of sources,
namely the composition change by type of asset, and the quality change in each type of asset. To takethe composition change of assets into account, the current database classifies ten types of assets(shown in Table 18). For countries in which detailed investment data is not available from national accounts, the ten
Table 18 Asset Classification andtypes of investment data are estimated based on the
Parameters in Hyperbolic Function
benchmark input–output tables and our estimates of thecommodity flow data of domestic production and export/T
β
1. IT hardware
7
0.50
import of assets. The input–output tables and supply and2. communications equipment
150.50
use tables are listed in Table 19. The starting years for esti3. transportation equipment
15
0.50
mating capital stock based on the perpetual inventory
4. other machinery and equipment
15
0.50
5. residential buildings30
0.75
method is 1901 for the US, 1951 for the ROC, 1952 for Chi6. non-residential buildings
30
0.75
na, 1953 for Korea, 1955 for Japan, 1960 for Singapore,
7. other construction
40
0.75
1961 for Hong Kong, and 1970 for other countries.
8. cultivated assets
10
0.50
3
7

0.50

0.50
It is well known that prices of constant-quality IT capital
have been falling rapidly. For cross-country comparisons,
Source: APO Productivity Database 2013.01.
it has been noted that there is great diversity inthe treatment of quality adjustment in price
Table 19 Input–Output Tables and Supply andstatistics among countries. Cross-country comUse Tables
parisons will be significantly biased if some
Input–Output Tables / Supply and Use Tablescountries adjust their deflators for quality
Benchmark (1981, 1984, 1986, 1989, 1991, 1994, 1996, 1999,
ROC
change while others do not. Price harmoniza2001, 2004, 2006) Annual (2006–2011)
Fiji
1972, 1982, 2005
tion is sometimes used in an attempt to control
India
1993/1994, 1998/1999, 2003/2004, 2006/2007
for methodological differences in the compilaIndonesia 1971, 1975, 1980, 1985, 1990, 1995, 2000, 2005
tion of price indexes, under the assumption that
Iran
1999, 2001
individual countries’ price data fails to captureJapan
1960, 1965, 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005
Benchmark (1960, 1963, 1966, 1970, 1975, 1980, 1985, 1990,
quality improvements. Assuming that the relaKorea
1995, 2000, 2005) Updated (1973, 1978, 1983, 1986–1988,
tive price of IT to non-IT capital in the countries
1993, 1998, 2003, 2006–2010)
compared is set equal to the IT to non-IT prices
Malaysia
1978, 1983, 1987, 1991, 2000, 2005
Mongolia
1970, 1977, 1983, 1987, 2000, 2005
relative in the reference country, the harmoPakistan
1975/1976, 1984/1985, 1989/1990, 1990/1991
X
X
nized price is formulated as: ∆ ln P̃IT = ∆ ln PnlT +Philippines 1969, 1975, 1985, 1988, 1990, 1995, 2000
refref(∆ ln PIT − ∆ ln PnlT ), where the superscript X deSingapore 1973, 1978, 1983, 1988, 2000, 2005, 2007
Sri Lanka
2006
notes the country included in the comparisons,Thailand
1975, 1980, 1985, 1990, 1995, 1998, 2000, 2005
PIT is the price of IT capital, and PnIT is the price ofVietnam
1996, 2000, 2007
non-IT capital. The price of IT capital in country
China
1987, 1992, 1997, 2002, 2007
X, P̃ITX , is computed by the observed prices PITref
Brunei2005
refX
Turkey1973, 1979, 1985, 1990, 1998, 2002
in the reference country and PnlTin X.
and PnlT

127©2013 Asian Productivity Organization

9. computer software
10. other intangible assets

Appendix

%

4.5

3.9

1980

4.0
3.5
3.0

3.4
2.9

2.9

2.7

2.6

2.3

2.5

2.0

2.0

1.7

1.5

2011

3.2

3.1

2.9

2.5

2.5
2.3

1.8

2.7
2.5

2.4 2.4 2.4

2.3
2.0

1.8

2.2
1.9

1.5

2.2
1.8

2.2
1.8

2.4
2.0
1.4

1.1

1.0
0.5
0.0
Pakistan

Iran

Sri Lanka

India

Malaysia

Philippines

US

Mongolia

VietnamSingapore

Fiji

Hong Kong

China

ROC

ThailandIndonesia

Korea

Japan

Schreyer (2002) and Schreyer,
Bignon, and Dupont (2003)
applied price harmonization
to OECD capital services, with
the US as a reference country,
since the possible error due tousing a harmonized price index would be smaller thanthe bias arising from comparing capital services based onnational deflators.

In this Databook, the same
Figure 98 Capital-Output Ratio, 1980 and 2011___Ratio of the beginning-of-period net capital stock to GDP at current
price harmonization method
is applied to adjust the quality
pricesimprovement for IT hardware
Source: APO Productivity Database 2013.01.
Note: The starting period for Vietnam is 1986.
and communications equipment in countries where theappropriate quality-adjusted price data is not available, with Japan’s prices as a reference country.
A similar procedure was applied in cases where the prices for some assets were not available, toestimate missing data based on the relative price of these assets to total GFCF. In measuring capi­
tal services, this Databook largely follows the framework of the OECD Productivity Database (seeSchreyer, Bignon, and Dupont, ibid.). The OECD assumes the truncated normal distribution as profiles
for asset discarding (retirement) and the hyperbolic distribution as profiles for asset decaying. The ageefficiency profile is defined as a combined distribution of discard and decay of assets. The ageefficiency profile in each 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 (no decay until T) when
β=1 and linear when β=0. These two parameters are set, as shown in Table 18. The estimates of productive capital stock by type of asset are used in measuring capital services (see Appendix 3).

©2013 Asian Productivity Organization

Figure 98 presents the estimated capital-output ratio (stock coefficient) that is defined by the ratio of
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 3.9. However, the ratio may not work well for cross-country comparisonssince 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.

128

A.3 Rate of Return and Capital Services

Rate of Return and Capital Services

A.3

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.

China

%
50

ROC

%
50

Fiji

%
50

40

40

40

40

30

30

30

30

20

20

20

20

10

10

10

10

0

0

%
50

India

0
1970 1980 1990 2000 2010

1970 1980 1990 2000 2010%
50

Indonesia

Iran1970 1980 1990 2000 2010
%
50

40

40

40

40

30

30

30

30

20

20

20

20

10

10

10

10

0

0

0

1970 1980 1990 2000 2010
%
50

Korea

1970 1980 1990 2000 2010%
50

Malaysia

Mongolia

1970 1980 1990 2000 2010
%
50

40

40

40

40

30

30

30

30

20

20

20

20

10

10

10

10

0

0

0

1970 1980 1990 2000 2010%
50

Philippines1970 1980 1990 2000 2010%50

Singapore1970 1980 1990 2000 2010

Sri Lanka

%
50

40

40

40

40

30

30

30

30

20

20

20

20

10

10

10

10

0

%
50

Vietnam1970 1980 1990 2000 2010
%
50

40

40

30

30

20

20

10

10

0

Thailand0001970 1980 1990 2000 2010

Pakistan01970 1980 1990 2000 2010

%
50

Japan

0
1970 1980 1990 2000 2010

%
50

App.

0
1970 1980 1990 2000 2010%
50

Hong Kong

1970 1980 1990 2000 2010

1970 1980 1990 2000 2010US01970 1980 1990 2000 2010

1970 1980 1990 2000 2010

Figure 99 Ex Post Real Rate of Return in Asia, 1970–2011
Source: APO Productivity Database 2013.01.
Note: The starting period for Vietnam is 1986.

129©2013 Asian Productivity Organization%50Appendix

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 2013.
k
The user cost of capital of a new asset (with type of asset denoted as k of the period t), ut,0
, is defined
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, cross-sectionk/depreciation rate, and asset price, respectively. The asset-specific inflation rate tk is defined as (qt,0k−1). The OECD assumes the country-specific ex ante real rate of return r * that is constant for the
qt−1,0whole 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 of changeof the CPI (see Schreyer, Bignon, and Dupont, 2003).

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) allows an estimation based on observed data. Assuming constant returns to scale and competitive markets, capital compensation can be derived from the summation of the capital service cost Vtk for each
asset, which is defined as the product of the user cost of capital and the productive capital stock (i.e.,k kSt ). Based on this identity and the n-equations of user cost of capital, the n+1 variables
Vt = Σk Vtk = Σk ut,0kof ut,0 and rt are simultaneously determined, using the observed capital compensation Vt as the totalkis not independent
sum of Vtk that is not observable in each asset. Note that the depreciation rate P,t,0of the estimated rt.
The estimated results of the ex post real rate of return based on rt* = (1 + rt) / (1 + ρt)−1 for 17 Asian
countries and the US are shown in Figure 99. Although there are large fluctuations in countries likeThailand, Mongolia, and Vietnam, many Asian countries may exhibit decreasing trends in the (endogenous) real rate of return, while the US holds a stable rate of around 10%. Table 20 presents the fiveyear-averages of the estimated rates for ex post real rate of return during 1970–2011. In 2005–2011,
the real rate of return ranged from 5.3% for Japan to 21.8% in Indonesia and 27.1% for Iran. 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 measureof capital services, regardless of the substantial differences in the rates of return and capital compensations (Nomura, 2004).
Table 20 Average Ex Post Real Rate of Return in Asia

©2013 Asian Productivity Organization

1970–1974 1975–1979 1980–1984 1985–1989 1990–1994 1995–1999 2000–2004 2005–2011
China
ROC
Fiji
Hong Kong
India
Indonesia
Iran
Japan
Korea
Malaysia
Mongolia
Pakistan
Philippines
Singapore
Sri Lanka
Thailand
Vietnam
US

21.4
30.7
11.3
20.1
19.3
34.3
24.7
15.4
28.2
27.1
12.3
19.7
11.2
25.3
24.5
13.9

16.6
20.9
12.5
24.1
21.5
32.3
21.5
7.8
23.0
27.6
14.0
21.8
15.1
17.7
32.9
10.4

14.2
15.1
5.0
17.4
16.7
30.5
9.9
6.4
12.1
17.0
13.6
17.9
11.7
14.5
16.3
4.9

9.7

8.1

5.3

Unit: Percentage.
Source: APO Productivity Database 2013.01.
Note: The starting period for Vietnam is 1986.

130

13.2
19.3
2.6
22.5
15.1
16.1
7.8
8.7
15.5
14.3
16.8
21.6
12.5
12.6
10.3
10.6
10.2
6.8

15.1
16.6
15.3
13.9
12.6
14.9
20.8
7.1
12.3
16.0
−5.5
18.0
9.1
14.9
9.8
11.6
18.9
6.9

10.8
15.0
7.0
11.5
11.4
18.6
13.4
4.8
8.4
16.8
22.0
9.0
13.4
12.4
7.8
10.2
12.2
9.6

12.9
17.1
7.2
9.4
13.8
18.1
24.2
5.1
8.0
17.6
−1.0
10.8
18.6
11.2
9.1
9.2
14.0
10.1

13.7
14.1
4.7
13.1
13.7
21.8
27.1
5.3
7.3
21.3
8.0
4.8
16.3
16.1
9.6
10.0
13.2
8.7

A.4 Hours Worked

A.4

Hours Worked

Labor volume can be measured in three measurement units: number of persons in employment,
number of filled jobs, and hours actually worked. Given the variations in working patterns and employment legislation both over time and across countries, hours worked, if accurately measured, offers the most time-consistent and somewhat internationally comparable unit measuring the volume
in each of different types of labor. This is the primary underlying reason for the importance of choosing hours actually worked in productivity analysis, but in reality, due to the difficulty in accurately estimating average hours actually worked, it is not always available or comparable across countries. The
large variety of data sources, definitions, and methodologies available in estimating these labor market variables often leads to a fragmentation of labor market statistics of an individual country concerned, dubious data quality, and incomparability across countries. Here follows an attempt to outline
some of these intricate measuring issues.

App.

Household-based labor force surveys (LFS), in contrast, have full coverage of the economy, although
they sometimes incorporate age or geographic exclusions and may have imperfect coverage of thearmed forces and other institutional households. Nonetheless, they provide valuable data on certain
employment groups such as the self-employed and unpaid family workers, and on the rate of multiple job holding. Employment status in LFS is independently determined and is not subject to the criteria used in company records. Most countries follow the International Labour Organization (ILO)
definitions. As LFS’ are surveys from the socio-economic perspective, they also provide rich data on
worker characteristics that are relevant to productivity analysis. The major weakness of the LFS, however, is data precision. By relying on the recollection of the respondents, their response also depends
on perception. Response errors could, therefore, arise from confusion of concepts and imprecise recollection of the respondents concerning work patterns and pay during the reference week. Anothersource of errors originates from proxy response, which relies on the proxy’s perception and knowledge of another household’s member. A high level of proxy responses could, therefore, reduce thereliability of data collected.
The common practice of statistical offices has been to combine information from both establishment
and household surveys, with a view to making use of the most reliable aspects of each of the surveys.

131©2013 Asian Productivity Organization

Data on labor volume comes from two main statistical surveys on establishment and household, withrespective strengths and weaknesses. Establishment surveys are surveys of firms with stratified sample frames by the size of establishments. The concentration of total employment in a relatively small
number of establishments means that this sampling strategy is cost effective in delivering high precision labor market estimates with fairly small sampling error. Questionnaires are designed to be close
to the concepts used in company administration. This has both strengths and weaknesses. On the one
hand, data collected is of high quality and accuracy. On the other hand, changes in legislation andregulation could be a source of instability to the definitions, and in turn of the data collected. Furthermore data that companies do not collect for administrative purpose, such as unpaid hours and worker characteristics, are unavailable. This greatly limits the varieties of labor market data that can becollected through establishments. Employment as measured is necessarily based on jobs rather thanon persons employed, as persons holding multiple jobs with different establishments cannot be identified and will be counted more than once. Information on hours is on paid hours rather than hours
actually worked. Certain categories of employment, most notably the self-employed, are not covered.
Sometimes small firms, informal employment or the public sector are also excluded. As a result of
these limitations, labor market data from establishment surveys often requires a raft of adjustmentsfor omissions and definition modifications during the compilation process.

Appendix

This seems to be the most promising avenue
forward in improving the quality and consistency of data on labor input. However, statistical offices could still differ a great deal in their
methodologies, especially in estimating theannual average hours worked per job/per person, depending on their starting points, namely LFS data or enterprise data. All these have tobe taken into account in international comparisons of productivity.

©2013 Asian Productivity Organization

In productivity analysis, ideally, labor volume
should be quality adjusted in order to reflect
workforce heterogeneity, as recommended
in the SNA 2008. To adjust total hours worked
for quality would require information on
worker characteristics so as to distinguish theworkforce into different types, which arethen weighed by their marginal productivity
and approximated by their respective sharesof total compensation. Deriving a quality
adjusted labor input (QALI) measure is a datademanding exercise. Even if LFS provides therequired information, researchers often run
into the consistency issues discussed above,
as well as sample size problems as they break
down the workforce into fine categories. See
Nomura and Amano (2012) as an exercise inthis for Singapore.

Table 21 Sources of Labor Data
Sources of Labor Data
Bangladesh Labor Force Survey, Populations Census
Cambodia

Socio-Economic Survey, Labor Force Survey
Yearbook of Manpower Survey Statistics in Taiwan Area,
Taiwan Statistical Data Book
Annual Employment Survey, Population Census, Estimates by
Fiji
FIBOS (Fiji Islands Bureau of Statistics), Labor Force Survey
Data download from Census and Statistics Department ofHong Kong
Hong Kong Statistics
India
Census of India, Employment and Unemployment Survey
ROC

Indonesia

Labor Force Situation in Indonesia

Iran

Population Census, Labor Force Survey

Japan

Labor Force Survey, National Accounts
Census on Basic Characteristics of Establishment, Economically
Active Population Survey, Monthly Labor Survey
Population Census, ADB Key Indicators for Asia and the Pacific
Economic Report Various issues, Malaysia Economic
Statistics-Time Series, Labor Force Survey Report
Mongolian Statistical Yearbook

Korea
Lao PDR
Malaysia
Mongolia
Nepal
Pakistan
Philippines
Singapore
Sri Lanka
Thailand
Vietnam

Population Census
Labor Force Survey, Pakistan Statistical Yearbook, Pakistan
Economic Survey
Labor Force Survey, Philippines Statistical Yearbook
Labor Force Survey, Singapore Yearbook of Manpower
Statistics
Central Bank of Sri Lanka Annual Report, Labor Force Survey
Labor Force Survey
Estimates by General Statistics Office, Labor Force and
Employment Survey

Cambodia
Korea
Iran
Malaysia
Vietnam
PakistanThailandHong Kong
Singapore
Bangladesh
China
India
ROC
Philippines
Indonesia
Sri Lanka
TurkeyJapan
Australia
EU15 −4

47
45
42
40
39
39
37
37
36
34

The APO Productivity Database 2013 defines
labor inputs as the simple sum of hours
32
30
worked. Hours worked are defined in this Data30
book as the economy-wide hours worked by
26
24
employees, the self-employed, and contribut20
ing family workers. Japanese and US national
15
7accounts publish estimates of the total hours
4
worked. Other Asian countries do not publish
hours worked in their national accounts. For−50
5 10 15 20 25 30 35 40 45 50 %these countries the procedure of constructing
Figure 100 Average Annual Hours Worked Per
economy-wide annual hours worked consists
Worker Relative to the US, 2000–2011of two steps; for many Asian countries first, an
Sources: Official national accounts and labor force survey in each
average weekly hours worked is obtained andcountry, including author adjustments.
the number of workers collated from official
statistics, such as a labor force survey. The data
we used is listed in Table 21. Multiplying the
average hours worked by the number of workers gives economy-wide averages of weekly hours
worked; second, the number of weeks worked is obtained, by counting the number of national holidays in each country. Multiplying economy-wide average weekly hours worked by the number of132

A.5 Other Data

weeks worked gives economy-wide annual hours worked. For Fiji, the Lao PDR, Mongolia, and Nepal,
total hours worked are not estimated due to data constraint.
Figure 100 presents a cross-country comparison of average annual hours worked per worker for
2000–2011, 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 of the countries sampled, the differencein annual hours worked per person relative to the US is more than 20% 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 and Cambodia to high-income countries such as the ROC
and Singapore. Exceptions are Japan and Vietnam. Workers in both these countries are likely to work
much shorter hours than those in other Asian countries. However, compared with the US and EU15,
hours worked by workers in Japan is still about 10% longer.

A.5

App.

Other Data

For China, multiple data sources has been used; GDP for the whole economy, industry GDP, final demands, employment, and income data are taken from China Statistical Yearbook and China National
Income 1952–1995; time-series data of GFCF during 1952–2011 at current and constant prices are constructed at KEO; the main references for GFCF construction are drawn from Statistics on Investment in
Fixed Assets of China 1950–2000, China Statistical Yearbook, and 1987, 1992, 1997, 2002, and 2007 Input–
Output Tables of China; and multiple data sources for manufacturing, electrics, and trade data from
China’s Customs Statistics are also utilized.99
The data source for EU15 and EU27 is the OECD.Stat (http://stats.oecd.org/). The data for the US, Australia, and Turkey are taken from the website of the US Bureau of Economic Analysis (http://www.bea.
gov), the Australian Bureau of Statistics (http://www.abs.gov.au/), and the Turkish Statistical Institute(http://www.turkstat.gov.tr), respectively.
The exchange rates used in this edition are adjusted rates, called the Analysis of Main Aggregate(UNSD database) rates, in the UNSD National Accounts Main Aggregate Database. The AMA rates coincide with IMF rates except for some 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.

99: Holz (2006) provides a useful reference on Chinese official statistics.

133©2013 Asian Productivity Organization

Tax data of member economies are supplemented by the IMF’s Government Finance Statistics. From
its tax revenue data, “taxes on goods and services” and “taxes on imports” are used for calculatingtaxes on products. From its expenditure data, “subsidies” are taken. Data taken from Government Finance Statistics play a key role in adjusting GDP at market prices to GDP at basic prices.

Appendix

A.6

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.
Table 22 Industry Classification
ISIC Databook
Rev.3 1st 2nd
A - Agriculture, hunting and forestry

01
02

1
1

Agriculture, hunting and related service activities
Forestry, logging and related service activities

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 workO - Other community, social andpersonal 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 - Extra-territorial organizations andbodies99

9Extra-territorial organizations and bodies

D - Manufacturing©2013 Asian Productivity Organization

E - Electricity, gas and water supply

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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