©2014 Asian Productivity Organization©2014 Asian Productivity Organization

Contents
Abbreviations
Forewordviii

1 Introduction

1ix

1.1 Databook 20141

1.2 List of Contributors

2

1.3 Map of Countries Covered

4

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

30
37

4.1 Composition of Final Demand37

4.2 Demand-Side Growth Decomposition48

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

79

6 Industry Perspective87

6.1 Output and Employment87

6.2 Industry Growth95

6.3 Labor Productivity by Industry

103

7 Real Income

111

7.1 Real Income and Terms of Trade111

7.2 Trading Gain and Productivity Growth120

Appendix

125

A.1 GDP Harmonization

125

A.2 Capital Stock

129

A.3 Rate of Return and Capital Services

131

A.4 Hours Worked

133

A.5 Other Data

135

A.6 Industry Classification

136

References

137

iii

©2014 Asian Productivity Organization

4 Expenditure

Contents

Box
Box

1

PPP Revisions by 2011 ICP Round

21

Box

2

Population and Demographic Dividend

34

Box

3

National Accounts in Asian Countries

50

Box

4

Turning Point in China

60

Box

5

Sensitivity of TFP Estimates

86

Box

6

Energy Productivity and CO2 Emission

109

Box

7

Resource-Rich Countries and the Possible Dutch Disease

121

Box

8

Quarterly Economic Growth122©2014 Asian Productivity Organization

Table
Table

1

GDP using Exchange Rate, 1970, 1990, 2000, 2010, 2011, and 2012

14

Table

2

GDP using PPP, 1970, 1990, 2000, 2010, 2011, and 2012

16

Table

3

GDP Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2012

19

Table

4

Per Capita GDP using Exchange Rate, 1970, 1990, 2000, 2010, 2011, and 2012

24

Table

5

Per Capita GDP, 1970, 1990, 2000, 2010, 2011, and 2012

26

Table

6

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

29

Table

7

Final Demand Shares in GDP, 1970, 1990, 2000, 2011, and 2012

37

Table

8

Per-Worker Labor Productivity Levels, 1970, 1980, 1990, 2000, 2010, and 2012

59

Table

9

Labor Productivity Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2012

61

Table 10

Per-Hour Labor Productivity Levels, 1970, 1980, 1990, 2000, 2010, and 201264

Table 11

Labor Productivity Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2012

66

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

74

Table 13

Role of TFP and Capital Deepening in Labor Productivity Growth, 1970–2012

84

Table 14

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

87

Table 15

Output Growth by Industry, 2000–2012

99

Table 16

Labor Productivity Growth by Industry, 2000–2012

106

Table 17

Real Income and Terms of Trade, 1970–2012, 1995–2000, 2000–2005, and 2005–2012

112

Table 18

Asset Classification and Parameters in Hyperbolic Function

129

Table 19

Input-Output Tables and Supply and Use Tables

129

Table 20

Average Ex Post Real Rate of Return in Asia

132

Table 21

Sources of Labor Data

134

Table 22

Industry Classification

136

iv

Figure1

GDP Growth of Asia, the EU, Japan, and the US, 1970-2012

13

Figure2

Share of Asia in World GDP in 2012 and Projection for 201913

Figure3

Price Level Indices of GDP, 201115

Figure4

Regional GDP of Asia and the EU, Relative to the US, 1970–2012

17

Figure5

GDP of China, India, and Japan, Relative to the US, 1970–2012

17

Figure6

Regional GDP of South Asia, ASEAN, and GCC, Relative to the US, 1970–2012

18

Figure7Country Contributions to Regional GDP Growth, 1970–1990 and 1990–201220

Figure8Correlation of GDP Growth, 1990–2000

22

Figure9Correlation of GDP Growth, 2000–2012

23

Figure 10

Share of Asian Population in the World in 2012

23

Figure 11

Per Capita GDP using Exchange Rate of Japan and Australia, Relative to the US, 1970–2012

25

Figure 12

Per Capita GDP using Exchange Rate of the Asian Tigers, Relative to the US, 1970–2012

25

Figure 13

Per Capita GDP of Japan, the EU, and Australia, Relative to the US, 1970–2012

27

Figure 14

Per Capita GDP of the Asian Tigers, Relative to the US, 1970–2012

27

Figure 15

Per Capita GDP of China, India, and ASEAN, Relative to the US, 1970–2012

27

Figure 16

Per Capita Non-Mining GDP in Oil-Rich Countries and Japan, 201228

Figure 17

Initial Level and Growth of Per Capita GDP, 1970–2012

29

Figure 18

Labor Productivity and Employment Rate Gap Relative to the US, 1990 and 201230

Figure 19

Sources of Per Capita GDP Growth, 1990–2000 and 2000–2012

31

Figure 20

Share of Female Employment

32

Figure 21

Employment Rates, 1970, 1990, and 201232

Figure 22

Final Demand Shares in GDP of China, 1952–2012

38

Figure 23

Final Demand Shares in GDP of the US, 1929–2012

39

Figure 24

Final Demand Shares in GDP, 1995 and 201240

Figure 25

Ratio of Dependent Population and Consumption Share in GDP at Current Market Prices, 201241

Figure 26

Export and Import Shares in GDP, 1995 and 201242

Figure 27

Long-Term Trend of Household Consumption Share in GDP, 1970–2012

43

Figure 28

Share of Dependent Population, 201244

Figure 29

Household Consumption by Purpose, 201245

Figure 30

Engel Curve of Japan during 1949–2012 and Levels of Asian Countries in 201245

Figure 31

Long-Term Trend of Investment Share in GDP, 1970–2012

46

Figure 32

Investment Share by Type of Asset, 1970 and 201246

Figure 33

Long-Term Trend of Net Export Share in GDP, 1970–2012

47

Figure 34

Final Demand Contributions to Economic Growth, 1990–2000 and 2000–201248

Figure 35

Final Demand Contribution Shares to Economic Growth of the Asian Tigers, 2000–2012

49

Figure 36

Impacts of Global Financial Crisis and Recoveries, 2007–2012

51

Figure 37

Impacts of Asian Financial Crisis, 1997–1998

52

Figure 38

Final Demand Decomposition of Real GDP Growth, 1970–2012

54

Figure 39

Labor Productivity Level by Per-Worker GDP, 2012

58

Figure 40

Labor Productivity Trends of China and India, 1970–2012

58

Figure 41

Labor Productivity Level Relative to the US, 1970–2012

62

Figure 42

Labor Productivity Gap by Per-Worker and Per-Hour GDP Relative to the US, 2012

63

Figure 43

Labor Productivity Trends in Japan and the Asian Tigers, 1970–2012

64

Figure 44

Labor Productivity Growth, 1970–2012, 1970–1990, and 1990–2012

65v©2014 Asian Productivity Organization

Figure©2014 Asian Productivity Organization

Contents

Figure 45

Labor Input Growth, 1970–2012, 1970–1990, and 1990–2012

65

Figure 46

Labor Productivity Trends of Japan during 1885–2012 and Levels of Asian Countries in 2012

67

Figure 47

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

67

Figure 48

TFP Growth, 1970–2012, 1970–1990, and 1990–2012

69

Figure 49

Sources of Economic Growth, 1970–2012

70

Figure 50

Contribution Shares of Economic Growth, 1970–2012

70

Figure 51

Sources of Economic Growth, 1970–1985, 1985–2000, and 2000–2012

71

Figure 52

Contribution Shares of Economic Growth, 1970–1985, 1985–2000, and 2000–2012

71

Figure 53

Comparison of Sources of Economic Growth with OECD Countries, 2000–2011

73

Figure 54

Individual Countries’ Growth Accounting Decomposition, 1970–201276

Figure 55

IT Capital Contribution to Capital Input Growth of Japan and the US, 1970–2012

77

Figure 56

IT Capital Contribution to Capital Input Growth of the Asian Tigers, China, and India,
1970–2012

77

Figure 57

Individual Countries’ Growth Accounting Decomposition (year-on-year), 1970–2012

78

Figure 58

Capital Deepening, 1970–2012, 1970–1990, and 1990–2012

80

Figure 59

Capital Productivity Growth, 1970–2012, 1970–1990, and 1990–2012

80

Figure 60

Capital Productivity Trends in Japan and the Asian Tigers, 1970–2012

81

Figure 61

Capital Productivity Trends in China and India, 1970–2012

81

Figure 62

Sources of Labor Productivity Growth, 1970–2012

81

Figure 63

Contribution Shares of Labor Productivity Growth, 1970–2012

81

Figure 64

Sources of Labor Productivity Growth, 1970–1985, 1985–2000, and 2000–2012

82

Figure 65

Contribution Shares of Labor Productivity Growth, 1970–1985, 1985–2000, and 2000–2012

82

Figure 66

Decomposition of Labor Productivity Growth, 1970–2012

83

Figure 67

Industry Shares of Value Added, 201288

Figure 68

Manufacturing Share and TFP Growth, 2000–2012

89

Figure 69

Industry Shares of Value Added in Manufacturing, 201289

Figure 70

Industry Shares of Value Added and Employment by Country Group, 1980, 1990, 2000,
and 2012

90

Figure 71

Long-Term Trends of Value-added Share in the Agriculture Sector, 1970–2012

92

Figure 72

Industry Shares of Employment, 201293

Figure 73

Employment Share of Agriculture in Japan during 1885–2012 and Levels of AsianCountries in 201293

Figure 74

Long-Term Trends of Employment Share in the Agriculture Sector, 1970–2012

94

Figure 75

Job Creation in Manufacturing, 1970–2012

95

Figure 76

Industry Origins of Economic Growth, 1990–2000 and 2000–2012

96

Figure 77

Contribution of Manufacturing to Economic Growth, 1990–2000 and 2000–2012

97

Figure 78

Contribution of Service Sector to Economic Growth, 1990–2000 and 2000–2012

98

Figure 79

Industry Origins of Output Growth in Manufacturing, 1990–2000 and 2000–2012

100

Figure 80

Industry Origins of Regional Economic Growth, 1990–2000 and 2000–2012

101

Figure 81

Industry Origins of Asian Economic Growth, 2000–2012

102

Figure 82

Industry Origins of Economic Growth, 1970–2012

104

Figure 83

Industry Origins of Labor Productivity Growth, 1990–2000 and 2000–2012

107

Figure 84

Contribution of Manufacturing to Labor Productivity Growth, 1990–2000 and 2000–2012

108

Figure 85

Contribution of Service Sector to Labor Productivity Growth, 1990–2000 and 2000–2012

108

Figure 86

Effect of Net Income Transfer on GDP, 1970–2012

113

vi

Real Income and Real GDP Growth, 1970–2012

114

Figure 88

Trading Gain Effect, 2005–2012

115

Figure 89

Price of Crude Oil, 1986 January–2014 June

115

Figure 90

Decomposition of Real Income Growth, 1970–2012 and 2000–2012

116

Figure 91

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

117

Figure 92

Sources of Real Income Growth, 1970–2012

118

Figure 93

Trading Gain Effect and Labor Productivity Growth, 1970–2012

120

Figure 94

Adjustment of FISIM

126

Figure 95

FISIM Share in GDP in the 2000–2012

126

Figure 96

Software Investment Ratio and GFCF Ratio to GDP, 2005

127

Figure 97

Capital-Output Ratio, 1980 and 2012

130

Figure 98

Ex Post Real Rate of Return in Asia, 1970–2012

131

Figure 99

Average Annual Hours Worked Per Worker Relative to the US, 2000–2012

134

Figure B1

Revisions of PPP for GDP by 2011 ICP Round

21

Figure B2.1

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

34

Figure B2.2

Asian Countries’ Population Size and Projection, 1970, 2012, and 2050

35

Figure B2.3

Proportion of the Dependent Population, 2012

35

Figure B2.4

Demographic Dividend, 1950–2100

36

Figure B3

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

50

Figure B4Price of Labor Relative to Capital in China, Japan, and the Asian Tigers, 1970–2012

60

Figure B5.1

Labor Income Share for Employees, 201286

Figure B5.2

Sensitivity of TFP Estimates by the Change of Income Share, 1970–2012

86

Figure B6.1

Shares of Asia in World Energy Consumption and CO2 Emission, 2011

109

Figure B6.2

Labor Productivity and Energy Productivity, 2011

109

Figure B6.3

Sources of CO2 Emission Growth, 2000–2011

110

Figure B7

Trading Gain Effect and Value-added Share in Mining Sector, 1970–2012

121

Figure B8.1

Views of Quarterly Economic Growth in Asian Countries by the AQGM

122

Figure B8.2

Quarterly Economic Growth in Asian Countries, 2012Q1 – 2014Q1

123

vii

©2014 Asian Productivity Organization

Figure 87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

ASEAN6

Brunei, Indonesia, Malaysia, the Philippines, Singapore, and Thailand

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, andthe UAEGDP

gross domestic product

GFCF

gross fixed capital formation

GNI

gross national income

ICP

International Comparisons Program

IMF

International Monetary Fund

ISIC

International Standard Industry ClassificationIT

information technology©2014 Asian Productivity Organization

KEO		
Keio Economic Observatory, Keio University

viii

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
Today, we are witnessing ever-vibrant dynamism in the Asian economies. This
vitality has been prompted by multiple factors, including globalization, diversified division of labor, and economic integrations. The changes and challenges
member economies face in this era demand the APO to devise new productivity
drivers. Currently, the APO is working on its Roadmap 2020 to illustrate how weenhance productivity further with specific activities. This will assist the member economies in becoming more productive and competitive, while ensuring
equal distribution of productivity gains.
Measuring productivity is one of the core research activities at the APO. The
outcome data offers empirical analysis of cross country comparisons of economic growth and productivity levels in the context of the global economy. This
guides us to assess economic performance and structural changes. The dataalso serves as numeric indicators for reviewing our contributions to our missionof enabling the APO economies to be more productive and competitive. Additionally, this is a mechanism for setting new targets for our future productivity
movements in the dynamic economic development in the region.
It is with pleasure that I introduce readers to this edition as a vital resource forcomprehending the dynamic economic development in the region. This publication is the fruit of 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. Shinyoung Oh, Mr. Hiroshi Shirane, Mr. Kei Okamoto, and Mr. Naoyuki
Akashi. I also wish to thank all of the national experts for providing their respective economic data. The APO does, and will continue to, work with our members
and their respective statistical offices to improve the data quality and coveragethat underpins the data presented in the APO Productivity Databook series.
I hope that readers will appreciate this publication as a useful reference and findpractical use for their own purposes.

Mari Amanoix©2014 Asian Productivity Organization

Secretary-General
Asian Productivity Organization
Tokyo, September 2014

1.1 Databook 2012

1 Introduction
1.1 Databook 2014

1

This is the seventh 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. The focus of the Databook is on long-term analysis. This is achievedby examining a country’s economic growth and productivity performance, as well as the sources andindustry origins of the growth. This complete analysis provides readers with a more comprehensive
description and comparison of a given country’s economic structure and characteristics.
Baseline indicators on economic growth and labor productivity are calculated for 29 Asian economies, representing the 20 Asian Productivity Organization (APO20) member economies and nine
non-member economies in Asia. This edition covers the period 1970–2012. The APO20 include:
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. The nine non-member economies in Asia are: 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 Arab Emirates (UAE). These two groups combine to make theAsia29. In addition, Australia, the European Union (EU), Turkey, and the United States (US) are
included as reference economies.
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. Estimates are based primarily on the System of National Accounts (SNA) in 1993. In this edition, some significant revisions on the national accounts wereincorporated. New developments for the upgrading of statistics systems in APO member economies
have resulted in Pakistan and Korea publishing their accounts based on the 2008 SNA in April 2013
and March 2014, respectively. While there are movements toward upgrading the SNA, some countries
in Asia, such as Indonesia, have still not fully introduced the 1993 SNA. Because the varying SNA adaptions among the member economies can result in discrepancies between data definitions and coverage, data harmonization is necessary for comparative productivity analyses. This Databook attempts
to reconcile the national accounts variations that are based on the different concepts and definitions,and provide harmonized estimates for international comparison.

The official national accounts and metadata information used for constructing the APO Productivity
Database 2014 have been prepared by national experts in APO member economies 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 on labor, production, prices, trades, and taxes as required. The project was managed by Koji Nomura (Keio University),

1©2014 Asian Productivity Organization

To analyze the overall productivity improvement as well as partial productivity improvement (laborproductivity 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, thesources of economic growth in each economy are further decomposed to factor inputs of labor andcapital and total factor productivity (TFP) for 18 Asian economies – Bangladesh, the 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 notableachievement that the TFP estimate for Bangladesh is newly developed in the APO Productivity Database 2014 and is presented in this edition of the Databook. This edition reflects the revisions to theofficial national accounts and other statistical data published as of May 2014.

1 Introduction

under the consultancy of Professors Dale W. Jorgenson (Harvard University) and W. Erwin Diewert(University of British Columbia), and with coordination by Yasuko Asano (APO). The text, tables, andfigures in the report were authored by Koji Nomura and Fukunari Kimura (Keio University), with support from research assistants Shinyoung Oh, Hiroshi Shirane, Kei Okamoto, and Naoyuki Akashi.

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

Research Assistants at KEO, Keio University
Ms. Shinyoung Oh
Mr. Hiroshi Shirane
Mr. Kei Okamoto
Mr. Naoyuki Akashi
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
Bangladesh
Mr. Ziauddin Ahmed©2014 Asian Productivity Organization

Joint Director, Bangladesh Bureau of Statistics,
Ministry of Planning, Parishankhyan Bhaban,
E/27/A, Agargaon, Sher-e-Bangla Nagar, Dhaka,
1207

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

2

Republic of China
Ms. Wei-jie Huang
Chief, National Accounts Section, Bureau of
Statistics, Directorate-General of Budget,
Accounting, and Statistics, Executive Yuan, No. 2,
Guangzhou St., Zhongzheng District Taipei,
10065

Fiji
Ms. Navilini Singh
Senior Statistician, Economics Statistics Division,
Fiji Bureau of Statistics, Ratu Sukuna House,
Government Buildings, Suva

India
Ms. P. Bhanumati
Director, National Accounts Division, Central
Statistics Office, Ministry of Statistics &Programme Implementation, NAD Hall 1, 4thFloor, Sardar Patel Bhawan, Sansad Marg,New Delhi, 110001

Indonesia
Ms. Wachyu Winarsih
Leader of Social Analysis, Directorate of Analysis
and Development Statistic/Statistic Indonesia,
JL. Dr. Sutomo No.6-8, Jakarta, 10710

Islamic Republic of Iran
Mr. Behzad Mahmoodi
Chief of Statistical Designs Survey Section,
Statistical Research and Survey Department,
Central Bank of Iran, Mirdamad Blvd., No.144,
TehranMr. Hamid Azarmand
Deputy, 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 and Social
Research Institute, Cabinet Office,
Government of Japan, 3-1-1 Kasumigaseki,
Chiyoda-ku, Tokyo, 100-8970

Republic of Korea
Dr. Keun Hee Rhee
Director/Senior Researcher, Productivity ResearchInstitute, Korea Productivity Center, 32, 5ga-gil,
Saemunan-ro, Jongno-gu, Seoul, 110-751

Lao PDR
Mr. Phousavanh Chanthasombath
Deputy Director of National Account,Department of Economic Statistics, Lao Statistics
Bureau, Ministry of Planning and Investment,
Luang Prabang 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, National Statistical Office ofMongolia, Government Building 3, Ulaanbaatar

Pakistan
Mr. Shahid Mahmood Butt

1

Consultant, Duetsche Gesellschaft fur
Internationale Zusammenarbeit PK, GmbH, 2nd
Floor, Statistics House, Pakistan Bureau of
Statistics, 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. Wirot Nararak
Director, 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©2014 Asian Productivity Organization

Director, Central Bureau of Statistics, Thapathali,
Kathmandu©2014 Asian Productivity Organization

APO member economies
Non-member Asian economies included in Databook 2014

1 Introduction

1.3 Map of Countries Covered4

Overview

2 Overview
In 2013 most of the Asian economies realized relatively strong economic growth. In most cases, therecovery of developed economies from the global financial crisis and its aftermath was still at a slow
pace in the world. However, US economic growth aimed towards a come-back, despite some politicalturmoil on fiscal deficit and other issues. Japan applied a series of policies called “Abenomics,” and its
first two arrows out of three, that is., bold monetary easing and flexible fiscal stimulus, seemed to pull
the Japanese economy back to the normal situation. Although the EU continued to struggle, they realized enough improvement to put the worst behind them. While the external conditions were far
from perfect, most of the Asian economies continued to grow steadily based on the expansion of theirown demand.

2

The Asian economies, particularly those in East Asia including Northeast Asia and Southeast Asia,
have recorded impressive economic growth in the past two decades. Average annual growth rates of
GDP in Asia29 and East Asia at constant market prices in 1990–2012 reached 5.5% and 5.7%, whichsignificantly exceeded those in the US (2.4%) or EU27 (1.7%), as shown in Table 3. East Asia has been
the most advanced region in taking advantage of a new type of international division of labor calledinternational production networks (Ando and Kimura, 2005) or the 2nd unbundling (Baldwin, 2011).
A new development strategy has aggressively applied the mechanism of international division of labor in terms of production processes or tasks, rather than industries.
Although global value chains are a subject of current discussion throughout the world (see for example Elms and Low, 2013), one must be mindful that not all global value chains are international
production networks or the 2nd unbundling. The latter refers to tightly connected production/distribution/function links with well-coordinated, high-frequency, and synchronized transactions, rather
than a simplistic international input-output linkage with slow and low-frequency transactions. Suchproduction networks are typically observed in machinery industries though other industries such as
garment, food processing, and services may also utilize the mechanics. Latecomers in the region
including Cambodia, the Lao PDR, Myanmar, and Vietnam (CLMV) have started participating in production networks and jump-starting industrialization, particularly since the global financial crisis
began.1 Per capita GDP (using exchange rate) in CLMV increased from $310 in 2000 to $1,410 in 2012
(Table 4). Countries in South Asia have good potential to take advantage of such a division of labor byconnecting themselves with East Asian production networks; per capita GDP (using exchange rate) in
India and Pakistan was still $1,490 and $1,240, respectively, in 2012 (Table 4).

While the long-run growth perspectives of most Asian economies are bright, there are several issues
to consider in the short run. In the globalization era, one cannot neglect investors’ views in the market;
1: The Databook separates ten countries of the Association of Southeast Asian Nations (ASEAN) into the ASEAN6 consisting of Brunei,Indonesia, Malaysia, the Philippines, Singapore, and Thailand; and the CLMV consisting of Cambodia, the Lao PDR, Myanmar, andVietnam.

5©2014 Asian Productivity Organization

After hosting a number of production blocks in international production networks, countries began
to form industrial agglomerations in which the inter-firm division of labor, including links between
multinationals and local firms, was intensively developed. Through these processes of industrialization, a number of the East Asian developing economies have successfully reduced the population
below the poverty line and have gradually built up affluent middle-income population. Strong growth
in productive sectors has generated benevolent labor movements from informal to formal, from rural
to urban, and from agriculture to modern sectors, which are smoother than in other parts of the developing world. Per capita GDP (using exchange rate) in China and ASEAN6 were $6,070 and $4,820,
respectively, in 2012 (Table 4). The Asian developing countries other than East Asia have not yet fully
achieved such transformation with production networks.

2 Overview

even if the logical background of such concern may not necessarily be fully warranted. The China factor is the first such issue to consider. China’s economic growth has been outstanding for the last two
decades; average annual growth rate of GDP at constant market prices in 1990–2012 was 9.8% (Table3). The significance of the Chinese economy, both as a production site and a market, has naturally increased in the Asian economy as well as in the world. Thus, investors in the market are becoming very
sensitive to the growth prospect of the Chinese economy. The macroeconomic management by the
Chinese government has accomplished remarkable performance and now seems to head for a softlanding on a medium-speed growth path. However, some economists and investors are carefully
watching on several issues in the Chinese economy: notably, a possible collapse of excessive real estate growth, possible instability of financial system triggered by shadow banking crisis, and possible
economic difficulty due to a huge debt held by local governments. The share of investment with respect to GDP in China is still as high as 48.7% in 2012 (Table 7), which partially reflects the government’s effort to keep growth rates high. If the Chinese economy were to make a hard landing, it would
affect investors’ perception for other parts of the Asian economy, as well.
The second issue to consider is a possible fragility of some newly developed economies against external shocks. As the financial exposure increases, market perception becomes a crucial element to makean economy shift. For example, an announcement by the US Federal Reserve in May 2013 of a gradualremoval of financial easing, triggered sudden depreciation of currencies in some newly developed
economies. This consequently effected stock prices and market sentiments. An economist at Morgan
Stanley listed five currencies that presented notable downturns, namely, Brazil real, Indian rupee, Indonesian rupiah, Turkish lira, and South African rand, dubbing them the “Fragile Five.” The markets
calmed down eventually, but another shock came in the latter half of 2013, suggesting these types ofshocks would hit anytime when the market considers an economy as fragile.

©2014 Asian Productivity Organization

The market in particular tries to detect possible signs of a major collapse of newly developed economies. Such indicators include current account deficit, slowdowns of inward foreign direct investment,
short-run external debts, small foreign currency reserves, insufficient ability of manipulating macroeconomic policies, and political instability. In cases of East Asian economies, resiliency against macro
shocks has been reinforced notably since the Asian Currency Crisis, with limited current account deficits, careful debt management, and enlarged foreign currency reserves. However, globalization has
continued, and the power of speculation has enhanced. By keeping macro figures healthy and preparing quick policy responses for unexpected happenings, the Asian countries can guard against a sudden attack in the market.
The third short-term issue to consider is the possible instability in politics. The Asian countries,
including India and Indonesia, are likely to have new governments soon. Whether the transition of thegovernments would go smoothly with the adoption of good economic policies is an important checkpoint of the market. A political turmoil in Thailand seems to continue, which may slow economic
growth to some extent. International conflicts, including territorial disputes in the East and South
China Sea, are another concern that may influence economic matters. Political stability and separationof economics and politics have been a basis for extending international production networks and vitalizing economic dynamism, particularly in East Asia. Overcoming domestic and international political difficulties would allow Asia to foster a favorable economic environment for strong economic
growth and the betterment of lifestyle.
On the positive front, there is the steady progress of economic integration in Asia. Political leaders
acknowledge the importance of their progress and try to keep momentum for deeper economic integration. The ASEAN is committed to finalize the ASEAN Economic Community (AEC) by the end of
2015. Although not all of the commitments under the AEC Blueprint, announced in 2007, can be6Overviewachieved, AEC will be a milestone of economic integration in the developing world. This will present a
new development strategy of pursuing both deepening economic integration and narrowing development gaps. East Asia and Asia-Pacific are also stepping into the era of mega-FTAs (free trade agreements). Mega-FTAs, particularly Trans-Pacific Strategic Economic Partnership Agreement (TPP), in
which some of the East Asian countries participate, are pursuing deep liberalization and international
rule making. The liberalization is not limited to tariff removal, but includes the liberalization of services, investment, and government procurement. International rule making covers intellectual property
rights protection, competition with state-owned enterprises, environment, dispute settlements, andothers. The wide coverage of such policy modes is clearly motivated by a new type of international
division of labor or the 2nd unbundling. Though a conclusion for TPP is uncertain, the negotiation itself is already influencing the East Asian economies. Negotiations over competing mega-FTAs, such as
Regional Comprehensive Economic Partnership (RCEP) and China-Japan-Korea (CJK) FTA, are likely tobe accelerated and upgraded in quality. Regardless of the details of these agreements the general
concept is necessary to pursue a more stimulated economic environment in East Asia and Asia-Pacific.

2

Asia’s economic dynamism warrants considerable attention to the rapid and vigorous changes in its
economic performance in the short run. To fully understand this economic dynamism, it is essential tograsp 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 undervarious political regimes. The APO Productivity Databook provides concise information and useful insights into the basis of growth performance and economic structure of Asian countries by presenting
such long-term data analysis.
International comparisons of economic performance are never a precise science; instead, they are
fraught with measurement and data comparability issues. Despite best efforts in harmonizing data,some data uncertainty remains. Operating within a reality of data issues, some of the adjustments inthe 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 othersimilar studies. Such 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 45% and
53% larger than the US and EU15 in 2012, respectively (Table 1).

even more tilted toward Asia, with Asia29 being 1.5 times and 2.3 times larger than the US and
EU15 in 2012, respectively. China has overtaken Japan as the largest Asian economy since 1999,
and its size was 94% relative to the US in 2012. India surpassed Japan, replacing it as the second
largest economy in Asia in 2008. In 2012, the total GDP of the three largest Asian economies alone
was 61% larger than the US economy (Table 2 and Figure 5).

2: This Databook based on the new PPP estimates of the 2011 International Comparisons Program (ICP) round published in April
2014. This has the significant effect of raising the relative sizes of Asian economies against the base economy, the US.

7©2014 Asian Productivity Organizationu Based on GDP adjusted for purchasing power parity (PPP),2 the weight of the world economy is2 Overview

u During the period 2000–2012, Asia29 grew at 5.9% on average per annum, compared with 1.7%

and 1.1% in the US and EU15, respectively. Japan was the slowest growing economy among theAsia29 at 0.7%, compared with 14 of the 29 Asian economies with over 5.0% of annual economic
growth (Table 3 and Figure 1).
u For the past two decades (1990–2012), China and India have emerged as the driving force propel-ling Asia forward, accounting for 45% and 16% of regional growth, respectively (Figure 7).
u The global financial crisis slowed Asia29’s growth significantly from a recent peak of 8.2% during

2006–2007, to 4.8% during 2007–2008 and further to 4.0% during 2008–2009, before rebounding
strongly to 8.0% during 2009–2010. This is in comparison to the deep recession of −3.1% and−4.7% experienced by the US and EU15, respectively, during 2008–2009 (Figure 1).
u The correlation coefficients between China and other Asian economies strengthened between

the two decades. This suggests 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).
Catching up in per capita GDP
u Our results show the outcome of the dramatic development effort of the four Asian Tigers.3 Singa-pore and Hong Kong have managed to close a per capita GDP gap with the US of around 60% injust under four decades. Singapore has even surpassed the US since 1992, and in 2012 its per capita GDP was 49% higher. In contrast, veteran Japan has fallen behind, widening its gap with the US
to 29%. In 2012, the ROC’s and Korea’s per capita GDP was 80% and 60% of the US level, respectively (Table 5 and Figure 14).
u Despite their rapid growth, due to their population size per capita GDP of China and India was 22%

and 10% of the US in 2012, respectively. However, this represents a tenfold increase in China’s relative per capita GDP over the last four decades. The level achieved by Asia29 was 16% of the US,
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 Asian Tigers, Japan, and Iran, all Asian countries have a labor productivity gap of 50% or higher (Figure 18).
u For most countries in Asia, the majority of per capita GDP growth can be explained by improvement

in labor productivity. However, the employment rate contribution relative to labor productivity
was also highly significant in Nepal, Pakistan, Bangladesh, Cambodia, and Thailand in 2000–2012(Figure 19).
u There is a significant variation in Asia’s employment rates from 25% to over 60% at present. The©2014 Asian Productivity Organization

employment rates have been rising in most countries in Asia and are 10–15 percentage points
above the US in Singapore, Cambodia, Thailand, Vietnam, and China (Figure 21).

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

8

Overview

Changes in demand composition2u With a few exceptions, household consumption is the biggest component of final demand. In

recent years, Asia29’s consumption ratio has dropped to 49.3% of GDP, largely reflecting the trend
in China. This compares to 70.8% in the US, 58.5% in EU15, and 55.6% in Australia (Table 7).
u The share of household consumption in GDP tends to be more volatile, dropping 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-15, over-65) 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 gap has been widen-

ing. Historically, Australia’s investment share has been sandwiched between that of Asia and the
US/EU15. In 2012, Asia29 invested 35.1% of its GDP, compared with 16.1% for the US, 17.8% for
EU15, and 27.5% for Australia (Table 7 and Figure 31).
u China faces huge internal and external imbalances. The investment share of GDP (at 48.7%) as thebiggest component in final demand and the household consumption share plummeted to 34.7%
in 2012. In contrast, the weight of net exports has been rising in the past decade, although it isdeclining in recent years due to weak foreign demand (Figure 22).
u GCC economies are unusually skewed toward net exports because of their oil. Net exports ac-

counted for 28.0% of final demand in 2012, compared with Asia29’s 2.1% and China’s 2.8%. Only
the US and South Asia run trade deficits of a more significant nature, which accounted for −3.5%
and −7.6% of final demand, respectively, in 2012 (Table 7).
u Basic necessities account for a high proportion of household consumption in lower-income coun-tries, according to the cross-country version of Engel’s Law, which says that basic necessities willaccount for a high proportion of household consumption for a lower per capita income group andvice versa. They spend 30–60% 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 theireconomic 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 laboru 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 9.5% on average per year in 2005–2012,
followed by Mongolia’s 7.2% and India’s 6.9%; this compares with the US’s 1.3%. Singapore’s 0.4%

9©2014 Asian Productivity Organization

productivity 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 18% of the US in 2012
(Table 8 and Figure 39).

2 Overview

growth over the same 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 14–31 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 9.0% between 1970–1990 and 1990–2012, compared to the US at 1.5% and 1.8% over thesame periods (Figure 44).
u Mapped onto Japan’s historical trajectory of GDP per hour, most Asian countries cluster around thelevel that Japan achieved in the 1950s and early 1970s, with the Asian Tigers being the clear frontrunners, sprinting away from the pack (Figure 46).
Total factor productivity
u Eleven of the 18 Asian countries compared experienced faster TFP growth than the US over theperiod 1970–2012, with China in a league of its own. Its TFP growth was at 3.1% on average per
year, compared with those of Thailand and Sri Lanka at 1.9% in second place and the US at 0.9%.
With TFP growing at 0.5% 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 11 of the 18 Asian countries compared, with
it being most prominent in Sri Lanka (38%), China (36%), Thailand (35%), and Pakistan (31%)(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 55% on average, while the contribution of TFP is getting progressively
more significant, rising to a share of above 35% on average in 2000–2012 (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).

©2014 Asian Productivity Organizationu Over the past decades, it has been observable that economic growth has decelerated in the earlystarters (Japan and the Asian Tigers). Their experience lends support to the likelihood of an eventual slowdown in China; the question is more likely “when,” than “if.” TFP growth slowed from its
former peaks achieved in the late 1970s or late 1980s until recent years when countries experienced TFP resurgence (Figure 54).

10

Overview

Capital deepening and capital productivity

2u 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 per year to 7.1% in Korea between 1970–1990 and 1990–2012, whereas it doubled in China from 5.3% to 10.6% (Figure 58).
u Capital deepening tends to go hand in hand with deterioration in capital productivity. China’s per-formance 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).
Industry structureu 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, Korea, Thailand, the ROC, Malaysia, and Indonesia,
in which higher TFP growths are measured in 2000–2012 (Figure 68). 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 69).
u While Asian countries are diversifying away from agriculture, the sector still dominates employ-ment, accounting for 38% of total employment in 2012 for Asia29, down from 61% in 1980. Its
share in total value added decreased more moderately, from 14% to 10% over the same period.
Shifting out of agriculture into more efficient sectors will boost economy-wide productivity(Figures 70 and 73).
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 the ROC, expansions to manufacturing output could account for the increases of employment in the 1970s andthe 1980s. 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 75).

u 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 manufacturing-driven to more services-driven. In the period

11©2014 Asian Productivity Organization

Industry origins of economic growth2 Overview

2000–2012, the contributions to economic growth by manufacturing and services were 35% and44%, respectively, compared with 44% and 34% in the 1990s (Figures 77 and 78).
u In contrast, growth in India has always been more driven by services, the contribution of whichrose from 51% in the late 1980s to 64% in 2000–2012, while manufacturing usually contributes
one-fifth or less (Figures 77 and 78).
u A total of 29% of Asia29’s regional growth originated from the expansion of manufacturing in the

2000s, 60% of which was accounted for by China. In other words, China’s manufacturing alone
contributed 17% to regional growth (Figure 81).
u The importance of manufacturing as a contributor to overall labor productivity growth has neverwaned in Korea and the ROC. However, manufacturing has never been a major contributor in India
in its recent development process, or in Hong Kong and Sri Lanka in 2000–2012 (Table 16 and Figure 85).
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 in some oil-exporting countries such as Kuwait and Brunei, where trading gain has always
been positive and significant (Table 17 and Figure 92).
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 0.7% of GDP in 1990 to 3.2% in 2012, compared with 1.4% in 1990 and
31.4% in 2012 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 86).
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 from 1970–2012; Kuwait and Brunei appear tobe the outliers (Figure 87).
u The five countries that have been enjoying a trading gain over 1% per annum in the past four de-©2014 Asian Productivity Organization

cades are all oil-exporting countries. Among them, only Iran managed to achieve a positive growthin 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 93).
Asia is a diverse regional economy in 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 toimprove 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 unparalleled economic dynamics inherent in the region.

123.1 Economic Scale and Growth

3 Growth of Asian Economy
In the past two decades, the story of the world economy belonged to Asia, featuring its steady rise ineconomic prowess. Before the mid-1980s, the fortune of Asia closely followed that of Japan but 1988
marked the start of their paths decoupling. The Asian economy is no longer defined by Japan alone(Figure 1). Asian growth consistently has been outperforming the West over the past two decades.
With the exception of 1997–1999, when the economy was adversely affected by the Asian financial
crisis, Asia29 has been growing faster than the US and EU15 by more than 3 to 4 percentage points on
average per year. This gap has been widening in recent years. In 2009, at the height of the global financial storm, the growth differentials were 7.1 and 8.6 percentage points with the US and EU15, respectively. In 2010, simultaneous large-scale fiscal stimulus packages helped major economies reboundstrongly, before growth slowed again in 2011. The fortunes of economies were mixed in 2012. The
slowdown in growth was less pronounced in Asia than in the previ%
10
ous year. Plagued by the euro crisis,8
EU15 saw their economy shrink by
6
0.6%, whereas the US and Japanese
4
economies picked up. Despite that,2
the differences in growth perfor0
mance have been sustained. It is
−2
Japan
US
therefore no surprise that the center−4
Asia29EU15
of gravity in the global economy is
−6
1970
1975
1980
1985
1990
1995
2000
2005
2010
gradually shifting toward Asia. In
2012, the Asian economy contributFigure 1 GDP Growth of Asia, the EU, Japan, and the US,
ed 41% (38% for Asia29) of world
1970–2012___Annual growth rate of GDP at constant market prices
output, compared with the US and
EU27, each accounting for 20% andSources: Official national accounts in each country, including author adjustments.
19%, respectively (Figure 2). The
International Monetary Fund (IMF)(2014) projects the Asian sharein world output will continue to
2012
2019
rise, reaching 46% (43% for Asia29)
by 2019. In contrast, the output
ASIA
ASIA
APO20
Others
41 %
46 %
APO20
Othersshares of the US and EU27 will
21 %
20 %
22 %
21 %
shrink by a similar extent to 18%, andAsia29Asia29
38 %
43 %
EU15
17%, respectively.
EU15
14 %

17 %

US

Other Asia
3%

EU27
17 %

US

Other Asia
To better understand the dynamics
20 %
18 %
3%
of the long-term economic growthwithin the region, the remainder ofthis chapter details countries’ diverse
Figure 2 Share of Asia in World GDP in 2012 and Projection for 2019
development efforts and achieve___Share of GDP using constant PPP
ments since the 1970s, throughcross-country level comparisons ofSource: IMF, World Economic Outlook Database, April 2014.
GDP and other related performanceindicators.4 To facilitate internation­
al level comparisons, harmonized GDP for each of the individual countries5 is expressed in its equiv­
alent in a common currency unit (customarily in the US dollar), using a set of conversion rates between
the individual national currencies. The choices for conversion rates are exchange rate and PPP.

13

©2014 Asian Productivity Organization

EU27
19 %

3

3 Growth of Asian Economy

Table 1 GDP using Exchange Rate, 1970, 1990, 2000, 2010, 2011, and 2012___GDP at current market prices, using annual average exchange rate
1970
Japan
China
India
Pakistan
IranIndonesia
Bangladesh
Korea
ThailandPhilippines
ROC
Saudi Arabia
Malaysia
Hong Kong
KuwaitMyanmar
Sri Lanka
Singapore
Vietnam
UAE
Nepal
Cambodia
Qatar
BahrainOman
Fiji
BruneiMongolia(regrouped)
357 170.9
APO20
451 216.1
Asia23462 221.2
Asia29319 152.8
East Asia
86 41.3
South Asia
35 16.6
ASEAN
30 14.4
ASEAN65 2.2
CLMV
11 5.1
GCC(reference)
1,038 497.6
US1,209 579.5
EU15
Australia
Turkey1990(%)

209 100.0
92 43.9
61 29.0
12 5.8
11 5.410 4.7
10 4.7
9 4.3
7 3.5
7 3.2
6 2.7
5 2.6
4 1.9
4 1.8
3 1.4
3 1.3
3 1.2
2 0.9
1 0.6
1 0.5
1 0.5
1 0.4
1 0.3
0 0.2
0 0.1
0 0.1
0 0.1
0 0.1

45
24

21.6
11.5

3,097 100.0
390 12.6
322 10.4
270 8.7
165 5.3
127 4.1
118 3.8
94 3.088 2.977 2.551 1.748 1.546 1.545 1.539 1.329 0.919 0.6
12 0.4
8 0.3
7 0.2
7 0.2
5 0.2
5 0.1
4 0.1
3 0.1
2 0.1
1 0.0
1 0.0
1 0.0

Australia
Turkey

322
200

4,473
4,872
5,083
4,001
412
363
349
14
211

2000

(%)

Japan
China
India
Korea
ROC
Indonesia
Saudi Arabia
IranThailandHong Kong
UAE
Pakistan
Philippines
Malaysia
Singapore
Bangladesh
KuwaitOman
Sri Lanka
Qatar
Vietnam
MyanmarBahrain
Nepal
Brunei
CambodiaFiji
Mongolia
Lao PDR(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLMV
GCC(reference)
US
EU15

144.4
157.3
164.1
129.2
13.3
11.7
11.3
0.5
6.8

5,801 187.3
6,155 198.7
10.4
6.5

4,741
Japan
1,198
China
533
Korea
468
India
326
ROC
Saudi Arabia 190
Hong Kong
169
Indonesia
168
126
Thailand
110
Iran
105
UAE
94
Singapore94
Malaysia
81
Philippines
Pakistan
72
46
Bangladesh
38
Kuwait33
Vietnam
20
Oman
18
Qatar
17
Sri Lanka
8
Bahrain7
Myanmar
6
Nepal
6
Brunei4
Cambodia2
Fiji2
Lao PDR
1
Mongolia(regrouped)
7,092
APO20
8,304
Asia23
8,684
Asia296,969
East Asia
609
South Asia
614
ASEAN
569
ASEAN6
45
CLMV
380
GCC
(reference)
9,952
US
9,571
EU15
10,637EU27
406
Australia
267
Turkey

(%)

100.0
25.3
11.3
9.9
6.9
4.0
3.6
3.5
2.7
2.3
2.2
2.0
2.0
1.7
1.5
1.0
0.8
0.7
0.4
0.4
0.4
0.2
0.2
0.1
0.1
0.1
0.0
0.0
0.0
149.6
175.2
183.2
147.0
12.8
13.0
12.0
1.0
8.0
209.9
201.9
224.4
8.6
5.6

2010
China
5,931
Japan
5,507
India
1,649
Korea
1,015
Indonesia
719
Saudi Arabia 531
Iran
467
ROC
428
Thailand
339
UAE
294
Malaysia
239
Singapore
233
Hong Kong
224
Philippines
199
Pakistan
176
Qatar
127
Kuwait123
Vietnam
117
Bangladesh
100
Oman
59
Sri Lanka
50
42
Myanmar
26
Bahrain
19
Nepal
14
Brunei
Cambodia
11
7
Lao PDR
6
Mongolia
3
Fiji(regrouped)
11,509APO20
17,495
Asia2318,654
Asia29
East Asia 13,111
South Asia 1,993
1,920
ASEAN
1,743
ASEAN6
177
CLMV
1,159
GCC
(reference)
14,499US
14,051EU15
16,124EU27
1,277
Australia
734
Turkey

(%)

100.0
92.9
27.8
17.1
12.1
8.9
7.9
7.2
5.7
5.0
4.0
3.9
3.8
3.4
3.0
2.1
2.1
2.0
1.7
1.0
0.8
0.7
0.4
0.3
0.2
0.2
0.1
0.1
0.1
194.1
295.0
314.5
221.1
33.6
32.4
29.4
3.0
19.5
244.5
236.9
271.9
21.5
12.4

2011
7,322
China
5,919
Japan
1,857
India
1,114
Korea
858
Indonesia
Saudi Arabia 674
Iran
637
ROC
465
367
Thailand
356
UAE
279
Malaysia
272
Singapore
244
Hong Kong
224
Philippines
Pakistan
211
174
Qatar
164
Kuwait137
Vietnam108
Bangladesh
70
Oman
59
Sri Lanka
56
Myanmar29
Bahrain
21
Nepal
17
Brunei13
Cambodia
9
Mongolia
8
Lao PDR
4
Fiji(regrouped)
12,806
APO20
20,201
Asia23
21,668Asia29
East Asia 15,073
South Asia 2,257
2,230
ASEAN
2,017
ASEAN6
213
CLMV
1,467
GCC
(reference)
15,076
US
14,636EU15
16,840EU27
1,516Australia
778
Turkey

(%)

100.0
80.8
25.4
15.2
11.7
9.2
8.7
6.4
5.0
4.9
3.8
3.7
3.3
3.1
2.9
2.4
2.2
1.9
1.5
1.0
0.8
0.8
0.4
0.3
0.2
0.2
0.1
0.1
0.1
174.9
275.9
295.9
205.9
30.8
30.5
27.5
2.9
20.0
205.9
199.9
230.0
20.7
10.6

2012
China
8,221
Japan
5,951
India
1,823
Korea
1,130
Indonesia
889
Saudi Arabia 739
Iran
617
ROC
475
Thailand
393
UAE
392
Malaysia
293
Singapore
284
Hong Kong
258
Philippines
250
Pakistan
224
Qatar
195
Kuwait187
Vietnam
157
Bangladesh
113
Oman
79
Sri Lanka
60
60
Myanmar
30
Bahrain
20
Nepal
17
Brunei
Cambodia14
10
Mongolia
9
Lao PDR
4
Fiji(regrouped)
12,974
APO20
21,272
Asia2322,894
Asia29
East Asia 16,045
South Asia 2,239
2,367
ASEAN
2,127
ASEAN6
240
CLMV
1,622
GCC
(reference)
15,775
US
14,925EU15
17,215EU27
1,558
Australia
791
Turkey

(%)

100.0
72.4
22.2
13.7
10.8
9.0
7.5
5.8
4.8
4.8
3.6
3.5
3.1
3.0
2.7
2.4
2.3
1.9
1.4
1.0
0.7
0.7
0.4
0.2
0.2
0.2
0.1
0.1
0.0
157.8
258.8
278.5
195.2
27.2
28.8
25.9
2.9
19.7
191.9
181.5
209.4
19.0
9.6

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.

©2014 Asian Productivity Organization

3.1 Economic Scale and Growth
Table 1 provides snapshot-level comparisons of Asian countries, based on GDP at current market
prices using exchange rates,6 for the six separate years of 1970, 1990, 2000, 2010, 2011, and 2012. By
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 between the 1970 and 1990 comparisons, dwarfing the relative size of all other Asian economies

143.1 Economic Scale and Growth

Comparisons based on exchange rates however, 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 the size of a developing
economy and, in turn, the perceived welfare of its residents. The scale of economy rankings change dramatically when international price differences are properly taken
into account.7
Figure 3 shows the extent to which the exchange rates
have failed to reflect countries’ price differentials properly
relative to the US, based on the PPP estimates of the 2011
International Comparisons Program (ICP) round published in April 2014. With the exception of Japan and

56 Australia
35
−23
−29
−30
−31
−34
−38
−41
−42
−43
−44
−46
−49
−50
−51
−52
−56
−58
−59
−59
−59
−65
−67
−67
−67
−68
−69
−69
−71
−72

−80 −60 −40 −20 0

Japan
Korea
Singapore
Hong Kong
UAE
Qatar
KuwaitTurkeyFiji
BruneiBahrain
China
ROC
Oman
Saudi Arabia
Malaysia
Iran
Mongolia
Philippines
Indonesia
ThailandSri Lanka
Nepal
Cambodia
Vietnam
India
Bangladesh
Lao PDR
Myanmar
Pakistan3

20 40 60 %Figure 3 Price Level Indices of GDP,
2011___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 (2014).

4: 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. At the end of 2011, Thailand officially switched to the1993 SNA, and its national accounts became compatible with the 1993 framework for the first time. To construct the long timeseries 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. In the new Vietnamese National Accounts published in 2013, the GDP was upwardly revised by about
9% (mainly due to the introduction of FISIM) and was published after the year of 2005. The backward estimates before 2004 areestimated 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. The Databook 2014 reflects some large revisions published bynational statistical offices in 2013 and in the first quarter of 2014.
5: Appendix 1 discusses the extent to which countries’ GDP data are comparable.
6: 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 the US.
7: This is because exchange rates embody the trade sector bias (i.e., is more influenced by the prices of traded than non-traded
goods and services) and thus do not necessarily succeed in correcting the price differentials among countries. As developing
economies tend to have relatively lower wages and, in turn, lower prices for non-traded goods and services, a unit of local currency has greater purchasing power in the local economy than reflected in its exchange rate.

15©2014 Asian Productivity Organization

and reducing the US lead from five times to less than twotimes its economy. The turn of Japan’s fortune came in1990, when the country’s excessive growth years of thelate 1980s ended and its descent began. Thereafter, stagnation in Japan combined with vibrant growth in developing Asia has resulted in the rapid erosion of Japan’s
prominence in the regional economy. The countries thatmake up the four largest Asian economies (China, Japan,
India and Korea) have been consistent with their positions
rather secure in the past two decades, whereas ASEAN asa group has been demonstrating vigor in catching up
since 2000. On this measure, Asia29 was 45% and 53%
larger than the US and EU15 in 2012, respectively.

3 Growth of Asian Economy

Australia, exchange rates systematically under-represent the relative purchasing power for all thecountries covered in this report. The underestimation is substantial for some, ranging from 23% for
Korea to 72% for Pakistan. Thus, the exchange-rate-based GDP considerably underestimates the economic scales in real terms for those countries. By taking into account the international price differentials, PPP rectifies the trade sector bias, and in turn the relative size of economies can be more
adequately measured.8

Table 2 GDP using PPP, 1970, 1990, 2000, 2010, 2011, and 2012___GDP at constant market prices, using 2011 PPP, reference year 20121970

©2014 Asian Productivity Organization(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLMV
GCC(reference)
US
EU15
Australia
Turkey

3,538
4,045
4,504
2,233
944
575
508
71
475

234.0
267.4
297.8
147.6
62.4
38.0
33.6
4.7
31.4

4,920 325.3
5,940 392.8
278
237

1990

(%)

1,512 100.0Japan
662 43.7
India
387 25.6
China
296 19.6
Iran
Saudi Arabia 247 16.4
190 12.6
Indonesia
148 9.8
Kuwait110 7.3
Pakistan
110 7.3
Philippines
92 6.1Thailand
84 5.6
Korea
77 5.1
Bangladesh
63 4.2ROC
44 2.9
Malaysia
41 2.7
Vietnam
34 2.2
Hong Kong
23 1.5
Sri Lanka
21 1.4Singapore
18 1.2
Qatar
17 1.1
Myanmar
11 0.7
Brunei
10 0.7UAE
10 0.7Oman
8 0.5
Bahrain
3 0.2
Mongolia
2 0.1
Fiji

18.4
15.7

(%)

3,665
Japan
1,719
China
1,540
India
787
Indonesia
Saudi Arabia 615
533
Iran
501
Korea
376
Thailand
331
ROC
321
Pakistan
235
Philippines
206
UAE
177
Malaysia
154
Hong Kong
117
Bangladesh
106
Singapore
91
Kuwait91
Vietnam
64
Oman
58
Sri Lanka
36
Qatar
29
Myanmar
26
Nepal
20
Brunei18
Bahrain
9
Mongolia
9
Cambodia
7
Lao PDR
4
Fiji(regrouped)
9,229
APO20
11,203
Asia23
12,257
Asia296,614
East Asia
South Asia 2,146
1,908
ASEAN
1,766
ASEAN6
144
CLMV
1,059
GCC
(reference)
9,256
US
10,315
EU15

100.0
46.9
42.0
21.5
16.8
14.5
13.7
10.3
9.0
8.8
6.4
5.6
4.8
4.2
3.2
2.9
2.5
2.5
1.7
1.6
1.0
0.8
0.7
0.6
0.5
0.2
0.2
0.2
0.1

502
587

13.7
16.0

Australia
Turkey

251.8
305.6
334.4
180.5
58.5
52.1
48.2
3.9
28.9
252.5
281.4

2000
4,636
China
4,163
Japan
2,644
India
1,197
Indonesia
944
Korea
Saudi Arabia 806
788
Iran
606
ROC
586
Thailand473
Pakistan
356
Malaysia
337
UAE
334
Philippines
226
Hong Kong
211
Singapore
196
Vietnam
187
Bangladesh
160
Kuwait102
Oman
96
Sri Lanka
69
Qatar
58
Myanmar
42
Nepal
29
Bahrain25
Brunei17
Cambodia
12
Lao PDR
10
Mongolia
5
Fiji(regrouped)
13,249APO20
18,212
Asia23
19,741
Asia29
East Asia 10,832
South Asia 3,535
3,045
ASEAN
2,751
ASEAN6
294
CLMV
1,532
GCC
(reference)
12,934
US
12,974EU15
14,707EU27
709
Australia
843
Turkey

(%)

100.0
89.8
57.0
25.8
20.4
17.4
17.0
13.1
12.6
10.2
7.7
7.3
7.2
4.9
4.6
4.2
4.0
3.5
2.2
2.1
1.5
1.3
0.9
0.6
0.5
0.4
0.3
0.2
0.1
285.8
392.8
425.8
233.7
76.3
65.7
59.3
6.4
33.1
279.0
279.9
317.2
15.3
18.2

2010
12,561
China
5,508
India
4,492
Japan
1,991
Indonesia
1,439
Iran
1,418
Korea
Saudi Arabia 1,289
914
Thailand
886
ROC
740
Pakistan
566
Malaysia
533
Philippines
502
UAE
400
Vietnam
369
Singapore
337
Hong Kong
330
Bangladesh
243
Kuwait
235
Qatar
182
Myanmar160
Sri Lanka
142
Oman
61
Nepal
52
Bahrain37
Cambodia
29
Brunei25
Lao PDR
18
Mongolia
6
Fiji(regrouped)
20,254
APO20
33,092
Asia2335,564
Asia29
East Asia 19,775
South Asia 6,817
5,059
ASEAN
4,414
ASEAN6
645
CLMV
2,473
GCC
(reference)
15,064
US
14,673EU15
16,852
EU27
955
Australia
1,234
Turkey

(%)

100.0
43.9
35.8
15.9
11.5
11.3
10.3
7.3
7.1
5.9
4.5
4.2
4.0
3.2
2.9
2.7
2.6
1.9
1.9
1.4
1.3
1.1
0.5
0.4
0.3
0.2
0.2
0.1
0.0
161.2
263.5
283.1
157.4
54.3
40.3
35.1
5.1
19.7
119.9
116.8
134.2
7.6
9.8

Unit: Billions of US dollars (as of 2012).
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

2011
13,729
China
5,835
India
4,472
Japan
2,122
Indonesia
1,477
Iran
1,470
Korea
Saudi Arabia 1,400
923
ROC
920
Thailand762
Pakistan
595
Malaysia
552
Philippines
523
UAE
425
Vietnam
391
Singapore
353
Hong Kong
352
Bangladesh
267
Kuwait
266
Qatar
192
Myanmar173
Sri Lanka
144
Oman
64
Nepal
53
Bahrain40
Cambodia
30
Brunei27
Lao PDR
21
Mongolia
6
Fiji(regrouped)
20,992
APO20
34,973
Asia2337,630
Asia29
East Asia 20,998
South Asia 7,194
5,303
ASEAN
4,618
ASEAN6
685
CLMV
2,657
GCC
(reference)
15,336
US
14,888EU15
17,131
EU27
989
Australia
1,343
Turkey

(%)

100.0
42.5
32.6
15.5
10.8
10.7
10.2
6.7
6.7
5.6
4.3
4.0
3.8
3.1
2.8
2.6
2.6
1.9
1.9
1.4
1.3
1.0
0.5
0.4
0.3
0.2
0.2
0.2
0.0
152.9
254.7
274.1
152.9
52.4
38.6
33.6
5.0
19.4
111.7
108.4
124.8
7.2
9.8

2012
14,779
China
6,119
India
4,537
Japan
2,256
Indonesia
1,500
Korea
Saudi Arabia 1,482
1,394
Iran
985
Thailand
936
ROC
794
Pakistan
626
Malaysia
590
Philippines
546
UAE
448
Vietnam
398
Singapore
374
Bangladesh
359
Hong Kong
289
Kuwait
282
Qatar
205
Myanmar184
Sri Lanka
152
Oman
67
Nepal
55
Bahrain
43
Cambodia
31
Brunei29
Lao PDR
24
Mongolia
7
Fiji(regrouped)
21,670APO20
36,684
Asia2339,490
Asia29
East Asia 22,135
South Asia 7,539
5,610
ASEAN
4,885
ASEAN6
724
CLMV
2,806
GCC
(reference)
15,775
US
14,806EU15
17,064EU27
1,015
Australia
1,372
Turkey

(%)

100.0
41.4
30.7
15.3
10.2
10.0
9.4
6.7
6.3
5.4
4.2
4.0
3.7
3.0
2.7
2.5
2.4
2.0
1.9
1.4
1.2
1.0
0.5
0.4
0.3
0.2
0.2
0.2
0.0
146.6
248.2
267.2
149.8
51.0
38.0
33.1
4.9
19.0
106.7
100.2
115.5
6.9
9.3

3.1 Economic Scale and Growth

Table 2 repeats the same snapshot level comparisons of Asian countries as in Table 1, but based on
GDP at constant market prices using constant PPP for Asian countries. By correcting for international
price differentials, Asia29 has been expanding rapidly. It was 150%, instead of 45%, larger than the US
economy in 2012, having overtaken it in 1975 (Figure 4).9 East Asia (China, the ROC, Hong Kong, Japan,
Korea, and Mongolia) caught up with the US in 2006 from a low base of 45% in 1970. In contrast, EU15
has been experiencing a gradual relative decline in economic size, from 121% of the US economy in1970 to a low of 94% in 2012. Based on GDP using constant PPP, the weight of the world economy iseven more tilted toward Asia than portrayed by GDP using exchange rates. This reflects the fact thatnearly all Asian countries increase in relative size after international price differentials have been properly taken into account.

3

The relative size of China’s economy in 2012 was 326% or more than three times that of Japan, compared with 138% when exchange rates are used in Table 1. Considering that the Chinese economy was
only 26% that of Japan and 59% that of India in 1970, represents remarkable growth. On this measure,
China overtook Japan after 1999 to become the leading economy in Asia (Figure 5).10 Similarly, its sizein 2012 increased from 52% to 94% relative to the US economy after adjusting for their price differences. Assuming that China and the US also grow at the usual pace as they have displayed since 2000,
China is projected to overtake the US economy in 2014.
Given that PPP for India have been revised by –24% in the 2011 ICP round (see Box 1), the effects havebeen to raise the relative size of India. Relative to Japan, the Indian economy has been increasing from

US=100

US=100

100

250
220

China

80

190
60

130
100
70

Asia29

EU15

40

US
20

APO20
East Asia

40
1970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 4 Regional GDP of Asia and the EU,
Relative to the US, 1970–2012___Indices of GDP at constant market prices, using

0

Japan
India

1970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 5 GDP of China, India, and Japan,
Relative to the US, 1970–2012

2011 PPP___Indices of GDP at constant market prices, using
2011 PPP

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

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

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, which are currently benchmarked every six years. PPPs for most Asian countries havebeen revised downward, compared with what they would have been by extrapolating the 2005 benchmark PPP (see Box 1). Thishas the effect of raising the relative sizes of these economies against the base economy. Consequently, the level comparisons in
Databook 2013, which were based on the 2005 benchmark PPP, are not comparable with the results presented in this Databook.
9: This compares with the finding in Databook 2013 that the economic size of Asia29 overtook the US in 1988.
10: The shift of the benchmark year PPP estimates from 2005 to 2011 has the effect of bringing forward the year when China overtook
Japan in relative GDP to 1999, from 2002 in Databook 2013.

17©2014 Asian Productivity Organization160

3 Growth of Asian Economy

44% in 1970 to 135% in 2012, surpassing Japanand replacing it as the second largest economy
in Asia in 2008. In 2012, the total GDP of thethree largest Asian economies alone was 61%
larger than the US economy.

US=100

50
40

ASEAN

30
20

South Asia
ASEAN6

Figure 6 shows the rapid expansion of the relaGCC
10
tive size of the South Asian economy (consisting
CLMVof Bangladesh, India, Nepal, Pakistan, and Sri
0Lanka), 81% of which was accounted for by India
1970 1975 1980 1985 1990 1995 2000 2005 2010
in 2012. ASEAN also showed vigor in their catchup effort. They were on a par with the South
Figure 6 Regional GDP of South Asia, ASEAN,
and GCC, Relative to the US, 1970–2012
Asian economy in 1996–1997 before the setback___Indices of GDP at constant market prices, using
caused by the Asian financial crisis of 1997–1998
2011 PPP
took hold, set them on a lower growth path,
Sources: Official national accounts in each country, including auopening up a divergence once again. In contrast,thor adjustments.
11
the progress of GCC countries flagged for two
decades. Only in the past decade has it pickedup and brought the relative size of the country group back to its previous peak of the early 1980s.12
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.13 The rankings vary from period to period and are no longer dominated by the economic giants. In fact, small developing Asian countries, like Qatar, Myanmar, Cambodia, Vietnam, the Lao PDR,
and Mongolia, are equally capable of exhibiting exuberant growth. As labor costs are edging up in
China, the workshop of the world has started shifting its location to the neighboring countries such as
Cambodia, the Lao PDR, Myanmar, and Vietnam. To capture the dynamism, a new country group,
called CLMV, is formed for the Databook to track from this edition onward. They are clearly the fastergrowing group among the ASEAN countries, at 7.6% on average per year compared with 4.8% managed by ASEAN6 in the period 1990–2012.

©2014 Asian Productivity Organization

At the other end of the table, Japan consistently has been struggling at the bottom over the past
two decades (1990–2012), with an average growth of 1.0% per year, compared with Asia29’s 5.5%
and the fastest growth of 9.8% achieved by China. During this period, only three Asian countries –Brunei, Fiji, and Japan – grew slower than the US (2.4%), and only Japan grew slower than EU15
(1.6%). The divergence of growth performance between the Asian countries on the one hand andthe US and EU15 on the other was even more pronounced if focusing on the most recent years,

11: 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.
12: 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.
13: Annual data maximize the use of available information and data, and are normally published two to three years in arrears. For
more timely analysis, quarterly economic data are used as they are normally published within a month of the reference period
and are subsequently revised as more data become available. A trade-off always exists between data timeliness and precision. See
Box 8 (p. 122) for more details.

18

3.1 Economic Scale and Growth

Table 3 GDP Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2012___Average annual growth rate of GDP at constant market prices
1990–1995

1995–2000

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
FijiPhilippines
Qatar
Japan
Mongolia(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
AESEAN6
CLMV
GCC(reference)
US
EU15

11.6
9.2
9.2
8.2
8.1
8.1
7.6
7.6
7.0
6.5
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
2.5
2.3
1.7
−1.8

Australia
Turkey

3.1
3.2

4.4
5.7
5.6
5.7
5.0
7.3
7.3
7.4
3.8
2.5
1.7

Qatar
China
MyanmarVietnam
Cambodia
UAE
Lao PDR
India
Singapore
ROC
Bangladesh
Korea
Sri Lanka
Nepal
Malaysia
Philippines
Bahrain
Iran
Oman
Mongolia
Pakistan
Hong Kong
Saudi Arabia
KuwaitFiji
BruneiJapan
Indonesia
Thailand(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
AESEAN6
CLMV
GCC(reference)
US
EU15
EU27
Australia
Turkey2000–2005
10.6
8.3
8.2
7.3
7.0
6.3
6.0
5.7
5.6
5.1
5.1
5.1
4.9
4.8
4.8
4.5
4.2
4.1
3.7
3.6
3.2
2.6
2.6
2.1
2.0
1.4
0.8
0.8
0.7
3.0
4.3
4.2
4.5
5.3
2.5
2.0
7.4
3.7
4.2
2.9
2.9
3.8
4.1

Myanmar
China
Cambodia
Vietnam
Qatar
Kuwait
Iran
India
Mongolia
Lao PDR
Bahrain
UAE
ThailandBangladesh
Pakistan
Singapore
Malaysia
Indonesia
Philippines
Korea
Hong Kong
Sri Lanka
Saudi Arabia
ROC
Nepal
Brunei
Fiji
Japan
Oman
(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
AESEAN6
CLMV
GCC(reference)
US
EU15
EU27
Australia
Turkey2005–2012
12.1
9.3
9.0
8.0
7.9
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
3.7
3.5
3.1
2.1
2.0
1.2
1.0
4.2
5.7
5.6
5.6
6.2
5.2
4.7
8.9
4.6
2.4
1.8
1.9
3.3
4.5

Qatar
China
MyanmarMongolia
Lao PDR
India
Cambodia
Sri Lanka
Bangladesh
Vietnam
Saudi Arabia
Indonesia
Singapore
Oman
Philippines
Malaysia
Bahrain
Nepal
Pakistan
ROC
Hong Kong
Thailand
Korea
Kuwait
Iran
UAE
Fiji
BruneiJapan(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
AESEAN6
CLMV
GCC(reference)
US
EU15
EU27
Australia
Turkey1990–2012
14.5
9.9
9.3
8.5
7.8
7.3
6.7
6.5
6.1
6.0
6.0
5.8
5.7
5.0
4.9
4.7
4.7
4.3
3.9
3.7
3.7
3.6
3.5
3.3
3.3
3.1
1.2
1.1
0.4
4.2
6.3
6.2
6.6
6.8
5.3
5.0
7.0
5.6
1.1
0.6
0.8
2.7
3.8

China
Qatar
MyanmarVietnam
Cambodia
Lao PDR
India
Singapore
Malaysia
Sri Lanka
Bangladesh
KuwaitBahrain
Korea
Indonesia
ROC
Mongolia
UAE
Thailand
Iran
Nepal
Philippines
Pakistan
Saudi Arabia
Oman
Hong Kong
Fiji
BruneiJapan(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
AESEAN6
CLMV
GCC(reference)
US
EU15
EU27
Australia
Turkey2000–2012
9.8
9.4
8.9
7.3
7.2
6.7
6.3
6.0
5.7
5.3
5.3
5.3
5.0
5.0
4.8
4.7
4.5
4.4
4.4
4.4
4.3
4.2
4.1
4.0
4.0
3.8
1.9
1.9
1.0
4.0
5.6
5.5
5.7
5.9
5.1
4.8
7.6
4.6
2.4
1.6
1.7
3.2
3.9

Qatar
Myanmar
China
Cambodia
Mongolia
Lao PDR
India
VietnamBangladesh
Sri Lanka
Singapore
Indonesia
BahrainSaudi Arabia
KuwaitIranPhilippines
Malaysia
Thailand
Pakistan
UAE
Korea
Hong Kong
Nepal
ROC
Oman
BruneiFijiJapan(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
AESEAN6
CLMV
GCC(reference)
US
EU15
EU27
Australia
Turkey

11.8
10.5
9.7
7.6
7.6
7.1
7.0
6.9
5.8
5.4
5.3
5.3
5.2
5.1
4.9
4.8
4.7
4.7
4.3
4.3
4.0
3.9
3.8
3.8
3.6
3.3
1.5
1.5
0.7

3

4.2
6.0
6.0
6.1
6.5
5.2
4.9
7.8
5.2
1.7
1.1
1.2
3.0
4.1

with Asia29 growing at 6.2% on average per annum, compared with 1.1% in the US and 0.6% in
EU15 in the period 2005–2012.
The change of guards in Asia is clearly illustrated in Figure 7. While Japan was the standard-bearer inyesteryears, China and India have emerged as the driving force propelling Asia forward over the past
two decades (1990–2012) and accounting for 45% and 16% of regional growth, respectively. Despite19©2014 Asian Productivity Organization

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.

3 Growth of Asian Economy

being the slowest growing economy in Asia, Japan has remained
the fifth largest contributor toregional growth in 1990–2012,
due to its size.

1970–1990
Japan
China
India
Indonesia
Saudi Arabia
Korea
Iran
Thailand
ROC
UAE
Pakistan
Philippines
Malaysia
Hong Kong
Singapore
Oman
Vietnam
Sri Lanka
Bangladesh
Qatar
Brunei
Myanmar
Nepal
BahrainMongolia
Cambodia
Lao PDR
Fiji
Kuwait1990–2012
28.3

16.2
10.7
7.7
6.4
5.2
4.1
3.4
3.4
3.1
2.6
1.8
1.7
1.6
1.1
0.7
0.6
0.5
0.4
0.3
0.2
0.2
0.2
0.2
0.1
0.1
0.1
0.0

China
India
Indonesia
5.5
Korea
4.1
Japan
4.1
Iran 3.4
Saudi Arabia 3.0
Thailand 2.5
ROC 2.5
Pakistan 1.8
Malaysia 1.8
UAE 1.3
Vietnam 1.3
Philippines 1.3
Singapore 1.1
Bangladesh 0.9
Hong Kong 0.8
Kuwait 0.8
Qatar 0.8
Myanmar 0.6
Sri Lanka 0.5
Oman 0.3
Nepal 0.2
Bahrain 0.1
Cambodia 0.1
Lao PDR 0.1
Brunei 0.0
Mongolia 0.0
Fiji 0.0

45.0
16.0

©2014 Asian Productivity Organization

Looking at the four sub-periodsin Table 3, growth in the reference
countries, namely the US, EU15,
and Australia, revived in the latter
half of the 1990s, before it dete­riorated in the subsequent two
periods in the 2000s. Both the
US and EU15 went through deep
recessions in 2009, following the
global financial storm. Consequently, the US managed a growthof only 1.1% on average per year
−0.8
in the period 2005–2012. EU15
−10
0
10
20
30 %
0
10 20 30 40 50 %fared worse as they dipped into
recession again in 2012 on the
Figure 7 Country Contributions to Regional GDP Growth,stress of the euro crisis. They man1970–1990 and 1990–2012___Contribution share to the growth of gross regional products (growth
aged an average annual growthrate of Asia29=100)
of 0.6% over the same period.
Growth in Australia has been
Sources: Official national accounts in each country, including author adjustments.
Note: The starting periods for the Lao PDR and Cambodia are 1984 and 1987, respecfaster than that in the US andtively.
EU15, and sustained by, among
other things, China’s surging demand for commodities even through the turbulent years of global financial crisis. Growth in Asia hasgone from strength to strength, 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 6.8% in 2005–2012, compared with 5.7% and 6.6% for East Asia, respectively.
Among all country groups, ASEAN6 was most impacted by the Asian financial crisis of 1997, whichslowed its average annual growth drastically from 7.3% to 2.0% in 1990–1995 and 1995–2000, respectively (see Figure 6). More than one decade later, it has not yet fully recovered its pre-crisis growth vitality, with the 2005–2012 average annual growth rate 2.3 percentage points lower than in the firsthalf of the 1990s. CLMV on the other hand has been the fastest growing country group in Asia.
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 5.6% to 6.2% between 2000–2005 and 2005–2012.
But, in fact, Asia29’s growth slowed significantly from a recent peak of 8.2% in 2007, to 4.9% in 2008
and further to 4.0% in 2009, before rebounding strongly to 8.0% in 2010. Growth moderated again in2011 to 5.8% and further to 5.0% in 2012, partly reflecting the retreating impact of the crisis responsein the form of fiscal stimulation. Out of the 29 countries, 11 Asian economies experienced negative
growth in 2009. Japan went through the deepest contraction of 5.7%. Of the Asian Tigers, only Korea
managed a narrow escape from recession with 0.3% growth in 2009.
It has been a subject of much debate 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) show that
East Asia has seen a marked increase in intra-regional trade, and, at the same time, diversified its

20

3.1 Economic Scale and Growth

Box 1

PPP Revisions by 2011 ICP RoundPurchasing power parities (PPPs) are indispensable inputs into economic research and policy analysis
involving cross-country comparisons of macroeconomic aggregates. They affect a double conversionof macroeconomic measures, estimated in national currencies and price levels, into comparable crosscountry volume measures. These are expressed in a common currency and at a uniform price level.

3

PPPs are price relatives that show the ratio of the prices in national currencies of a comparable basket ofgoods and services in different countries. They are compiled within the International Comparisons Program (ICP) for GDP and its main aggregates. Comparisons are made from the expenditure side of GDP. To
this end, the ICP compiles PPPs by holding worldwide surveys at regular intervals (currently, every six
years) to collect comparable price and expenditure data for the whole range of final goods and services
that make up the final expenditure on GDP. In April 2014, the new benchmark PPP estimates were published by the ICP 2011 round. For a number of methodological improvements, see Eurostat-OECD (2012) andWorld Bank (2014).

Figure B1 shows the revisions of PPPs in Asian countries atthe 2011 ICP round, in comparison with the 2005 ICP
round. The 2011 benchmark PPP for most of the Asian
countries are lower than suggested by their extrapolated
equivalents from the 2005 benchmark, with a difference
ranging from +3% for Korea to –47 % for Myanmar. With
the exception of Singapore, it is observed that revisions
for the more mature economies are much smaller (ranging within ±4%) than those for the rapidly developing
economies (with downward revisions larger than 10%).
Therefore, the impact of the PPP revisions is to raise therelative size of Asian economies, moving them closer tothe level of the more mature economies. More specifically,
the PPP revisions for India and China are –24% and –16%
respectively. As a result, the relative position of India has
improved considerably in cross-country level comparisons after PPP revisions.

−1
−4
−4
−13
−16
−16
−18
−21
−22
−23
−24
−27
−28
−28
−29
−31
−31
−34
−35
−36
−37
−39
−39
−40
−41
−45
−45
−47

−50

−40

−30

−20

−10

0

Korea
Australia
Hong KongJapan
ROC
TurkeyCambodia
Singapore
China
Iran
VietnamBangladesh
Malaysia
India
Brunei
UAE
Philippines
ThailandSri Lanka
Nepal
Pakistan
Lao PDR
Mongolia
Fiji
Saudi Arabia
Qatar
BahrainOman
KuwaitIndonesia
Myanmar

10 %Figure B1 Revisions of PPP for GDP
by 2011 ICP Round__Ratio of the 2011 ICP PPP to the 2005 ICP
PPP (extrapolated for 2011)

Source: World Bank, World Development Indicators
2014.

export markets to other parts of the world resulting in an output movement that is more idiosyncratic
than before. In turn, East Asia is 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 conduit for
financial contagion. East Asia still suffers from the flight for quality when a crisis strikes. As the im­pact of the global financial crisis was filtering through, Asia seemed immune to the adverse impacts

21©2014 Asian Productivity Organization

Chapter 3 mainly provides the cross-country comparisonof economic volumes. To obtain comparable volume measures, the Databook uses the constant PPP approach. This
creates national series for volumes at the prices of a common reference year (2012), and deflates these by the PPP
for a fixed year (one of the ICP benchmark years). This
Databook uses the new ICP 2011 estimates. It is inevitablethat they will be compared with the results of the previous
round in 2005, which has provided the benchmark estimate for the past Databook series in 2009–2013.

3
11

3 Growth of Asian Economy

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

US

TUR

AUS

UAE

SAU

QAT

KWT

OMN

BHR

THA

VIE

SIN

EU15

Group 5

Group 4
PHL

MYA

MAL

LAO

IDN

CAM

FIJ

BRN

PAK

Group 3
SRI

NEP

IRN

IND

BAN

ROC

Group 2
MGL

KOR

JPN

HKG

CHN

Group 1

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

If less than −0.55

Figure 8 Correlation of GDP Growth, 1990–2000___Correlation of GDP growth at constant market prices

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

©2014 Asian Productivity Organization

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.
Figures 8 and 9 compare the correlation coefficients of growth rates among countries in the 1990s andthe 2000s, respectively. Countries are grouped by region. Overall, the fortunes of the reference countries have become increasingly tied to Asia in a pro-cyclical manner. It is interesting to note that China’s correlation with the US and EU15 has moved from negative to moderately positive. Correlation
among the East Asian countries has strengthened over time. With the exception of China, their correlation with the US and EU15 has strengthened as well. The correlation among countries in Group 3 andtheir correlation with the US and EU15, has also grown much stronger. Therefore, comparisons of thecorrelation coefficients of growth between the two periods lend support to an increase, not a decrease, in business cycle synchronicity.

223.2 Catching Up in Per Capita GDP

US

TUR

AUS

UAE

SAU

QAT

KWT

OMN

BHR

THA

VIE

SIN

EU15

Group 5

Group 4
PHL

MYA

MAL

LAO

IDN

CAM

FIJ

BRN

PAK

Group 3
SRI

NEP

IRN

IND

BAN

ROC

Group 2
MGL

KOR

JPN

HKG

CHN

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

3

If less than −0.55

Figure 9 Correlation of GDP Growth, 2000–2012___Correlation of GDP growth at constant market prices

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

3.2 Catching Up in Per Capita GDP
2012

Others
28 %

EU27
7%

EU15
6%
US
5 % Other Asia
4%

Asia
60 %
APO20
35 %
Asia2956 %Figure 10 Share of Asian Population in
the World in 2012
Source: IMF, World Economic Outlook Database, April 2014.

23©2014 Asian Productivity Organization

Performance comparisons based on whole-economy
GDP do not take into account the population size andcan in turn exaggerate the wellbeing of countries withlarge populations. Asia is the world’s most populous
region. In 2012, it accounted for 60% 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 (China and India) are still
substantially less well-off when compared with the US
standard. Conversely, the Asian Tigers fare exceptionally well.

3 Growth of Asian Economy

Table 4 Per Capita GDP using Exchange Rate, 1970, 1990, 2000, 2010, 2011, and 2012___GDP at current market prices per person, using annual average exchange rate
1970

1990

(%)

(%)

2000

(%)

2010

(%)

2011

(%)

2012

(%)

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
0.18 9.3
0.14 6.9
0.12 5.9
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
ROC
Korea
MalaysiaFiji
IranThailandPhilippines
Indonesia
Mongolia
Sri Lanka
Pakistan
India
China
Bangladesh
Nepal
Lao PDR
Cambodia
MyanmarVietnam

25.06 100.0
13.48 53.8
12.75 50.9
8.08 32.2
6.31 25.2
2.49 10.0
1.85 7.4
1.71 6.8
1.62 6.5
0.76 3.0
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
0.25 1.0
0.21 0.8
0.20 0.8
0.13 0.5
0.10 0.4

Japan
Hong Kong
Singapore
ROC
Korea
Malaysia
Fiji
ThailandIranPhilippines
China
Sri Lanka
Indonesia
Pakistan
Mongolia
India
VietnamBangladesh
Lao PDR
Cambodia
Nepal
Myanmar37.35 100.0
25.38 67.9
23.41 62.7
14.64 39.2
11.35 30.4
4.00 10.7
2.10 5.6
2.09 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
0.42 1.1
0.37 1.0
0.32 0.9
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

45.95 100.0
43.01 93.6
31.91 69.4
20.54 44.7
18.49 40.2
8.35 18.2
6.28 13.7
5.14 11.2
4.42 9.6
3.70 8.0
3.03 6.6
2.41 5.2
2.25 4.9
2.16 4.7
1.40 3.0
1.34 2.9
1.11 2.4
1.01 2.2
0.82 1.8
0.72 1.6
0.70 1.5
0.68 1.5

SingaporeJapan
Hong Kong
Korea
ROC
Malaysia
Iran
ThailandChina
Fiji
Indonesia
Mongolia
Sri Lanka
Philippines
VietnamIndia
Lao PDR
Pakistan
Cambodia
Myanmar
Nepal
Bangladesh

52.53 100.046.32 88.2
34.46 65.6
22.39 42.6
20.03 38.1
9.60 18.3
8.48 16.1
5.55 10.6
5.43 10.3
4.28 8.1
3.56 6.8
3.13 6.0
2.85 5.4
2.38 4.5
1.56 3.0
1.53 2.9
1.28 2.4
1.19 2.3
0.92 1.8
0.92 1.8
0.79 1.5
0.72 1.4

SingaporeJapan
Hong Kong
Korea
ROC
Malaysia
Iran
China
ThailandFiji
Indonesia
Mongolia
Sri Lanka
Philippines
VietnamIndia
Lao PDR
Pakistan
Cambodia
Myanmar
Nepal
Bangladesh

53.52 100.0
46.67 87.2
35.99 67.3
22.59 42.2
20.38 38.1
9.92 18.5
8.10 15.1
6.07 11.3
5.93 11.1
4.48 8.4
3.65 6.8
3.63 6.8
2.94 5.5
2.61 4.9
1.77 3.3
1.49 2.8
1.42 2.7
1.24 2.3
0.99 1.9
0.98 1.8
0.76 1.4
0.74 1.4

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLVM
GCC(reference)USEU15

1.88 94.4
3.95 198.3
0.39 19.8
4.95 248.4
0.93 46.5
4.27 214.3
1.49 74.6

9.27 37.0
8.96 35.7
7.20 28.7
17.66 70.5
7.26 29.0
28.86 115.2
12.92 51.5

35.3
48.0
22.0
78.2
25.3
94.2
47.7

3.57 178.9
0.67 33.7

Australia
Turkey

35.27
25.32
22.02
21.36
3.94

94.4
67.8
59.0
57.2
10.5

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLVM
GCC(reference)
US
EU15
EU27
Australia
Turkey24.92 46.6
58.55 109.4
21.69 40.5
97.84 182.8
26.13 48.8
43.47 81.2
43.58 81.4

9.2
6.6
6.8
12.7
1.2
3.2
4.1
0.8
35.2

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLVM
GCC(reference)
US
EU15
EU27
Australia
Turkey24.30 46.3
53.40 101.6
21.39 40.7
93.57 178.1
24.29 46.2
40.74 77.6
43.24 82.3

3.45
2.46
2.55
4.73
0.46
1.19
1.53
0.31
13.13

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLVM
GCC(reference)
US
EU15
EU27
Australia
Turkey20.83 45.3
41.20 89.6
21.43 46.6
74.63 162.4
19.47 42.4
35.55 77.4
35.66 77.6

Australia
TurkeyBahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLVM
GCC(reference)
US
EU15
EU27
Australia
Turkey

13.17
17.94
8.21
29.20
9.44
35.20
17.81

5.06 254.0
3.54 177.4

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLVM
GCC(reference)
US
EU15

0.31
0.23
0.23
0.32
0.12
0.12
0.15
0.06
1.36

15.8
11.4
11.6
16.2
6.2
6.2
7.5
3.0
68.2

2.58
1.67
1.73
2.99
0.38
0.83
1.10
0.12
9.34

10.3
6.7
6.9
11.9
1.5
3.3
4.4
0.5
37.3

23.24
16.82

92.7
67.1

18.88
3.54

75.4
14.1

4.86
4.64
4.89
8.45
1.29
3.22
4.05
1.06
26.22

10.6
10.1
10.6
18.4
2.8
7.0
8.8
2.3
57.1

46.87 102.0
35.26 76.7
32.31 70.3
57.95 126.1
9.95 21.7

5.30
5.28
5.60
9.67
1.42
3.69
4.63
1.27
31.96

10.1
10.1
10.7
18.4
2.7
7.0
8.8
2.4
60.8

48.38 92.1
36.59 69.7
33.63 64.0
67.84 129.1
10.41 19.8

5.31
5.51
5.86
10.25
1.40
3.87
4.82
1.41
34.27

9.9
10.3
11.0
19.2
2.6
7.2
9.0
2.6
64.0

50.25 93.9
37.14 69.4
34.31 64.1
68.57 128.1
10.46 19.6

©2014 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.

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 comparisonsamong the Asian Tigers. Singapore and Hong Kong have been moving closely with one another for24

3.2 Catching Up in Per Capita GDP

In terms of per capita GDP at constant prices using PPP, Japan was the first country in Asia tostart catching up with the US. By 1970, its per
capita GDP was 60% of the US, quite a distanceahead of other Asian countries. Japan had beenclosing the gap with the US steadily until 1991(84%), but the gap widened again when the impact of the long recession of the 1990s started tomanifest itself.14 In recent years, Japan’s level has
stabilized to around 70–73% of the US (Figure 13).

US=100 in each year

160
140

Japan
120
100
80
60

Australia

40
201970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 11 Per Capita GDP using Exchange
Rate of Japan and Australia, Relative to theUS, 1970–2012___GDP at current market prices per person, using
annual average exchange rate, relative to the US
Sources: Official national accounts in each country, including author adjustments.

US=100 in each year

120
100

US
Singapore

80
60

Hong Kong

40
20

Japan’s per capita GDP was the highest among
Asian countries until it was overtaken by Singapore15 in 1980.16 The result highlights the outcome of the dramatic development effort madeby the Asian Tigers, as shown in Figure 14. Not
only were they inching to the top, they wereconstantly closing the gap with the US. Startingfrom a level of 42% the US in 1970, Singapore
surpassed the US in 1992.17 In 2012, Singapore

3

US

ROC

Korea

0
1970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 12 Per Capita GDP using Exchange
Rate of the Asian Tigers, Relative to the US,
1970–2012___GDP at current market prices per person, using
annual average exchange rate, relative to the US
Sources: Official national accounts in each country, including author adjustments.

14: Jorgenson and Nomura (2007) indicated that the manufacturing sector was the main contributor to the catching-up process of
the Japanese economy in the 1960s, and that, by 1990, the US–Japan TFP gap for the manufacturing sector had almost disappeared.
15: 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%.
16: Among the mature economies in Asia, Singapore is a unique country, in which the PPP was downwardly revised from the 2005
ICP to the 2011 ICP (Box 1). This shift has the significant effect of bringing forward the year when Singapore overtook Japan (or US)
in relative per capita GDP to 1980 (1992 for the US), from 1993 (2004 for the US) as estimated in the Databook 2013. Although thisDatabook follows the 2011 ICP results, it may require a further examination if this can provide an appropriate picture, especially for
Singapore.

25©2014 Asian Productivity Organization

three and a half decades until the mid-2000s,
when Singapore sprinted ahead of Hong Kong.
Hong Kong’s per capita GDP peaked in 1997, theyear when Hong Kong was returned to China,
and subsequently plummeted until 2004. Singapore followed a similar path: peaking in 1996,
and falling to an all-time low in 2002 before thesurge of recent years. The ROC and Korea moved
together but at a lower level than Singapore andHong Kong. Similarly, Korea’s income level
peaked in 1996; but with lows short lived compared to Hong Kong or Singapore. In Asia, Japanand Singapore are the two countries that haveincome levels almost equivalent to the US. However, this view is considerably revised if focusing
on production or real income per capita, using
PPP as the conversion rates (Table 5).

3 Growth of Asian Economy

Table 5 Per Capita GDP, 1970, 1990, 2000, 2010, 2011, and 2012___GDP at constant market prices per person, using 2011 PPP, reference year 2012
1970
Japan
Iran
Singapore
Hong Kong
ROC
Fiji
Malaysia
Philippines
Thailand
Korea
Mongolia
Sri Lanka
PakistanIndonesia
India
Bangladesh
Vietnam
Myanmar
China

Bahrain36.3 251.4
Kuwait198.1 1371.0
Oman
15.0 103.8
Qatar
164.4 1137.8
Saudi Arabia 42.6 295.0
42.0 290.8
UAE
84.6 585.5
Brunei(regrouped)
3.1 21.6
APO20
2.0 14.1
Asia23
2.3 15.6
Asia292.3 15.7
East Asia
1.4
9.4
South Asia
2.1 14.2
ASEAN
2.5 17.5
ASEAN60.9
6.2
CLVM
60.9 421.6
GCC(reference)
24.0 166.0
US
17.4 120.3
EU15Australia
Turkey1990(%)

14.4 100.0
10.4 72.0
10.2 70.5
8.6 59.4
4.3 29.5
4.2 28.8
4.0 27.8
3.0 20.7
2.7 18.6
2.6 18.0
2.3 15.9
1.9 12.9
1.8 12.6
1.6 11.3
1.2
8.5
1.1
7.4
1.0
6.6
0.6
4.4
0.5
3.2

22.0 152.2
6.7 46.1

SingaporeJapan
Hong Kong
ROC
Korea
Malaysia
Iran
ThailandFiji
Indonesia
Mongolia
Philippines
Sri Lanka
PakistanIndia
Lao PDR
China
Nepal
VietnamBangladesh
Cambodia
Myanmar(%)

34.8 100.0
29.7 85.3
27.0 77.8
16.2 46.7
11.7 33.7
9.8 28.1
9.7 27.9
6.9 19.8
5.9 16.8
4.4 12.6
4.2 12.1
3.9 11.1
3.4 9.7
2.9 8.2
1.8 5.3
1.6 4.7
1.5 4.3
1.4 4.1
1.4 4.0
1.1 3.1
1.0 2.8
0.7 2.1

37.0 106.6
Bahrain
42.8 123.1
Kuwait39.2 112.7
Oman
85.8 246.8
Qatar
Saudi Arabia 37.9 109.2
115.9 333.6
UAE
80.4 231.5
Brunei(regrouped)
5.3 15.3
APO20
3.8 11.0
Asia23
4.2 12.0
Asia294.9 14.2
East Asia
2.0 5.7
South Asia
4.4 12.6
ASEAN
5.6 16.1
ASEAN6
1.2 3.5
CLVM
46.8 134.6
GCC(reference)
37.1 106.7
US28.2 81.1
EU15
Australia
Turkey

29.4
10.4

84.6
29.9

2000
Singapore
Hong Kong
Japan
ROC
Korea
Malaysia
Iran
ThailandFiji
Indonesia
Sri Lanka
Philippines
Mongolia
China
Pakistan
India
VietnamLao PDR
Nepal
Bangladesh
Cambodia
Myanmar(%)

52.4 100.0
34.0 64.8
32.8 62.6
27.2 51.9
20.1 38.3
15.1 28.9
12.3 23.4
9.7 18.4
6.8 13.0
5.8 11.1
5.0 9.6
4.4 8.3
4.0 7.6
3.7 7.0
3.4 6.5
2.6 5.0
2.5 4.8
2.4 4.5
1.9 3.5
1.5 2.9
1.4 2.7
1.2 2.2

Bahrain
45.9 87.5
Kuwait74.9 142.9
42.5 81.0
Oman
112.2 213.9
Qatar
Saudi Arabia 40.0 76.3
112.6 214.7
UAE
78.3 149.4
Brunei(regrouped)
6.5 12.3
APO20
5.4 10.3
Asia23
5.8 11.1
Asia297.4 14.0
East Asia
2.7 5.1
South Asia
5.9 11.3
ASEAN
7.4 14.1
ASEAN6
2.0 3.9
CLVM
53.0 101.0
GCC(reference)
45.8 87.4
US
34.3 65.5
EU15EU27
30.4 58.1
37.3 71.1
Australia
12.4 23.7
Turkey2010
Singapore
Hong Kong
ROC
Japan
Korea
Malaysia
Iran
ThailandChina
Indonesia
Sri Lanka
Fiji
Mongolia
Philippines
India
Vietnam
Pakistan
Lao PDR
MyanmarCambodia
Nepal
Bangladesh(%)

72.6 100.0
47.9 66.0
38.2 52.6
35.1 48.3
28.7 39.5
19.8 27.2
19.4 26.7
13.9 19.1
9.4 12.9
8.4 11.5
7.7 10.7
7.3 10.1
6.5 8.9
5.8 7.9
4.7 6.4
4.6 6.3
4.3 5.9
4.0 5.5
3.0 4.2
2.7 3.7
2.3 3.2
2.2 3.1

Bahrain
41.8 57.6
Kuwait81.5 112.2
51.3 70.7
Oman
138.4 190.5
Qatar
Saudi Arabia 47.3 65.1
60.7 83.6
UAE
75.8 104.4
Brunei(regrouped)
8.6 11.8APO20
8.8 12.1
Asia23
9.3 12.8
Asia2912.7 17.6
East Asia
4.4 6.1
South Asia
8.5 11.7
ASEAN
10.3 14.1
ASEAN6
3.9 5.3
CLVM
55.9 77.0
GCC(reference)
48.7 67.1
US
36.8 50.7
EU15
EU27
33.8 46.5
43.4 59.7
Australia
16.7 23.1
Turkey2011
Singapore
Hong Kong
ROC
Japan
Korea
Malaysia
Iran
ThailandChina
Indonesia
Sri Lanka
Mongolia
Fiji
Philippines
Vietnam
India
Pakistan
Lao PDR
MyanmarCambodia
Nepal
Bangladesh(%)

75.4 100.0
50.0 66.3
39.7 52.7
35.0 46.4
29.5 39.2
20.5 27.2
19.7 26.1
13.9 18.5
10.2 13.5
8.8 11.7
8.3 11.0
7.5 9.9
7.5 9.9
5.9 7.8
4.8 6.4
4.8 6.4
4.3 5.7
4.3 5.6
3.2 4.2
2.8 3.8
2.4 3.2
2.4 3.1

Bahrain44.1 58.5
Kuwait87.2 115.6
43.7 57.9
Oman
143.2 190.0
Qatar
Saudi Arabia 50.4 66.9
59.8 79.3
UAE
77.1 102.3
Brunei(regrouped)
8.7 11.5
APO20
9.1 12.1
Asia23
9.7 12.9
Asia2913.5 17.9
East Asia
4.5 6.0
South Asia
8.8 11.6
ASEAN
10.6 14.1
ASEAN6
4.1 5.4
CLVM
57.9 76.7
GCC(reference)
49.2 65.3
US37.2 49.4
EU15
EU27
34.2 45.4
44.3 58.7
Australia
18.0 23.8
Turkey2012
Singapore
Hong Kong
ROC
Japan
Korea
Malaysia
Iran
ThailandChina
Indonesia
Sri Lanka
Mongolia
Fiji
Philippines
VietnamIndia
Lao PDR
Pakistan
MyanmarCambodia
Nepal
Bangladesh(%)

75.0 100.0
50.1 66.9
40.2 53.6
35.6 47.5
30.0 40.0
21.2 28.3
18.3 24.4
14.9 19.8
10.9 14.6
9.3 12.3
9.1 12.1
8.3 11.1
7.6 10.1
6.2 8.2
5.0 6.7
5.0 6.7
4.5 6.0
4.4 5.9
3.4 4.5
3.0 4.0
2.5 3.3
2.5 3.3

Bahrain44.7 59.7
Kuwait90.7 121.0
Oman
42.0 56.1
Qatar
141.8 189.2
Saudi Arabia 52.4 69.9
60.6 80.8
UAE
76.6 102.2
Brunei(regrouped)
8.9 11.8
APO20
9.5 12.7
Asia2310.1 13.5
Asia2914.1 18.9
East Asia
4.7 6.3
South Asia
9.2 12.2
ASEAN
11.1 14.8
ASEAN6
4.2 5.7
CLVM
59.3 79.1
GCC(reference)
50.3 67.0
US36.8 49.1
EU15
EU27
34.0 45.4
44.7 59.6
Australia
18.1 24.2
Turkey©2014 Asian Productivity Organization

Unit: Thousands of US dollars (as of 2012)
Sources: Official national accounts in each country, including author adjustments.
Note: See Appendix 1 for the adjustments made to harmonize GDP coverage across countries.

had a per capita GDP which was 49% above the US. It became the richest economy in Asia, representing a remarkable achievement. Hong Kong holds second place, with a per capita GDP similar to the
US. Japan’s per capita GDP, at 71% of the US, or around 47% of the group leader (Singapore), is simi17: 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.

26

3.2 Catching Up in Per Capita GDP

US=100 in each year

100
90
80

Australia

US=100 in each year

160
140

Singapore

120

EU15

100

HongKong

80

70
60

3

US

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, 1970–2012___GDP at current market prices per person, using

ROC

20

Korea

0

1970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 14 Per Capita GDP of the Asian Tigers,
Relative to the US, 1970–2012

2011 PPP, relative to the US___Ratio of per capita GDP at constant market prices,using 2011 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.

lar to the EU15. The ROC and Korea trail behind the other two Asian Tigers at 80% and 60% of theUS, respectively.
The relative performance of China and India, the two most populous countries in the world, is diminished in this measure due to their population, with their per capita GDP at 21.7% and 9.9% of the US
in 2012, respectively (Figure 15). However, this should not taint the remarkable progress made overthe past decades, especially of China, with a per capita GDP was less than 2% of the US in 1970. China’s
relative per capita GDP has increased tenfold in four decades. The income gap between the US andthe majority of Asian countries is still sizable,18
indicating significant opportunity for catch up.
US=100 in each year
24
20
16
12
ASEAN

8
4

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, 1970–2012___Ratio of per capita GDP at constant market prices,using 2011 PPP, relative to the US
Sources: Official national accounts in each country, including author adjustments.

18: 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 morethan 30% higher than GDP in the 2010s (Figure 86 in Chapter 7).

27©2014 Asian Productivity Organization

Table 5 presents individual figures for seven oilrich economies (Brunei and the six GCC countries). At first glance, figures in 1970, and to alesser extent in 1990, suggest these economies
enjoyed an income many times that of Japanand the US. For example, in 1970, Kuwait, Qatar,and Brunei had a per capita GDP 13.7 times, 11.4
times, and 5.9 times that of Japan, respectively.
However, the measurement of GDP as an indi­cator of production is misleading for thesecountries, as it erroneously includes proceedsfrom the liquidation of a natural resource stock
as part of the income flow. In other words, GDPoverestimates income from the oil-exporting
economies, because it does not account for3 Growth of Asian Economy

depletion of their natural resource assets. To
give a rough indication of the extent of distortion, Figure 16 provides comparisons of percapita GDP excluding production of the mining
sector (i.e., crude oil, natural gas, and so on). The
non-mining GDP per person in Brunei and GCC
economies, such as the UAE, Bahrain, and Kuwait, is almost similar to Japan’s level, although
total GDP per capita is much larger.

Qatar

62.4

Brunei

40.9

UAE

34.9

25.7

Japan

33.8

1.8 35.6

Bahrain

33.0

11.8 44.7

Kuwait32.2

Saudi Arabia

26.2

Oman

21.6

Malaysia

76.6
60.6

58.5
26.2
20.4

90.7

52.4

Non-mining
Non-mining
GDP

42.0

Mining GDP

17.5 3.7 21.2

Thousands of US dollars (as of 2012)

Iran 15.3 3.1 18.3
0

30

141.8

79.4

35.7

60

90

120

150

Catching up with the per capita GDP level of advanced economies is a long-term process that
Figure 16 Per Capita Non-Mining GDP in Oilcould take several decades to accomplish. EmRich Countries and Japan, 2012___GDP at constant market prices per person, using
pirical evidence suggests there may be a nega2011 PPP, reference year 2012
tive correlation between per capita GDP level
and the speed of catching up, although with
Sources: Official national accounts in each country, including author adjustments.
exceptions. With the possibility of adopting successful practices and technologies from themore 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 those of the more advanced countries,
their economic growth rates are expected to gradually decline over time.19
Figure 17 plots countries’ initial per capita GDP levels against their respective average growth rates
per year between 1970 (or the initial year data first became available for the country in question) and2012. If the two variables have a correlation coefficient of –0.5 (i.e., a negative relationship of medium
strength), the higher the initial income level, the slower the average growth rate per year is expected.
However, this is not always true. Low-income countries like Nepal, Bangladesh, the Philippines, and Fiji
have failed to catch up, while Thailand and Malaysia could be expected to have grown even fastergiven their initial income levels. The Asian Tigers have enjoyed 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 the start of thecatch-up process. Mature economies like the US, EU15, and Japan shared similar growth experiences(around 2% on average per year, in the past four decades).

©2014 Asian Productivity Organization

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%; GroupL3, 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%
to under 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
each country and the US. Table 6 shows that many Asian countries (not belonging to Group-C4) havemanaged to close the gap in per capita real GDP with the US over the last four decades, althoughsome are more successful than others.

19: The OECD (2013) 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.

28

3.2 Catching Up in Per Capita GDP% Growth rate of per capita GDP during 1970–2012%

5=1970,

Cambodia

6

Sri Lanka
India
3=1970,=1990, =20127

Vietnam

MyanmarGrowth rate of per capita GDP during 1970–2012

China

Indonesia

Lao PDR

4

8=1990, =2012

3

Korea
ROC

5

Singapore

Mongolia

Nepal

2

Bangladesh

Hong Kong

Thailand
Malaysia

4
Pakistan
3

Philippines

Japan

Turkey

Fiji

2

EU15

1

US

Australia

Iran
1
Thousands of US dollars (as of 2012)

Thousands of US dollars (as of 2012)

0

0
0

2

4

6

8

10

Per capita GDP at constant prices

0

10

20

30

40

50

60

70

80

Per capita GDP at constant prices

Figure 17 Initial Level and Growth of Per Capita GDP, 1970–2012___Level and average annual growth rate of GDP at constant market prices, using 2011 PPP, reference year 2012

Table 6 Country Groups Based on the Initial Economic
From Table 6 one can see the initial
Level and the Pace of Catching Up
economic level does not fully ex___Level and average annual growth rate of GDP at constant market
plain the catch-up process. If it did,prices, using 2011 PPP
the table would have been popuAnnual rate of catch-up to the US
Initial GDP
lated diagonally from the bottom
level
(C2)
(C3)
(C4)
(C1)
left corner to top right corner. Of
to the US
1% <–< 3%
0% <–< 1%< 0%> 3%
the Asia29 countries, five achieved
Brunei, Bahrain,
Japan, EU15,
Kuwait, Qatar,(L1)
a very fast catch-up (over 3% per
Oman
Saudi Arabia, UAE,
60% <year on average) between the reAustralia
spective starting years of their data
(L2)
Singapore
Hong Kong
TurkeyIran
20% <–< 60%series and 2012. Their initial per
capita GDP level classifies them
Malaysia, Mongolia,(L3)Fiji, Philippines
ROC, Korea
Thailand8% <–< 20%
into the three group: Singapore
India, Indonesia,
from Group-L2, the ROC and Korea
Bangladesh, Nepal,(L4)
Cambodia, China Lao PDR, Myanmar,
Pakistan< 8%from Group-L3, and Cambodia and
Sri Lanka,Vietnam
China from Group-L4. Eleven counSources: Official national accounts in each country, including author adjustments.
tries in Group-C4 experienced deNote: The annual catch-up rates are based on the difference in the growths of percapita GDP at constant prices between each country and the US during 1970–2012.
terioration in their relative income
The starting years for some countries are different due to data availability: Cambolevel against the US with lowdia (1987–), the Lao PDR (1984–), and Nepal (1974–).
income countries like Fiji and thePhilippines failing to take off. The
seven high-income countries in Group-C4 are all GCC countries except Australia. It is worth notingthat GCC countries had an exceptionally high GDP (a distortion, as aforementioned) at the beginningof the period. Japan was the only Asian non-oil-exporting country with a high-income level in 1970.
But, like EU15, it has since failed to achieve further parity with the US.

29©2014 Asian Productivity Organization

Sources: Official national accounts in each country, including author adjustments.
Note: The starting periods for Nepal, the Lao PDR, and Cambodia are 1974, 1984, and 1987, respectively.

3 Growth of Asian Economy

3.3 Sources of Per Capita GDP Gap©2014 Asian Productivity Organization

Figure 19 focuses on explaining a country’s per capita GDP
growth by its components: name­ly labor productivity growth
and the change in the employment rate for the periods
1990–2000 and 2000–2012, respectively.22 For most countries
in Asia, the per capita GDP
growth can be explained by
improvement in labor productivity. However, this should
not lead us to underestimate
the role of changes in the%

Bangladesh
Nepal
Cambodia
Myanmar
CLMV
Pakistan
Lao PDRSouth Asia
India
VietnamPhilippinesFiji
Mongolia
APO20
Sri Lanka
ASEAN
Indonesia
Asia23
Asia29China
ASEAN6
East Asia
ThailandTurkeyIranMalaysia
Korea
Japan
EU15
ROC
Australia
Hong Kong
Singapore

MyanmarBangladesh
CLMV
Vietnam
Nepal
China
Lao PDR
India
South Asia
Pakistan
Sri Lanka
Asia23
Philippines
Asia29Mongolia
ASEAN
Indonesia
East Asia
APO20
ASEAN6Fiji
ThailandIran
Malaysia
TurkeyKorea
ROC
Hong Kong
EU15
Australia
Japan
SingaporeTo further understand the diverse performance in the Asian group, per capita GDP can be broken into
two components: labor productivity (defined here as real GDP per worker) and the corresponding labor utilization rate (number of workers to population ratio, or employment rate used in this report).20
Figure 18 shows the percentage point differences in per capita GDP decomposed into the contributions by the labor productivity gap and the employment rate gap, relative to the US in 1990 and2012.21 Most of the Asian countries display a huge per capita GDP gap with the US, predominantly
explained by their relative labor productivity performance. With the exception of the Asian Tigers,
Japan, and Iran, all the other Asian countries had labor productivity gaps of more than 50% against
the US in 2012. At the top end of performance, estimates show Singapore was 16% above while Hong
Kong was 7% below the US labor productivity level. The la1990
bor productivity gaps of theother two Asian Tigers are stillsizable against the US, at 19%%20
and 44% for the ROC and
5
4
3
2
0
−11−12−22 −6−21Korea, respectively. In most
0
−30
−9
−13
−41
−20
−7
−49
−56
−57
countries, the effect of the em−64−70−70 −77 −77−72−77−81−40−86−84−82−85 −84 −81−79−90−15−96 −92−93−89−99−93−44
ployment rate is to widen the−23−60−18 −11per capita GDP gap. However, in−21−14 −8−80−22−21 −13 −12 −7 −9
−5
−5
−13
−16
−5 −3 −7
−3 −11
recent years more Asian coun−2−100tries have employment rate
higher than the US, with the ef2012
fect of narrowing the gap.
40
33

20

1 9 1 5

0
−20
−40
−60
−80
−100

3

1

8

9 13

9

7 7 16
−18
−22
−19
−7
−29
−35
−41
−52−44 −5 −1
3 6−73−72 −69−75−76 −83−80−81−79−88−77−81−83−83−83 −80−88−35−96−103−94−97 −94−98−23 −6

−7

−17

−8 −7

−11 −6 −13−8 −12

Employment rate

−2

0

0

−1

Labor productivity

Per capita GDP

Figure 18 Labor Productivity and Employment Rate Gap
Relative to the US, 1990 and 2012___Decomposition of per capita GDP gap at constant market prices, using
2011 PPP

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

20: 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. 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.
21: 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 ) − In (GDPUSt / POPUSt ) = In (GDPxt / EMPxt ) − In (GDPUSt / EMPUSt ) + In (EMPxt / POPxt ) − In (EMPUSt / POPUSt )Gap of per capita GDP

Gap of labor productivity

Gap of employment rate

where POPxt is population of country x­in period t and EMPxt is the number of employment of country x in period t.

30

3.3 Sources of Per Capita GDP Gap%

10

1990–2000

8
6

0.7

4 8.9

0.6

5.4 4.8

2

1.4

3.8

0.5 0.5
0.8 0.7
4.7 4.4

0.2
1.1

3.7 3.7 3.9

2.9

0.1 0.2

0.5 0.2
1.1

3.9 3.6

3.0 3.3 2.30

0.2 0.5
4.3

3.2 2.6

3

0.5 0.1
0.7

0.5

2.5 2.7 2.1 2.0

1.3
1.1

−0.9

0.3 0.1 0.3

0.1 0.4

2.1 2.2 1.9 1.8 1.5 1.9 2.4 1.1
1.3 1.4
0.4
1.1 0.6−0.1 −0.6−0.2−0.1−1.1−2Mongolia
Japan
Philippines
GCC
Fiji
TurkeyPakistan
APO20
EU15
US
Hong Kong
Australia
Iran
Nepal
Indonesia
ASEAN6ASEAN
South Asia
Asia29ThailandBangladesh
Asia23India
Lao PDR
East Asia
Sri Lanka
Singapore
Malaysia
Cambodia
Myanmar
ROC
CLMV
Korea
Vietnam
China
%

10

2000–2012

8
6
4

0.9
9.1 8.9
5.3

20

1.8 0.8 1.3

0.4

5.3

5.5 5.0

4.4

4.4

0.7 0.7 0.2

0.6

0.2

0.4
1.6

4.6 4.2 4.5 4.1 4.4

2.5

0.6 1.1 0.6
3.5 3.0

0.8

0.4

0.5 0.7

0.3

2.5 2.8 2.6 3.0 2.7 2.5 2.9

1.4 0.7 0.7 0.5

1.3 0.9
1.7
1.6 2.2 2.1 2.1 1.2 1.1 0.6
0.9
−0.8

−0.1

1.6
0.9 0.6−0.8−0.2

0.9

−2
EU15
Japan
US
Fiji
GCC
Australia
Pakistan
Nepal
APO20
Malaysia
Philippines
Singapore
TurkeyROC
Hong Kong
Iran
Korea
ASEAN6
Thailand
ASEAN
Indonesia
Bangladesh
Asia29South Asia
Asia23
Sri Lanka
Lao PDR
India
East Asia
VietnamMongolia
Cambodia
CLMV
MyanmarChina

employment rate. On average,
Asia29’s per capita GDP grew by
3.4% per year between 1990 and
2000, and accelerated to 4.6%
per year between 2000 and 2012.
The earlier period captured thedampening effect of the Asianfinancial crisis of the late 1990s.
Emerging from the crisis, bothlabor productivity growth andemployment growth strengthen­ed. For most countries, labor productivity explains a larger shareof per capita GDP growth thanemployment. Additionally, theemployment rate contribution
relative to labor productivity was
also highly significant in countries such as, Nepal (over 50%),
Pakistan (45%), Bangladesh (40%),
and Cambodia and Thailand(around 30%).

Employment rate

Labor productivity

Per capita GDP

22: 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 x­in period t and EMPxt is the number of
Per capita GDP

Labor productivity

Employment rate

employment of country x­in period t.
23: The author would caution readers as to the reliability and quality of Myanmar’s official statistics (especially a decade from the late
1990s, based on our observations), which have been questioned. Researchers have suggested that this is not consistent withother variables closely correlated with GDP, such as energy use. Non-official 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.

31©2014 Asian Productivity Organization

Figure 19 Sources of Per Capita GDP Growth, 1990–2000
China’s improvement was theand 2000–2012
most impressive, achieving per___Decomposition of average annual growth rate of per capita GDP atcapita GDP growth of 8.9% andconstant market prices, using 2011 PPP
9.1% per year on average in the
Sources: Official national accounts in each country, including author adjustments.
two periods, respectively. ImNote: The starting period for Cambodia are 1993.
provement in labor productivity
explains almost all of that growth.
According to official statistics,23 Myanmar achieved a similar performance to China in growth terms,
with per capita GDP growth of 4.9% and 8.8% per year on average in the two periods. However, thisgrowth was from a very low base; even in 2012, Myanmar’s per capita GDP was only 30% of China’s(see Table 5). Like China, Myanmar’s per capita GDP growth has been predominantly explained bylabor productivity. In both periods Japan had a deteriorating employment rate. With an aging population (see Box 2), this pattern may well continue. To sustain per capita GDP growth, China’s labor productivity growth will have to accelerate to counteract the negative effect of its employment rate. The
US also experienced deteriorating employment rate in the recent period, which was a drag on percapita GDP growth. In contrast, falling labor productivity was the drag in GCC countries.

3 Growth of Asian Economy

Most countries also have an employment rate shortof the US level. In the case of Iran, Turkey, and Pakistan, the employment rate is significantly less thanthe US, further reinforcing the poor productivity
performances of these countries (Figure 18). It is no
coincidence they are among the countries with thelowest shares of female workers in employment, at
17%, 29% and 20%, respectively (Figure 20). In contrast, a handful of countries such as Cambodia, China, and Thailand, had higher employment rates
than the US, counteracting the negative impact of
their productivity performances. In Singapore, thepositive gap in employment rate further reinforced
the already impressive relative labor productivity
performance, pulling ahead of the US in per capita
GDP. More specifically, Singapore’s labor productivity was 16 percentage points higher than the US
level, but its employment rate was 33 percentage
points higher, giving an overall per capita GDP
which was 49% higher than the US.

Figure 21 shows cross-country com­
parisons of employment rates in
2012, based on the labor statistics
of each country. Employment consists of employees, own-accountworkers, and contributing family
workers. Singapore and Cambodia
lead the Asian group with em­
ployment rates of over 60%, around
14 and 17 percentage points

32

33
33
32
29
26
21
20
19
17
17
13
13
12

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.

%

65
60
55
50
45
40
35
30
25

2012

1990

1970

20
Singapore
Cambodia
Thailand
VietnamChina
Lao PDR
Hong Kong
Australia
Japan
Korea
Nepal
Myanmar
US
Brunei
ROC
Indonesia
EU15
Malaysia
India
Philippines
Bangladesh
MongoliaFiji
Sri Lanka
TurkeyPakistan
Iran©2014 Asian Productivity Organization

All other things being equal, increasing employment and im­proving labor productivity could
present a policy trade-off in the
short term, as they cannot be
achieved simultaneously. If thepolicy target is to increase employment, productivity may suffer
in the short term as marginal andless-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 beconsidered in the context of thegenerally high employment rate in
Asia.

50
49
48
48
48
48
47
46
46
46
46
45
44
43
42
42
41
39
38
36

Lao PDR (2005)
Cambodia (2012)
Vietnam (2012)
Hong Kong (2012)
Mongolia (2012)
Canada (2012)
US (2012)
Nepal (2008)
Thailand (2012)
Australia (2012)
EU27 (2012)
China (2010)
Singapore (2012)
ROC (2008)
Japan (2012)
Korea (2012)
Brunei (2011)
Philippines (2012)
Indonesia (2012)
Malaysia (2012)
Kuwait (2011)
Sri Lanka (2012)
Fiji (2007)
Turkey (2012)
India (2010)
Bahrain (2012)
Pakistan (2008)
UAE (2008)
Oman (2010)
Iran (2010)
Bangladesh (2011)
Saudi Arabia (2012)
Qatar (2012)

Figure 21 Employment Rates, 1970, 1990, and 2012___Ratio of employment to total population

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

3.3 Sources of Per Capita GDP Gaphigher than the US and EU15, respectively, in 2012. It is clear that employment rates have been risingin Asia.24 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: China, Korea, Cambodia and the ROC. However, China seems to have exhausted its capacity for further improvement as its employment ratechanged little between 1990 and 2012 at 57%. Some of the countries in Group C2 also experienced
significant improvements in employment rates (for example, Indonesia and Vietnam). While there are
exceptions, generally 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.

33©2014 Asian Productivity Organization

24: Japan is the only exception where the employment rate in 2012 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 2012 lower than that in 1990 (i.e.,
47% compared with 51%).

3

3 Growth of Asian Economy

Population and Demographic Dividend

Box 2

According to the United Nations (UN) (2013), the world’s population is estimated to reach 7.1 billion in2012, of which Asian countries account for 60.1%. The region is by far the most populous in the world.
China and India account for 19.4% and 17.5% 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 supply-side and demand-side impacts.
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 5.0 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 6.0 children to 1.6 (below the replacement level), in East Asia. In comparison, some parts of Africa have seen onlya modest drop in total fertility, which today remains at more than five children per woman. What is evenmore staggering is the pace of change. For example, it took Britain over 130 years (1800–1930) to halve its
fertility rate, while it took Korea only 20 years to achieve it. This is echoed around the world. This widespread social revolution has been heralded by a complex mix of economic and social development.
Economic growth, greater access for 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, bringing with it
economic implications.
The growth rate of the world’s population has slowed from its peak of around 2.00% in the 1970s to today’s
1.20% per year. With falling fertility rates, the UN projects the world’s population growth rate will decelerate to 0.49% per year by 2050 and further to 0.09% by 2100. Even so, the world population will still increaseby one-third in the next 40 years, from 6.9 billion to 9.5 billion and a further 13% to 10.8 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 (10.9 billion by 2050 and 16.6 billion in2100) or lower (8.3 billion in 2050 and 6.8 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 share from the more developed regions gradually

BillionLeast developed countries
Less developed regions, excluding
least developed countries
More developed regions
1.2

10
8

0.3

4
0.2

©2014 Asian Productivity Organization

0

2.9

Billion

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

1.8

8

0.7

6

2

2.4

6
5.6

6.4

6.7

6.6

4

4.3
2.7

2

1.5
0.8

1.0

1.2

1950

1975

2000

1.3

1.3

1.3

1.3

2025

2050

2075

2100

0

0.5
0.5

1950

0.3
0.7
0.4
0.5
0.3
0.9

0.5
0.8

0.4
0.8

0.7

0.5
0.7
0.6

0.7
3.4

2.3

4.2

0.8

1.2

1.4

1.4

0.9
0.5

0.7

0.8

0.8

1.4

1.4

1.2

1.1

1.6

1.6

1.5

2050

2075

2100

1.3

0.6

1.0

1.4

1975

2000

2025

1.3
0.7

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 2012 Revision.
continued on next page >34

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

1970

2050

1400
1200
1000
800

3

600
400
scale by 50 millions

350
300
250
200
150
100
50
30

scale by 5 millions

25
20
15
10
5
0

Figure B2.2 Asian Countries’ Population Size and Projection,
1970, 2012, and 2050
Source: World Bank, World Development Indicators 2013.

18.9
19.5

30.6

24.9
22.9
26.3

34.1

40 %

30

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

11.4
15.1
14.6
16.5
18.5
16.5

23.4

26.4
28.9
29.4
29.3
30.6
33.1
32.0
34.3
27.0
37.2
24.9
29.7
24.2
24.9
20.2

Ages 0–14

13.0

20

13.2
14.0

10

0

24.1

14.2
13.7
13.7
11.7
11.2
9.7
9.4
9.4
7.5
6.6
6.5
6.1
5.8
5.3
5.3
5.2
5.2
5.1
4.7
4.5
4.4
4.4
3.8
3.7
3.7
2.9
2.8
2.2
2.1
0.7
0.3

0

5

10

15

20

25 %

Ages over 65

Figure B2.3 Proportion of the Dependent Population, 2012
Sources: Population census and official national accounts in each country.

continued on next page >35©2014 Asian Productivity Organization

Figure B2.3 shows the demographic make-up of countries in2012 (the population proportions of the under-15 and over65 age groups, which together
make up the dependent population). Ranking the countries by
the share of old-age population,filters the rich economies to the
top end. These economies also
have a relatively low share of theyoung age group compared toless developed countries. Thissuggests that demographic transition tends to run parallel witheconomic progress, although
the direction of causation is notcertain. As countries move fromhigh to low mortality and fertility
rates, the demographic transition produces a “boom” generation that is larger than those
immediately before and after it.

2012

1600

BruneiFiji
Bahrain
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’s share will decline from its
60.2% today to 54.1% in 2050
and 43.4% in 2100, while Africa’s
share will rise from today’s 14.9%
to 25.1% and 38.6%, respectively. Figure B2.2 shows the current
population size of individual
Asian countries compared withthe 1970 level and its 2050 projection. As can be seen from thechart, China’s population is expected to more or less stabilize
around the current level. China
has socially engineered thechange with its one-child policy,
which has made its current population 300–400 million lower
than it would have been otherwise. In less than two decades,
India is projected to overtake
China as the most populous
country in the world.

Millionscale by 200 millions

declining from 17.9% to 13.6% in
2050 and 11.8% in 2100, compared with 32.2% in 1950. Conversely, the share of the least
developed countries is depicted
as rising from today’s 12.1% to a
projected 19.0% in 2050 and
27.0% in 2100, up from 7.7%
in 1950.

3 Growth of Asian Economy> continued from previous pageAs this boom generation gradually works through a nation’s age structure, it produces a demographic
dividend of economic growth as people reach their prime.

©2014 Asian Productivity Organization

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 until the 2040s. The reaping of this dividend,
however, is far from automatic. A
favorable demography can work
wonders to produce a virtuous cycle
Dependent population (aged under 14 and over 65)=1.0
Hong Kongof wealth creation only if it is com3.0
Japan
bined with appropriate health, labor,
Korea
2.5
Singaporefinancial, human capital, and growthUS
enhancing economic policies. The
2.0
presence of these complementary
1.5
factors cannot be taken for granted,
but needs to be cultivated in order to
1.01950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
earn the demographic dividend. As
the analysis of the Databook show,
Dependent population (aged under 14 and over 65)=1.0
the contribution of labor to economChina
3.0
India
ic growth has been smaller thanIndonesia
2.5
those of capital and TFP for mostThailandAustralia
countries (Figure 52, p.71). This
2.0
means that countries should not be
1.5
afraid of aging too much as long as
fairly high growth rates of capital and
1.0
TFP are maintained. Nevertheless,1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
understanding the demographic
shift and its implications is highly
Figure B2.4 Demographic Dividend, 1950–2100
relevant for economic projections,providing valuable foresight for ecoSource: UN (Department of Economic and Social Affairs), World Population Prospects: The 2012 Revision.
nomic policy making.

36

4.1 Composition of Final Demand

4 Expenditure
In national accounts, GDP is measured by three approaches: production by industry; expenditure on
final demand; and income to factor inputs. In theory, these three approaches are accounting identities, and should yield the same result, but in reality, they differ by statistical discrepancies. Decompositions of GDP are valuable in understanding the structure, and in turn the behavior, of an economy. In
this chapter, the economic insights are drawn from analyzing the composition of countries’ expenditure (the demand side). 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 are obviously quite diverse. Table
7 presents comparisons of final demand shares of nominal GDP, covering: (1) household consumption, including consumption of non-profit institutions serving households (NPISHs); (2) government
consumption; (3) investment or, in national accounts terminology, gross fixed capital formation (GFCF)
plus changes in inventories; and (4) net exports (exports minus imports).
For most countries, household consumption is by far the biggest component of GDP.25 The GCC countries, Brunei, and China are the exceptions. Over the past four decades, the share of household
Table 7 Final Demand Shares in GDP, 1970, 1990, 2000, 2011, and 2012___Share of final demands with respect to GDP at current market prices

APO20

Household consumption
Government consumption
Investment
Net exports
1970 1990 2000 2011 2012 1970 1990 2000 2011 2012 1970 1990 2000 2011 2012 1970 1990 2000 2011 201260.5 57.6 59.7 60.2 61.6 11.1 12.0 12.9 13.0 13.2 28.9 31.2 24.5 27.3 27.1 −0.5 −0.7
2.9 −0.6 −1.9

Asia23

60.1

55.9

56.3

50.6

50.7

11.1

12.3

13.7

13.1

13.4

29.2

31.9

27.2

35.5

35.9

−0.5

−0.1

2.8

0.7

0.1

Asia29

57.5

55.3

55.2

49.2

49.3

11.5

13.5

14.2

13.3

13.5

28.1

30.5

26.5

34.8

35.1

2.9

0.7

4.1

2.7

2.1

East Asia

51.9

51.3

52.2

43.8

42.9

10.9

13.5

15.6

14.9

15.1

36.5

33.6

30.1

39.4

40.0

0.6

1.6

2.1

2.0

2.0

South Asia

76.1

68.0

67.6

66.9

68.5

8.5

11.3

11.6

10.6

10.9

15.8

23.2

22.4

29.3

28.2

−0.4

−2.5

−1.6

−6.9

−7.6

ASEAN

69.0

57.6

58.2

56.8

57.2

12.4

9.6

9.4

10.7

10.8

23.3

33.8

23.4

28.2

29.4

−4.7

−1.0

9.0

4.3

2.6

ASEAN6

68.5

55.9

57.2

55.6

56.5

10.5

9.7

9.6

11.2

11.3

23.4

34.9

23.1

27.9

29.4

−2.5

−0.5

10.1

5.3

2.7

CLMV

76.7

84.2

71.3

68.0

63.4

27.5

8.9

6.8

5.3

5.2

19.4

14.2

24.4

29.7

29.4 −23.5

−7.3

−2.5

−3.0

1.9

GCC

35.3

49.6

41.7

30.9

30.9

14.8

25.5

20.5

15.5

15.9

18.8

15.7

18.0

24.8

25.2

9.1

19.8

28.8

28.0

31.1

China

55.6

47.0

46.7

35.8

34.7

11.2

14.1

15.8

13.3

13.8

33.1

36.1

35.1

48.3

48.7

0.1

2.7

2.4

2.6

2.8

India

74.8

65.2

65.1

63.7

65.3

9.4

11.7

12.6

11.2

11.5

15.9

24.5

23.2

31.7

30.1

−0.1

−1.4

−0.9

−6.6

−7.0

Japan

49.2

52.9

56.4

60.2

60.6

10.7

13.3

16.9

20.3

20.4

38.8

32.9

25.3

20.4

21.0

1.2

0.9

1.4

−0.9

−2.0

Australia

54.5

58.1

59.1

54.4

55.6

13.9

18.2

17.8

18.0

18.1

31.8

24.0

23.0

27.7

27.5

−0.3

−0.2

0.2

−0.2

−1.2

US

62.4

66.1

68.6

71.2

70.8

18.3

16.7

14.3

17.1

16.5

18.9

18.6

20.9

15.5

16.1

0.4

−1.3

−3.8

−3.8

−3.5

EU15

58.0

58.1

58.7

58.3

58.5

16.3

19.9

19.7

21.8

21.7

26.1

22.6

21.3

18.9

17.8

−0.5

−0.7

0.3

1.1

2.0

25: 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.

37©2014 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 PPP for GDP. Household consumption includes consumption of
NPISHs. Investment includes GFCF plus changes in inventories.

4 Expenditureconsumption for mature economies tends to bestable and trending upward in recent years, It is
more volatile and largely trending downward ineconomies undergoing rapid transformation,such as the Asian Tigers in the 1970s and 1980s,
and India and China in the present day, as theinvestment share increases for their development effort.

%

70
60

Household consumption

50
40
30

Investment
Exports

20
10

Imports (−)

0
China’s household consumption has been trend1952
1962
1972
1982
1992
2002
2012
ing downward as a share of GDP. It fell from
55.6% in 1970 to 46.7% in 2000. This compares
Figure 22 Final Demand Shares in GDP ofwith the early Communist era when household
China, 1952–2012_ Share of final demands with respect to GDP at
consumption was more volatile and at a higher
current market prices
level of over 60% of GDP (Figure 22). China wasless well-off then. Figure 22 shows how houseSources: National accounts by National Bureau Statistics of China,
including author interpolation.
hold consumption share and investment sharemirror each other. As the decline in household
consumption share accelerated in the 2000s,
plummeting to 34.7% in 2012, the investment share rose rapidly to 48.7% of GDP from 35.1% in 2000.
Investment has overtaken household consumption as the largest component in GDP expendituresince 2004, and the divide shows no sign of narrowing. There also is a notably rapid rise in exports asa 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 24.9% in 2012.

©2014 Asian Productivity Organization

With a low consumption ratio, coupled with an unsustainable rise in investment and an overdependence on exports, China faces huge internal and external imbalances. If not addressed, this could
jeopardize its medium-term growth prospects. A low consumption share of GDP is not merely a reflection of consumer behavior or preference, but a manifestation of an array of underlying distortions in
the economy. An undervalued currency with a wide range of factor price distortions which favors the
production of tradables over non-tradables, may result in an unusually low consumption ratio and aheavy reliance on exports. Lax corporate governance of state-owned enterprises is not conducive to
distribution of dividends and therefore, in effect, may act to subsidize investment. Additionally, in theabsence 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 ofthese factors suggest that there are policy levers available to the government to impede or rebalance
the economy.26
In recent years, even labor-abundant China faced a tightened supply of surplus labor at its coasts, putting an upward pressure on wages (See Box 4, p. 60). This could be good news for the world, as ahigher labor share of GDP will enable higher household consumption, helping the domestic market
fulfill its potential. This will make China less dependent on foreign demand as well as generate demand for foreign products. Early signs that the Chinese economy may have started moving in theright 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 2.8% in 2012, which is

26: In recent years, the local governments have been ratcheting up debt, which the central government struggles to count, let alone
control. Although currently a financial meltdown is unlikely, the pace and scale of debt being piled up is starting to cause jitters.
See, for example, the Economist, “Local-government debt: Counting Ghosts,” 4 January 2014, and the Economist, “Local government: Emerging from the Shadows,” 19 April 2014.

38

4.1 Composition of Final Demand

the lowest since 2004. Since the peak of 8.8% in
2007, net exports have been shrinking. Only
time will tell if this is the start 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 65.3% in 2012 (Table 7). In contrast, the shareof household consumption was relatively stablein the US at around 62–63% for the 1970s and1980s before edging up to 70.8% of GDP in 2012.
From a historical perspective, the current level isbelow that experienced during the Great Depression in the US, when the consumption share
was over 75%, even as high as 83% in 1932, andabove its all-time low of below 50% in 1944 during World War II (Figure 23).

%

80
70

consumption
Household Consumption

60
50

4

40
30

Investment

20
10

Imports (−)
Exports0
1929 1939 1949 1959 1969 1979 1989 1999 2009

Figure 23 Final Demand Shares in GDP of theUS, 1929–2012_ Share of final demands with respect to GDP atcurrent market prices

Sources: National accounts by Bureau of Economic Analysis, US.

Overall, Asian countries invest significantly more than the US and EU15 as a share of GDP. Historically,
the gap in the investment share between Asia29 and EU15 never exceeded 10 percentage points.
However, since the beginning of the 1990s, it has started to widen (except for the period of the Asian
Financial Crisis). In 2012, the difference was over 17 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. 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 than that of EU15 (Figure 31.3). In 2012, investment accounted for 16.1% and 17.8% of final demand in the US and EU15, respectively, compared with 35.9% for Asia23. Australia’s investment levelhas been closer to the level of the APO20 than the US/EU15. In 2012 it accounted for over a quarter offinal demand. The share of investment in China is the biggest final demand component of GDP since2004. At 48.7% in 2012, it is probably unsustainable in the long term. East Asia has the highest investment ratio among the Asian regions. While South Asia caught up with them in 2007, since then thepaths of the two regions diverged in opposite directions. Now South Asia is converging with ASEAN
countries, the investment intensity of which has not recovered since the Asian financial crisis of thelate 1990s.
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 –0.1% to
2.8%, the contribution of net exports has been ebbing away once again to 0.1% in 2012. In contrast,
the net export share in China has been steady at a rate of 2.4–2.8% over the past two decades. This

39

©2014 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
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 in the past decade to 55.6% in 2012, reflecting a pickup in the investment share. Within Asia, all regions display a decline in household
consumption ratios. South Asia maintains the highest share, despite its fall from 76.1% in 1970 down
to 68.5% in 2012. In contrast, GCC economies are unusually skewed towards net exports because of
their oil production.

4 Expenditurecompares with the oil-exporting GCC countries at 9.1% in 1990, rising to 19.8% in 2000 and further to28.0% in 2012. Including the GCC countries, the contribution of net exports to the GDP of Asia29 was
2.1% in 2012, compared to 2.9% in 1970 when net exports accounted for nearly a third of final demand in GCC countries. In the US, there is an observable trend of persistent deficit between exports
and imports, which has considerably expanded from 0.5% of GDP in 1980 to nearly 6.0% in the mid2000s before narrowing to 3.5% in 2012. South Asia is the only Asian region that consistently runs afluctuating trade deficit over the years. Lately, it has become historically sizable at 7.6% of GDP in
2012. In EU15, net exports have become a positive component in the past two decades, accountingfor 2.0% in 2012.
The regional averages disguise the great variation displayed by individual countries. Figure 24 shows
the cross-country comparisons of final demand shares in current-price GDP in 1995 and 2012. Countries are arranged in descending order of their household consumption shares. Although most countries fall to the right of the US, there are a handful of Asian countries that have a higher consumption
ratio than the US. Bangladesh, Cambodia, Nepal, Pakistan, and the Philippines fell to the left of the US
in both years of comparisons. A deficit in net exports tends to be associated with high household
consumption. Countries with a low income will struggle to defer consumption. It is no coincidence

1995

%

125
100

15
6 19 27
5

75
50

95

14 24 27 20 26 24

8 8

83 81 78

25
0
−25

−6
−15

8

8

9 12 14

24

19

4
2
0
2
8
25 27 27 25 17 34 23 29 20 24 27 36

9 15 10 11 1176 74 73 72 71 68 67

8 13 8 16 12 20 18 15

67 64 63 63 62 62 61−1 −8 −9 −2 −10 −9 0 −1 −2 −1 −1

−4

7

4 1
2
1
8
10 5 1011
16
37 37 32 28 31 14 43 37 34 21 43 20 21 15
35 35
42
0

9

1

1

9 12 15 13 21 11 11 14 22
23 28 3212

59 58 58 57 57 57 55 55 55 55 54 53 52 51
49 49 47 45

00

0 −2 −2

−7

−15

−1

33
14

8 25 3143 43 42 36

33

−4

Qatar
BruneiSingapore
China
KuwaitOman
Saudi Arabia
Malaysia
GCC
East Asia
Korea
ThailandBahrain
Asia29Japan
Asia23ASEAN6ASEAN
Indonesia
ROC
Australia
EU15
APO20
Fiji
Hong Kong
Iran
UAE
Mongolia
India
South Asia
US
TurkeySri Lanka
Philippines
Pakistan
Vietnam
CLMV
Myanmar
Nepal
Bangladesh
Cambodia

2012

%

125
100
75
50
25
0

−8

−25

37

2 3
0
1
2
3 3
1 3 1 022
3
8
19 26 18 16 20 30 28
64
12
30 26
21
20
18
22 27
27
28 29 2824
28 26 25
10 6
35
20
29 28
29 29
35
38 36
35
6 11 16 15 1340
47 49 4124
11 9 12 154920
23
5 6 1312 22
28 20
9 11 11 18 16 16
27
25
25
4
10 13 7 14 14 14
15
15 14
9 15
87 81
34
14 16 19 20
80 77 74
71 70 70 68 67 65 65 64
63 62 61 61 60 58 58 57 57 56
15 17
54 54 52 51 50 50 49 49
43 41 3813
35 31 30 29
23 21
12

12
8

−28

−5

−9

−3 −3 −5
−14

−8

−7 −6

−2

−2

−2

−1

−27

©2014 Asian Productivity Organization

Qatar
Brunei
KuwaitSaudi Arabia
Oman
GCC
China
Bahrain
Singapore
East Asia
Mongolia
Asia 29
Malaysia
UAE
Asia23
Iran
Korea
ThailandAustralia
ASEAN6ASEAN
Indonesia
EU15
ROC
Japan
Myanmar
APO20
Vietnam
CLMV
Fiji
India
Hong Kong
South Asia
Sri Lanka
TurkeyUS
Philippines
Bangladesh
Cambodia
Nepal
Pakistan
Household consumption

Government consumption

Investment

Net exports

Figure 24 Final Demand Shares in GDP, 1995 and 2012___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. Investment includes GFCF plus changes in inventories.

40

4.1 Composition of Final Demandthat countries clustered on the left of Figure
24 tend to be those in the bottom income
groups27 among the countries studied in thisreport (see Table 14, p. 87). Countries with ahigh proportion of dependent population(under-15, over-65) 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 49.3% in 1995 to 30.9% in 2012.28
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 andinstead purposefully invest to generate a
steady income stream in the eventuality of oil
depletion, regardless of how distant this may
seem now. Among the non-oil-exporting
Asian countries, Singapore had the smallest
household consumption share. However,since 2002 China has replaced Singapore inthat position, with a share of 34.7% in 2012.

% Household consumption share in GDP

90

Pakistan
Cambodia

80

Nepal

Bangladesh
PhilippinesUS
Sri Lanka
Hong Kong
Fiji
Vietnam India Myanmar
Japan
ROC
Indonesia
ThailandAustralia
Iran
Korea
Mongolia
Malaysia
Singapore
Turkey

70

60
UAE

50

4

40
Bahrain

China

30

Oman
Kuwait20

Saudi Arabia

Brunei

Qatar

10

10

15

20

25

30

35

40

45 %

Dependent population ratio

Figure 25 Ratio of Dependent Population andConsumption Share in GDP at Current Market
Prices, 2012
_Shares of dependent population (under-15, over-65)
to total population and consumption share to GDP

Sources: Population data by national statistical office in each country; World Bank, World Development Indicators 2013; official national
accounts in each country with author estimates.

Net exports are particularly important in a handful of economies. In 2012 in Singapore export shareswere at 197%, and in Hong Kong 230%, reflecting their port 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 reflecta change in ownership of goods, rather than accounting for goods moved for processing without incurring actual transactions.

27: 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.
28: 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 32.7% in 1995 to 12.4% in 2012, while over the same period, net exports swung from 1.0%
to 41.3%. Similarly, net exports for GCC countries as a whole swung from 8.0% to 28.0%, squeezing household consumption from
49.3% in 1995 to 30.9% in 2012.

41©2014 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 2012, the household consumption share of

4 Expenditure

1995

%

100

91 143

182
78

80
60

37

40

59

57

52
34
22

20

47

44
20

44

29

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

−43

40
20

11

−12
−12 −16

−17

−36

−67

32 34 33

22

31

−38
−41 −43−46−48 −43

−59
−148
−95

2012

%

60

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
ROC
EU15
China
Brunei
UAE
Oman
Iran
Saudi Arabia
KuwaitBahrain
Singapore

GDP fell from 69.1% of GDP to40.6% and from 74.1% to 53.5%
in Singapore and Korea, respectively. In contrast, household consumption as a share of GDP, at
66.7% in 2012, has been risingin Hong Kong since the mid2000s. The household consumption share did fall from 64.8% in
1970 to nearly 55% in the late1980s, but it was subsequently
reversed. Similarly, relative household consumption fell in 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%.

79

197 93 91
69 65

75

73
62

54

230

79

70
57

57

57

51

43
25

22

20 24

31
15

14

26

25

23 23
12

10

©2014 Asian Productivity Organization

Nepal
Mongolia
Sri Lanka
Bangladesh
Pakistan
India
Fiji
TurkeyCambodia
US
Philippines
Japan
Indonesia
Australia
Myanmar
Iran
ThailandHong Kong
EU15
China
Korea
Vietnam
ROC
Malaysia
UAE
Singapore
Saudi Arabia
Oman
Bahrain
Qatar
KuwaitBruneiFigure 27.2 plots the trends of00household consumption in the−20−20−21 −21−25−17 −17
−22
−23
−29
−30 −24−31 −32 −32
three largest Asian economies by
−34
−35
−40
−36 −38−41−48−53
size. The downward long-term−60−62 −63
−66
−69
−73
−80
trend in India and China is−77−78 −76
−174
−229
−100
unmistakable.29 The falling shareof household consumption may
partially reflect the falling labor
income share of GDP and/or an
Exports
Imports
Net exports
uneven distribution of economic
gain between the rich and the
Figure 26 Export and Import Shares in GDP, 1995 and 2012poor in these countries. India has___Share of exports and imports with respect to GDP at current market
a dependent population (unprices
der-15, over-65) of 34.6%, comSources: Official national accounts in each country, including author adjustments.
pared with 25.8% in China. Thismay help explain why India has
had to sustain a relatively highshare of household consumption despite its falling trend over time, whereas China’s share has fallen
below the norm of country’s experience (Figure 25). There are, however, tentative signs that the downward trend in household consumption share seen in China may have bottomed out in recent years. In
contrast, the household consumption share in Japan has been rising slowly since 1970, from just under 50% in 1970 to over 60% in 2012. With a rapidly aging population, this rising trend can be expected to continue. Japan’s share of dependent population stood at 37.1% in 2012, nearly 60% of

29: The Chinese official statistics on household consumption could be misleading. Zhang and Tain (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

China
India
Japan

70

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

100
90

East Asia
ASEAN
CLMV

South Asia
ASEAN6

80
60
50

70
60
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, 1970–2012___Share of household consumption with respect to GDP at current market prices
Sources: Official national accounts in each country, including author adjustments.

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 toover 70% of GDP since 2008, from a level of around 62%. Today the US level is more than 10% higher
than that of EU15 and the APO20.30 The share in EU15 has been stable, fluctuating within a narrow
range between 57% and 60% since the mid-1990s. In 1970, household consumption accounted foraround 60% of GDP in APO countries. It rose to a peak of 61.8% in 1982 before falling back and hovering around 59%. Since the early 1990s, however, it has been trending upwards and went over the 60%
mark in 2012. After the bubble economy burst and its economy floundered, the investment share of
GDP shrank – with household consumption and government consumption both inflating their sharesto sustain final demand (see Figure 24). In contrast, the consumption share for Asia29 declined rapidly
from 57.5% to below 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 have been fluctuating between that of EU15 and Asia29 in the 1970s and 1980s, and inclined towards EU15’s level

30: It is worth noting that the GDP share of government consumption in EU15 was 8.4 percentage points higher than the average of
Asia23 in 2012 (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©2014 Asian Productivity Organization

which was accounted for by the over-65 age group (Figure 28). To a lesser extent, all the Asian Tigers,
China, Australia, and the US have a high proportion of over-65 relative to other countries.

4 Expenditurein the 1990s. Its trend in the past decade has diverged
again and become similar to Asia29, albeit at different
levels. The trends of South Asia and East Asia aredominated by those of India and China, respectively(Figure 27.4).

Lao PDR
Nepal
Pakistan
Philippines
Japan
MyanmarCambodia
Bangladesh
South Asia
India
Indonesia
APO20
Fiji
ASEAN6
ASEAN
EU27
US
Australia
CLMV
Sri Lanka
Saudi Arabia
TurkeyMalaysia
Asia23
Asia29Mongolia
Vietnam
IranBruneiThailand
GCC
KuwaitOman
Korea
East Asia
Singapore
China
ROC
Hong Kong
Bahrain
UAE
Qatar

4

37
34
34
33

5
4
5
24

13
31
32
31
30
29
29
28
29
28
28

6
4
5
5
5
5
6
5
6
6

©2014 Asian Productivity Organization

The decomposition of household consumption reveals ahuge diversity of consumption patterns among individual countries, partly reflecting their income levels and16
18
partly the idiosyncratic characteristics of the society. Fig19
14
ure 29 strongly illustrates the cross-country version of
19
14
27
6
Engel’s Law, which says that basic necessities will ac26
6
count for a high proportion of household consumption
30
3
25
8
for a lower per capita income group and vice versa.
26
5
24
7
More specifically, countries where food and non24
7
alcoholic beverages account for a large proportion of
27
4
23
7
consumption tend to have low income (i.e., in groups
23
6
25
4
L3 or L4 in Table 14). The other end of the spectrum is
18
9
occupied by the rich Asian countries, namely, the Asian
25
2
25
2
Tigers and Japan. Figure 30 traces the decreasing
24
3
15
12
long-term path of Japan’s Engel’s Curve for the period1611
1949–2012. The countries’ levels in 2012 are mapped
16
10
16
9
against Japan’s experience (as circles). Among the select­
15
11
11
14
ed countries, it is staggering to note that in 2012, 54.7%
202
Age 0–14
of Bangladesh’s household consumption was spent on
140
Age over 65
13 1
food and non-alcoholic beverages at one end of the
0 5 10 15 20 25 30 35 40 45 %spectrum, compared with only 7.9% in the US at theother end. This translates into the fact that low-income
Figure 28 Share of Dependent Popucountries spend 30–50% of their GDP on food and nonlation, 2012
alcoholic beverages, which corresponds to Japan’s expeSources: Population data by national statistical office inrience in the 1950s and the 1960s. Eating out, recreationeach country; World Bank, World Development Indicaand culture are luxuries that the least well-off countries
tors 2013.
cannot afford in contrast to their richer counterparts.
Besides food and non-alcoholic beverages, housing/utilities and transportation are the other two large spending categories. In rich economies, these twocategories account for bigger shares in household consumption than food and non-alcoholic beverages. Idiosyncratic spending, such as education in Indonesia and Korea accounting for 7.5% and6.7% of household consumption, respectively, and health in the US, accounting for one-fifth of
consumption, are not reflected 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 21.0%
in 2012 (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
2012, the investment ratio was 27.6%. The investment share hit around 40% in the ROC and Korea at
different times but these were no more than temporary spikes (Figure 31.1). In contrast, the investment share in China and India has been rising. India in particular has been investing very aggressively
since 2000, coming as close as 5.6 percentage points to China’s 41.7% share in 2007. Since then, thegap has widened to 18.6 percentage points in 2012 as investment in India softened (Figure 31.2). At

44

4.1 Composition of Final Demand

Figure 33 plots the long-term trendof net export share in GDP from1970 to 2012. Among the selected
countries, India can be identified asprone to running a trade deficit,
which deteriorated rapidly from themid-2000s to 7.0% of GDP in 2012
(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 of
the Asian Tigers. The share of net

90
80
70
60
50
40
30
20
10
0

4
4 2 3 4 5
8 2 2 210 3
6 22
14 12 15 14 16
2 14 14
2 4
17
7
19
3
3
5 4
3
4
7
6 4
5
3
8
7 6
3 14 9 10 7
2 3 25 5
2
3
4
2
2
3 9
14
5
4
2
7 7
9
9
9 4
9
5
8 6
14
2 16 210
12 17 13 8 8 4
2
6 4
3
7
13
5
2
2
2 4
3
10
7 4
17
4
12
2 6 15
12
2
11
19 4
13
10
2
12
18
5 9
13
3
4
10 6
31 3 4
13
9
21
4
7
6
4
11 4 117
16 3 5
9
3
7
6
4
15 25
4
4 5
16 17 24
57
5
3
53
3
17
2
19 20
41
5 5
3
36 36
32
3
3
2
2
29
25 25
4
21
3 2
2
14 14 14 13
10
7 7

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

Figure 29 Household Consumption by Purpose, 2012
Sources: Official national accounts in each country.
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 and Iran, the observation periods are 2009 and 2010, respectively.
Food consumption share in 2012 relative to Japan

0.7
Japan (1949–2012)

Fiji

0.6

Bangladesh
Lao PDR
0.5

Indonesia
Philippines

0.4

Sri Lanka
Cambodia

Mongolia
0.3

India
ThailandIran
Malaysia

0.2

Japan

Korea
Hong Kong ROC
0.1

Singapore
US

1940

1950

1960

1970

1980

1990

2000

2010

2020

Figure 30 Engel Curve of Japan during 1949–2012 andLevels of Asian Countries in 2012___Share of food in household consumption

Sources: Official national accounts in each country. The historical data of Japan isbased on JSNA by ESRI, Cabinet Office of Japan.
Note: Food is defined as sum of food and non-alcoholic beverages and alcoholic
beverages, tobacco and narcotics. For Fiji and Indonesia, Iran, and the Lao PDR, theobservation periods are 2009, 2010, and 2005, respectively.

45©2014 Asian Productivity Organization

Figure 32 shows the nominal investment share of six types of assets forsome selected countries.31 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, the Asian Tigers, andMalaysia, even at the current pricecomparisons. The real-term comparisons are conducted at the flow
and stock levels in Chapter 5.

%100

Singapore
US
Australia
ROC
Korea
Hong KongJapan
Malaysia
Iran
ThailandIndia
Mongolia
Cambodia
Indonesia
Sri Lanka
BangladeshFiji

48.7% in 2012, China’s investment
share has reached a level previously
unseen in Asia. If history is any
guide, the contribution of investment to final demand in China will
drop sooner or later. South Asia andEast Asia’s investment shares are
dominated by the effort in India andChina, respectively. ASEAN’s investment share used to be around 35%,
but it fell sharply to the lowest pointof 20.1% in 1999 in the aftermath of
the Asian financial crisis. Since thenit has been slowly inching up, reaching 29.3% in 2012. In the past
two and a half decades, the investment share in GCC countries has
fluctuated between 15–30% of GDP(Figure 31.4).

4 Expenditure

%

%

50

ROC
Hong Kong
Korea
Singapore

40

50
40

30

30

20

20

10

10

0
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 31.1

China
India
Japan

0
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 31.2
%

%

50

APO20
US
EU15

40

50

Asia29Australia

40

30

30

20

20

10

10

0
1970 1975

1980

1985

1990

1995

East Asia
ASEAN
CLMV

2000

2005

2010

Figure 31.3

0
1970

1975

1980

1985

1990

1995

South Asia
ASEAN6
GCC

2000

2005

2010

Figure 31.4

Figure 31 Long-Term Trend of Investment Share in GDP, 1970–2012___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

36

24 18

Dwellings
Transport equipment

100
80
60
40
20
0

17 14

24 30

31

40

23 24 2635 38

927 27 5
4 24

38 31

23

44
6
10
15 3
10 11
9 6 3
4
18
42
8
12
7
13 7
12 14 5
14
9 24
10
21
6
12
9
28
10
20 18
17
8 22 32
13
25
21
25
21
29 14
18
20
14
15 12 14
13
26
32
12
31
9 7
12 13 21 13 23 13
19 16
29 24 2419
7
22 18 18 17 15
18
15 13 13 11 10 9 8
8 8 5

13
11

Non-residential buildings
IT capital

85
8 22 15

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

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

0

16
17
28
30
30
32 4 27 26
4 35
42 35
42
43
8
13
12
4
7
10
5
12
8
4
11
12 10 1355 12 30 21 4 11 16 5
13
23 13
16
5
22
8
17 21 11 32
24
15 21
18
8
18
22
34
18
9
26
21
21
14
8 7 1517 16
29
13 13 13 18
17 15 2539
19 27
27 26 23 23 23 22 22 20
19 18 16 16 15
11 9 8 5
3

26 30

2012

%

11

Other structures
Other non-IT©2014 Asian Productivity Organization

Figure 32 Investment Share by Type of Asset, 1970 and 2012
Sources: Official national accounts in each country, including author adjustments based on input–output tables and trade data.

31: 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
16

%

9

ROC
Hong Kong
Korea
Singapore

6

China
India
Japan

3

8

4

0
0
−3

−8

−6

−16
−24
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 33.1

−9
1970

1975

1980

1985

1990

1995

2000

2005

2010

Figure 33.2

%

%

10

APO20
US
Australia8

Asia29
EU15

6

12
6
0

4

−6

2
−12

0

−18

−2

−24

−4
−6
1970

1975

Figure 33.3

1980

1985

1990

1995

2000

2005

2010

−30
1970

1975

1980

1985

1990

East Asia
ASEAN
CLMV

South Asia
ASEAN6

1995

2005

2000

2010

Figure 33.4

Figure 33 Long-Term Trend of Net Export Share in GDP, 1970–2012___Share of net exports with respect to GDP at current market prices
Sources: Official national accounts in each country, including author adjustments.

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 of this period. While EU15 managed to recover, being in surplus
since the early 1990s (within a range 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 late1980s. In 2012, the size of the US trade deficit stood at 3.5% 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-image of the US. Asia29’s net exports share of GDP was 2.1%, compared to therecent peak of 5.5% in 2012. Addressing this external imbalance has been highlighted as a necessary
step to healthy and sustained growth in the world economy.

47©2014 Asian Productivity Organization

exports in Singapore is particularly large, at 22.3% in 2012, compared with 3.1%, 7.6%, and 1.1% for
Korea, the ROC, and Hong Kong, respectively (Figure 33.1). China is another country that has turned
around its net export position to transform it into a significant positive contribution to final demand.
The net export share of GDP peaked at 8.8% in 2007. Since then, it has lagged to 2.8% in 2012. Japan
had enjoyed a trade surplus for most of the period compared, but recently, its trade balance hasturned negative amounting to –0.9% in 2011 deepening to –2.0 in 2012 (Figure 33.2). In the aftermathof the triple disaster (earthquake, tsunami, and nuclear) in 2011, Japan had to increase imports tomeet the shortfall of energy production as a result of the shutdown of its nuclear power plants. This
trend may change in response to its new energy policy, which will in turn reduce imports.

4 Expenditure

The time series of ASEAN’s trade balance has a clear structural break which is marked by the Asian financial crisis of 1997 (Figure 33.4). The impact was a trade balance spike in 1998 at 9.9%, up from 0.3%
in the previous year. Trade balance moderated over time to the more normal level of 2.6% in 2012. In
recent years, the trade performance of CLMV has been strong and is in surplus for the first time since1970.32 Its improvement has been rapid, from a deficit of 10.1% in 2007 to a surplus of 1.9% in 2012.
This should not be a surprise when CLMV is picking up the slack from China as the workshop of theworld. If the time series of China’s net exports is any guide, CLMV’s trade surplus could continue toexpand for more years to come.

4.2 Demand-Side Growth
Decomposition©2014 Asian Productivity Organization

8

0.1
3.9

6
4

3.2

1.3 1.3

1.5

2.7 2.6 3.2 0.8

0−2

0.2 0.0
1.9 2.1

1.3 2.4

0.4

1.6 0.5

0.5

1.4

2000–2012
0.0

10

3.8
0.3

6
4
2
0
−2
−4

0.7

0.7

%

12

8

1.5

0.4
1.3 1.0
0.0 0.2
0.6
0.1
0.7 0.7 0.7 1.4 0.5 1.6 1.4
0.4 1.0
1.1 1.1
1.6 0.1
0.3
0.6 0.1 0.8
0.2
0.5
0.1
0.7
0.4
0.5
0.3
2.6 4.5
4.3
0.2
1.4
0.5 3.6
3.8 3.9
3.6 3.3
0.2 3.2
1.0 0.5 0.2
3.4
3.2
3.1
2.9
0.3
2.8 2.8
2.5
2.5 2.0
2.4 2.0 2.4
2.3 2.7
2.3
0.6 0.7
0.5
1.8
0.8
0.8 0.6 1.3 0.7
0.1
0.0 −0.3−0.3−0.1−0.1 0.0 −0.4 −0.4−0.1
−0.1
−0.2
−0.3
−0.4
−0.7

1.6

0.8 0.6

2

1.3

1.7

6.0

0.3

5.9

1.9
0.5 2.9

7.4

2.8 2.0

2.7 1.8

0.1

2.9
0.1 0.0 1.0
0.4
2.3
0.9
2.3 0.6 1.5 2.4 1.0
1.7
1.7
2.2
1.0
1.0
6.5
1.4 0.8 2.6
1.3
0.5 0.6
0.4
0.5
0.5
0.8 0.3
0.5 0.5
0.9
1.3
4.8 4.4
0.7
0.0
0.6 0.4
4.1
1.0
0.2 0.1
3.6 0.4
3.4
3.3
3.2
3.0
0.2 0.2 0.7
2.9
2.8
2.8
2.7
2.6
2.6 2.4 2.3
2.3
2.2
1.9 0.2 0.3 0.3
1.7
1.7
1.5
1.6
1.3
1.4 0.6 0.6 1.1
−0.1
−0.7
−0.4
0.0
0.0 −0.2−1.1 0.0 0.0 −0.3
−0.4
−0.3
−0.7
−0.7
−2.0
−2.3
−0.9
−0.9
−1.0
−1.3
−2.9
0.6

1.4

0.4

0.8

1.1 0.4

2.6 1.9

Brunei
Japan
EU15
US
Australia
Nepal
ROC
Hong Kong
Oman
UAE
Korea
TurkeyIranThailand
Pakistan
Saudi Arabia
Malaysia
Philippines
KuwaitIndonesia
Singapore
Bangladesh
Bahrain
Sri Lanka
Vietnam
India
Cambodia
China
Qatar
MyanmarOn 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,
3.8 percentage points in Myanmar,

0.4

Japan
EU15
Saudi Arabia
Brunei
Philippines
US
Australia
TurkeyPakistan
Bangladesh
Hong Kong
ThailandIran
BahrainIndonesia
Oman
India
Sri Lanka
KuwaitUAE
Myanmar
ROC
Korea
Cambodia
Qatar
Malaysia
Singapore
Vietnam
China

Figure 34 shows the decomposition of the average annual economic growth by final demand forthe periods 1990–2000 and 2000–
2012, respectively. Here, Asia29
grew faster in the latter period
than the former (at 5.9% on average per annum compared with
4.9%, as presented in Table 3, p.
19).33 The earlier period embodied
the atypical economic event of
the Asian financial crisis, whichcaused some erratic contributions
by the final demand components
observed in some countries in thelate 1990s. In the 1990s overall,the engine of growth for mostcountries in Asia was household
consumption, while investment
growth was more subdued.34

1990–2000%

10

Household consumption
Investment

Government consumption
Net exports

Real GDP

Figure 34 Final Demand Contributions to Economic Growth,
1990–2000 and 2000–2012_ Decomposition: Average annual growth rate of GDP at constantmarket prices

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

32: The huge deficit of CLMV in the 1970s due to a large impact by the Vietnam War.
33: 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.

48

4.2 Demand-Side Growth Decomposition

4

Hong Kong

Korea

SingaporeROC%
2.9 percentage points in India, and 2.8 per120
centage points in Vietnam. China grew by
Household consumption
100
10.7% on average per year in the latter peri80
Government consumption
od. The role played by investment has
60
strengthened, with its contribution to ecoInvestment
nomic growth expanding between the two
40
periods from 42.4% to 55.1%, squeezing the20
Net exports
contribution of net exports from 4.3% to
0
2.8%, and that of household consumption
from 37.0% to 29.9%. However, for Singapore
and the ROC, the strength of net exports was
the real economic story, accounting for
47.9% and 69.9% of their economic growth
Figure 35 Final Demand Contribution Shares toon average per year between 2000 and 2012,
Economic Growth of the Asian Tigers, 2000–2012___Shares of final demand contributions to growth rate ofrespectively. Even in the other two Asian TiGDP at constant market prices
gers, net exports accounted for 25.3% and21.5% of Korea’s and Hong Kong’s economic
Sources: Official national accounts in each country, including author
adjustments.
growth, respectively (Figure 35). In contrast,
net exports have been a drag on economic
growth in India over both periods, making anegative contribution of –2.2% and –10.0%, respectively. In some of these economies, the contribution of household consumption to economic growth was really squeezed. For example, from 36.5% in
1990–2000 to 29.4% in 2000–2012 in China, from 36.7% to 28.3% in Singapore, and from 59.7% to36.6% in the ROC. In contrast, the role played by household consumption in economic growth increased in the US and Japan, from 72.4% to 84.1% and from 66.0% to 78.9%. Overall economic growth
in Japan slowed from 1.1% to 0.7% between the two periods compared. This was a sluggish performance, especially relative to the acceleration that most Asian economies experienced. Also, in thelatter period net exports made negative contributions in more countries than previously, with its impact in certain oil-exporting countries particularly large.

In the 2000s, economic growth slowed in both the US and EU15 from 3.3% on average per year in
1990–2000 to 1.6% in 2000–2012, and from 2.3% to 1.1%, respectively. In terms of contributions,household consumption increased from 72.4% to 84.1% and government spending tripled from 4.7%
to 15.2% in the US over the two periods. Investment in the US took a plunge, however, from a contribution of 34.0% to –1.2% over the two periods. However, its net exports improved from –11.0% to
1.9%. EU15 had a similar pattern where the contribution of government spending doubled over thetwo periods from 14.9% to 29.8%, making up the slack in the contribution of investment which wentfrom 22.3% to –2.9%, while household consumption remained more or less stable. Its net exports also
improved from –5.6% to 21.0%.

34: The exceptions are some of the oil-producing countries, which enjoyed a positive contribution from net exports bigger than mostcountries, and China, which experienced the fastest economic growth among the countries studied, averaging 9.2% per year,
42.4% of which was driven by investment, compared with 36.5% by household consumption. This compares with average annual
growths of 3.3% in the US and 2.3% in EU15. The contribution from household consumption was 72.4% and 57.2%, whereas investment growth accounted for 34.0% and 22.3% of overall growth in the US and EU15, respectively.

49©2014 Asian Productivity Organization

Figure 36 shows the impacts of the global financial crisis and countries’ path of recovery from theviewpoint of final demand between 2007 and 2012. The crisis made its adverse impact felt throughinvestment in most countries, and to a lesser extent, through net exports. Drastic contraction in
investment became commonplace in countries from 2008–2009. China’s robust growth in investment

4 Expenditure

Box 3

National Accounts in Asian Countries

Understanding data comparability is essential for the construction of an international database, and requires significant effort and expert knowledge. Between September and December 2013, metadata
surveys on the national accounts and other statistical data required for international comparisons of productivity were conducted among 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. However, country data can deviate from the international best practice and vary in terms of omissions and coverage achieved. Countries can also vary in theirestimation methodology and assumptions. This may account for part of the differences observable in thedata, as well as interfere with comparisons of countries’ underlying economic performance.
Most of the economic performance indicators in this report are GDP-related. The surveys therefore put
much emphasis on discerning countries’ GDP compilation practices. For GDP, the 1993 SNA is used as thestandard, 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 the data series definitions and classification started to switch over. This allows identification in breaks inthe time series. Figure B3 presents the current situation in compilations and data availability of the
backward estimates based on the 1968 SNA, the 1993 SNAs, and the 2008 SNA (including the future planfor introducing the 2008 SNA). For example, Japan started to publish national accounts based on the 1968

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©2014 Asian Productivity Organization

Vietnam

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

1973

1979

1951
1951

1988
1968

2009
2005

1974

1950

2000

1993
1993

1995
1978

1960

2014

2003
2005 2008
1999

2007
2010

2004

1970

N.A.(Some definitions of 1993 SNA are introduced.)
1959

2015

1981

1955

1991

1978
1980
1970
1970

2006
2000

1986
2000

1990

2000
1980

1946

1988

2000
1998
1998

1975

1998

1975
1986

Introduction year

2005

2007

2015
2012
2014

2000

1972

1972

2008

1995

1975
1981

2014

2002

1960
1975
(mixture of 1953 SNA until 1968)

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

2016
2004

1990
1989

2006
2004
2006

2015
2012
2011
2011

2001

2015
2012

1993

2015

Backward estimates and implementation

Figure B3 Implementation of the 1968 and 1993 SNA and Plan for the 2008 SNA
Source: APO Metadata Survey 2013.
continued on next page >50

4.2 Demand-Side Growth Decomposition> continued from previous page

SNA in 1978 (backward estimates based on the 1968 SNA are available from 1955 at present) and national
accounts based on the 1993 SNA in 2000 (backward estimates based on the 1993 SNA are available from1980 at present), and will introduce the 2008 SNA progressively and switch it in 2016.
As Figure B3 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.
For Indonesia, the 1993 SNA is 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 theavailability 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.

4

was a result of prompt active policy intervention in face of the potential detrimental effects of thecrisis on the economy, and shrinking net exports. Hong Kong and Japan also suffered from the negative impact of net exports on growth. Investment rebounded strongly in 2009–2010 with favorable
policy levers, but moderated in the subsequent years when the effects of policy faded out. Only China
and Singapore sustained their robust investment growth. The global financial crisis hit the US and
EU15 earlier and deeper with retrenchment in household consumption as well as investment. These
economies subsequently recovered, but EU15 was pulled down again in 2011–2012 when it faced its
specific adverse economic shock originated from the euro crisis.
In comparison, the impact of the Asian financial crisis was more contained. Figure 37 suggests that the
impact was contained within Asia, except for the handful of countries effected, it marked an exceptional time. In 1998, investment took a nosedive in Indonesia, Korea, Malaysia, Singapore, and Thailand. Household consumption also fell, albeit to a lesser extent. The crisis however greatly boosted
these countries’ net exports, likely to have benefitted from the rapid devaluation of the Asian currencies at the time of the crisis. This helped to bolster the effected economies against the retrenchment
in other components of final demand.

2007–2008

10

%

15

2008–2009

10

5

5

0

0

−5

−5

−10

−10

2009–2010%12

2010–2011

%

10

12

10

8

10

8

6

8

6

4

6

4

2

4

2

0

2

0

−2

0

−2

−4

−2

−4

−6

Investment

Net exports

2011–2012

EU15
US
Japan
India
China
Hong Kong
ROC
Korea
Singapore

Government consumption

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

EU15
US
Japan
India
China
Hong Kong
ROC
Korea
Singapore

Household consumption

%

14

GDP

Figure 36 Impacts of Global Financial Crisis and Recoveries, 2007–2012___Annual growth rate of GDP at constant market prices and contributions of final demands
Sources: Official national accounts in each country, including author adjustments.

51©2014 Asian Productivity Organization%

15

4 Expenditure©2014 Asian Productivity Organization

Australia
EU15
US
Myanmar
China
VietnamBahrainOman
Cambodia
India
Sri Lanka
Bangladesh
Qatar
ROC
Saudi Arabia
TurkeyKuwaitUAE
Pakistan
Iran
Fiji
SingaporeJapan
Philippines
Malaysia
Korea
Hong Kong
BruneiThailandIndonesia%
Figure 38 shows how the contri20
bution of economic growth by
15
final demand varies across coun10
tries and over time for the period5
1970–2012. The immediate im0
pact of the global financial crisis−5of 2007–2008 is represented in−10
the data. Most countries felt an−15
adverse impact in 2008 and 2009,
with the exception of India where−20
in 2009 growth rebounded strong­−25
ly from a slowdown in the previous year. The impact on the Asian
countries varied both in magnitude and nature. Japan’s recession
Household consumption
Government consumption
Investment
Net exportsGDP
was particularly deep with theeconomy falling by 1.1% and 5.6%
Figure 37 Impacts of Asian Financial Crisis, 1997–1998
in 2008 and 2009, respectively,___Annual growth rate of GDP at constant market prices and contribucompared with 2.1% growth intions of final demands
2007. The economic retrenchSources: Official national accounts in each country, including author adjustments.
ment in Japan was deeper thanthe –3.1% in the US and –4.9%
in the EU15 in 2009. Besides
Japan, other Asian countries either experienced a mild recession or a growth slowdown. Even so,
relative to their rapid growth, the magnitude of the impact could still be substantial. For example,
growth in Singapore dropped from 11.8% in 2007 to 0.2% and 1.0% in 2008 and 2009, respectively.
Similarly, growth in Hong Kong slowed from 6.3% in 2007 to 2.3% 2008 before moving into the negative zone of –2.3% in 2009. The corresponding real GDP growth figures for the ROC were 5.8% in 2007,
0.9% in 2008, and –1.5% in 2009. India’s growth slowed from 10.1% in 2007 to 4.2% in 2008 before
bouncing back to 7.8% in 2009. In contrast, the slowdown in China was more gradual although it
lasted longer. From 13.1% in 2007, growth decelerated to 10.6% in 2010, and further dipped to 8.6%
in 2012, which was the slowest in more than a decade. Most countries experienced a rebound (strongly in some cases) in 2010, but it was largely due to some temporary effects, which wore off and resulted in a more subdued growth trajectory beyond 2010. For example, growth in Japan swung from
4.5% in 2010 to 0.5% in 2011 (reflecting a country-specific economic shock, namely the triple disasterof 2011) and 1.4% in 2012, and similarly from 10.5% to 7.1% and 4.8% in India, from 13.8% to 5.7% and1.6% in Singapore, and from 9.5% to 4.1% and 1.7% in the ROC. The US also bounced back strongly in2010 from –3.1% in 2009 to 2.3%, which subsequently slowed in 2011 to 1.8% before returning to
2.7% in 2012. A similar pattern can be seen in EU15 when the economy revived in 2010 from a –4.9%
growth in 2009 to 2.1%, which slowed to 1.6% in 2011. Growth went negative (at –0.5%) again in 2012
under the impact of a region-specific economic shock (the euro crisis). For Asia29, the figures were8.0% in 2010 and 5.2% in 2012.

The channels through which economic growth was adversely impacted also varied across countries.
Japan’s recession 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). Meanwhile the 0.4% growthof government spending canceled out the 0.4% fall in household consumption. Similarly, in the ROC,
investment fell by 4.9% in 2009, while household consumption and net exports grew, albeit more
slowly than it had previously enjoyed. Growth in government consumption was stronger to negate
some of the adverse impact. In Singapore, net exports and investment in 2008 accounted for –7.7

52

4.2 Demand-Side Growth Decomposition

percentage points and 6.1 percentage points of the final demand growth, respectively. The reverse
was true in 2009 with net exports accounting for 5.7 percentage points and investment –4.9 percentage points of final demand growth. In China, the financial contagion was through trades. Net exports
were the only component to fall (by 2.4 percentage points) in 2009, while other final demand components expanded handsomely. In the subsequent years, investment growth softened from an all-timehigh of 9.3 percentage points in 2009 to the decade-norm of 4.5 percentage points in 2012. This contributed to a slowdown in growth. It is worth noting that the level of investment growth in China in
the past decade is unprecedented historically. Hong Kong also took a hard hit in terms of net exports
in 2009, which fell by 3.0 percentage points. Household consumption growth slowed considerably in2009 to 0.4 percentage point before bouncing back to its normal range of 3–5%. 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 uncertain.
Household consumption fell by 1.4 percentage points and 0.9 percentage points, whereas investment
fell by 3.6 percentage points and 4.0 percentage points in the US and EU15, respectively. In the subsequent years, there was no further retrenchment in these activities, which still struggled to grow. Whenthe final demand components returned to growth, we see governments in the US and EU15 go
through a period of fiscal austerity in 2011 and 2012, when government consumption contracted
marginally. As the euro crisis deepened and was answered with further austerity policy, both household consumption and investment contracted in 2012. That is, of the four final demand components,
only net exports were growing. Japan was the only Asian country in which the global financial stormof 2007–2008 caused deeper retrenchment in its economy than the Asian financial crisis of 1997–1998(Figure 37).

4

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

53©2014 Asian Productivity Organization

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 valleys, particularly in the
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. However, its economy is still very dependent on oil and gas and related industries, which accounted for 56% of its GDP in 2012 (Figure 67, p. 88) – roughly 80% of its export earnings, and 70% of
government revenues in the 2000s.35 In contrast, Bahrain has diversified into a regional banking andfinancial center and benefited from the regional boom in recent years. Even so, petroleum production
and processing accounted for 25.5% of its GDP in 2012 (Figure 67) – about 60% of export earnings,
and 75% of government revenues in the 2000s.36 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 well they candiversify away from oil and gas while the stock of natural resources remains.

4 Expenditure%
60

Bahrain%20

Bangladesh

15

45

20

10

30

10

5
15

0

0

%
15

0

−5

−15
−30

−10

−10
−15
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

0
3
−6

0

0

−5
−10

Iran

−24
1971 1976 1981 1986 1991 1996 2001 2006 2011

%
10

Japan

6

4

0

0

2

−8

−6

0

−16

−12

−2

−24

−4

−32

−6

−18
−24

1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

KuwaitMalaysia

150

%
18

20

0

10

0
−6

−50

0

−12

−100

−10

−18

−150
−200

−20

−24
1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

Myanmar

12

%
12

Nepal

©2014 Asian Productivity Organization

Oman

30

9

20

6

4

1971 1976 1981 1986 1991 1996 2001 2006 2011

%
40

8

10

0

3

−4

0

0

−10

−8
−3

−12
−16

−20
−30

−6
1971 1976 1981 1986 1991 1996 2001 2006 2011

Household consumption

54

Mongolia

30

6

50

1971 1976 1981 1986 1991 1996 2001 2006 2011
%
40

12

100

%
16

Korea

12

6

8

1971 1976 1981 1986 1991 1996 2001 2006 2011
%
18

8

16

%
200

−18

−6
1971 1976 1981 1986 1991 1996 2001 2006 2011

%
24

−12

−3

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

8
4
0
−4
−8

%
60

1971 1976 1981 1986 1991 1996 2001 2006 2011

Saudi Arabia%
15

Philippines

10

20

5

10

0

0

−5

−10

−10

−20

−15

%
20

1971 1976 1981 1986 1991 1996 2001 2006 2011

Singapore

1971 1976 1981 1986 1991 1996 2001 2006 2011

Sri Lanka

4

12

10

20

−30

%
18

15

40

Qatar

%
30

6

5
0
−20

−6

−5

−40

−10

Thailand10−121971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

%
20

0

0

%
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

4

6
2

4
2

2
0

0

0

−2

−2

−4

−2
−4

−4
−6

−6
−8

−6
1971 1976 1981 1986 1991 1996 2001 2006 2011

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

Turkey

10
5
0
−5
−10
−15

%
10

APO20

Household consumption

Asia29

%
12

8

10

6

8

4

6

2

4

0

2

−2

0

−4

−2
−4

−6
1971 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

Government consumption

Investment

1971 1976 1981 1986 1991 1996 2001 2006 2011

Net exports

Real GDP

Figure 38 Final Demand Decomposition of Real GDP Growth, 1970–201255©2014 Asian Productivity Organization

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

5.1 Per-Worker Measure of Labor Productivity

5 Productivity
Productivity performance is crucial to a country’s future economic prospects, especially when many
countries 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.37 Two productivity measures are mainly presented in this chapter, namelylabor 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.38 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, cast the Asian countries in a particularly favorable light. 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 18 Asian countries and the US,39 based on the estimates of capital services (see Appendix 3).

5.1 Per-Worker Measure of Labor Productivity

37: 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 such
as H. Zvi Griliches, Dale W. Jorgenson, Charles R. Hulten, and W. Erwin Diewert. See OECD (2001) for a presentation of definitions,
theoretical foundations, and a number of practical issues in measuring productivity.
38: 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.
39: In this Databook, the TFP estimates were newly developed for Bangladesh and backwardly estimated until 1970 for Vietnam. The
estimates for factor incomes are revised through the examinations with Vietnam Productivity Centre (VPC) in May 2014.
40: Cross-country level productivity comparisons are notoriously difficult to make and hence subject to much data uncertainty. Estimates should therefore be taken as indicative for broad groupings rather than precise ranking. The level of labor productivity in
Singapore was slightly lower than the US level in 2011, in the Databook 2013 which was based on the 2005 benchmark PPP. However, in this Databook, it was upwardly revised by 16% due to the use of the new 2011 benchmark PPP. (See Box 1)57©2014 Asian Productivity Organization

Figure 39 presents the cross-country comparisons of labor productivity levels in 2012, measured as
GDP per worker in US dollars. The countries naturally bundle into groups. On this measure, Singapore
is the leading economy, more than 10% larger than the US level.40 Hong Kong and the ROC 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. 32). Japan took the fifth place, with productivity levels at 35% below the US.
Korea and Malaysia followed, with gaps of 47% and 55%, respectively. Thereafter, a number of5 Productivity

countries from among the Asia group followed withlabor productivity levels at less than 25% of the US,
pulling down the average performance of the group
to 20% for the APO20, 20% for Asia29, and 18% for
ASEAN. Bringing up the rear were China and India,
with productivity levels that were 16% and 12% of
the US level, respectively.
In 2000–2012, the APO20 as a group has achieved
little change in its labor productivity relative to theUS, stagnating at around 20%, while Asia23’s has risen from 13% to 18% (Table 8). In 2000, Hong Kong
sustained a productivity gap of 17% with the US, but
by 2012 the gap had narrowed to around 6%. In contrast, the relative productivity level of Singapore
against the US has been slightly deteriorated overthe last 12 years.

©2014 Asian Productivity Organization

China and India are the two giant and fast-emerging
economies in Asia. China began with one-third of India’s productivity levels in 1970. Four decades later itshows signs of pulling ahead of India (Figure 40).
China’s relative performance against the US moved
up from 2% in 1970 to 7% in 2000 and 16% in 2012,
compared with the corresponding figures of 6%, 8%,
and 12% for India.41

Singapore
US
Hong Kong
ROC
Australia
EU15
Iran
Japan
Korea
TurkeyMalaysia
Sri Lanka
Thailand
ASEAN6
East Asia
APO20
Indonesia
Asia29Mongolia
Asia23
ASEAN
Fiji
China
Philippines
Pakistan
India
South Asia
VietnamLao PDR
CLMV
MyanmarBangladesh
Nepal
Cambodia

114.4
102.6
96.9
83.8
83.0
74.0
67.1
66.9
54.8
48.3
46.6
23.3
22.9
22.9
22.8
20.3
20.0
20.0
19.0
18.6
18.0
17.4
16.9
14.7
13.9
11.9
11.5
7.9
7.9
7.2
6.7
6.0
4.6
4.6

0

20

Thousands of US dollars (as of 2012)

40

60

80

100

120

Figure 39 Labor Productivity Level by
Per-Worker GDP, 2012___GDP at constant basic prices per worker,
using 2011 PPP, reference year 2012

The figures for GCC countries and Brunei are uncharSource: APO Productivity Database 2014.01.
acteristically high, especially in 1970. There are noticeable variations within the country group. The
Thousands of US dollars (as of 2012)
atypically high figures in the early period reflect
16
the natural resource rents (the value of the re14
source over and above the cost of extraction)
12
Chinawhich are erroneously included in these coun10
tries’ GDP. The extent of exaggeration appears to
8
be proportional to their oil production. Saudi
6
India
Arabia has the largest proven oil reserves in the4world and is the largest world oil exporter. Ku2
wait has the fourth-largest oil reserves in the0world. In addition, Qatar has become the fourth1970 1975 1980 1985 1990 1995 2000 2005 2010
largest exporter of liquefied natural gas. In
contrast, Bahrain has the smallest oil reserve
Figure 40 Labor Productivity Trends of China
compared to its peers. Its dependence on oil isand India, 1970–2012___GDP at constant basic prices per worker, using
therefore considerably lower and it has worked
2011 PPP, reference year 2012
to diversify its economy over the past decade(see Figure 82, p. 104).42
Source: APO Productivity Database 2014.01.

41: 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 2012___GDP at constant basic prices per worker, using 2011 PPP, reference year 2012
1970

1980

(%)

1990

(%)

(%)

2000

(%)

2010

(%)

2012

(%)

Iran
SingaporeJapan
Hong Kong
Fiji
ROC
Malaysia
Philippines
Korea
Sri Lanka
Pakistan
Mongolia
Indonesia
Thailand
India
Bangladesh
VietnamChina

39.2 100.0
30.6 78.2
26.3 67.0
21.5 54.8
15.0 38.2
13.3 34.1
12.4 31.6
9.1 23.2
8.3 21.3
6.0 15.2
5.9 15.1
5.7 14.5
5.1 13.0
5.1 13.0
3.5 8.8
3.3 8.5
2.3 5.9
1.0 2.5

Singapore
Iran
Japan
Hong Kong
ROC
Malaysia
Fiji
Korea
Philippines
Sri Lanka
Mongolia
Indonesia
Thailand
Pakistan
India
Bangladesh
Vietnam
Nepal
MyanmarChina

43.2 100.042.2 97.5
37.6 86.9
35.6 82.3
23.6 54.6
19.0 44.0
14.2 32.9
13.4 31.0
10.7 24.8
8.7 20.1
8.5 19.7
8.1 18.8
7.1 16.4
7.0 16.1
3.9 9.1
3.4 8.0
2.4 5.6
2.3 5.4
1.5 3.5
1.5 3.4

Singapore
Hong Kong
Japan
Iran
ROC
Korea
Malaysia
Fiji
ThailandSri Lanka
Indonesia
Pakistan
Philippines
Mongolia
India
Bangladesh
Nepal
Lao PDR
Vietnam
China
Myanmar64.5 100.0
56.2 87.1
53.9 83.5
42.2 65.3
38.9 60.2
25.2 39.1
25.0 38.8
15.0 23.3
11.1 17.1
10.6 16.4
10.6 16.4
10.0 15.5
9.8 15.2
9.5 14.6
4.8 7.4
3.5 5.5
3.3 5.2
3.2 4.9
2.7 4.2
2.3 3.6
1.5 2.3

Singapore
Hong Kong
ROC
Japan
Iran
Korea
Malaysia
ThailandFiji
Sri Lanka
Indonesia
Pakistan
Philippines
Mongolia
India
China
VietnamLao PDR
Bangladesh
Nepal
Cambodia
Myanmar95.3 100.0
69.8 73.2
62.1 65.2
60.3 63.2
46.9 49.3
40.0 41.9
36.4 38.2
16.9 17.8
15.6 16.4
14.1 14.8
13.1 13.7
12.1 12.7
11.3 11.9
10.0 10.5
6.4 6.7
5.6 5.9
4.7 4.9
4.5 4.8
4.5 4.7
4.1 4.3
2.7 2.8
2.3 2.4

Singapore
Hong Kong
ROC
Iran
Japan
Korea
Malaysia
ThailandSri Lanka
Indonesia
Fiji
Mongolia
China
Philippines
Pakistan
India
VietnamLao PDR
MyanmarBangladesh
Nepal
Cambodia113.7 100.0
95.8 84.2
82.1 72.2
69.2 60.8
66.2 58.2
53.8 47.3
45.0 39.6
21.8 19.2
20.5 18.0
18.1 15.9
17.0 14.9
14.7 12.9
14.5 12.7
13.7 12.1
13.6 12.0
11.1 9.7
7.4 6.5
7.1 6.3
6.1 5.4
5.7 5.0
4.5 4.0
4.1 3.6

Singapore
Hong Kong
ROC
Iran
Japan
Korea
Malaysia
Sri Lanka
ThailandIndonesia
Mongolia
Fiji
China
Philippines
Pakistan
India
VietnamLao PDR
MyanmarBangladesh
Nepal
Cambodia

114.4 100.0
96.9 84.7
83.8 73.3
67.1 58.6
66.9 58.5
54.8 47.9
46.6 40.7
23.3 20.4
22.9 20.0
20.0 17.5
19.0 16.6
17.4 15.2
16.9 14.8
14.7 12.9
13.9 12.1
11.9 10.4
7.9 6.9
7.9 6.9
6.7 5.9
6.0 5.3
4.6 4.0
4.6 4.0

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE

129.8 331.2
625.0 1595.2
120.1 306.5
304.7 777.6
212.1 541.3
97.5 248.9

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLMV
GCC(reference)
US
EU15

118.6
244.3
164.0
258.0
213.1
359.3
414.2

274.3
565.1
379.4
597.0
493.0
831.1
958.3

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLMV
GCC(reference)
US
EU15

87.9
99.2
175.4
166.1
117.6
223.7
200.0

136.2
153.7
271.8
257.3
182.3
346.5
309.8

104.0
193.1
151.6
222.0
131.4
192.9
180.0

109.1
202.6
159.1
232.9
137.8
202.4
188.9

63.4
127.0
94.8
161.8
126.6
126.1
144.7

Australia
Turkey59.8
26.9

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLMV
GCC(reference)
US
EU15
EU27
Australia
Turkey

70.9
157.5
88.9
209.4
140.7
141.6
163.8

55.3 127.9

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLMV
GCC(reference)
US
EU15
EU27
Australia
Turkey

72.1
144.5
107.8
184.0
144.0
143.4
164.6

Australia

Bahrain
KuwaitOman
Qatar
Saudi Arabia
UAE
Brunei(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLMV
GCC(reference)
US
EU15
EU27
Australia
Turkey(regrouped)
8.6 22.0
APO20
5.1 12.9
Asia23
5.7 14.5
Asia294.8 12.3
East Asia
4.0 10.1
South Asia
6.4 16.3
ASEAN
7.1 18.1
ASEAN6
3.8 9.8
CLMV
277.4 708.0
GCC(reference)
54.6 139.4
US37.3 95.2
EU15
Australia

48.2 122.9

11.1 25.6
6.5 15.0
7.6 17.5
6.5 15.1
4.5 10.4
7.9 18.3
10.1 23.3
2.3 5.4
240.4 556.1
60.6 140.2
48.2 111.4

13.5 20.9
7.8 12.1
8.6 13.3
8.0 12.4
5.4 8.4
9.8 15.1
12.5 19.4
2.6 4.0
134.9 208.9
70.2 108.8
57.3 88.7
92.6
41.7

15.7 16.5
10.8 11.4
11.7 12.3
11.9 12.4
7.0 7.4
12.5 13.1
16.4 17.2
3.8 4.0
153.4 160.9
84.6
68.9
61.5
73.9
34.1

88.7
72.3
64.5
77.5
35.8

19.7 17.3
17.2 15.1
18.4 16.2
20.6 18.1
10.8 9.5
16.7 14.7
21.3 18.7
6.7 5.9
141.4 124.4
100.5
73.4
67.4
80.3
47.7

88.4
64.5
59.2
70.6
42.0

5

62.0
137.6
77.7
182.9
123.0
123.7
143.1

20.3 17.7
18.6 16.3
20.0 17.4
22.8 19.9
11.5 10.0
18.0 15.7
22.9 20.0
7.2 6.3
139.6 122.0
102.6
74.0
68.5
83.0
48.3

89.6
64.7
59.9
72.5
42.2

When labor productivity growth is compared however, the ranking of countries is substantially reshuffled (Table 9). In the 2000s there was a spurt in labor productivity growth among low-income
countries. While they were scattered around the table in the earlier periods, by 2000–2005 the six

42: The GCC countries have also been experiencing high population growth, especially in the late 1970s and the early 1980s. In
2000–2012, this has somewhat stabilized at around 3.0% per year, except in the Qatar and the UAE where the population grew at
9.8% and 9.2%, 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©2014 Asian Productivity Organization

Unit: Thousands of US dollars (as of 2012).
Source: APO Productivity Database 2014.01.

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 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 the APO Productivity Database 2014 (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 late 1980s
and the beginning of the 1990s, respectively. In
these periods, China’s low price of labor could bea main source of superior price competitive1970=1.040
ness in labor-intensive manufacturing. The turnChina
ing point is found at around 2008, in which the35
ROC
Hong Kong
price of labor started to increase sharply relative30
Korea
to capital.
Singapore
25
Japan

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 thatthe aggravation of income disparity is a serious
concern, the alleviation of poverty in China arecertainly great achievements. The Chinese economy has overcome its first-round of economic
development issues and now faces new challenges to move beyond the upper middleincome plateau.

20
15
10
5
0
1970 1975 1980 1985 1990 1995 2000 2005 2010

Figure B4 Price of Labor Relative to Capital in
China, Japan, and the Asian Tigers, 1970–2012
Source: APO Productivity Database 2014.01.

©2014 Asian Productivity Organization

countries with the fastest labor productivity growth were all from Group-L4 (as defined in Table 6, p.
29). In the latest period, 2005–2012, five out of the top six were from Group-L4 and one from GroupL3. Among them, China has been sustaining rapid productivity growth in the past two decades. Its
growth accelerated to an average of 9.5% per year in 2005–2012 from 7.1% per year in 1995–2000 and
8.6% per year in 2000–2005. This compares with India at 6.9%, 3.4%, and 2.6% over the same periods.
Labor productivity growth amongst the Asian Tigers was steady, ranging from 2.6% to 3.3% on average per year in 2000–2005. This performance was sustained in 2005–2012, except in Singapore. While
Singapore’s average annual productivity growth slowed significantly to 0.4%, the others enjoyedgrowth of about 2.4% in 2005–2012. The 2000s were an era when labor productivity deteriorated in
GCC countries. The decline accelerated from –0.4% to –1.0% between the two halves of the 2000s.
As a group, Asia23 achieved the highest labor productivity growth in recent years, reaching 5.2% on
average per year in 2005–2012, up from 3.6% in 2000–2005. Within Asia, labor productivity growthhas been accelerating in both South Asia and East Asia, to 5.5% and 6.0% in 2005–2012, respectively.
South Asia displayed a newfound vigor in recent years. In contrast, average annual productivity
growth in the US slowed abruptly to 1.3% between 2005 and 2012, after a decade of over 2.0% growth
per year. The EU15 shows signs of weakening as well, slowing in every successive period from 2.3% in
the first half of the 1990s to 0.4% in the most recent period of 2005–2012. Japan’s labor productivity

60

5.1 Per-Worker Measure of Labor Productivity

Table 9 Labor Productivity Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2012___Average annual growth rate of GDP at constant basic prices per worker, using 2011 PPP
1990–1995

1995–2000

KuwaitChina
Thailand
Malaysia
Indonesia
Vietnam
ROC
Korea
Cambodia
Singapore
Sri Lanka
Hong Kong
Pakistan
Lao PDR
MyanmarBahrain
India
Nepal
Bangladesh
Iran
Japan
Saudi Arabia
Qatar
Philippines
BruneiFiji
Mongolia
UAE
Oman(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLMV
GCC(reference)
US
EU15

13.1
10.6
8.2
6.6
5.7
5.4
5.2
5.0
4.3
4.1
4.1
3.7
3.5
3.3
3.2
3.0
2.6
2.4
2.3
1.4
0.9
0.6
0.3
−0.1
−0.2
−0.4
−1.3
−3.7
−9.3

Australia
Turkey

2.2
1.3

2.1
3.9
3.8
4.5
2.5
4.6
5.4
2.9
0.6
1.5
2.3

China
Oman
Qatar
MyanmarVietnam
Korea
ROC
Lao PDR
Singapore
Cambodia
India
Philippines
Mongolia
Bangladesh
Nepal
Sri Lanka
Saudi Arabia
Japan
Fiji
Malaysia
Iran
UAE
Hong Kong
ThailandBahrainPakistan
KuwaitIndonesia
Brunei(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLMV
GCC(reference)
US
EU15
EU27
Australia
Turkey2000–2005

7.1
6.4
5.5
5.5
5.3
4.2
4.1
3.9
3.7
3.4
3.4
2.9
2.5
2.3
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
−1.5
−1.9
0.9
2.6
2.5
3.4
2.7
0.3
0.0
4.8
1.9
2.3
1.4
1.5
2.0
3.4

Myanmar
China
VietnamLao PDR
Indonesia
Cambodia
IranHong Kong
Singapore
Malaysia
Thailand
Korea
Mongolia
ROC
India
Sri Lanka
Pakistan
Bangladesh
Fiji
Japan
Philippines
Oman
KuwaitNepal
Saudi Arabia
Brunei
Qatar
UAE
Bahrain(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLMV
GCC(reference)
US
EU15
EU27
Australia
Turkey2005–2012

10.4
8.6
5.5
4.1
3.7
3.6
3.5
3.3
3.1
3.0
2.9
2.9
2.7
2.6
2.6
2.5
2.0
1.9
1.5
1.2
1.1
1.1
0.9
0.5
−0.2
−0.6
−0.9
−1.8
−4.8
1.2
3.6
3.5
4.8
2.1
3.1
2.9
6.0
−0.4
2.1
0.9
1.3
1.3
5.9

China
MyanmarMongolia
India
Sri Lanka
Cambodia
Lao PDR
VietnamIndonesia
Philippines
Bangladesh
Iran
Korea
ROC
Hong Kong
Thailand
Malaysia
Nepal
Saudi Arabia
Japan
PakistanFiji
Singapore
Qatar
BruneiBahrain
UAE
KuwaitOman(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLMV
GCC(reference)
US
EU15
EU27
Australia
Turkey1990–2000

9.5
7.9
7.2
6.9
5.4
5.0
4.9
3.6
3.4
3.0
2.9
2.6
2.4
2.4
2.4
2.2
1.4
1.3
1.1
0.6
0.6
0.4
0.4
−0.2
−0.9
−2.1
−3.1
−3.5
−8.4
2.8
5.2
5.1
6.0
5.5
3.0
2.7
4.7
−1.0
1.3
0.4
0.6
0.8
0.7

China
KuwaitVietnam
ROC
Korea
MyanmarThailandSingapore
Malaysia
Cambodia
Lao PDR
India
Qatar
Sri Lanka
Bangladesh
Hong Kong
Indonesia
Nepal
PakistanBahrain
Philippines
Japan
Saudi Arabia
IranMongolia
Fiji
BruneiOman
UAE(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLMV
GCC(reference)
US
EU15
EU27
Australia
Turkey2000–2012

8.9
6.7
5.4
4.7
4.6
4.4
4.3
3.9
3.7
3.7
3.6
3.0
2.9
2.9
2.3
2.2
2.1
2.0
1.9
1.7
1.4
1.1
1.1
1.1
0.6
0.4
−1.0
−1.5
−1.5
1.5
3.3
3.2
3.9
2.6
2.5
2.7
3.8
1.3
1.9
1.8
1.5
2.1
2.4

China
MyanmarMongolia
India
Lao PDR
Vietnam
Cambodia
Sri Lanka
Indonesia
IranHong Kong
Korea
Thailand
ROC
Bangladesh
Philippines
Malaysia
Singapore
Pakistan
Nepal
Fiji
Japan
Saudi Arabia
Qatar
Brunei
KuwaitUAE
BahrainOman(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLMV
GCC(reference)
US
EU15
EU27
Australia
Turkey

9.1
8.9
5.3
5.1
4.6
4.4
4.4
4.2
3.5
3.0
2.7
2.6
2.5
2.5
2.5
2.2
2.1
1.5
1.1
1.0
0.9
0.9
0.6
−0.5
−0.8
−1.7
−2.6
−3.2
−4.5

5

2.1
4.5
4.4
5.5
4.1
3.0
2.8
5.3
−0.8
1.6
0.6
0.9
1.0
2.9

growth performed closer to that of other mature economies. Having managed to grow at 1.2% on
average per 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

61©2014 Asian Productivity Organization

Unit: Percentage.
Source: APO Productivity Database 2014.01.

5 Productivity

US=100120
100

US=100120
Cambodia
ROC
Singapore

China
Korea

100

Hong Kong
Lao PDR
MyanmarVietnam

India
Malaysia
Sri Lanka

Indonesia
Mongolia
Thailand

80

80

60

60

40

40

20

20

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

Figure 41.1: Group-C1 Countries
US=100120

US=100120
100

Figure 41.2: Group-C2 Countries

Bangladesh
Nepal
EU15

Japan
Pakistan
TurkeyFiji
Philippines

100

Iran
Australia

80

80

60

60

40

40

20

20

0
1970 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, 1970–2012___Indices of GDP at constant basic prices per worker, using 2011 PPP
Source: APO Productivity Database 2014.01.

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).

©2014 Asian Productivity Organization

Among the countries that are catching up with the US in per capita GDP (Group-C1 and Group-C2),
the Asian Tigers have made a tremendous effort in improving their relative labor productivity over the
past four decades. Singapore passed the US in the middle of the 1990s and Hong Kong closed the gap
from 39% in 1970 to 6% in 2012 (Figures 41.1 and 41.2). Similarly, the ROC and Korea reduced a gapof around 80% initially to 20% and 45% by 2012, respectively (Figure 41.1). Malaysia is making
steady progress, raising its relative productivity level from 23% of the US in 1970 to 45% in 2012
(Figure 41.2). The rest of the countries in these two groups all display an initial relative labor productivity
level of below 15%, but have shown signs of a strong and promising start in their catch-up process inthe past decade.43
Countries 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 produc­
tivity. Japan is the only high-income Asian country in this group, while the rest (except Iran) are all
low-income countries with per capita GDP less than 30% of the US. Japan showed strong catch-up
43: 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.

625.2 Per-Hour Measure of Labor Productivity

behaviors in the earlier period, with relative labor productivity peaking at 77% of the US in 1991. Since
then the gap has widened again to over 30% in 2012. Similarly EU15, a reference economy
with high income, has seen its productivity gap double against the US since 1995, from 12% to
28% in 2012; whereas the low-income countries have managed little catch-up (Figure 41.3) or adeclining 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 105% in 1976 to 52% in 1988, before
recovering to 65% in 2012.

5

5.2 Per-Hour Measure of Labor Productivity

−47

−50
−55

−60

−60

−53
−58

−54

−67

−70
−80
−90
−100

Singapore−29 −28−35−40−96−97 −94−96

−92
−95

−86
−88 −86−90 −89
−91

−80
−84
−84
−88

−78 −77−84 −82

Per-worker GDP
Per-hour GDP

Figure 42 Labor Productivity Gap by Per-Worker and PerHour GDP Relative to the US, 2012___GDP at constant basic prices per worker and hour, using 2011 PPP
Source: APO Productivity Database 2014.01.

44: 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 arethen 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.
45: The labor productivity gap for country x is country x’s labor productivity divided by the US’s labor productivity in Figure 42.

63©2014 Asian Productivity Organization

Based on GDP at constant basic
prices per hour worked, US laborproductivity has been able tosustain a big lead over even the
Asian high performers (Table
10).46 In 1970, the US productivity level was nearly 2.5 times thatof Japan. This gap was reduced
to around 36% in 1990. Since
1990, Japan’s pace in closing the
gap has slowed. By 2012, a sizable

EU15

−35

Australia

ROC

−35
−38

−30

Hong Kong

Japan

Iran

TurkeyMalaysia

Korea

Sri Lanka

ThailandIndonesia

China

Philippines

Pakistan

India

Bangladesh

Vietnam

Cambodia

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 18 Asian countries, although the quality of the estimates may vary considerably across countries.44
Figure 42 shows how the productivity gap against the US in 2012 varies depending on which measureof labor productivity is used.45 The productivity gap with the US widens for all Asian countries when
the differences in working hours are taken into account. However, for 11 of these countries, the adjustments are within 2–5 percentage points, and hence are not deemed as statistically significant. In contrast,
the choice of labor productivity measure makes a significant difference for the previously high-performing countries in their relative performance. On a per-hour GDP basis, the labor productivity gap
with the US widens by 14–31
percentage points for the AsianTigers. Europeans generally wo­
rk fewer hours. This is reflected in%
12comparisons of hourly labor pro100
ductivity showing EU15 in a more
−6
−10
favorable light against the US, al−18−20−19−20 −20
beit only marginally.
−24

5 Productivity

Table 10 Per-Hour Labor Productivity Levels, 1970, 1980, 1990, 2000, 2010, and 2012___GDP at constant basic prices per hour, using 2011 PPP, reference year 2012
1970

1980

(%)

1990

(%)

(%)

Iran
SingaporeJapan
Hong Kong
Malaysia
ROC
Philippines
Sri Lanka
Korea
Indonesia
PakistanThailand
India
Bangladesh
VietnamChina

16.1 100.0
13.9 86.0
12.4 76.9
8.3 51.6
5.6 34.7
5.5 34.2
3.9 24.2
3.8 23.5
3.0 18.7
2.6 16.4
2.5 15.4
2.3 14.4
1.6 9.8
1.6 9.7
1.0 5.9
0.4 2.8

Singapore
Japan
Iran
Hong Kong
ROC
Malaysia
Korea
Philippines
Sri Lanka
Indonesia
Thailand
Pakistan
India
Bangladesh
VietnamChina

20.3 100.0
18.1 89.3
17.3 85.3
14.2 69.9
9.8 48.3
8.6 42.2
4.9 23.9
4.8 23.5
4.4 21.5
4.2 20.6
3.2 15.9
3.0 14.8
1.8 8.7
1.6 8.0
1.0 4.9
0.7 3.3

SingaporeJapan
Hong Kong
Iran
ROC
Malaysia
Korea
Sri Lanka
Indonesia
ThailandPhilippines
Pakistan
India
Bangladesh
VietnamChina

28.5 100.0
26.7 93.8
24.0 84.4
17.4 60.9
16.9 59.3
11.1 39.1
9.2 32.4
5.4 19.1
5.3 18.7
5.0 17.7
4.5 15.8
4.3 15.0
2.2 7.6
1.8 6.2
1.1 3.9
1.1 3.7(reference)US

30.7 190.7(reference)US35.6 175.0(reference)US41.5 145.8

Australia

30.1 148.2

Australia
Turkey33.5 117.6
14.4 50.7

2000

2010

(%)

39.7 100.0
33.1 83.3
30.6 76.9
27.8 70.0
19.3 48.6
15.6 39.2
15.5 39.1
7.4 18.7
7.2 18.1
6.5 16.4
5.3 13.4
5.1 13.0
2.9 7.4
2.6 6.5
2.2 5.6
2.0 4.9
1.1 2.8

SingaporeJapan
Hong Kong
ROC
Iran
Korea
Malaysia
ThailandSri Lanka
Indonesia
Philippines
Pakistan
India
China
Bangladesh
Vietnam
Cambodia(reference)
US
EU15
Australia
Turkey50.0 125.9
41.9 105.6
41.5 104.5
17.6 44.3

Singapore
Hong Kong
ROC
Japan
Iran
Korea
Malaysia
Sri Lanka
ThailandIndonesia
China
Philippines
Pakistan
India
VietnamBangladesh
Cambodia(reference)
US
EU15
Australia
Turkey(%)

49.0 100.0
40.2 82.1
39.0 79.6
38.2 78.0
29.3 59.8
23.7 48.5
19.6 40.0
10.2 20.8
9.5 19.5
8.7 17.7
6.6 13.4
6.5 13.3
5.9 12.1
5.1 10.5
3.1 6.3
2.4 4.9
1.6 3.4
60.7 123.9
46.3 94.7
47.4 96.9
25.4 51.9

2012
Singapore
Hong Kong
ROC
Japan
Iran
Korea
Malaysia
Sri Lanka
ThailandIndonesia
China
Philippines
Pakistan
India
VietnamBangladesh
Cambodia(reference)
US
EU15
Australia
Turkey(%)

49.5 100.0
43.4 87.7
39.8 80.4
38.4 77.5
28.3 57.2
24.4 49.4
20.5 41.4
11.3 22.7
10.0 20.3
9.9 19.9
7.7 15.5
6.9 13.9
6.1 12.3
5.5 11.1
3.4 6.8
2.5 5.1
1.8 3.7
61.5 124.3
47.0 95.0
49.1 99.3
26.0 52.6

Unit: US dollar (as of 2012).
Source: APO Productivity Database 2014.01.

gap of 38% remained. The gap between the US and the Asian leader of the past decade (Singapore)has been constant at around 20%. This is in contrast with the picture painted by the per-worker productivity measure, in which the Asian leaders have overcome or almost closed the gap with the US(Figure 41).

©2014 Asian Productivity Organization

Thousands of US dollars (as of 2012)

The levels of labor productivity for the top six
economies – Japan, Iran, and the four Asian Tigers – maintained their relative positions foralmost four decades. The progress of labor productivity in these countries during 1970–2012 isshown in Figure 43. Within four decades, GDP
per hour has roughly tripled for Japan and Singapore. Hong Kong and the ROC have improvedby five and eight times in this period and haveovercome Japan in 2006 and 2010, respectively.
They were ahead of Korea, despite the duo’s effort in catching up with Japan by 2.3% per year
on average, respectively, over the past four decades (1970–2012). If they could maintain thiseffort at the same pace, it would take Korea 20
years to finally draw level with Japan.

50
40
30

ROC
Hong Kong
Japan
Korea
Singapore20
1001970 1975 1980 1985 1990 1995 2000 2005 2010

Figure 43 Labor Productivity Trends in Japanand the Asian Tigers, 1970–2012___GDP at constant basic prices per hour, using 2011
PPP, reference year 2012
Unit: Thousands of US dollars (as of 2012).
Source: APO Productivity Database 2014.01.

46: 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.

645.2 Per-Hour Measure of Labor Productivity

Over the past four decades, hourly labor productivity growth ranged from 1.2% (Bangladesh) to 6.8%
(China) on average per year, compared with the US at 1.7% and Australia at 1.5% (Figure 44). Amongthe 16 Asian countries compared, only Bangladesh, Iran, and the Philippines grew slower than the US.
Between the two sub-periods (1970–1990 and 1990–2012), there is a notable deceleration in thehourly productivity growth for 11 of 16 Asian countries. For example, 2.6 percentage points and 2.2
percentage points were shaved off productivity growth in the earlier period in Hong Kong and Japan,
respectively. Five Asian 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 9.0% between the two sub-periods.

5

The deceleration of labor productivity growth, in most countries, between the two sub-periods, reflect weaknesses in output growth. Figure 45 shows all countries except Bangladesh experienced aslowdown in hours-worked growth between the sub-periods, which should have worked to boost labor productivity growth, all other things being equal.47 For labor productivity growth to slow implies that
output growth must have been decelerating more than labor input in percentage points. In China,
output growth was reinforced by the slower pace of labor input growth to result in an extraordinary
1970−2012%10

1970−1990

1990−2012
9.0

8
6.8

6
5.0

5.6 5.6
4.7
3.9

4

3.7 3.5

5.0
4.3

3.13.1 3.03.03.0

2.7 2.6 2.52

2.1

3.9 3.8 3.6

4.44.2
3.5 3.5

3.9 3.7

2.7
1.7 1.5

1.8 1.5 1.5

1.41.3 1.2

1.0 0.8 0.7

0.6

3.3 3.1

2.82.8 2.72.7

2.5 2.2

1.9 1.81.7

1.61.61.6

0.4 0.3

Pakistan
BangladeshJapan
Australia
US
Philippines
Iran
Singapore
TurkeyHong Kong
Malaysia
Indonesia
ThailandSri Lanka
Cambodia
ROC
India
Korea
Vietnam
China

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

Banglades
Iran
Philippine
Australia
US
Pakistan
TurkeySri Lanka
Japan
India
VietnamSingapore
Malaysia
Indonesia
ThailandCambodiaHong Kong
ROC
Korea
China

0

5.3

Figure 44 Labor Productivity Growth, 1970–2012, 1970–1990, and 1990–2012___Average annual growth rate of GDP at constant basic prices per hour

Source: APO Productivity Database 2014.01.
Note: The starting periods for Australia, Cambodia, and Turkey are 1978, 1993, and 1988, respectively.

1970−2012
4
3
2
1
0

1970−1990

4.5

1990−2012

3.9
3.6
3.2
2.8 2.7 2.6

2.6 2.6

2.4 2.42.3 2.3

2.12.1

1.9

3.5 3.4

3.2 3.2 3.1 3.13.1

1.7 1.7 1.7

3.7 3.5
3.0

2.7 2.7 2.72.6

2.9
2.6

2.5

2.3
1.7

2.2 2.2 2.1

1.5

2.1 2.0 2.0
1.4 1.2 1.2

1.1
0.6

1.2

0.8 0.8

0.6 0.5

−0.1
−0.7

−1

Japan
Korea
US
China
ROC
Hong Kong
Fiji
ThailandMongolia
Sri Lanka
Indonesia
India
Iran
VietnamPhilippines
Pakistan
Malaysia
Singapore
Bangladesh

Japan
Bangladesh
US
Hong Kong
Iran
Pakistan
India
ROC
Sri Lanka
Mongolia
Philippines
Korea
Thailand
China
VietnamFiji
Malaysia
Indonesia
SingaporeJapan
US
Hong Kong
ROC
Korea
China
ThailandMongoliaFiji
Sri Lanka
Iran
India
Pakistan
Bangladesh
Philippines
VietnamIndonesia
Malaysia
Singapore

Figure 45 Labor Input Growth, 1970–2012, 1970–1990, and 1990–2012___Average annual growth rate of total hours worked
Source: APO Productivity Database 2014.01.

65©2014 Asian Productivity Organization%

5 Productivity

Table 11 Labor Productivity Growth, 1990–1995, 1995–2000, 2000–2005, and 2005–2012___Average annual growth rate of GDP at constant basic prices per hour, using 2011 PPP
1990–1995

1995–2000

China
ThailandIndonesia
Malaysia
Korea
Cambodia
ROC
VietnamHong Kong
Sri Lanka
India
Singapore
PakistanJapan
Bangladesh
Iran
Philippines(reference)
US

10.6
7.4
6.4
6.0
5.5
5.4
5.4
4.7
4.6
4.2
3.6
3.5
3.2
2.3
1.9
1.4
0.4

Australia
Turkey

2.1
1.2

1.4

China
Vietnam
Korea
ROC
Singapore
Philippines
India
Bangladesh
Japan
Cambodia
Sri Lanka
Iran
Malaysia
PakistanThailandHong Kong
Indonesia(reference)
US
EU15
Australia
Turkey2000–2005

7.1
6.6
4.9
4.5
3.2
3.0
2.5
2.5
2.0
1.7
1.4
0.7
0.7
0.6
0.4
0.2
−2.4
2.3
1.8
2.2
2.8

China
Vietnam
Cambodia
Korea
Iran
Singapore
Indonesia
Hong Kong
ROC
Malaysia
ThailandIndia
PakistanJapan
Sri Lanka
Philippines
Bangladesh(reference)
US
EU15
Australia
Turkey2005–2012

8.6
6.7
4.0
4.0
3.7
3.5
3.3
3.1
3.0
3.0
2.9
2.7
2.3
1.7
1.7
1.3
−0.5
2.4
1.3
1.9
5.9

China
India
Sri Lanka
Cambodia
Korea
Indonesia
ROC
Vietnam
Iran
Philippines
Hong Kong
Bangladesh
Thailand
Malaysia
Japan
Pakistan
Singapore(reference)
US
EU15
Australia
Turkey1990–2000
9.5
7.0
5.2
4.4
3.6
3.5
3.0
2.9
2.8
2.8
2.8
2.3
2.2
1.8
0.9
0.8
0.6
1.2
0.7
1.1
1.3

China
Vietnam
Korea
ROC
ThailandSingapore
Malaysia
India
Sri Lanka
CambodiaHong Kong
BangladeshJapan
Indonesia
Pakistan
Philippines
Iran(reference)
US
EU15
Australia
Turkey2000–2012
8.9
5.7
5.2
5.0
3.9
3.3
3.3
3.0
2.8
2.7
2.4
2.2
2.1
2.0
1.9
1.7
1.1
1.9
1.8
2.1
2.0

China
India
Vietnam
Cambodia
Korea
Sri Lanka
Indonesia
Iran
ROC
Hong Kong
Thailand
Malaysia
Philippines
Singapore
PakistanJapan
Bangladesh(reference)
US
EU15
Australia
Turkey

9.1
5.2
4.5
4.2
3.8
3.7
3.4
3.2
3.0
2.9
2.5
2.3
2.2
1.8
1.4
1.2
1.1
1.7
0.9
1.4
3.3

Unit: Percentage.
Source: APO Productivity Database 2014.01.
Note: The annual average growth rate for Cambodia during 1990–1995 replicate their annual average growth rates of
1993–1995 due to absent data.

surge in labor productivity growth. Labor input growth slowed to 0.8% per year on average in thelatter period, from 3.2% in the previous period. Japan was the only economy to experience an actual
fall in labor input in the period 1990–2012. This served to compensate for a sluggish output growth during said period, and to sustain a positive labor productivity growth of 1.6% per year on average.
Table 11 looks more closely at the sub-period from 1990–2012, providing the growth rates of perhour-based labor productivity since 1990. The growth patterns of individual countries generally follow their counterparts closely in per-worker productivity growth, as illustrated in Table 9. In somecountries the two measures diverge greatly and are not at all consistent through the periods compared.48 This contrast was particularly stark in the first half of the 1990s, when Japan’s hourly
productivity growth was 2.3% compared with 0.9% in per-worker productivity growth. However, thedivergence narrowed to 0.3 percentage points in the 2000s. Korea is another country in which hourly
productivity growth was consistently higher than its per-worker counterpart. Instead of narrowing,
the divergence widened to 1.1 percentage points in the second half of the 2000s. Hours worked in the
ROC have also grown at a slower rate than number of workers. The portion ranged from 0.2 to 0.6
percentage points.

©2014 Asian Productivity Organization

One can identify where countries are today in terms of their hourly productivity performance against
a backdrop of Japan’s historical experience. Figure 46 traces the long-term path of Japan’s per-hour

47: 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.
48: 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.

665.2 Per-Hour Measure of Labor Productivity

Labor productivity gap in 2012 relative to Japan(Japan's level in 2012=1.0)

Singapore
1.2

Japan (1885−2012)

Hong Kong

1.1

ROC

1.0
0.9

5

0.8
Iran
0.7
Korea
0.6
Malaysia
0.5
0.4
Sri Lanka

0.3

ThailandChina
Indonesia
Pakistan
India Philippines

0.2
0.1

Cambodia

VietnamBangladesh

1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Figure 46 Labor Productivity Trends of Japan during
1885–2012 and Levels of Asian Countries in 2012___GDP at constant basic prices per hour, using 2011 PPP

Sources: For historical data of Japan, the sources of GDP are Long-Term Economic
Statistics by Ohkawa et al. (1974) during 1885–1954 and the JSNA by ESRI, Cabinet
Office of Japan, during 1955–2012 (including author adjustments). Hours worked data
is based on KEO Database, Keio University, during 1955–2012. During 1885–1954, theaverage hours worked per person are assumed to be constant. For the labor productivity level of Asian countries in 2012, it is based on the APO Productivity Database2014.01.

1970

1980

1990

1970

2000

2010
Japan (21)

1991
1977

Hong Kong (15)

1992
1984

ROC (16)

2000
1995

2012

Korea (17)In pole position are the Asian Tigers, of which Singapore, Hong
Figure 47 Time Durations Taken to Improve Labor ProducKong, and the ROC have alreadytivity by Japan and the Asian Tigers
surpassed Japan. Figure 47 compares the time periods taken by
Sources: See Figure 46.
each country to raise its laborproductivity from 30–70% of Japan’s level today (unit of measurement on the y-axis of Figure 46). What Japan had achieved in the 21
years from 1970 to 1991, Hong Kong, the ROC, and Korea managed to achieve in 15, 16, and 17 years,
respectively (Figure 47). Although the speed of catch-up for latecomers is somewhat increasing, mostAsian countries will still take a long time to catch up with the leaders, currently clustered at around
Japan’s 1960 levels.
49: 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©2014 Asian Productivity Organizationlabor productivity for the period
1885–2012 along the red line, expressed as relative to Japan’s 2012
level (set equal to 1.0).49 A structural break is observed during
World War II when output collapsed. Countries’ relative hourly
productivity levels against Japan
in 2012 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 the country inquestion. The two countries withthe lowest hourly productivity in2012 (Cambodia and Bangladesh)see levels corresponding to Japan’s in the 1920s. Even if they
manage Japan’s long-term productivity growth of 2.9% on average per year, this means it willtake them over a century to catch
up with the Asian leader’s current
position (Singapore, Hong Kong,
the ROC, and Japan). Most Asian
countries are clustered around Japan’s level in the 1950s and early
1970s. Among them, China has
been leading the catch-up effort,
with productivity growing threetimes faster than Japan’s longterm average (Table 11), followedby India and Vietnam.

5 Productivity

5.3 Total Factor Productivity
Labor productivity in the previous sections is only a one-factor or partial-factor productivity measure and does not provide a full perspective of production efficiency. An observation of low laborproductivity could suggest production inefficiency, but it could also reflect different capital intensities
in the chosen 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 isthe 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) laborintensive and with little 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.50
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.51 The required basis for estimating
capital services is the appropriate measure of capital stock. The SNA recommends constructing thenational balance sheet accounts for official national accounts, but this is still not common practicein the national accounts of many Asian countries.52 Even where estimates of net capital stocks areavailable for the whole economy, assumptions and methodologies can differ considerably among
countries. In response to this challenge, harmonized estimates for productive capital stocks andcapital services have been constructed and compiled within the APO Productivity Database built
on the same methodology and assumptions.53 In this methodology, changes in the quality ofcapital 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 harmo­
nized deflator is used for IT capital to reflect the rapid quality change embodied in IT-related assets(see Appendix 2).
The current APO Productivity Database estimates capital services and TFP for 18 Asian countries54 forwhich long-time investment data by type of asset are available or estimated.55 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.56 Labor input is measured by total hours worked (except
for Fiji and Mongolia), without adjustments for changes in labor quality.57©2014 Asian Productivity Organization

Cross-country comparisons of TFP growth for the 18 Asian countries and the US are shown in Figure 48
for the period 1970–2012, and the two sub-periods 1970–1990 and 1990–2012. The average annual

50: 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 capital inputs.
51: 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.
52: 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).
53: 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, 2013) and ourestimates for the period of 1970–2012 are high; they are 88.7% and 93.7% 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 18 Asian countries compared.
54: In APO Productivity Database 2014, the TFP estimate for Bangladesh was newly developed and the estimate for Vietnam was
backwardly estimated until 1970.

685.3 Total Factor Productivity

growth rate of TFP during the entire observation period ranges from almost 0–2%, with the exceptionof China which has achieved considerably high growth of TFP over 3%. Taking the US as the reference
economy, with TFP growth of 0.9% on average per year, 11 Asian countries achieved higher TFP
growth than the US.
Looking at the sub-periods (1970–1990 and 1990–2012), 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. Eleven of the 18 Asian countries experienced acceleration in TFP growth. China
and Iran accelerated the most between the two sub-periods: from 1.7% to 4.4%, and from –1.4% to
1.6%, respectively. More modestly, the TFP growths in India and Mongolia improved from 0.5% on
average per year in the earlier period to 2.4% since 1990 and from –0.03% to 2.1%, respectively.58
Three countries saw their productivity growth more than halved: Thailand,59 Hong Kong, and Japan.
TFP growth in the ROC, Malaysia, and the US was changed slightly.

5

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 1970–2012, China achieved the fastest output
growth of 8.7% on average per year. This is followed by Singapore and Korea, growing at 7.1% and
1970−2012

1970−1990

1990−2012

%

4.4

4.5

3.0

3.1

2.8
1.91.91.5

0.0

1.71.61.6

1.51.51.4

2.6

2.62.52.4
1.71.71.6

1.1

0.90.90.70.50.50.30.3

0.20.1

1.5

1.11.10.90.90.8

0.60.50.10.02.1

1.71.6

1.4

1.31.2

1.01.00.9

0.80.70.50.50.50.4−0.1−0.3−0.3

−1.5

−1.4

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

Iran
PhilippinesFiji
Singapore
Mongolia
Bangladesh
India
Malaysia
US
VietnamJapan
Indonesia
Sri Lanka
Korea
ROC
Pakistan
China
Hong Kong
ThailandFiji
IranBangladesh
Philippines
Singapore
Malaysia
Japan
US
Indonesia
Mongolia
India
Pakistan
ROC
Korea
Hong Kong
Vietnam
Sri Lanka
Thailand
China

Figure 48 TFP Growth, 1970–2012, 1970–1990, and 1990–2012

55: 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% to 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).
56: IT capital is defined as a composite asset of IT hardware (computers and copying machines), communications equipment, andcomputer software.
57: 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 developed in 2012. See Nomura and Amano (2012).
58: In Mongolia, subsoil assets may have a significant role in economic growth, although they are omitted in our measures of capital
inputs.
59: Warr (2006) shows that the average annual TFP growths of Thailand were 2.0% in the period of economic boom (1986–1996),–9.0% during the Asian financial crisis (1996–1998), and 1.6% in the period of recovery (1998–2002). These compare with our estimates of 3.0%, –8.6%, and 2.5%, respectively. The contribution rates of TFP and labor quality (to economic growth) in Vu (2013)
are estimated as 0.7% and 0.3%, respectively, on average per year during 1990–2010. The sum of both is comparable with our estimate of TFP growth of 1.2% in 1990–2012.

69©2014 Asian Productivity Organization

Source: APO Productivity Database 2014.01.
Note: The labor inputs for Fiji and Mongolia are defined by numbers of employment.

5 Productivity

6.8% on average per year, respectively (Figure 49). From these GDP growths, the TFP contribution accounted for over 30% of economic growth in five of the 18 Asian countries compared (Figure 50).
Among them, TFP contribution was the largest in Sri Lanka (38%), China (36%), Thailand (35%), andPakistan (31%). The TFP accounted for about a quarter of economic growth in Hong Kong (29%), Japan (25%), the ROC (24%), and Korea (24%). In contrast, TFP performance was erratic in Singapore,
resulting in its relatively small contribution of only 7% to economic growth over the same period.
China’s productivity performance was outstanding in this period. The average TFP growth was 3.1%
per year during 1970–2012 (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 toJorgenson and Nomura (2005), Japan achieved an annual TFP growth of 3.1% during 1960–1973, evenafter improvements in labor quality had been taken into account in the estimation of labor growth(and, as such, eliminating overestimation in TFP).60 Both the ROC and Korea61 also achieved a TFP
growth of 2.4% and 2.2%, respectively, during the period 1985–2000,62 as shown in the second chartof Figure 51. Since 2000, TFP growth was 2.9% in India.
In the long run, TFP growth has no impact on economic growth for the Philippines and Fiji, while labor
input growth explained 58% and 35% of their economic growth, respectively (Figure 50). Looking at
the breakdown of the period in Figure 51, one can see 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.63
%

%

9

TFP
Non-IT Capital
Output

8
7

3.1

1.6

3

1
0

80
1.7 1.9 1.6

3.7 3.5

1.9

0.4 0.4

9
24 24

36

IT Capital
9

15
31 35

29 27

22
38

0.3

1.0 1.0 1.4

1.4 1.1
1.9 1.5 0.3

3.3

2.1

0.2 0.2

2.1 2.7 2.3 2.8
0.3

1.6 1.7 1.3

0.1
0.4
0.9

1.5

0.2

1.6 1.7

0.1 0.0 0.2

0.9 1.3

0.3

2.0 1.5
0.1

1.5 1.4 1.8

0.2

55 54
0.1

2.5 0.9
0.1

64 56

0.8

0.9
0.1

0.4 1.5
0.9 0.7

40

50

20

3

9

0.7
1.7
0.3
0.0

12

0

27

3
6

6

15 15

5
22

37

4

37 47

43 55
2

5

26 29 24

2

28

19

27

5
25

31
34

27
65

6

32 35

3

67
2

36
1

41

48

4

7
16

32

9

31
51

58

60

Labor
5

3

16

58

26 26
11
−1

Japan
Fiji
US
Iran
Bangladesh
Philippines
Pakistan
Sri Lanka
Mongolia
India
Hong Kong
Thailand
VietnamIndonesia
Malaysia
ROC
Korea
Singapore
China©2014 Asian Productivity Organization

1.0

7

Non-IT Capital

0.9

0.6
0.2

TFP

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

−1

1.5

4.1

4.3

2

120
100

0.5

4.0

4

Labor

0.5

6
5

IT Capital

Figure 49 Sources of Economic Growth,
1970–2012

Figure 50 Contribution Shares of Economic
Growth, 1970–2012

Source: APO Productivity Database 2014.01.
Note: The labor inputs for Fiji and Mongolia are defined bynumbers of employment.

Source: APO Productivity Database 2014.01.
Note: The labor inputs for Fiji and Mongolia are defined bynumbers of employment.

60: 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.
61: 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.
62: 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

Negative TFP growth can be caused by many things, including a rapid, temporary decline in demandor the inefficient use of resources by political interventions to the economy. This is unlikely to be sustainable in the long run. As shown in the year-on-year changes of growth decomposition in eachcountry (Figure 57), the Philippine’s TFP fell severely in the beginning of the 1980s, in which the economy declined by 15.4% for two years from 1983–1985 under the regime of Ferdinand Marcos. In Mongolia, negative TFP growths are observed before the transition to market economy in 1992.
1970−1985%

1985−2000

5

2000−201210

8

0.9 0.8

0.1
2.3 2.06

0.8
5.2 4.1
3.5 3.9

0.1

0.8

2.2
2.5

2.7 1.7

0.1
4.1

1.0 2.1
0.1 3.1 0.1
0.0

0.1

0.1

3.4
0.8

4.1
0.0

1.7

3.2 1.9

0.8

3.3

0.2

2.2 2.2 1.8 1.1

0.8

4.8
3.6

1.2 0.8

3.2
2.1

0.1

4.0 2.9

3.1

2.7
1.9

1.0

1.9

3.7 0.2

5.1

1.2
1.2 1.0

0.8

2.0 2.9

1.8

1.5 1.6 1.2
2.2

2.1
1.9 2.3

0.6 2.6

1.7

1.9

1.5
0.5
0.1

1.8 1.8

1.3

1.0
0.0 0.1
0.3 0.7
0.1
0.0
0.1
0.0
1.8 1.7 2.1 1.6 1.5 1.7 2.0 1.8 1.8 0.3 1.9
2.2 2.8
1.5 1.2
1.0 0.9
0.8 1.1
0.3
−0.9
−1.2
−1.8 −1.5

0.0 1.7 0.7 0.7
0.8 0.1
0.6
0.3
0.1
0.4
0.2 0.6 0.1 0.1 1.5 0.1
0.5
0.1
0.5
1.8
1.7
0.5
1.7
1.6
1.3 1.6 0.9 1.0 1.1 1.2
1.2
1.2
1.0
1.0 1.4 0.8
0.9
0.6
0.4

−0.2
−0.9

0.9
0.2
0.4 0.7 0.3 2.3 1.7 1.1 1.7 0.7
0.8 0.7
1.5 0.2
0.4 0.3 0.6 0.2
1.1 1.0
1.1 1.0 0.9
0.1
0.5
0.3 0.5 0.3
0.4 0.0 0.2
0.1
0.0 0.4
−0.3

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

−2

0.2

0.5

0.3

1.4

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

0

1.8

0.1

1.6 0.8

1.5
2.9

Bangladesh
US
FijiPhilippines
Iran
India
VietnamJapan
Sri Lanka
PakistanThailandMongolia
Indonesia
Malaysia
China
Hong Kong
Singapore
ROC
Korea

0.3

0.5

4.4

2.2

0.5
2.4

2.3

5.4 6.3

2

1.3

0.7

6.3

4

3.7

3.7

0.4

TFP

0.1 0.2

Non-IT Capital

IT Capital

0.4

0.2 0.4 3.3 0.2

0.6 1.2 1.2 1.3
0.3

Labor

OutputFigure 51 Sources of Economic Growth, 1970–1985, 1985–2000, and 2000–2012
Source: APO Productivity Database 2014.01.

100

1985−2000

11 10

11 13
30 27

38

31

40
3

20
0

5

3

1

1

22 21 27 20 20 24

73

2
13

0
29

21

1
2
50

37
6
8

40

6

7
22

30

35

34

17

27

18

32
30 30

44

46

39
53

53 38

50
10

46 29

45

2
13

25

7
14

5
20

6
7
12

25

44
61

19

43

20
42

17 1
2

31 30 11
12

22

29

21
24 3

5
37
23

32 34

62

52 26
46

42

39

3 6
17 20

4 4
20 19

29

40

3

3

36 44
54

1
21

8 14 7 52

11

46 48

11

35
54
11

57

35
51

35 43

40

25

23 21 2243

29

46 34 15 1631034
9 25 28
8 13 9
2

−3

−48

−41

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

TFP

5
6 16

15

31 34

Mongolia
Japan
Fiji
Iran
US
Philippines
Bangladesh
Pakistan
Sri Lanka
Hong Kong
Indonesia
India
Thailand
Vietnam
ROC
Malaysia
Korea
Singapore
China−53−45−37

35

53

7

−8

−12

38 41

40

3

18 2

1

2 3

3

11

56
32

61

68

21

21

39 34

59

84
63

92
2

30

4

2

1

41

32 1

2

1
28

30 47

57

Bangladesh
US
FijiPhilippines
Iran
India
VietnamJapan
Sri Lanka
PakistanThailandMongolia
Indonesia
Malaysia
China
Hong Kong
Singapore
ROC
Korea

−20

7

27

45
72

18

2 26
41

74 60
46 52

2

17 12 22

78
64 64

95

2

1

80
60

2000−2012

118 78 52

Non-IT Capital

IT Capital

Labor

Figure 52 Contribution Shares of Economic Growth, 1970–1985, 1985–2000, and 2000–2012
Source: APO Productivity Database 2014.01.

63: 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©2014 Asian Productivity Organization

1970−1985%

120

5 Productivity

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 34% in Sri Lanka to 76% in Japan.
Among the Asian Tigers, the contribution of capital services ranged from 54% in Hong Kong to 67% in
Singapore, whereas in China and India, it accounted for 52% and 45% of economic growth, respectively.
This compares with 41% in the US, of which 16 percentage points were contributed by IT capital, ashare unmatched by Asian countries. Japan has been leading Asian countries in terms of contribution
from IT capital (11% of economic growth) whereas in other Asian countries it has been 1–9%, with
China and India trailing behind.
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 by capital accumulation more than 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 and52), 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 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.

©2014 Asian Productivity Organization

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 55% on average, while the contribution of TFP became progressively more significant, rising to a share of above 35% on average in
2000–2012. The evident rise in the contribution of IT capital is also noteworthy. In 1970–1985, IT capital accounted for less than 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 of Bangladesh, India, Iran, Pakistan, Sri Lanka, and Indonesia. Between 1985–2000 and 2000–2012, the contribution of IT capital more than doubled in Malaysia and Japan, from 5% to 14%, and from 15% to 34%,
respectively. Hong Kong sustained an IT share of around 10% in the same period. This yearly accumulation of IT investment may have paved the way for countries to capitalize on the productivity gainfrom the IT revolution. Reflecting on these results, capital accumulation appears to be a necessary
step to economic growth. 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. The reasons as towhy this is so, are beyond the scope of this report.
Figure 53 places our estimates among those of OECD for 17 other OECD countries to give readers awider perspective.64 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.
Asian countries are also among those that experienced the fastest TFP growth in the 2000s: 3.9% in
China, 3.8% in Mongolia, 3.1% in India, 2.2% in Sri Lanka, 2.1% in Hong Kong, and 2.0% in both Korea
and Thailand. Though growing at a more subdued pace, the contribution made by TFP in theslower-growing, mature economies should not be underestimated. For example, TFP accounted forhalf or more of economic growth in Germany (67%), Austria (56%), Sweden (52%), and Finland (50%).
Table 12 and Figure 54 show the growth accounting decomposition for individual countries in fiveyear intervals covering the period 1970–2012. The relative importance of drivers behind economic72

5.3 Total Factor Productivity

%

9

TFP

CapitalLabor

Output

3.9

1.6

6

3.1

3.8
2.4 2.4

3

3.0

2.6

0.5

1.2

5

0.1
0.9 1.1 1.0

Italy

Japan

Denmark

Germany

FranceNetherlands

BelgiumFiji

USAustria

United Kingdom

Switzerland

FinlandSpain

CanadaSwedenAustralia

ROC

Hong Kong

Korea

Thailand

1.5

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

2.1
2.1 1.5

1.0

Pakistan

Philippines

Malaysia

Indonesia

Iran

Bangladesh

VietnamMongolia

India

China

1.1 1.1 1.0 1.3

0.3
1.2

2.4

1.5

2.0 2.0 2.1 1.5

New Zealand

0.6

2.1

Sri Lanka

1.2 1.2 1.3

2.0 2.4 2.5

2.8

1.4

Ireland

2.1

Singapore

0.3

2.2 1.7 1.2
1.2

4.1

5.6

3.3

0

1.4

Figure 53 Comparison of Sources of Economic Growth with OECD Countries, 2000–2011
Sources: APO Productivity Database 2014.01 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: Australia and Portugal are until 2010 and the UK is until 2009.

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. 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 3.6% in 1985–1990, when TFP growth also peaked in the ROC, Korea,
Singapore, and Japan, at 4.0%, 3.2%, 2.3%, and 2.1%, respectively. Thereafter, TFP growth slowed until
recent years when countries experienced productivity growth resurgence. This resurgence is also
shared by Malaysia and the Philippines. TFP growth in Mongolia has been particularly strong since1995. It has also bounced back in Indonesia65 and Thailand66 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 2005–2012.

64: The multi-factor productivity in the OECD Productivity Database (OECD, 2013), 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.
65: 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.
66: 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.

73©2014 Asian Productivity Organization

Looking at the decomposition of economic growth in China and India, the two key drivers have been
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 TFP performance that has more bearing in determining the overall economic growth over time. For example, the low economic growth that China experienced in 1985–1990 was explained largely by the lack of TFP growth. Similarly, when output growthslowed from its peak in the latter half of the 1990s, it was due to the slowdown in TFP growth from

5 Productivity

ROC

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

8.5
10.1
6.2
8.5
7.0
5.1
3.5
4.0
2.8
6.4

2.0
1.9
1.1
1.2
1.0
0.3
0.3
0.2
0.9
1.0

(24)
(19)
(18)
(14)
(14)
(6)
(7)
(4)
(32)
(15)

0.5
0.4
0.4
0.3
0.3
0.8
0.6
0.1
0.1
0.4

(6)
(4)
(6)
(4)
(5)
(15)
(18)
(2)
(4)
(6)

6.6
5.3
4.0
3.1
3.4
3.1
2.1
1.5
1.1
3.5

(78) −0.7(52) 2.5(64) 0.8(36) 4.0(49) 2.3(61) 0.9(59) 0.6(38) 2.3(38) 0.7(54) 1.5

Hong Kong

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

6.2
11.0
5.6
7.4
5.1
2.6
4.1
3.9
3.2
5.6

1.9
1.9
0.9
0.4
0.2
1.2
0.5
0.8
−0.3
0.9

(30)
(17)
(16)
(5)
(5)
(48)
(12)
(21)
(−10)
(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)
(7)
(7)

2.7
3.6
4.1
3.0
3.4
2.7
1.3
1.1
0.8
2.7

(44) 1.5 (23)(33) 5.2 (48)(74) 0.2(4)(41) 3.6 (48)(67) 1.0 (20)(105) −2.1 (−80)(31) 1.8 (44)(28) 1.6 (42)(25) 2.5 (79)(47) 1.6 (29)Indonesia

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

8.3
7.8
4.8
7.5
7.6
0.8
4.6
5.6
6.2
5.9

2.1
1.6
2.2
2.3
0.7
1.8
0.7
1.7
−0.1
1.6

(25)
(20)
(47)
(30)
(9)
(225)
(16)
(31)
(−2)
(26)

0.0
0.1
0.1
0.1
0.2
0.2
0.2
0.2
0.2
0.2

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

3.8
4.5
4.1
2.9
3.6
3.2
1.9
2.4
2.8
3.3

(46) 2.3 (28)(58) 1.6 (20)(86) −1.7 (−35)(39) 2.2 (29)(47) 3.1 (41)(399) −4.4 (−543)(42) 1.8 (39)(43) 1.3 (23)(45) 3.3 (53)(56) 0.9 (15)1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

4.4
4.3
4.2
4.9
1.7
0.8
1.2
0.3
0.5
2.6

−0.3 (−7)
0.9
(22)
0.4
(9)
0.4
(9)
−0.4 (−21)−0.7 (−79)−0.3 (−27)−0.4 (−133)0.2(31)0.0 (−1)

0.4
0.2
0.2
0.4
0.3
0.3
0.4
0.2
0.0
0.3

(8) 4.9 (112) −0.6 (−14)(5) 2.6 (60) 0.5 (12)(6) 1.9 (46) 1.7 (40)(9) 1.9 (40) 2.1 (42)(19) 1.7 (100) 0.0(1)(39) 0.9 (110) 0.3 (30)(33) 0.3 (27) 0.8 (66)(53) 0.0 (13) 0.6 (167)(3) −0.2 (−50) 0.6 (116)(11) 1.7 (65) 0.7 (25)

(−8)
(24)
(12)
(47)
(33)
(18)
(16)
(56)
(25)
(24)

Labor

IT

TFP

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

5.7
6.3
10.2
7.6
11.6
8.3
9.3
10.6
8.1
8.7

1.0
1.1
2.4
2.2
0.6
0.7
0.4
0.2
0.2
1.0

(18)
(17)
(23)
(29)
(5)
(8)
(4)
(2)
(3)
(12)

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

5.6
3.7
0.7
3.8
2.7
2.1
2.0
0.7
2.2
2.6

4.1
2.8
1.5
1.0
1.9
0.7
0.3
0.4
0.7
1.5

(73) 0.1(76) 0.1(204) 0.0(27) 0.1(70) 0.2(32) 0.0(15) 0.1(56) 0.1(33) −0.1(58) 0.1(2) 1.9(2) 2.0(6) 1.3(3) 0.0(7) 1.0(−1) 0.7(3) 0.4(11) 0.1(−3) −0.1(3) 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 (61)(19) 0.1 (14)(−2) 1.6 (73)(34) 0.1(5)

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

2.9
3.1
5.0
5.9
5.1
5.7
6.6
8.4
5.4
5.3

1.1
1.2
2.2
2.2
0.9
2.0
2.5
−0.1
1.2
1.5

(38)
(38)
(43)
(38)
(18)
(35)
(37)
(−1)
(22)
(28)

0.0
0.0
0.0
0.1
0.1
0.1
0.1
0.2
0.2
0.1

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

2.1
2.1
2.1
2.0
2.1
2.1
2.0
3.5
3.4
2.3

(72) −0.3 (−10)(68) −0.2 (−8)(41) 0.8 (15)(34) 1.6 (27)(41) 2.0 (39)(38) 1.4 (25)(31) 2.0 (30)(42) 4.7 (56)(63) 0.6 (11)(43) 1.4 (27)1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

9.4
−2.9
3.8
1.4
3.7
4.1
6.8
5.2
−1.6
3.7

0.9
(9)
1.5 (−52)
1.1
(30)
1.2
(87)
0.8
(22)
1.2
(28)
1.1
(16)
0.2
(4)
0.0 (−2)
0.9
(26)

0.0
0.1
0.0
0.1
0.1
0.1
0.2
0.2
0.1
0.1

(0)
(−2)
(1)
(4)
(2)
(2)
(3)
(3)
(−8)
(3)

4.6 (48) 3.9
5.5 (−192) −9.9
2.2 (58) 0.4
0.2 (18) −0.1
0.9 (24) 1.9
1.1 (26) 1.8
2.4 (36) 3.1
2.9 (56) 2.0
2.1 (−132) −3.8
2.5 (67) 0.2

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

9.3
7.3
8.5
9.7
7.4
4.9
4.5
3.9
2.7
6.7

2.3
1.8
1.4
1.9
1.2
0.0
0.3
−0.4
0.7
1.0

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)
(5)
(6)

5.7
6.5
3.9
4.0
4.1
2.8
1.9
1.6
1.4
3.7

(24)
(25)
(16)
(20)
(16)
(0)
(6)
(−9)
(26)
(15)

0.0
0.0
0.0
0.1
0.1
0.2
0.7
0.6
0.4
0.2

CapitalNon-IT(1) 4.2 (73)(1) 4.0 (64)(0) 3.4 (34)(1) 4.3 (57)(1) 3.8 (33)(3) 4.3 (52)(7) 4.3 (46)(5) 5.7 (53)(5) 5.3 (65)(3) 4.3 (50)

China

0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.3
0.2
0.1

Output

Fiji

(30)
(33)
(66)
(40)
(38)
(34)
(77)
(47)
(37)
(48)

IT

India

−0.6
1.2
2.1
1.5
1.6
1.7
4.0
2.8
2.4
1.8

Labor

Iran

−2.0
3.7
3.1
3.7
4.3
5.1
5.3
6.0
6.3
3.8

OutputKorea

Bangladesh

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

CapitalTFP
Non-IT(0) 0.2 (−11) −1.7 (82)(0) 0.5 (14) 1.9 (52)(0) 1.2 (39) −0.2 (−5)(0) 1.7 (46) 0.5 (13)(1) 1.7 (40) 0.9 (21)(1) 2.3 (46) 1.0 (20)(1) 2.3 (43) −1.1 (−21)(4) 2.2 (36) 0.8 (13)(3) 2.0 (32) 1.7 (28)(2) 1.5 (41) 0.3
(9)

Japan

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

0.5
1.2
4.3
0.9
7.1
3.1
3.9
4.2
2.1
3.1

(8)
(19)
(43)
(12)
(61)
(38)
(42)
(39)
(26)
(36)

(42)
(346)
(12)
(−9)
(52)
(43)
(46)
(37)
(242)
(5)

(62) 1.1 (12)(90) −1.4 (−19)(45) 3.0 (35)(41) 3.2 (33)(56) 1.7 (23)(58) 1.6 (32)(43) 1.7 (38)(41) 2.5 (63)(53) 0.4 (16)(55) 1.6 (24)©2014 Asian Productivity Organization

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 accelerated and has increasingly accounted for a greater proportion of economic
growth. In 2005–2012, India achieved TFP growth of 3.5% – its highest in the past four decades.
Through trial and error, China and India invested first and then learned 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 over time in the two countries.
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. This started with the US in the 1990s. Unlike technological advancements in the past, whichwere largely confined to manufacturing, IT is a technology that can permeate the economy and bringabout significant production gains in, for example, wholesale and retail, banking and finance, and

74

0.1
0.1
0.1
0.2
0.3
0.5
0.7
0.7
0.5
0.3

Pakistan

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

3.6
5.8
6.4
5.6
4.6
3.2
4.9
4.1
3.5
4.7

1.4
0.9
1.1
1.2
0.7
1.9
1.9
2.8
1.6
1.5

(39)
(15)
(17)
(22)
(16)
(59)
(40)
(69)
(47)
(32)

0.0
0.0
0.0
0.1
0.1
0.0
0.1
0.1
0.0
0.0

(1)
(0)
(0)
(1)
(2)
(1)
(1)
(2)
(1)
(1)

2.2
2.6
2.6
2.7
2.2
0.9
0.4
0.6
0.3
1.7

(62) −0.1(45) 2.3(41) 2.7(47) 1.7(48) 1.6(29) 0.4(9) 2.4(14) 0.6(9) 1.5(36) 1.5

Singapore

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

9.1
8.2
6.6
8.3
8.2
5.6
4.7
6.4
3.9
7.0

2.6
2.4
1.4
2.2
2.2
1.1
0.5
2.6
1.5
1.9

(28)
(29)
(21)
(27)
(26)
(20)
(12)
(40)
(39)
(27)

0.6
0.4
0.6
0.8
0.9
0.7
0.6
0.6
0.4
0.6

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

7.9
5.2
5.7
3.0
3.3
3.9
2.1
2.0
2.2
4.0

(87) −1.9 (−21)(63) 0.2(3)(86) −1.1 (−16)(36) 2.3 (28)(41) 1.8 (22)(70) −0.1 (−2)(44) 1.5 (32)(32) 1.2 (19)(56) −0.2 (−6)(58) 0.5(7)

Thailand

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

5.5
7.4
5.3
9.8
8.1
0.7
5.3
3.6
3.7
5.6

−0.2
4.5
1.0
3.1
0.3
0.2
1.3
0.7
0.6
1.3

(−4)
(61)
(19)
(31)
(4)
(26)
(24)
(21)
(16)
(24)

0.1
0.2
0.2
0.3
0.5
0.3
0.2
0.4
0.3
0.3

(1)
(2)
(3)
(3)
(7)
(43)
(4)
(11)
(7)
(5)

2.0
1.8
1.8
2.3
4.9
2.7
0.6
1.1
1.0
2.1

(36) 3.7 (67)(24) 1.0 (13)(34) 2.3 (44)(24) 4.2 (42)(60) 2.3 (29)(372) −2.4 (−341)(12) 3.2 (60)(31) 1.3 (37)(26) 1.9 (50)(37) 1.9 (35)

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

2.7
3.6
3.2
3.2
2.5
4.2
2.4
0.7
2.3
2.8

0.5
(19)
1.7
(47)
0.8
(26)
1.3
(40)
0.7
(27)
1.2
(28)
0.0 (−1)−0.5 (−71)
1.0
(43)
(26)
0.7

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)
(19)
(25)
(49)
(9)
(16)

1.2
1.1
0.7
0.8
0.5
0.8
0.7
0.6
0.1
0.8

(46)
(29)
(23)
(24)
(21)
(18)
(31)
(86)
(4)
(27)

0.7
0.6
1.2
0.6
0.8
1.5
1.1
0.2
1.0
0.9

(−2)
(40)
(42)
(30)
(34)
(12)
(50)
(15)
(43)
(31)

(28)
(17)
(36)
(20)
(34)
(35)
(46)
(36)
(45)
(31)

Output

Labor
(9)
(17)
(15)
(61)
(12)
(14)
(32)
(10)
(5)
(19)

IT
0.0
0.1
0.2
0.2
0.1
0.2
0.3
0.4
0.6
0.2

CapitalTFP
Non-IT(1) 2.9 (45) 2.9 (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) 2.9 (45) 2.3 (37)(5) 3.2 (23) 9.4 (68)(4) 2.8 (55) 1.1 (22)Mongolia

(23)
(21)
(29)
(23)
(12)
(30)
(12)
(28)
(26)
(22)

IT

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

6.5
5.4
6.6
3.8
−1.8
3.6
6.3
6.3
13.9
5.0

0.6
0.9
1.0
2.3
−0.2
0.5
2.0
0.6
0.6
0.9

Philippines

1.8
1.7
1.5
1.6
1.1
1.4
0.6
1.3
1.3
1.4

Labor

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

5.6
5.9
−1.3
5.0
2.5
4.5
4.5
4.8
5.1
4.0

3.0
(53)
1.7
(28)
1.8 (−134)
0.9
(19)
1.2
(46)
0.6
(14)
1.2
(28)
0.9
(19)
1.1
(23)
1.4
(35)

0.1
(2)
0.1
(2)
0.1 (−11)
0.1
(2)
0.1
(3)
0.4 (10)0.6 (13)
0.3
(5)
0.1
(3)
0.2
(6)

2.0 (36) 0.5(9)3.3 (55) 0.9 (15)
2.7 (−202) −6.0 (447)
0.7 (14) 3.2 (65)
1.8 (70) −0.5 (−18)
2.5 (57) 0.9 (19)
1.8 (40) 0.9 (19)
1.6 (32) 2.1 (44)
1.5 (30) 2.3 (45)2.0 (51) 0.3(9)

Sri Lanka

7.7
8.2
5.1
6.9
9.2
4.8
4.6
4.6
5.1
6.3

Output1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

4.2
5.6
5.0
3.3
5.3
4.9
4.0
6.2
7.1
4.9

2.0
1.4
2.0
0.2
0.6
2.1
1.4
0.6
1.5
1.3

(48)
(26)
(41)
(6)
(12)
(43)
(36)
(10)
(21)
(27)

0.0
0.0
0.1
0.0
0.1
0.2
0.2
0.3
0.1
0.1

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

1.9
2.0
2.8
1.1
0.3
0.8
1.6
1.9
2.5
1.6

(45)
(36)
(56)
(34)
(6)
(16)
(40)
(30)
(36)
(32)

Vietnam

Malaysia

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

CapitalTFP
Non-IT(1) 4.7 (61) 1.2 (15)(1) 4.8 (59) 1.6 (19)(2) 5.9 (117) −2.5 (−49)(2) 3.0 (44) 2.2 (31)(3) 6.0 (65) 1.8 (20)(11) 5.3 (111) −2.5 (−52)(16) 2.1 (45) 1.3 (27)(15) 1.7 (37) 1.0 (21)(10) 1.8 (36) 1.5 (29)(5) 4.1 (64) 0.5(9)US

5.3 Total Factor Productivity

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

1.8
3.5
6.2
4.4
8.1
7.3
8.0
6.2
5.7
5.7

1.2
1.2
3.3
2.0
2.4
0.5
0.8
2.1
0.8
1.7

(70)
(35)
(53)
(46)
(30)
(7)
(10)
(34)
(14)
(29)

0.0
0.1
0.1
0.1
0.1
0.3
0.3
0.5
0.4
0.2

(1)
(2)
(2)
(3)
(2)
(4)
(4)
(9)
(7)
(4)

1.0
1.1
1.1
1.2
1.7
2.8
3.2
4.2
3.5
2.1

(54) −0.4 (−25)(30) 1.2 (34)(17) 1.7 (28)(27) 1.0 (23)(21) 3.9 (48)(38) 3.8 (52)(39) 3.8 (47)(68) −0.7 (−11)(61) 1.0 (17)(37) 1.7 (31)

0.3
2.1
0.1
2.0
4.3
1.8
0.7
3.4
3.0
1.9

5

(7)
(38)
(2)
(59)
(81)
(37)
(18)
(55)
(43)
(38)

Unit: Average annual growth rate (percentage), contribution share inparentheses.
Source: APO Productivity Database 2014.01.

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
67: 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.

75©2014 Asian Productivity Organizationtransportation and telecommunications (service sectors that have traditionally struggled with slow
productivity growth). Given the share of the service sector in the economy (Figure 70, p. 90), its potential and implications for economic development and productivity gains could therefore be immense.
A frequent question asked by policymakers and researchers is how best to capitalize on the produc­
tivity 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
growth prospects.67

5 Productivity

Bangladesh

%

8
6
4
2
0

–2

1.0
1.0 4.0

0.9
2.7
0.5
1.7
1.9
2.1 1.5 1.6
2.3 2.3 2.1
1.2
1.7 1.7
0.2 0.5 1.2
0.1 0.2
–0.6
–0.2
–1.1
–1.7

1990–1995

1995–2000

2005–2012

2000–2005

1985–1990

1980–1985

1975–1980

1970–1975

Mongolia

–2.5

3

4.4
2.3
2.9 1.1
0.9 7.0
0.6

0.6

3.9

2.4 2.0 2.9
1.0
0.5
0.1 0.2 0.2 0.1 0.5 0.6 0.5–0.2 0.2 0.3
–1.6
–2.5
–2.6

2.9 3.3

0

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

2005–2012

2000–2005

1995–2000–3

3.4

Sri Lanka

%

7
6

0.2

1.4

2.4

5

2.3 1.8

0.8

4

0.3

1.1
1.5 2.3
3.9 0.5
2.1 2.1
0.6 0.4 0.6
0.8 0.9 0.7 0.6 0.5
–1.1
–0.1
–1.9

3

2.0

2.2 2.2

5.2

5.7

3.0 3.3

2.1

1.9

4.3

1.4
2.0

2.0
2.8
0.1

0

0.2
1.1

0.8

1.2
1.3 0.8
1.1

0.7 0.8
0.7 0.5
1.2 1.1 0.7 0.8 0.5
0.8 0.6 0.4
0.2
0.5
0.5
0.3
0.3 0.4–0.1

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

IT capital

Labor

Output1.4

0.9

1.6 2.1
0.8
0.2 0.2 0.2

2005–2012

0.5

1.2

0.7

2000–2005

0.7 1.7

0.6

0.6
0.3
0.1

1995–2000

1.5

0.6

2.1

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

2005–2012

2000–2005

1995–2000

1990–1995

–1

3.3
1.8

2.0

2
1

0.1

US

1980–1985©2014 Asian Productivity Organization

2005–2012

2000–2005

1995–2000

3.1
0.3
1.8 1.1 0.1
1.2 2.4 2.7
1.1
0.1 0.2 0.1

1.0

6

1.6

1990–1995

2.6

–12

9

Singapore

1975–1980

76

1.9
0.8
0.9
0.1

–9.9

Figure 54 Individual Countries’ Growth Accounting Decomposition, 1970–2012
Source: APO Productivity Database 2014.01.

1990–1995

0
–3

%

1.8
1.1 1.4–2.5

1970–1975

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985–1

2005–2012

5.9

1985–1990

0

2.2

1985–19901

1985–1990

2.5
0.2

1.5
0.4
4.6 5.5 1.1 1.2
0.1 0.1 2.2 0.2
0.1
–0.1
0.9

–6

2000–2005

4.8

1980–1985

4.0

1980–1985

3

1.3 1.1
6.0 5.3 0.6 1.3
2.1 1.7
3.0
0.5
0.1 0.1 0.1 0.2 0.3
0.7 0.6

4.7

3
2

0.8

1995–2000

1.5

1980–1985

1.7

1990–1995

1.7

7.9

–3

1985–1990

1980–1985

1.8

1975–1980

0.5

3.8

2.0
2.8 3.2
1.2 1.2
1.1 1.1 1.2 1.7
1.0 0.1
0.1 0.1 0.1 0.3 0.3 0.5
–0.4
–0.2

Non–IT capital

1.6

1970–1975

2.4

1.2

1975–1980

6

1975–1980

6

1.2

Malaysia

1970–1975

2005–2012

1.0

1975–1980

2005–2012

9

Iran
3.9

–9
1970–1975

2005–2012

2000–2005

1995–2000

1.7

1975–1980–2

1990–1995

0–4

1970–1975

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

9
1.9

–4.4

4

3.8

1.2 3.3

2

0

–3

2.6
2.8
1.9
1.5
0.7
1.2
1.9 2.0
1.0 1.0 0.7 0.3 0.5
0.1 0.1 1.3 0.1 0.2 0.7 0.4 0.5–0.5
0.1 0.1
–1.1
–0.4
–2.1

%

2.2 2.2%

3.9

1970–1975

2005–2012

2000–2005

1995–2000

1985–1990

1990–1995

1980–1985

1975–1980

1970–1975

TFP

1985–1990

1980–1985

Vietnam

4

0.3

1.6

0

12

3.1
2.3 0.7 1.8
3.2 1.8
0.7
4.5
4.1
3.8
2.9 3.6
1.9
0.2
0.2
0.1 0.1 0.1
0.2
–1.7

2.1

–2

0

1975–1980

–8

2

3

–6

0.3
1.5
0.7
1.1

2.3

%

–6.0

6

0.2 3.2
4.9
1.0
2.7
1.3
2.0 1.8 1.8 2.3
0.6
0.1 0.2 0.2 0.3 0.5
0.3 0.2–0.2–2.4

Indonesia
1.6

12

0.9

0.9 2.2
0.6 1.2
3.2 1.2
1.0
3.3 2.7
2.5 1.8 1.5
0.9 1.8
2.0
0.1 0.1 0.1 0.7 0.1 0.4 0.6 0.2
0.1 –0.58

3.7 4.5 2.3 3.1

2005–2012

Philippines

–4

–6

4

1.6

2000–2005

0

1.2

0.5 0.9
1.7
1.8
3.0

%

2.3

5.3

–3

6

1.7
5.7
1.9
3.9 4.0 4.1 2.8 0.3
1.9 1.5
0.2 0.4 0.3 0.6 0.4 0.5 0.5 0.2–1.4

1970–1975

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

4.2

1.0

3

2.3

0.9
1.2 1.0 0.3 0.6
0.3 1.8
4.0
3.1
3.1 3.4
2.1 0.4
1.4
0.5 0.4 0.4 0.3 0.3
0.8 0.6
–0.7
0.1
6.6

%

1995–2000

1.9

0.4 0.5
0.1 0.1

Thailand

6

–4

0.9

4.1
4.0

0.8
1.1

10

1.7

6.5

–2
2.5

0

8

1990–1995

–0.1

8

0

–2

1.4

1.9

1985–1990

0.1 0.1

0.4
1.9

2.4 0.9

3.5

3.2
3.0

1980–1985

0.7

2.7 2.2
2.2 2.6 2.6

%

–2

1.8

1975–1980

1.2
1.4 0.9 1.1

10

2

0

2

2

4

2

6

1.6

2.0

6

2.5 0.3

Korea

1970–1975

2005–2012

2000–2005

1995–2000

4

0.9

3.5

1.1

%

1.7

0
–2

3

2000–2005

4

1990–1995

2.7

2.0

1995–2000

0.4

1985–1990

1980–1985

1975–1980
2.3

2.2 2.2

2

6

2.5
1.9

9

1.4

1990–1995

6

4

5

–1

–2

2.1

Pakistan

5.6

2.1 2.1 2.1 20 2.1 2.1 2.0
0.1 0.1 0.1 0.1 0.2

2.3

6

0

1.2

%

2.6
1.9 1.9 1.7
0.6
0.9 0.3
0.2 0.2 0.4
0.4
0.3 0.3 0.4 0.1–0.3–0.4 –0.7 –0.3 –0.3
–0.6

4

Fiji

%

–0.3 –0.2

10

0.3 0.8

7

1

1.1

1.6

1985–1990

0.4

%

3

0.8

1980–1985

0.9 1.7

0.2

2.0

%

2.0

1975–1980

0.5

1970–1975

–1

0

6

India

1970–1975

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

0

2

4.3

2000–2005

1.9
0.5
1.0
0.3

3.6

0.1 0.1 0.2 0.7 0.5
1995–2000

3.6 1.0

1.2
0.4 0.2
1.8
3.6 4.1 3.0 3.4 2.7 0.5
1.3
0.4
0.4
0.2 0.3
0.7
0.5
–2.1
1975–1980

1

0.6

3.9

0.7 0.4

4.3 3.8 4.3
4.2 4.0
3.4

8

4.9

3.1

2.2

1990–1995

4

Japan

4

2

1.0 1.1 2.4

8

5

3

0

0.9
1.2

1985–1990

1.9 0.9

6

2

7.1

6
0.2

%

4

0.5

1980–1985

2.7
0.2

6

1975–1980

1.9

4.3

1970–1975

2005–2012

2000–2005

1.5

8

8

ROC

%

10

10

%

5.2

1970–1975–3

1995–2000

0

1990–1995

93

1985–1990

Hong Kong

%

12

6

1980–1985

1975–1980

1970–1975

–4

China

%

12

5.3 Total Factor Productivity

Japan

%

80

%

80

70

7.0

70

60

6.0

50

5.0

40

4.0

30

3.0

20

2.0

−1.0

0

1991

1996

2001

Non-IT capital (right-axis)

2006

5

1.0

20
10

1986

1.5

30

0.0

1981

2.0

40

0

1976

2.5

50

1.0

1971

%

3.0

60

10

–10

US

%

8.0

0.5
0.0
1971

2011

IT capital (right-axis)

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, 1970–2012
Source: APO Productivity Database 2014.01.

%

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 the Asian Tigers, China, and India,
1970–2012of IT capital to capital input growth rising from a low of 12% in 1995 to a peak of 63% in 2005 (Figure55).68 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 shifted awayfrom non-IT to IT capital as a profitable investment. In contrast, the US started its shift toward IT capitalmuch earlier than any Asian economy and over a longer period of time. For two decades (between
1983 and 2003), IT capital accounted for over 40% of the US’ capital input growth, reaching height ofover 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 in both Japan andthe US. The findings here are in accordance with Jorgenson, Ho, and Stiroh (2005). Based on theirmeasurement, IT capital in the 1980s contributed 31.9% of the growth of total capital inputs in the US,
but only 13.5% in Japan.69 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 53.3%, which
is higher than the US’ 49.8%.

68: 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.

77©2014 Asian Productivity Organization

Source: APO Productivity Database 2014.01.

5 Productivity%
12

Bangladesh

9

12

6

9

3

6

0

3

–3

0

–6
–9

–3

–12

–6
–9

–15

Fiji

1971 1976 1981 1986 1991 1996 2001 2006 2011

15

9

12

6

9

6

6

3

–3
–6

0

0

–3

–3

–6

–9

–9

–12

–12
1971 1976 1981 1986 1991 1996 2001 2006 2011

%
12

9

3

0

Indonesia–6–91971 1976 1981 1986 1991 1996 2001 2006 2011

Iran

%
20

9
6
3

10

6

0

0

–6

–5

4
2
0
–2

–10

–4

–15

–15

–6

–18

–20

–12

%
15

Korea

–8
1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

Malaysia%
121971 1976 1981 1986 1991 1996 2001 2006 2011

9

15

9

6

12

3

9

0

6

–3

3

3
0

–6

0

–3

–9

–3

–6

–12

–6

–9

–15
1971 1976 1981 1986 1991 1996 2001 2006 2011

TFP

Mongolia

%
18

12

6

Japan

%
10

15

–3
–9

1971 1976 1981 1986 1991 1996 2001 2006 2011

8

5

India

%
12

12

3

©2014 Asian Productivity Organization

Hong Kong

%
18

ROC

%
14
12
10
8
6
4
2
0
–2
–4
–6
–8

1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

%
15

China

%
15

–9
1971 1976 1981 1986 1991 1996 2001 2006 2011

Non–IT capital

IT capital

1971 1976 1981 1986 1991 1996 2001 2006 2011

Labor

OutputA similar allocation shift to IT capital is also found in the Asian Tigers (Figure 56).70 In Korea, the ROC,
and Hong Kong, the contribution of IT capital to total capital input peaked in excess of 30% at the turnof 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%. The second in
2005–2006 when it peaked at 28% again. China was a latecomer in terms of investing in IT capital witha 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 9% in the early 2000s before lessening recently.
69: 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.).

78

5.4 Enhancement of Labor Productivity%
10

Pakistan

Philippines

%
12

8
6
4
2

9

12

6

9

3

6

0

3

–3

0

–6

–3

–2

–9

–6

–4

–12

0

%
10

Sri Lanka

12

6

8

4
2
0

9

4

6

0

3
0
–3
–6

–12

–6
1971 1976 1981 1986 1991 1996 2001 2006 2011

Vietnam

%
18
12

–8

–4

1971 1976 1981 1986 1991 1996 2001 2006 2011

15

–4

–2

%
8

Thailand

%
16

8

5

–9
1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

Singapore

%
15

–9

1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

US

6
4
2
0
–2
–4

1971 1976 1981 1986 1991 1996 2001 2006 2011

TFP

Non–IT capital

IT capital

Labor

OutputFigure 57 Individual Countries’ Growth Accounting Decomposition (year-on-year), 1970–2012
Source: APO Productivity Database 2014.01.

5.4 Enhancement of Labor Productivity

70: 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.

79©2014 Asian Productivity Organization

Although TFP more accurately measures how efficiently an economy utilizes its factor inputs, laborproductivity and its drivers are of interest because of the close link to GDP per capita. Within the same
growth accounting framework, average labor productivity growth at the aggregate level can be broken down into effects of capital deepening (as measured by capital input per hour worked), whichreflect the capital–labor substitution, and of TFP. In other words, these factors are key in fostering labor productivity.

5 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 (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 1990–2012, China, Vietnam, India, Indonesia, and Thailand 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 average
per year in Korea and the ROC, respectively. Over the subsequent two decades it slowed to 7.1% and5.8% respectively. Meanwhile, China’s pace doubled between the two periods, from 5.3% to 10.6% on
average per year. In Vietnam, it has accelerated to 7.1% since 1990. In the US, the pace of capital
deepening also increased from 2.1% to 2.3% between the two sub-periods.
While labor productivity steadily improved for all countries (Figure 44), the growth rate of capital
productivity (as the other measure of partial productivity) remains negative for almost all countries
during 1970–2012 (Figure 59). Although rates of capital deepening in Korea and the ROC were
outstanding, at 8.6% and 7.5% per year, on average during this period their capital productivity

1970−2012%12

1970−1990

1990−2012
10.6

10.2
9.5

10
8.6

8

8.0

7.6

7.5

6

5.15.1 4.9 4.8

4

7.1 7.1

7.1
5.8 5.6 5.5

4.6

3.9 3.63.6

5.8
4.8 4.8

5.3
4.2

3.2

2.8

2

3.4
2.22.2 2.1

1.8

1.2

3.0 2.8

2.6

2.1 1.91.9

1.6

0.8

4.2 4.0

3.83.6

2.92.91.0

2.3 2.22.1
1.7
0.9 0.6 0.6

−0.2

0

PakistanFiji
IranPhilippines
Sri Lanka
Mongolia
US
SingaporeJapan
Bangladesh
Malaysia
Hong Kong
ThailandIndia
Indonesia
ROC
Vietnam
Korea
China

VietnamFiji
Sri Lanka
Bangladesh
Pakistan
US
Philippines
India
ThailandIranMongolia
China
Malaysia
Indonesia
Hong Kong
Japan
Singapore
ROC
Korea

Fiji
Pakistan
Sri Lanka
IranPhilippine
US
Banglades
Mongolia
VietnamThailandIndia
Malaysia
Hong Kong
Japan
Singapore
Indonesia
ROC
China
Korea

Figure 58 Capital Deepening, 1970–2012, 1970–1990, and 1990–2012
Source: APO Productivity Database 2014.01.
Note: The labor inputs for Fiji and Mongolia are defined by numbers of employment.

1970−2012%

1970−1990

1990−2012

2
1
0

–1
–2
–3
–4

0.9

1.0 0.9

0.7

0.8

1.0 0.9

0.2–0.1–0.3 –0.4

0.2 0.1–0.6–0.6–0.7–0.8 –0.9–0.9–0.5 –0.6–1.3–1.0–1.0
–1.5

–1.6

–2.0 –2.1

–2.2
–2.8

–1.2 –1.3–0.4 –0.5–0.5–1.0 –1.1–1.6–1.9 –2.0–2.0
–3.0

–3.6

–1.6

–1.9 –2.0–2.0 –2.0
–2.6

–3.3
–3.9 –4.0

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

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

Korea
ROC
Japan
Singapore
Indonesia
Bangladesh
Malaysia
China
Hong Kong
India
Philippines
Iran
VietnamUSFiji
Mongolia
ThailandSri Lanka
Pakistan

Figure 59 Capital Productivity Growth, 1970–2012, 1970–1990, and 1990–2012
Source: APO Productivity Database 2014.01.

80–1.3–1.3–4.6–5©2014 Asian Productivity Organization

1.3 1.3

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 Asian Tigers, 1970–2012

Figure 61 Capital Productivity Trends in
China and India, 1970–2012

Source: APO Productivity Database 2014.01.

Source: APO Productivity Database 2014.01.

%

%

7
6
5
4

0

Non-IT capital deepening

TFP

17

3.1

80
1.6

1.5

3.4 3.0

33 32
46

15

IT capital deepening

24

29

42
56

58

49

0.5

2.8

1.7 1.4
2.3

1.9

0.9 0.5

2.1

1.9

2.1

1.7

1.5

51
0.9 0.3 0.2

0.3
0.4 0.8 1.1
0.8 0.1
0.6 0.6
0.2
0.5
0.4
0.4
0.3 0.2 0.3 0.1
0.2 0.3
0.2 0.1 0.1
0.2 0.1 0.2 0.3 0.1
1.3

1.1 1.4

1.6

61 60

−1

0

62 80

64
24

56
23 30

3

7

8

9

6

37

67 51

36 48

38

20

29

73 68

67

49

14

52

69

74

40

1.1 0.7

25

38

60
1.6
1.9

1

120
100

3
2

Non-IT capital deepening
Labor productivity

TFP
IT capital deepening

9

4

16

6

3

6 11 4

1

24

13

6

5

12

−20
Fiji
Bangladesh
Iran
Philippines
US
Pakistan
Sri Lanka
Japan
Mongolia
India
VietnamSingapore
Indonesia
Malaysia
ThailandHong Kong
ROC
Korea
China

Fiji
Bangladesh
Iran
Philippines
US
Pakistan
Sri Lanka
Japan
Mongolia
India
VietnamSingapore
Indonesia
Malaysia
ThailandHong Kong
ROC
Korea
China

Figure 62 Sources of Labor Productivity
Growth, 1970–2012

Figure 63 Contribution Shares of Labor
Productivity Growth, 1970–2012

Source: APO Productivity Database 2014.01

Source: APO Productivity Database 2014.01.

Looking at the two sub-periods of 1970–1990 and 1990–2012, overall the rate of deterioration in capital productivity for all countries was slower in the latter period. China’s performance is particularly
impressive. Its acceleration in capital deepening in the latter period did not compromise its capital
productivity as much as the early starters (Figure 61). In 1990–2012, China’s capital–labor ratio rose by
10.6% whereas its capital productivity fell by 1.6%. 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. It remains theprime motor of labor productivity growth, generally explaining 50% of it. Taking the US as the reference economy, with contribution share of capital deepening to labor productivity growth of 48.1% on

81©2014 Asian Productivity Organization

experienced the sharpest decline of 3.6 and 2.8% per year, respectively (Figure 60). In contrast, thedeterioration of capital productivity (by 1.3%) was relatively mild in China as shown in Figure 59, despite its fast capital deepening of 8.0% (Figure 58).

5 Productivity

1970−1985%

1985−2000

2000−2012

10

8
3.7

6
3.7

0.9 0.84

2.2
2.3 2.0 0.8

0.8 0.5
2.9

4.0

2.9 1.5
1.8

1.3

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

1.8
2.2 1.6 1.2 1.1 0.7
0.1
1.3 1.4 1.6 1.4 0.7
0.4 0.4 0.6 1.5 0.7 0.8
0.3
0.3
0.8
0.6 0.4 0.2 0.4 0.3 0.2 0.2 0.1 0.3 0.3 0.1
0.2 0.3 0.5 0.4 0.4 0.0 0.3 0.1 0.0
0.0
−0.2

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

2.2 1.8 1.5

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

0.8

4.8

0.3

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

3.0 2.7

1.3

0.8 0.8
0.8
0.9 0.5 0.5 1.2
1.1
0.0 1.3 0.5
0.2 0.0 0.1 0.3 0.4 0.1 0.1 0.1
0.2
0.0 0.3 0.0 0.0 0.0 0.0 0.3 0.1 0.0
0.4
0.0 −1.2
−0.9
−0.3
−1.5
−1.8

2.3 2.6

0

1.4
0.7

4.2 2.3

4.1 4.1

2

2.4

0.1

0.5

3.1 2.9

3.3

2.6

1.6

3.2

0.1 2.8

2.5 2.9

2.6

1.4 2.7

1.7

1.7 2.2

1.2 1.2 0.8

2.7

1.0

1.6

2.2

−2

TFP

IT capital deepening

Non-IT capital deepening

Labor productivity

Figure 64 Sources of Labor Productivity Growth, 1970–1985, 1985–2000, and 2000–2012
Source: APO Productivity Database 2014.01.

1970−1985%

120

1985−2000

114

288 141

100
17 16

80

20

3

14

6

63

66

52

40

77

0

12

13

3 7 12 3 2 2
5 7 4 1
0

17

−3

55

60

53

59

42

60

13 8
2 8 8 8 4

45 38

38
18

4 3
2

59

109
75

6 2 8 1

44
42

20
6
−1

91

34

60

53

32
13

75
88

8

53

57 60

63

83

−51
−193 −47
−65

35 42

49

17

47
25

25

20

12

19
26
22
3
20 24
13 5
12 9 136 7 3 8 8 5 5 5 1034−12−401 −46

Non-IT capital deepening

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

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

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

48

60

42

46 44

94

94

28

3 2
5 6 2

53 54

32

41
75

45

37

36

40

59

65 79
53 49

12

28
40

88
31

31

22

32
68

76

−25

−20

53

39 43

92

95

79

48 56

20

10

60

60
78 77

481 38222

48 44

2000−2012

1027 168

IT capital deepening

Figure 65 Contribution Shares of Labor Productivity Growth, 1970–1985, 1985–2000, and 2000–2012
Source: APO Productivity Database 2014.01.

©2014 Asian Productivity Organization

average in 1970–2012, it has been a main engine to enhance labor productivity in 14 Asian countries(Figure 63). The exceptions to this observation are Sri Lanka, Pakistan, Vietnam, and Thailand, in which
the role of TFP has been more significant.
Within this long period, the composition of labor productivity growth has seen substantial shifts(Figures 64 and 65). In the earlier period of 1970–1985, TFP growth was enjoyed by 11 out of the 18
Asian countries compared. It was a significant drag on labor productivity growth in four countries (Iran,the Philippines, Fiji, and Singapore). During the middle period of 1985–2000, all countries (except Mongolia) achieved positive TFP growth to bolster labor productivity growth. By 2000–2012, TFP growth82

5.4 Enhancement of Labor Productivity

3
2

0.5

–1

1.0
0.6
0.1 0.2–1.1–1.7

2005–2012

1995–2000

1990–1995

1980–1985

1975–1980

1970–1975

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985–9.9

2005–2012
4.4

2.9

1.1 5.3
3.4 2.4
2.4
2.1 2.0
1.2
0.1
0.1 0.2 0.6
0.2 0.5
0.1 0.1 –0.1 –0.9
–1.6
–2.5 –2.6

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1975–1980

1980–1985

1970–1975

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985–4

2000–2005

0–2

1995–2000

2

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

Mongolia

Sri Lanka

%

6

5.9

4
0.2
3.9

2.3

1.5

1.8

2.7

2

1.8

0.7

2005–2012

1995–2000

1.6
0.8
0.1 0.2 0.2–0.1 –0.6
2000–2005

1.2 1.0
0.1

1985–1990

0.7

1990–1995

1970–1975

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

–1

0.3
–0.4

4.3

1980–1985

0.1

1
0

2.0

2.1

1975–1980

1.5
1.0
0.5
0.8
0.5 0.3 0.5 0.6 0.6 0.5 0.5 0.3
–0.5
–0.1
–1.1
–.9
1970–1975

0

3.3

3

2.7

US

1.5

1.2

1.1

0.7 0.5
0.6 0.8
0.1
1.0 0.6 0.3
0.5
0.1 0.2
0.2 0.4 0.5 0.4 0.7 0.6
0.3
0.2 0.2–1

IT capital deepening

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

2005–2012

Non-IT capital deepening

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980–2

Singapore

1975–1980

1

1.2 1.7 1.0–0.1 0.1 0.1 0.2 0.8 0.3 0.3 0.4
–0.4
–0.2
–0.9 0.1 0.1–104

4.3 2.2 4.5 3.0 1.3
1.1 1.1
1.3 0.3
0.1 0.1 0.1
0.4 0.7 0.4
0.1
–0.2
–2.5
–2.5

0.7

2.6 2.7 2.7

1970–1975

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

TFP

0

–4

6

2

3.9

2

0.1

8

2.8 2.9

1975–1980

2.5 3.2 1.5
2.2
1.0 1.3 0.6 0.5
0.4
0.3 0.1
0.1 0.1–0.4 0.3–0.3 0.2 0.2–2.40

3.1 0.3
2.4
1.9 1.8
0.4
0.1–1.3 –0.6 –1.1 0.2 0.1
–0.1

0.4
0.9

–2

1.8

3

3.8 3.8

3.5 3.8%

1.2 1.6

1970–1975

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980–24

2.3 4.2 4.6

5

3.9

2

Malaysia

%

6

Iran

5
4

–6
1970–1975

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1970–1975

1975–1980

2.3
3.7

–2

–2.1

–6

0.9

Vietnam–1

0.3 0.5
0.1 –0.1

–8

6

0

8

1.8 1.9

–4.4

2

%

–1.1

0.2 0.5
0.1–0.4 –0.2
–0.4

4

3.1
3.1 2.5
1.9 1.3 1.5
1.5
0.1 0.1
0.1 0.2 0.1 0.1 0.2
–1.7

%

3.2
2.2
1.7
0.9
0.5 2.1 1.3
0.5 0.1
0.1 0.8 0.4 0.5 0.5
0.1
0.1
0.1
–0.5

–0.5

0.8

8

2.2

1975–1980

–4

–4

–8

2.1

1970–1975

2005–2012

2000–2005

1995–2000–0.2 –0.2

1975–1980

2005–2012

2000–2005

1990–1995

0.9

0

–6.0

Thailand6

Philippines

–2
0.9

0.4
0.2

1985–1990

0.1 0.1

8–2

1980–1985

0
2.4

1.4 1.2 1.3 1.5

%

1.8
1.6
0.1 0.3 0.3 0.5 0.4 0.5 0.5 0.2–1.4
1975–1980

1.7

–6

0

0.7 1.2
0.6

%

–4

2

4
2

0.2
–0.1

1.7

1.8

3.1

1.6

–2

4

3.1 2.7 3.5 2.8

%

1.6

2.3

0

1.9

4.1

1970–1975

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

Pakistan

1970–1975

2005–2012

2000–2005

1995–2000
1995–2000

1990–1995

0
–2

1

–4

1990–1995

2.0 1.7 1.7 2.0 1.3 0.8
0.5 0.6
0.4 0.2 0.2 0.4 0.4 0.4 0.4 0.2
0.2
–0.6

2

1.9

1.1
0.3 0.3 0.7 0.6 0.1

6

5.2
0.3

2

–2

1985–1990

1.7

2.3 2.7

0

1980–1985

0.5

0.6

6

8

1.6

2.9

2.8

2.6

1

Indonesia%

3.0 3.2 1.7

4

3

2

1975–1980

5.1

4

4

Korea

8

1.1

%

–1

–2

6

2

0

1.4 2.0 3.3
1.6
0.8
0.8 0.7 1.5 1.0 0.7–0.3 –0.2
0.1 0.1 0.1 0.2

%

2.1

4
2

2.0

1.4 1.4

0

–1

2.3

6

1970–1975

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

1975–1980

1970–1975

Japan

2

3.2

0.4 0.4 0.3
–0.7

8

4

1.0

4

0

1985–1990

0.2

1.8
3.3 2.7 3.1
1.9
1.7
1.6 2.0
0.9
0.3 0.4 0.4 0.6 0.5
0.6
0.2
0.2 0.2
–2.1

3.9

1
0

2.3 0.9

5.1

%

3.5

5

–1

5.4
0.9
4.0
3.4 3.8
2.4
0.1 0.1 0.2 0.7 0.5

India

8

1.5

6

1

1.5
1980–1985

3.6

%

3

3.2 3.0

0.8

2

6
5.2

–3

0

0.5 1.2 4.3

%

6

0

4

4.0

4
3

3.1

1975–1980

9

3.9

6

1970–1975

2005–2012

2000–2005

1995–2000

1990–1995

1985–1990

1980–1985

Hong Kong

%

3

7.1

2
1975–1980

1970–1975–2

1.1 1.0

1.5

3.6

2

2.5

5

8

3

2000–2005

0

0.4 0.1 0.4
–0.2

6

Fiji

%

1985–1990

1

7

1.0

0.9

ROC

%

10

1.0
1.9

China

%

12

Labor productivity

Figure 66 Decomposition of Labor Productivity Growth, 1970–2012
Source: APO Productivity Database 2014.01.

83©2014 Asian Productivity Organization

Bangladesh%5 Productivity

(9)
(5)
(8)
(4)
(6)
(16)
(20)
(2)
(6)
(8)

5.1
3.9
3.2
2.3
2.8
2.9
1.9
1.4
0.3
2.8

(105)
(58)
(75)
(35)
(52)
(64)
(62)
(37)
(25)
(60)

−0.7
2.5
0.8
4.0
2.3
0.9
0.6
2.3
0.7
1.5

(−14)
(37)
(17)
(61)
(42)
(20)
(19)
(61)
(68)
(32)

Hong Kong

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

3.2
7.5
3.8
6.7
4.6
0.2
3.1
2.3
3.8
3.9

0.2
0.2
0.3
0.4
0.4
0.6
0.5
0.2
0.2
0.3

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

1.6
2.0
3.3
2.7
3.1
1.7
0.9
0.5
1.1
1.9

(50)
(27)
(87)
(40)
(68)
(807)
(28)
(20)
(28)
(49)

1.5
5.2
0.2
3.6
1.0
−2.1
1.8
1.6
2.5
1.6

(45)
(70)
(6)
(53)
(22)
(−999)
(57)
(70)
(66)
(42)

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

4.4
4.8
0.9
3.9
6.4
−2.4
3.3
2.4
6.5
3.1

0.0
0.1
0.1
0.1
0.2
0.1
0.1
0.2
0.2
0.1

(1)
(2)
(10)
(3)
(3)
(−5)
(4)
(7)
(4)
(4)

2.1
3.1
2.5
1.5
3.1
1.9
1.3
0.9
2.9
2.1

(47)
(65)
(266)
(40)
(48)
(−80)
(41)
(40)
(45)
(67)

2.3
1.6
−1.7
2.2
3.1
−4.4
1.8
1.3
3.3
0.9

(53)
(33)
(−177)
(57)
(48)
(185)
(55)
(54)
(51)
(29)

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

4.8
2.8
3.6
4.2
2.3
2.0
1.7
1.1
0.2
2.7

0.4
0.2
0.2
0.4
0.4
0.4
0.4
0.2
0.0
0.3

(8)
(7)
(6)
(10)
(15)
(19)
(24)
(19)
(3)
(11)

5.1 (105)
2.0
(74)
1.7
(47)
1.7
(40)
2.0
(84)
1.3
(68)
0.5
(30)
0.4
(31)
−0.3 (−150)
1.7
(64)

−0.6
0.5
1.7
2.1
0.0
0.3
0.8
0.6
0.6
0.7

(−13)
(19)
(46)
(50)
(1)
(13)
(45)
(50)
(247)
(24)

China

0.4
0.4
0.3
0.3
0.3
0.7
0.6
0.1
0.1
0.4

Fiji

4.8
6.7
4.3
6.5
5.4
4.5
3.0
3.7
1.0
4.7

3.7
4.2
5.9
3.4
10.6
7.1
8.6
10.2
7.7
6.8

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

−0.5
−0.5
−1.2
2.3
−0.4
1.2
1.5
0.1
1.2
0.4

0.0 (−5)0.0 (−3)0.0 (−2)0.1(3)0.2 (−38)
0.0 (−3)
0.1
(4)
0.1
(47)
−0.1 (−8)
0.0
(12)

0.0
(−5)
0.6 (−112)
0.8 (−67)−0.4 (−16)
−0.2
(39)
0.5
(44)
0.3
(17)
0.0 (−19)−0.3 (−28)
0.2
(51)

−0.5
−1.1
−2.1
2.6
−0.4
0.7
1.2
0.1
1.6
0.1

(110)
(216)
(170)
(113)
(98)
(59)
(79)
(72)
(136)
(37)

India

ROC

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

1970−1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

Capital deepeningIT
Non-IT
0.0
(1)
3.2
(86)
0.0
(1)
3.0
(71)
0.0
(1)
1.5
(25)
0.1
(2)
2.4
(70)
0.1
(1)
3.4
(32)
0.2
(3)
3.8
(54)
0.7
(8)
4.0
(47)
0.6
(5)
5.5
(54)
0.4
(6)
5.2
(67)
0.2
(3)
3.4
(51)

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

1.1
1.1
1.6
2.3
3.6
2.5
2.7
8.5
3.4
3.0

0.0
0.0
0.0
0.0
0.1
0.1
0.1
0.2
0.2
0.1

(2)
(2)
(2)
(2)
(2)
(5)
(4)
(3)
(6)
(3)

1.4
1.4
0.8
0.7
1.5
1.0
0.7
3.5
2.6
1.4

(125)
(119)
(49)
(31)
(43)
(38)
(24)
(42)
(77)
(48)

−0.3
−0.2
0.8
1.6
2.0
1.4
2.0
4.7
0.6
1.4

(−27)
(−21)
(49)
(67)
(56)
(57)
(72)
(55)
(18)
(49)

Iran

−1.3
2.1
0.2
1.6
1.9
2.5
−0.5
2.0
3.0
1.2

Indonesia

Labor
Productivity

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

7.5
−6.0
1.4
−1.4
1.4
0.7
3.7
4.6
−1.7
1.3

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)
(−8)
(6)

3.5
(47)
3.8 (−63)
0.9
(66)
−1.3
(94)
−0.6 (−39)−1.1 (−150)
0.4
(12)
2.5
(54)
2.0 (−123)
1.1
(80)

3.9
−9.9
0.4
−0.1
1.9
1.8
3.1
2.0
−3.8
0.2

(52)
(164)
(32)
(8)
(136)
(241)
(84)
(43)
(231)
(14)

Korea

Bangladesh

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

Capital deepeningIT
Non-IT0.0(0)0.4 (−31)
0.0
(0)
0.1
(6)
0.0
(3)
0.4 (164)
0.0
(1)
1.1
(68)
0.0
(1)
1.0
(52)
0.0
(1)
1.5
(59)
0.1 (−12)
0.6 (−125)
0.2
(11)
1.0
(50)
0.2
(6)
1.1
(36)
0.1
(5)
0.8
(67)

Japan

Table 13 Role of TFP and Capital Deepening in Labor Productivity Growth, 1970–2012
Labor
Productivity

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

5.4
4.2
6.4
6.5
5.5
4.9
4.0
4.5
1.5
5.0

0.1
0.3
0.3
0.5
0.4
0.5
0.5
0.2
0.1
0.3

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

4.1
5.2
3.1
2.7
3.5
2.8
1.8
1.8
1.0
3.0

1.1
−1.4
3.0
3.2
1.7
1.6
1.7
2.5
0.4
1.6

(21)
(−34)
(48)
(50)
(31)
(32)
(43)
(55)
(29)
(33)

TFP
−1.7
1.9
−0.2
0.5
0.9
1.0
−1.1
0.8
1.7
0.3

(131)
(93)
(−67)
(31)
(47)
(40)
(237)
(38)
(59)
(29)

(76)
(126)
(48)
(42)
(63)
(57)
(44)
(40)
(65)
(61)

TFP
0.5
1.2
4.3
0.9
7.1
3.1
3.9
4.2
2.1
3.1

(13)
(28)
(74)
(27)
(67)
(44)
(46)
(41)
(28)
(46)

©2014 Asian Productivity Organization

had become the dominant driver of labor productivity growth in 12 of the 18 countries compared. At
the same time, the contribution from IT capital deepening was also strengthening, from a range of
0–12% in 1970–1985, to 1–20% in 1985–2000, and 3–26% in 2000–2012. This may have accounted fora 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 60%.
Figure 66 and Table 13 show the decomposition of labor productivity growth for individual countries
in five-year intervals covering the period 1970–2012. Productivity is procyclical in nature. In turn, it isdifficult 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 (China and India) is accelerating. China has clearly leapt from a growth rate of around84

5.4 Enhancement of Labor Productivity

0.2
0.2
0.4
0.5
0.4
0.7
0.6
0.4
0.1
0.4

(10)
(21)
(22)
(38)
(29)
(30)
(24)
(25)
(18)
(24)

1.0
0.2
0.3
0.1
0.2
0.1
0.7
0.9
−0.5
0.4

(51)
(20)
(16)
(9)
(11)
(6)
(31)
(58)
(−73)
(24)

0.7
0.6
1.2
0.6
0.8
1.5
1.1
0.2
1.0
0.9

(38)
(60)
(62)
(53)
(60)
(64)
(45)
(17)
(155)
(52)

Mongolia

1.9
1.0
1.9
1.2
1.4
2.3
2.4
1.5
0.7
1.7

(29)
(35)
(−128)(61)(28)(−273)
(42)
(78)
(86)
(17)
(−36)
(62)
(68)
(55)
(49)
(66)
(106)
(125)
(110)
(68)
(−43)
(7)
(−32)
(68)
(52)
(−3)
(42)
(195)
(−44)
(15)
(62)
(122)
(61)
(84)
(32)
(−637)
(111)
(64)
(74)
(56)

Philippines

1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

1.2
1.6
−2.5
2.2
1.8
−2.5
1.3
1.0
1.5
0.5
−0.1
2.3
2.7
1.7
1.6
0.4
2.4
0.6
1.5
1.5
−1.9
0.2
−1.1
2.3
1.8
−0.1
1.5
1.2
−0.2
0.5
3.7
1.0
2.3
4.2
2.3
−2.4
3.2
1.3
1.9
1.9

Sri Lanka

4.0
4.5
1.9
3.6
6.6
0.9
3.0
1.2
1.7
3.2
0.2
3.7
3.9
3.0
3.2
0.6
2.3
0.5
1.4
2.1
4.5
3.2
3.4
3.4
3.5
3.2
3.5
0.6
0.5
3.0
5.9
0.8
3.8
5.0
7.4
0.4
2.9
2.1
2.5
3.5

Labor
Productivity

TFP

Vietnam1970−1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

Capital deepeningIT
Non-IT
0.1
(1)
2.8
(70)
0.1
(2)
2.9
(63)
0.1
(4)
4.3 (224)
0.1
(4)
1.3
(36)
0.3
(4)
4.5
(68)
0.4
(49)
3.0 (324)
0.7
(22)
1.1
(36)
0.5
(40)
−0.2 (−18)
0.3
(18)
−0.1
(−4)
0.3
(9)
2.3
(74)
0.0
(7)
0.2 (129)
0.0
(0)
1.4
(37)
0.0
(0)
1.2
(31)
0.1
(2)
1.3
(43)
0.1
(2)
1.5
(49)
0.0
(3)
0.2
(31)
0.0
(2)
−0.2
(−8)
0.1
(10)
−0.2 (−35)0.0(2)−0.2 (−12)
0.0
(1)
0.6
(30)
0.5
(11)
5.9 (133)
0.3
(9)
2.7
(84)
0.5
(16)
3.9 (117)
0.6
(18)
0.5
(14)
0.6
(18)
1.0
(29)
0.5
(17)
2.7
(86)
0.5
(15)
1.5
(43)
0.2
(39)
−0.8 (−133)
0.3
(54)
0.5
(90)
0.5
(16)
2.1
(69)
0.1
(1)
2.2
(37)
0.1
(11)
−0.3 (−33)
0.2
(4)
1.3
(35)
0.2
(4)
0.6
(12)
0.5
(7)
4.6
(62)
0.3
(79)
2.5 (659)
0.1(4)−0.4 (−16)
0.3
(16)
0.4
(21)
0.2
(9)
0.4
(17)
0.2
(6)
1.3
(38)

1970−1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012
1970–1975
1975–1980
1980–1985
1985–1990
1990–1995
1995–2000
2000–2005
2005–20102010–2012
1970–2012

5.1
3.1
3.9
−1.9
−1.3
2.5
2.7
5.0
12.8
2.9
1.0
3.1
−4.6
3.4
0.4
3.0
1.3
2.8
2.8
1.4
−0.1
2.9
1.4
3.0
4.2
1.4
1.7
5.3
4.9
2.6
−0.6
1.4
1.0
1.3
4.7
6.6
6.7
2.4
4.3
3.0

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
(7)
−0.9 (−35)
0.4
(8)
2.2
(45)
0.6
(5)
2.8
(22)
0.2
(6)
1.6
(56)
0.1
(5)
0.5
(46)
0.1
(2)
2.1
(69)
0.1 (−2)
1.3 (−29)
0.1
(3)
0.0
(1)
0.0
(11)
0.8 (222)
0.4
(14)
1.7
(57)
0.5
(36)
0.0
(−2)
0.2
(6)
0.5
(17)
0.1
(3)
0.5
(17)
0.2
(13)
0.8
(62)
0.0 (−35)−0.4 (613)
0.0
(2)
0.7
(25)
0.1
(5)
1.2
(87)
0.0
(1)
1.0
(33)
0.0
(1)
−0.1
(−2)
0.1
(9)
−0.6 (−40)
0.2
(12)
0.8
(47)
0.3
(5)
1.6
(30)
0.1
(1)
1.8
(37)
0.1
(4)
0.6
(23)
0.0
(0)
−0.1
(21)
0.0
(3)
0.1
(10)
0.1
(7)
−0.9 (−89)
0.1
(8)
0.2
(15)
0.1
(2)
0.8
(16)
0.3
(4)
2.6
(39)
0.3
(4)
2.7
(40)
0.4
(19)
2.6 (109)
0.4
(9)
2.9
(68)
0.2
(6)
1.1
(36)

TFP
2.9
1.1
−1.6
−2.5
−2.6
2.4
3.4
2.3
9.4
1.1
0.5
0.9
−6.0
3.2
−0.5
0.9
0.9
2.1
2.3
0.3
0.3
2.1
0.1
2.0
4.3
1.8
0.7
3.4
3.0
1.9
−0.4
1.2
1.7
1.0
3.9
3.8
3.8
−0.7
1.0
1.7

(58)
(35)
(−41)
(135)
(194)
(96)
(128)
(47)
(74)
(38)
(50)
(29)
(132)
(96)
(−133)
(29)
(66)
(76)
(81)
(25)
(−478)
(74)
(8)
(66)
(101)
(131)
(42)
(65)
(62)
(73)
(79)
(87)
(181)
(77)
(82)
(57)
(56)
(−28)
(23)
(58)

5

Unit: Average annual growth rate (percentage), contribution share inparentheses.
Source: APO Productivity Database 2014.01.

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% in
the 1970s to 7.0% in 2005–2012. Both TFP growth and capital deepening took a leap in 2005–2012 toreinforce the positive trend. In contrast, the early starters (Japan and the Asian Tigers) have been
experiencing a slowdown in labor productivity growth since their heights of the late 1980s. In bothHong Kong and Korea, labor productivity growth appeared to stabilize in the 2000s, but at a lower rate
than previously. Singapore’s productivity performance, albeit robust, compared with other matureeconomies like the US, has been very modest against its Asian counterparts. A recent peak of 3.2–3.5%
in the 1990s, is compared with over 6% in Hong Kong, the ROC, and Korea in the late 1980s. The US
clearly enjoyed a labor productivity growth spurt in the late 1990s (2.3%) and early 2000s (2.4%), theorigin of which attracted much research attention at the time. In recent years, it has returned to its
long-term average of under 2%.

85©2014 Asian Productivity Organization

US

ThailandSingapore

Pakistan

Malaysia

Labor
Productivity

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 18 Asian countries and the US in 2012 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
89
58
China
94
57
US
countries with an approxi56
56
Sri Lanka
mately a 30% share of com87
55
Japan
94
52
Hong Kong
pensation for employees. This
44
52
Fiji
does not necessarily reflect
72
51
Korea
78
47
ROC
differences in the number of94
44Singapore
employees in total employ36
41
Pakistan
37
40
Vietnamment. Although Malaysia has
15
39
Bangladesha high employee share of
57
38
Philippines
44
34
Thailand
79%, the labor income share
19
32
India
is only 32%.
45
32
Mongolia
Malaysia
Indonesia
IranRatio of employees to employment

32
32
21

Labor income share for employees

Figure B5.1 Labor Income Share for Employees, 2012
Sources: Official national accounts in each country, including author adjustments.

%

4

3.9

3

3.1
1.6 1.8
1.5 1.4
1.3 1.1

India

Pakistan

Hong Kong

VietnamThailand

−1

1.1
0.7
0.2

1.0
0.5
0.1

1.0 0.6
0.5 0.3−0.1 0.1

0.6
0.3
0.1

0.4
0.2
0.0

0.3
0.1
0.1

Fiji

0

1.1
0.9
0.6

Iran

1.4
0.9
0.4

Bangladesh

1.4
1.1
0.8

Philippines

0.8

0.8

Singapore

1.5

Malaysia

2.3

1.6

US

2.5

Japan

2.1
1.6
1.2

Indonesia

1

2.1
1.7
1.4

TFP(vL+10)
TFP
TFP(vL−10)

Mongolia

2.3 2.1
1.9 1.9
1.6 1.7

ROC

2.3

Korea

2

Sri Lanka

86

50
54

China

©2014 Asian Productivity Organization

79

Figure B5.2 illustrates the sensitivity of TFP estimates bychanging the factor income
share during the period 1970–2012. 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
1970–2012, 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, 1970–2012
Source: APO Productivity Database 2014.01.
Note: The labor inputs for Fiji and Mongolia are defined by number of employment.

6 Industry Perspective
This chapter provides the industry origins of economic growth and labor productivity improvementin 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 theeconomy, and in turn is more resourceful in weathering economic shocks. On the other hand, relianceon 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 theother end 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 be
strengthened accordingly. 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.71

6

6.1 Output and Employment
Table 6 (p. 29) 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
Table 14 Country Groups Based on the Current Economic
countries based on the same set
Level and the Pace of Catching Upof criteria as in Table 6, but applies___Level and average annual growth rate of GDP at constant market
it to 2012 income levels. The difprices, using 2011 PPP
ference in relative per capita GDP
Annual rate to catch-up to the US
Per capita
between the two tables reflects
GDP level to
(C2)
(C3)
(C4)
(C1)
the impact of their catch-up efthe US in 2012
1% <–< 3%
0% <–< 1%< 0%>3%
forts since 1970, or the year of first
Bahrain, Brunei,
ROC, Korea,
Japan, EU15,(L1)
Kuwait, Qatar,recorded data.
Hong Kong
Singapore
Oman
60% <
Saudi Arabia,
UAE, Australia(L3)
10% <–< 30%
(L4)
< 10%

Malaysia,
ThailandChina

India, Indonesia,
Mongolia,
Sri Lanka, Vietnam

Cambodia

Lao PDR, Myanmar

TurkeyIranFiji, Philippines
Bangladesh,
Nepal
Pakistan

Sources: Official national accounts in each country, including author adjustments.
Note: The annual catch-up rates are based on the data during 1970–2012. The starting
years for some countries are different due to data availability: Cambodia (1987–), theLao PDR (1984–), and Nepal (1974–).

71: 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 notavailable, series are spliced together using different benchmarks and growth rates. Data inconsistencies in terms of concepts,
coverage, and data sources have not been fully treated although levels of breakdown are deliberately chosen to minimize thepotential impact of these data inconsistencies. In this sense, the industry data in APO Productivity Database should be treated asa work in 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©2014 Asian Productivity Organization

Comparing Table 14 with Table 6,
it is notable that 13 of the 29 Asian
economies have moved up in income group, whereas 14 havestagnated. Among them, themost upwardly mobile countries
are the ROC and Korea, both in
the fast catch-up group. They
have moved up two income levels
during the past four decades to(L2)
30% <–< 60%6 Industry Perspective

join Japan in the top income group.
Singapore and Hong Kong havealso 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 toL3, although they are in different
catch-up groups. Indonesia andVietnam (in Group-C2) have also
improved their income level to L3.
This means the number of lowestincome countries has decreased
from 11 at the start of the period tosix (Cambodia, the Lao PDR, Myanmar, Bangladesh, Nepal, and Pakistan)
as of 2012. As expected, there
were few movements in countrygroups with little or no catch-up.

4
19
13
20
1 5
1
10
16
8
8
14
1 7
1
13
9
16
1 6 1 7
13
10
11
27
4 7
20
4 7
10
17
19
20
7
13
18
22
2
10
17
20
11
4
17
4 6
12
18
18
18
9
11
16
1 9
1
14
14
18
17
8
17
2 8
2
16
7 22
16
13
10
13
21
11
24
15
7
7
14
1 10
12
14
16
13
17
16
19
1
23
14
21
12 1
19
6
18
4 6
14
29
11
13
7
18
3 3
4
10
18
11 2
14
13
21
2 9
13
26
10
13
6
15
2 4
11
15
31
10
11
7
12
2 7
5
18
17
9 2
15
16
16
3 5
13
15
8
14
7
14
7 5
16
21
31
3
19
8
11
2 6
30
7 3 8
2 9
20
8
12
22
26
2
20
5
22
13
14
10 1 4
2
8
5
8
48
31
18
1
17
11
14
2 6
14
10 1 5
1
7 4 7
49
28
12 2 4
12
33
7
12
17
12 1 3 3 3 5
1
55
7
9 2 9
1
15
8
12
39
18
15
21
6
6
1 6
25
14
5 12 3 5
9
61
10
4 6 3
10
11
56
17
22 4
38
10
29
11
20
31
11
21
2 4
36
36
34

0

10

20

30

40

50

60

70

80

90

MyanmarCambodia
Nepal
Lao PDR
Pakistan
VietnamBangladesh
India
Mongolia
Indonesia
Fiji
Philippines
ThailandSri Lanka
Malaysia
China
TurkeyIran
Korea
Australia
ROC
Saudi Arabia
Japan
Oman
US
BruneiUAE
Bahrain
Kuwait
Qatar
Hong Kong
Singapore

Group-L4

Group-L3(except for
Bangladesh
and Thailand)Group-L2(except for
China)

Group-L1

100 %©2014 Asian Productivity Organization

Countries at the lower rungs of the
1. Agriculture
2. Mining
3. Manufacturing
4. Electricity, gas, and water supply
development ladder tend to have a
5. Construction
6. Wholesale and retail trade, hotels, and restaurants
bigger agriculture sector as a share
7. Transport, storage, and communications
8. Finance, real estate, and business activities
9. Community, social, and personal servicesof value added.72 Figure 67 shows73
the industry composition of the
Figure 67 Industry Shares of Value Added, 2012
Asian economies in 2012, and indiSources: Official national accounts in each country, including author adjustments.
cates a broad, negative correlation
between the share of the agriculture sector and the relative per capita GDP against the US. Half of the Asian countries compared have an agriculture sector accounting forover 10% of total value added. They all have a relative per capita GDP that is 20% below the US.
Among them, the three countries with the biggest agricultural share are all in the lowest income
group (with a per capita GDP less than 10% of the US). In contrast, the agriculture sector is 10% or lessof the total value added for Group-L2 countries, compared with 3% or less for Group-L1 economies. In
particular, agriculture accounts for less than 1% in the US, and is negligible in Hong Kong and 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 (31%), andthe US (33%). Mining appears to be what defines oil-exporting countries, typically accounting for over
40% of total value added, except in Bahrain (26%), Iran (16%), and the UAE (39%), which are countries
that have managed to diversify mining. Finance is the biggest sector in Bahrain, accounting for 21% of
total value added, whereas it is the second largest sector (15%) in the UAE, following mining.

72: 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 and Pakistan; at basic prices for Cambodia, Hong Kong, India, Korea, the Lao PDR, Mongolia, Nepal, andSingapore; at producers’ prices for Iran, the ROC and the Philippines; and at market prices for Bangladesh, Indonesia, Japan, Malaysia, Sri Lanka, Thailand, and Vietnam.
73: 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.

88

6.1 Output and Employment

Figure 69 shows the breakdown of
the manufacturing sector, comprising nine sub-industries, for 17 selected Asian countries and the US.74
The dominance of machinery andequipment in Asian manufacturing
can be clearly seen, particularly in
the ROC and Singapore (close to
60% of 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 light manufacturing (e.g., the food products,% TFP Growth during 2000–2012

4.5
4.0

Mongolia
China

3.5
India
3.0
2.5
Sri Lanka
2.0

Hong Kong

Indonesia

Pakistan

1.5

Iran

1.0

ROC
Malaysia

Singapore
Fiji

10

15

Korea

Philippines

VietnamUS

6

Thailand

Japan

0.5

Bangladesh

0.0
0

5

20

25

30

35 %

Manufacturing Share, 2012

Figure 68 Manufacturing Share and TFP Growth, 2000–
2012
Sources: Official national accounts in each country, including author adjustments,
and APO Productivity Database 2014.01.

51
51
50

19

38
32

8

27
25

7

20

8
12

9
6
4 3
15
21
47
65
3
9

15
16
11 5
14
29
23 5
12
42
3 21
12
35
1 3 3
12
22
14
2 3
10
2 5
16
5 3 2
5 2 3
18
16
3
4 4 2
31
4 2

0

20

4

13
11

7

40

3 2
1

7

19

9
3 2

15
24
10

15

6
3 3

15

5 1
31
33
8

2
4 2
3 3

18
11
24

4
7
22 3 3 2

45
40
11

2 3
8
6

20
39
27

4 2
10
61

5 1

75
50
57

60

80

2 3 Mongolia
4 Sri Lanka
3 Philippines
6Fiji
1 Indonesia
6
Hong Kong
5 Thailand
6 2 Bangladesh
8
Cambodia
5
Japan
5 US
1 Iran1 Malaysia
6
India
5 ROC
8 1 Kuwait
1 Korea
4 Singapore

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 69 Industry Shares of Value Added in Manufacturing, 2012
Sources: Official national accounts in each country, including author adjustments.

74: 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.

89©2014 Asian Productivity Organization

For fostering productivity in theless-developed countries, it is important to adopt existing technologies from the advanced economies.
In this view, manufacturing is a key
sector in propelling countries tomake a leap in economic development. It accounts for around 20% of
total value added or more in eightof the 29 Asian countries compared.
Among these, manufacturing is thelargest sector in China, Korea, andThailand, equivalent to around 30%
of total value added, while in the
ROC, Malaysia, and Indonesia it accounts for a quarter or more. Our
TFP estimate in Chapter 5 shows apositive correlation between the
TFP growth during 2000–2012 andthe shares of manufacturing in2012 in 18 Asian countries and the
US (Figure 68). At the other endof the spectrum are six countries
where manufacturing accounts forless than 10%. Among these, twoare oil-exporting countries and theother three are Hong Kong (2%),
Mongolia (7%), and Nepal (6%).
These compare with the values for
the US at 12% and Australia at 7%.

6 Industry Perspective

beverages, and tobacco products sector in the Philippines, Sri Lanka, Fiji, and Mongolia, and the textiles, wearing apparel, and leather products sector in Cambodia and Bangladesh). Coke, refined petroleum products, chemicals, rubber, and plastic products are also a prominent subsector, not least in
Kuwait, where they account for two-thirds of the country’s manufacturing value added.
Figure 70 shows the industry shares of value added and employment by the four country groups
based on 2012 income levels, compared with the Asia29 average and the US for the years 1980, 1990,
2000, and 2012.75 The first thing to note is that in 2012, the service sector accounted for the largest
share of total value added in all country groups, independent of their economic development.76 Thatsaid, Group-L1 has always had the biggest service sector among all Asian countries. This has becomemuch more distinctive as the bulk of the economy in this group continues to shift heavily toward
services over time. By 2012, the service sector accounted for 62% of total value added in Group-L1,
compared to 80% in the US and 54% in Group-L2.77 The weight of the service sector is similar in GroupL3 and Group-L4 at 47% to 53%. This reflects the relative importance of manufacturing to the former,
and agriculture for the latter, at their particular stages of development.
The second noteworthy point is that Asia29 remains 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 61% in 1980 to 38% in 2012. In the past three decades, thevalue-added share of agriculture in Group-L3 has more than halved from 30% in 1980 to 13% in 2012,
with the most rapid shift taking place in the 1990s. Employment in the sector was also cut by one-third

%

100

1980

1990

2000

2012

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
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

US

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 70 Industry Shares of Value Added and Employment by Country Group, 1980,
1990, 2000, and 2012©2014 Asian Productivity Organization

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

75: 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.
76: 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.
77: If Figure 67 was to rank by the size of the service sector, Hong Kong would top the table at 93.0%, followed by the US (79.9%), andother Group-L1 countries, namely the ROC (68.2%), Japan (72.6%), and Singapore (73.9%). Fiji is an exception, with a large service
sector share (65.2%) relative to its per capita GDP level.

906.1 Output and Employment

over the same period. The least well-off countries, in contrast, have not been as successful in diversifying away from agriculture, which accounted for 21% of total value added and 47% of employment in
2012, compared with 33% and 64%, respectively, in 1980. In the meantime, the richest economies continued to squeeze agriculture even though it had a share of only 4% in total value added
and 16% in total employment in 1980. By 2012, the figures had fallen to 2% 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.78 Thus,
countries with a big agriculture sector often have low per capita GDP, and shifting out of agriculture
will help boost economy-wide labor productivity. The US is an exception, where its agricultural valueadded share and employment share are similar; suggesting that labor productivity in this sector ishigher than that experienced in Asian countries. The reverse is true for the sector of finance, real estate, and business activities, which often generate a much bigger value-added share than suggested
by its employment share. In 2012, the sector accounted for 33% of total value added generated by
19% of employment in the US, and 14% and 2%, 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 3 percentage points in Asia29.

6

The third point to note is that the industry structure in Asian countries differs from that in the US regarding the relative importance of manufacturing, even in Group-L1 countries, where manufacturingaccounts for 17% of the economies’ value added, compared with 12% in the US in 2012. The US economy is highly skewed toward the service sector, accounting for 80% of the total value added, compared with an average of 62% 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 17%. 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 sizeof a country’s manufacturing sector.79 In Asia, the manufacturing employment share is typicallysmaller than the value-added share 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.

78: 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.
79: If Figure 67 was to rank by the size of the manufacturing sector, China would lead with a share of 31.1%, followed by Thailand andKorea at 29.1% and 31.1%, respectively.

91©2014 Asian Productivity Organization

Figure 71 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 2012. Vietnam and Mongolia
are two countries where the agriculture sector experienced similar declines but within a much shorter6 Industry Perspective

%

%

30

Bahrain
ROC
Japan
Kuwait
Qatar
Singapore

25
20

BruneiHong Kong
Korea
Oman
Saudi Arabia
UAE
Australia

30

Iran
Malaysia
ThailandTurkey

25
20

15

15

10

10

5

5
0

0
1970

1980

1990

2000

1970

2010

1980

1990

2000

2010

Group-L2

Group-L1
%

%

60

China
India
Mongolia
Sri Lanka

50

70

Fiji
Indonesia
Philippines
Vietnam

60
50

40
40
30
30
20

Bangladesh
Lao PDR
Nepal

20
10

10
1970

1980

1990

2000

2010

Group-L3

1970

1980

Cambodia
Myanmar
Pakistan
1990

2000

2010

Group-L4

Figure 71 Long-Term Trends of Value-added Share in the Agriculture Sector, 1970–2012
Sources: Official national accounts in each country, including author adjustments.

©2014 Asian Productivity Organization

period (from the late 1980s and mid-1990s, respectively). The relative decline of agriculture was most
rapid in Korea, from 29.0% of total value added in 1970 to 2.6% in 2012. In many countries, the shareof the agriculture sector more than halved between 1970 and 2012: for example, from 44% to 15% inIndonesia, from 42% to 18% in India, and from 40% in 1972 to 18% in Bangladesh. In China, the shareof this sector also significantly declined, from 36% in 1970 to 10% in 2012.
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 2012. Figure 72 shows countries’ industry shares in total employment, and ranks them by size of employment in the agriculture sector.80
Group-L4 and Group-L3 countries and Thailand cluster at the top in Figure 72, with the share of
agricultural employment ranging from 31% (Sri Lanka) to 73% (Nepal). Figure 73 traces the historical trajectory of Japan’s employment share of agriculture for the period 1885–2012 and the countries’
levels in 2012, mapped against Japan’s experience (as circles). Large shares of agriculture employment over 30% in 12 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 andper capita income.

80: Data for the Lao PDR and Myanmar are unavailable for Figure 72.

926.1 Output and Employment

It is the manufacturing sector
that largely absorbs workers
who have been displaced fromthe agriculture sector, especiallyin the initial stages of economic
development. Figure 75 traces
the trajectory of growth rates of
GDP and employment in combination with manufacturing forseveral Asian countries and the
US over the past four decades.
Each dot represents the averageannual growth rate in the 1970s,
1980s, 1990s, and 2000s (2000–
2012). The growth rate in the
2000s is illustrated by a white
dot. If manufacturing GDP and
employment grow at the samerate, a dot will be on a 45° line
through the origin running fromthe lower left to upper rightquadrants. Despite positive
gains in manufacturing GDP, for
the US and Japan, the overall
growth in manufacturing employment was negative, except
during the 1970s for the US andthe 1980s for Japan.

Nepal
CambodiaIndia
3 1 1116
1
14
647
Vietnam
8 2 1016
13
547
Bangladesh
5 1 1116
14
7
45
Pakistan
13
5
1
21
4 8
8
40
Myanmar
23
21
14
6
13
40
Thailand7 2
15
4 6 2 623
35
Mongolia
5 2
21
1
14
6
15
35
Indonesia
41
11
1 10
1
19
20
33
China
5
8
22
1 8
6
18
32
Philippines
6 4
15
1
19
6
18
31
Sri Lanka
7
5
20
1 6
1
19
17
25
Turkey
4
10
15
1
1
16
15
17
19
Iran
10
7
24
1 9
18
19
13 1
Malaysia
3
14
21
7
18
6
22
9 2
Fiji
14
8
23
17
7
24
6
Korea
9
5
23
27
8
22
5
ROC
4 4
18
16
42
5 1 7 1
Saudi Arabia
5
8
18
1 8
16
40
5
Japan
6 3
12
33
33
5 1 7 1
Oman
10
8
18
40
3 2 8 1 11
UAE
5
7
21
43
32 8 1 9
Australia
5 4
21
20
36
3 4 6 2
Brunei10 3 1057
1 2 5 1 11
Kuwait
19
5
14
5
46
11 8
US
6 2
13
8 1
37
27
1 6
Qatar
9 3
14
20
40
1 12
Bahrain
8
10
20
16
13
32
Singapore
18
12
31
4
8
26
Hong Kong
0
10
20
30
40
50
60
70
80
90 100 %
7 13

8

21 6

3

15

31

10

10

11

5 2

8

73

11

56

52

1

11

1. Agriculture
3. Manufacturing
5. Construction
7. Transport, storage, and communications
9. Community, social, and personal services

Group-L4(except for
India and
Vietnam)Group-L3(except for
Thailand)6

Group-L2(except for Fiji)Group-L1

2. Mining
4. Electricity, gas, and water supply
6. Wholesale and retail trade, hotels, and restaurants
8. Finance, real estate, and business activities

Figure 72 Industry Shares of Employment, 2012
Sources: Official national accounts in each country, including author adjustments.

Agriculture Share in Total Employment

0.8
Nepal

Japan (1885–2012)

0.7
0.6
0.5
0.4
0.3
0.2

Cambodia

India
VietnamBangladesh

PakistanThailandIndonesia
Philippines

Mongolia
China
Sri Lanka
Iran
Malaysia

0.1

Fiji

ROC
Korea
BruneiSingapore
0.0
Hong Kong
1881 1891 1901 1911 1921 1931 1941 1951 1961 1971 1981 1991 2001 2011

Figure 73 Employment Share of Agriculture in Japan
during 1885–2012 and Levels of Asian Countries in 2012
Sources: Official national accounts in each country, including author adjustments. The
sources of historical data of Japan are Long-Term Economic Statistics by Ohkawa et al.
(1974) during 1885–1954 and Population Censuses since 1920.

93©2014 Asian Productivity Organization

The trend of employment shareover time (Figure 74) suggeststhat the relative decline in theshare of agriculture in total value added has been accompanied by a downward trend in its
share in total employment.81
This trend is unmistakable inmost of the countries plotted in
Figure 74.82 Between 1970 and2012, the employment share in
agriculture shrank from 50% to
6% in Korea and from 20% to 5%
in Japan. Employment in agriculture also fell rapidly in the
ROC, from 25% in 1978 to 5% in
2012. In China, the share has declined from 71% in 1978 to 33%
in 2012.

6 Industry Perspective

%

%

60

Bahrain
ROC
Japan
Kuwait
Qatar
Singapore

50
40

BruneiHong Kong
Korea
Oman
Saudi Arabia
UAE
Australia

90

Iran
Malaysia
ThailandTurkey

80
70
60
50

30

40

20

30
10

20

0
1970 1975 1980 1985 1990 1995 2000 2005 2010101970 1975 1980 1985 1990 1995 2000 2005 2010

Group-L1

Group-L2

%

%

80

100

70

90

60

Bangladesh
MyanmarCambodia
Nepal
Pakistan

80

50
70
40
60

30
20
10

50
China
Fiji
Indonesia
Philippines

India
Mongolia
SriLanka

40
Vietnam01970 1975 1980 1985 1990 1995 2000 2005 201030
1970 1975 1980 1985 1990 1995 2000 2005 2010

Group-L3

Group-L4

Figure 74 Long-Term Trends of Employment Share in the Agriculture Sector, 1970–2012
Sources: Official national accounts in each country, including author adjustments.

©2014 Asian Productivity Organization

In Korea and the ROC, expansions of manufacturing output could allow for increases of employment
in the 1970s and the 1980s, but since the 1990s manufacturing has no longer been an absorption sector of employment, regardless of the sound expansion of production in this sector (Figure 75). The
experiences of Singapore, Indonesia, and Thailand are closer to the 45° line through the origin, which
implies well-balanced growth of output and employment in the manufacturing sector. The job creation role of manufacturing still seems effective or becoming more important in Indonesia andPakistan, but it is diminishing rapidly in India and Iran.

81: Nepal’s employment-by-industry figures are constructed by interpolating benchmark data taken from its labor force survey as wellas its population census. Figure 74 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.
82: 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.

946.2 Industry Growth

%

2

%

10

Growth of
Employment in Mnf
1980s

1

0

−2

6

Growth of
GDP in Mnf

0

2

4

4

1970s

1970s

2

6%

−1

−8

−4

2000s

−2

Growth of
Employment in Mnf

8

0
−2

Growth of
GDP in Mnf

0

4

8

12

16 %

1980s

6

−4

1990s

−6
−3

−8

Japan
US
Australia

ROC
Hong Kong
Korea

2000s

−10

1990s

−4

−12
%

%

10

6

Growth of
Employment in Mnf
1970s

Growth of
Employment in Mnf

5

8
China
Indonesia
Singapore
Thailand

6

2000s

India
Iran
Pakistan
Sri Lanka

4

3
4
2

1980s

2

0

1990s

1

2000s
Growth of
GDP in Mnf

1990s

0

1970s

5

10

15

20

25 %

1980s

Growth of GDP in Mnf

0
0

2

4

6

8

10 %

Figure 75 Job Creation in Manufacturing, 1970–2012___Average annual growth rates of GDP at constant prices and number of employment
Sources: Official national accounts in each country, including author adjustments.
Note: Each dot represents the average annual growth rate in manufacturing (mnf ) in the 1970s, 1980s, 1990s, and 2000s (2000–
2012). The white dots indicate the rate in the latest decade.

In Section 3.1, it can be seen that, as a region, growth in Asia29 accelerated in the most recent period
2005–2012, averaging 6.2% per annum, up from 5.6% in 2000–2005. China and India have been thetwo main drivers among the Asian economies, accounting for 45% and 16% of the region’s growthduring 1990–2012, respectively (Figure 7, p. 20). However, looking at the industry composition, theorigins of economic growth in China and India are quite different. Bosworth and Collins (2008) indicate that China’s economic growth has been fueled by industry sector expansion,83 whereas India
economic growth has been led by service sector expansion, based on their observation during 1978–
2004. Although the findings broadly support their conclusion, it also discerns that the nature of
growth in China may have started shifting more toward services in recent years.

83: The industry sector in Bosworth and Collins (2008) is equivalent to the industry groups 2–5 in this report.

95©2014 Asian Productivity Organization

6.2 Industry Growth6 Industry Perspective%

12

1990−2000

10

2000−2012

8
6
4
2
0
−2
Japan
BruneiFiji
USAustralia
ROC
Nepal
Korea
Hong Kong
Malaysia
TurkeyThailand
Pakistan
Iran
UAE
Oman
Saudi Arabia
Philippines
KuwaitSingapore
Indonesia
Sri Lanka
Bahrain
Bangladesh
VietnamMongolia
India
Cambodia
Lao PDR
China
Myanmar
Qatar

MongoliaJapan
Fiji
Brunei
Saudi Arabia
Philippines
Hong Kong
US
TurkeyAustralia
Indonesia
Pakistan
Oman
ThailandBahrain
Bangladesh
Nepal
KuwaitIran
Sri LankaIndia
Lao PDR
ROC
Korea
Qatar
MyanmarCambodia
UAE
Singapore
Malaysia
Vietnam
China
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 76 Industry Origins of Economic Growth, 1990–2000 and 2000–2012___Industry decomposition: Average annual growth rate of GDP at constant prices
Sources: Official national accounts in each country, including author adjustments.

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 76).84 The gap
between contributions of manufacturing and services was the widest in the early 1990s; narrowing in
the late 1990s until a redress in 2000–2012, with manufacturing and services accounting for 35% (Figure 77) and 44% (Figure 78) of economic growth, respectively. In contrast, economic growth in India
has always been dominated by services. Its growth has only become more pronounced over time. The
contribution of manufacturing and services to economic growth were 16% (Figure 77) versus 64%(Figure 78) in 2000–2012, compared with 18% and 51% in 1985–1990. The increased prominence ofthe service sector has weakened, not so much manufacturing’s hold, but agriculture’s, where the contribution shrank from 18% in the late 1980s to 9% in the latest period of comparisons.
Manufacturing has sustained its prominence in Thailand, Korea, and the ROC, contributing 32%, 42%,and 48% to economic growth in 2000–2012, respectively. Its importance is modest in Singapore at
25% (Figure 77). In Hong Kong, it has been a drag on economic growth in the past decade or so. During the Asian crisis, the most impaired economies were Thailand and Indonesia, and the sectors whichbore the brunt were construction, wholesale and retail trade, hotels, and restaurants, and finance, realestate, and business activities. In contrast, manufacturing played a significant role in bolstering the
economy at the time (Figure 77).

©2014 Asian Productivity Organization

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 78). 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

84: 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) = ∑ j (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.

96

6.2 Industry Growth

1990−2000
5.0 4.0 3.0 2.0 1.0 0.0 −1.0 %
4.4
2.4
2.2
2.1
1.8
1.6
1.6
1.5
1.3
1.3
1.3
1.3
1.2
1.0
1.0
0.9
0.7
0.7
0.6
0.6
0.6
0.5
0.5
0.5
0.5
0.4
0.3
0.2
0.2
0.1

Contribution

China
Malaysia
Korea
Cambodia
Singapore
VietnamIndonesia
ThailandSri Lanka
UAE
ROC
Lao PDR
TurkeyBangladesh
Iran
India
Bahrain
Nepal
US
Philippines
Pakistan
MyanmarOman
Fiji
Saudi Arabia
Brunei
KuwaitAustralia
Japan
Qatar
−0.4
Hong Kong−0.8 Mongolia

2000−2012
−30

0

30

60 %
44

4.0 3.0 2.0 1.0 0.0 −1.0 %
3.3
2.2

33

1.8

36
31

1.8

25

1.7

22

1.6
1.4

41

1.3

34

1.3

25

1.2

18

1.1

22

1.1

22

1.0

33
22

0.9

19

0.9

16

0.9

17

0.9

15

0.9

19

0.8

21

0.8
0.8

14

0.8

9

0.6

12

0.5

24
17

0.3

18

0.3
0.2

5

0.1

7

0.1

18

0.1

1

0.0

−14

−0.1

50

Contribution share

Contribution

0

−30
China
MyanmarCambodia
Vietnam
ROC
Korea
ThailandBangladesh
Singapore
Indonesia
India
Pakistan
Malaysia
Oman
Bahrain
Iran
Philippines
Qatar
Lao PDR
Sri Lanka
TurkeySaudi Arabia
Mongolia
Kuwait
UAE
Japan
US
Fiji
Nepal
Australia
BruneiHong Kong

30

60 %
35

21
25
28
48
42
32
22
25
24

6

16
25
24
21
17
22
19
8
11
15
19
17
9
9
7
49
10
8
2
2
6
−3

Contribution share

Figure 77 Contribution of Manufacturing to Economic Growth, 1990–2000 and 2000–2012
Sources: Official national accounts in each country, including author adjustments.

stage when manufacturing steers growth.85 Within the service sector, contribution is quite evenly
spread among the sub-sectors, more recently the iron/steel and motor vehicle sectors have been intensively developed.86 For further improvement in per capita GDP and to capitalize on the demographic dividend (see Box 2, p. 34), expansion of labor-intensive manufacturing may be required inIndia for greater job creation.

85: 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).
86: In 2013, India was the 6th largest producer (3.9 million) of motor vehicles (87.3), following Korea (4.5), Germany (5.7), Japan (9.6), theUS (11.0), and China (22.1), 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©2014 Asian Productivity Organization

Economic growth in the Asian Tigers was also dominated by the service sector, albeit more so in Singapore and Hong Kong than in the ROC and Korea, where manufacturing remained a significant force.
The service sector accounted for 51% of growth in the ROC for the period 2000–2012, 52% in Korea,
71% in Singapore, and 102% in Hong Kong, counterbalancing the negative contribution of 3% by
manufacturing and 2% by construction (Figure 78). 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 40% of
growth. This compares with 21% in Singapore and 18% in the ROC. In contrast, the sector contributed
only 7% to Korea’s growth over the same period. Finance, real estate, and business activities also
played an important role, contributing 43% to growth in Hong Kong, 29% in Singapore, and 14% in
the ROC.

6 Industry Perspective

1990−2000
5.0 4.0 3.0 2.0 1.0 0.0 −1.0 %
4.8
4.6
4.4
3.9
3.4
3.3
3.3
3.2
3.1
2.9
2.9
2.8
2.8
2.5
2.5
2.5
2.3
2.3
2.2
2.1
2.1
2.0
1.9
1.8
1.8
1.7
1.4
1.3
1.2
1.1
0.9

Contribution

Singapore
UAE
ROC
Malaysia
China
Korea
India
KuwaitHong Kong
Sri Lanka
Iran
Australia
Vietnam
US
Nepal
Cambodia
BahrainThailand
Pakistan
Bangladesh
Oman
MyanmarTurkeyQatar
Lao PDR
Philippines
Indonesia
Fiji
Japan
Saudi Arabia
Brunei−0.3 Mongolia

2000−2012
0

30

60

90 %
65

5.0

4.0

3.0

2.0

1.0

4.5

64

4.3
74

4.3

54

4.3

34

4.2
55

4.1

60

4.0

67

3.7
103

56

3.5
3.3

59

3.2
79

3.1

38

3.0
76

3.0

53

2.9

36

2.9
53

2.8

52

2.7

51

2.7

47

2.6

49

2.5

32

2.5
54

2.4

29

2.3

30

2.2
57

2.1

36

2.0
59

1.8
97

1.4

40

1.2

39

1.1

17

0.5

Contribution share

Contribution

0.0 %
India
Mongolia
China
Qatar
Hong Kong
Bahrain
MyanmarLao PDR
Singapore
Sri Lanka
Cambodia
Bangladesh
Philippines
TurkeyUAE
Vietnam
Malaysia
Indonesia
Iran
Oman
KuwaitPakistan
Saudi Arabia
Thailand
Nepal
Australia
Korea
ROC
US
Brunei
Fiji
Japan

0

30

60

90 %
64
64

44
38
102
76
39
49
71
61
44
53
63
69
67
45
65
52
61
58
51
57
53
54
59
71
52
51
95
196
80
93

Contribution share

Figure 78 Contribution of Service Sector to Economic Growth, 1990–2000 and 2000–2012
Sources: Official national accounts in each country, including author adjustments.

©2014 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
economies from one period to another. In 2000–2012, mining accounted for almost half of economic
growth in Qatar, 33% in Kuwait, 20% in Saudi Arabia, and only 3% in Iran, reflecting a drop in the demand toward the end of 2008 and 2009 (Figure 76). Still, it has been a drain on growth, in some cases
a quite significant one. Its contribution was –7% in Bahrain and –134% in Brunei, reflecting a reduction in oil or gas production. These countries would do well to diversify. Bahrain has been successful
in branching into finance, real estate, and business activities, which accounted for 32% of the 5.5%
overall growth over the same period. Oman also sustained growth of 4.5% on average per year, 58%
of which originated from the service sector. Brunei has not managed as well, with dismal growth of
0.7% on average per year between 2000 and 2012. Oil and gas production activities are also reflected
in Mongolia and the Lao PDR, where mining accounted for 17% and 18% of overall economic growth,
respectively, in the 2000s.
For some Asian countries, agriculture is still the biggest sector. The four countries in which the agriculture sector has the largest share in total value added are Myanmar, Cambodia, Nepal, and the Lao PDR(Figure 67). For the period 2000–2012, agriculture in Myanmar, Nepal, and Cambodia had the highest
contribution to economic growth among all Asian countries, accounting for 33%, 30%, and 22% ofgrowth, respectively.87 In the latest period, agricultural output is still expanding in the majority of

87: In Myanmar, agriculture accounted for over 36.4% of GDP in 2012. 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 32.9% of GDP growth in 2000–2012.

98

6.2 Industry Growth

Table 15 Output Growth by Industry, 2000–2012

6. Wholesale andretail trade, hotels,
and restaurants

7. Transport,
storage, andcommunications

8. Finance, realestate, andbusiness activities

9. Community,social, andpersonal services

Total economy−1.7 (−0.4) 7.4 (0.9) 12.3 (0.2) 7.6 (0.6)
7.6 (0.1) 7.5 (1.3) 7.2 (0.1) 7.1 (0.6)−1.3 (−0.8) 0.2 (0.0) 2.6 (0.0) 4.5 (0.1)
18.1 (0.1) 10.3 (1.8) 11.0 (0.1) 7.8 (0.5)
10.3 (0.5) 10.3 (3.3) 10.3 (0.3) 11.4 (0.7)−2.6 (−0.0) 6.4 (1.7) 2.6 (0.0) −0.4 (−0.0)
0.8 (0.0) 0.8 (0.1) 2.4 (0.1) 2.1 (0.1)−3.1 (−0.0) −3.2 (−0.1) 1.5 (0.0) 0.2 (0.0)
3.8 (0.1) 7.4 (1.1) 5.7 (0.1) 8.2 (0.6)
1.2 (0.1) 4.6 (1.2) 7.3 (0.1) 6.7 (0.5)
0.8 (0.2) 7.0 (0.9) 6.5 (0.1) 2.5 (0.1)−8.1 (−0.0) 1.3 (0.3) −2.0 (−0.0) −2.4 (−0.1)−1.3 (−0.0) 5.9 (1.6) 5.0 (0.1) 1.2 (0.1)
3.3 (1.6) 7.0 (0.5) 12.6 (0.2) 4.2 (0.1)
36.8 (1.4) 9.0 (0.8) 5.6 (0.2) 9.0 (0.5)−0.0 (−0.0) 3.6 (1.0) 4.5 (0.1) 3.9 (0.1)
5.7 (1.1) 7.9 (0.6) 4.0 (0.1) 9.7 (0.3)
12.5 (0.1) 17.4 (2.2) 11.1 (0.1) 16.5 (0.6)
3.8 (0.0) 1.3 (0.1) 5.4 (0.1) 3.3 (0.2)
0.1 (0.1) 10.6 (0.9) 9.2 (0.1) 17.9 (0.7)
4.8 (0.1) 6.4 (1.1) −0.4 (−0.0) 3.3 (0.1)
9.7 (0.1) 3.9 (0.9) 4.1 (0.2) 4.3 (0.2)
9.5 (5.0) 10.1 (0.9) 7.9 (0.1) 20.3 (1.1)
2.1 (0.9) 7.6 (0.8) 10.3 (0.1) 6.1 (0.3)
0.0 (0.0) 5.2 (1.3) 3.8 (0.1) 3.3 (0.1)
12.9 (0.2) 4.4 (0.8) 6.3 (0.1) 7.9 (0.6)
4.6 (0.1) 4.6 (1.4) 5.6 (0.2) 3.3 (0.1)
0.9 (0.3) 3.0 (0.3) 9.0 (0.2) 7.4 (0.7)
2.5 (0.2) 9.6 (1.8) 10.2 (0.4) 8.0 (0.5)

5.3
6.4
5.1
7.3
11.9
3.1
2.0
6.1
7.9
6.2
4.9
0.1
2.6
2.8
10.0
6.2
11.8
9.9
1.7
6.0
4.2
5.2
14.8
9.6
5.6
5.2
3.7
4.8
7.5

(0.4)
(0.9)
(0.2)
(1.1)
(1.2)
(0.6)
(0.3)
(1.7)
(1.3)
(0.9)
(0.7)
(0.0)
(0.3)
(0.2)
(2.0)
(0.8)
(1.3)
(2.2)
(0.2)
(0.5)
(0.7)
(0.9)
(0.9)
(0.7)
(1.1)
(1.2)
(0.7)
(0.9)
(1.2)

9.0
7.1
4.2
7.2
8.6
3.1
2.0
4.0
11.3
11.7
8.1
1.4
4.8
10.6
8.5
6.0
12.6
15.0
6.3
13.2
3.1
6.6
21.0
11.6
4.0
8.3
5.8
7.7
8.0

(0.5)
(0.7)
(0.1)
(0.5)
(0.7)
(0.2)
(0.3)
(0.5)
(0.9)
(0.7)
(0.6)
(0.1)
(0.4)
(0.6)
(0.4)
(0.4)
(1.6)
(1.5)
(0.6)
(0.7)
(0.4)
(0.5)
(0.7)
(0.5)
(0.5)
(1.0)
(0.4)
(0.6)
(0.3)

6.8
4.5
4.0
8.4
10.7
2.5
1.5
5.0
9.7
6.5
6.3
0.1
3.3
4.4
8.6
6.8
8.5
22.3
4.3
6.4
5.2
6.3
14.9
6.8
5.3
5.6
6.0
6.0
5.5

(1.7)
(0.4)
(0.2)
(0.7)
(1.0)
(0.5)
(0.3)
(1.7)
(1.5)
(0.5)
(0.9)
(0.0)
(0.7)
(0.7)
(0.5)
(0.9)
(0.9)
(0.0)
(0.6)
(0.6)
(0.4)
(1.0)
(1.7)
(0.6)
(1.4)
(0.7)
(0.7)
(1.0)
(0.6)

8.8
5.6
3.9
8.9
10.1
2.5
1.2
1.7
6.1
5.3
3.0
1.1
3.3
6.1
9.7
5.7
4.3
11.1
7.2
5.7
6.4
4.6
10.6
3.7
4.8
4.0
3.4
7.5
6.6

(1.5)
(1.0)
(0.7)
(1.0)
(1.4)
(0.5)
(0.2)
(0.3)
(0.8)
(0.5)
(0.4)
(0.3)
(0.6)
(1.0)
(0.8)
(0.7)
(0.6)
(0.3)
(0.8)
(0.8)
(1.0)
(0.6)
(1.0)
(0.6)
(0.5)
(0.4)
(0.5)
(0.5)
(0.7)

5.5
5.8
0.6
7.3
9.7
3.6
1.4
4.1
7.1
5.2
4.3
0.5
3.9
4.9
7.6
4.3
6.7
10.5
3.7
4.5
4.3
4.7
11.3
4.6
5.0
5.4
4.3
4.4
6.5

2.9
3.5
3.4
3.7
3.1
3.6
3.1
5.1
1.0

(0.3)
(0.4)
(0.3)
(0.3)
(0.6)
(0.4)
(0.4)
(1.4)
(0.0)

1.8
5.2
4.0
10.0
4.2
1.5
1.2
3.6
2.5

(0.1)
(0.2)
(0.3)
(0.3)
(0.1)
(0.1)
(0.1)
(0.2)
(1.1)

4.7
7.2
7.2
7.9
7.1
4.9
4.4
11.0
6.9

(0.9)
(1.7)
(1.6)
(2.1)
(1.1)
(1.2)
(1.2)
(1.9)
(0.7)

2.9
5.9
6.1
6.2
4.7
6.0
5.2
10.0
10.1

(0.1)
(0.2)
(0.2)
(0.2)
(0.1)
(0.1)
(0.1)
(0.3)
(0.1)

(0.2)
(0.4)
(0.4)
(0.3)
(0.5)
(0.3)
(0.3)
(0.5)
(0.4)

4.4
6.4
6.5
6.5
7.1
5.7
5.4
8.3
7.4

(0.7)
(0.9)
(0.9)
(0.8)
(1.2)
(0.9)
(0.9)
(0.0)
(0.7)

5.9
6.8
7.0
5.5
9.4
8.2
8.0
10.7
10.7

(0.5)
(0.6)
(0.6)
(0.5)
(0.8)
(0.6)
(0.6)
(0.6)
(0.6)

4.7
6.1
6.1
5.0
9.1
6.2
6.2
5.8
6.7

(0.7)
(0.8)
(0.8)
(0.7)
(1.3)
(0.7)
(0.7)
(0.5)
(0.8)

3.2
5.1
5.1
5.0
6.1
4.9
4.7
7.2
5.1

(0.6)
(0.8)
(0.8)
(1.0)
(0.8)
(0.6)
(0.5)
(0.6)
(0.7)

4.0
5.9
5.8
6.1
6.6
4.9
4.8
6.1
5.1

1.4
1.1
1.8

(0.0)
(0.0)
(0.2)

1.2
3.8
1.7

(0.0)
(0.3)
(0.0)

1.2
3.0
4.0

(0.2)
(0.1)
(0.8)

0.4
1.0
4.9

(0.0) −2.8 (−0.1)(0.0) 6.4 (0.4)(0.1) 4.0 (0.2)

1.4
3.0
3.5

(0.2)
(0.4)
(0.6)

3.6
3.4
5.6

(0.3)
(0.3)
(0.9)

2.1
3.1
5.8

(0.7)
(0.6)
(0.9)

1.2
3.0
4.0

(0.3)
(0.9)
(0.6)

1.5
3.0
4.3

5. Construction

2. Mining

4. Electricity, gas,
and water supply−0.8 (−0.0)
3.5 (0.7)
3.1 (0.0)
4.7 (1.6)
4.2 (0.5)
0.5 (0.0)
0.0 (0.0)−3.1 (−0.0)
3.2 (0.6)
3.5 (0.5)
3.3 (0.3)−1.5 (−0.0)
0.9 (0.0)
10.2 (0.0)
2.8 (0.9)
2.9 (0.3)
2.2 (0.3)
7.4 (3.5)
3.2 (1.1)
2.8 (0.0)
2.7 (0.6)
2.8 (0.4)
5.4 (0.0)
1.2 (0.0)
0.9 (0.0)
2.9 (0.4)
2.4 (0.2)−2.8 (−0.0)
3.6 (0.7)

1. Agriculture
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(regrouped)
APO20
Asia23
Asia29
East Asia
South Asia
ASEAN
ASEAN6
CLMV
GCC(reference)
US
Australia
Turkey3. Manufacturing___Average annual growth rate of industry GDP at constant prices

3.5
6.1
6.3
5.8
7.9
5.9
5.5
9.3
7.9

6

Asian countries, suggesting that the shrinkage in its value-added share (Figure 71) over the recent
period is more a result of rapid growth in other sectors than any actual contraction of 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 CLMV and the GCC countries at 8.8% and 7.9% per year on average, respectively. Apart

99©2014 Asian Productivity Organization

Unit: Average annual growth rate (percentage), contribution in parentheses.
Sources: Official national accounts in each country, including author adjustments.

6 Industry Perspective

1990–2000%

20

2000–2012

%

10

0.5

1.3

16

8

12

6
12.6

8
4
0

0.7
0.3
0.4
0.3
1.6 1.4
0.4 0.3 1.1
0.9
1.7 0.8 0.7 1.3
0.5 0.9
0.4
0.4
3.6 1.7
1.7 5.6
1.6 1.5
2.3
4.9
1.0
0.6 0.3 0.3 3.5
0.6
0.3 0.9
0.3 0.5 0.6
0.6
0.4
0.4
1.3
0.5 1.0 1.8 1.3
0.7 1.2 1.2 0.7−0.4 −1.0
−0.3
−0.3

4
2
0

1.3 0.5 0.6
0.3
0.8
8.5
2.2 0.3
3.8

0.8
0.6
0.5

1.6
0.5
5.7
0.7 0.3
0.5

0.7 2.9 2.2
0.3
0.4 0.4
0.5 0.7
0.4 0.4
−0.3

2.9
5.3

4.5

0.9

1.2

0.7
0.6

2.0 2.5 2.1

0.6
1.5

2.0
0.3

1.3 1.1
0.3

1.8

Japan
Philippines
Malaysia
Indonesia
ThailandSingapore
Korea
ROC
KuwaitIndia
IranBangladesh
CambodiaJapan
US
Philippines
Indonesia
ROC
India
ThailandIran
Bangladesh
Korea
Malaysia
Cambodiafrom construction, the other fastgrowing sectors in CLMV and the
GCC countries were transportation,
storage, and communications (atover 10% per 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 9.1% per year on average in South Asia. Manufacturing
has been growing at 10.5% per year
on average in CLMV, comparedwith 4.4% in ASEAN6.

3-1. Food products, beverages, and tobacco products
3-2. Textiles, wearing apparel, and leather products
3-3. Wood and wood products
3-4. Paper, paper products, printing, and publishing
3-5. Coke, petroluem, chemicals, rubber, and plastic products
3-6. Other non-metallic mineral products
3-7. Basic metals
3-8. Machinery and equipment
3-9. Other manufacturing
3. Manufacturing

Figure 79 presents the sub-industry
origins of average annual growth of
manufacturing GDP for selected
Asian countries for the periods
1990–2000 and 2000–2012.88 Manufacturing in Asia has been domi­
Figure 79 Industry Origins of Output Growth in Manufacnated by 3-8 (machinery andturing, 1990–2000 and 2000–2012
equipment) accounting for 40%___Sub-industry decomposition: Average annual growth rate of GDP
or more of overall manufacturat constant prices of manufacturing
ing growth in half of the Asian
Sources: Official national accounts in each country, including author adjustments.
countries compared. In Korea
and the ROC, it was over 80%. The
sub-sector 3-1 (food products, beverages, and tobacco products) is the largest contributor in thePhilippines for 2000–2012, accounting for 54% of manufacturing output growth. In Bangladesh andCambodia, manufacturing growth has been dominated by the sub-sector of 3-2 (textiles, wearing
apparel, and leather products), whereas in Kuwait, and to a lesser extent Singapore and Malaysia,
it is 3-5 (coke, petroleum, chemicals, rubber, and plastic products).

©2014 Asian Productivity Organization

Figure 80 contrasts industry contributions to economic growth for the periods of 1990–2000 and
2000–2012, as well as between the US and Asian averages.89 Even within such a short period, one cansee that the industry structure of growth is changing. The first striking feature is the dominance of
manufacturing in Asian countries. Between 1990 and 2000, its contribution to economic growth in
Asia23 was 32% compared to 19% in the US. Although its significance has fallen in recent years, it stillaccounted for 29% of economic growth in Asia23 between 2000 and 2012, compared with 10% in the
US. This, however, masks a divergence within Asia. In the earlier period, manufacturing accounted for
38% of growth in East Asia but only 17% in South Asia. The corresponding figures were 35% and 17%

88: 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)= ∑ j (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.
89: 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.

100

6.2 Industry Growthin 2000–2012. The differential is somewhat narrowing.

2000−2012100
17 14 14 15 1580
15

12 12 1110 10 1114 14 12
18

40

10

3
3

4
3

2
3

9

32 31 38

20

18

24

17

4
3

4
3

33 35

8

7

4
5

15

9

5
8

15 15

10
17

6
2
15

28 24
4
6

10

12

23

19

29 28

2
7

11

6
3

5

5

6

6

4

8

11 44

6

13

18

18
6
2

1
17

4

12

16

4

7
2
35

11
0

12
18

23

25 25

2

2

2

9

9

7

31

9
3

4

18

13
11

24 21

0

1
10
2
1
−8

US

GCC

CLMV

ASEAN6ASEAN

South Asia

East Asia

Asia29

1. Agriculture
3. Manufacturing
5. Construction
6. Wholesale and retail trade,hotels, and restaurants
8. Finance, real estate, andbusiness activities

6
3

13

14 16

8

Asia23

1
0

6
3

8

5
2

APO20

CLMV

ASEAN

ASEAN6

East Asia

South Asia

Asia293

US

8

Asia23

−20

5

8

15

9

13 14 11
19

31

3

22

21

8

GCC

0

3

10
13
14 14 14 16 13 11 12

18

3
1

2
2

5
0
8

16 16

5
3

2
4

12

12
9

11

15

12 13
13
16

10 10 10

60

APO20

In ASEAN, manufacturing’s contribution
was reduced to 25% in 2000–2012 from
33% in the 1990s, while wholesale and retail trade, hotels, and restaurants increased from 16% to 18%. In the US, thefinance, real estate, and business activities
sub-sector made the biggest contribution
in both periods, accounting for 31% ofeconomic growth in 1990–2000 and rising
to 44% in 2000–2012. In contrast, its contribution in Asia23 was 13% in the period
2000–2012. Mining in GCC countries took
a hit in 2008–2009 due to the downturn inthe world economy. Consequently, thecontribution of mining fell from 24% to
21% between the two periods while construction’s share increased from 6% to 9%.
Finance, real estate, and business activities became the biggest contributors of
economic growth in GCC countries, with
its share rising from 12% to 16% between
the two periods.

1990−2000%120

2. Mining
4. Electricity, gas, andwater supply
7. Transport, storage, andcommunications
9. Community, social, andpersonal services

Figure 81 presents industry contributions
to regional economic growth in Asia29
Figure 80 Industry Origins of Regional Economic
during 2000–2012, decomposing Figure 7
Growth, 1990–2000 and 2000–2012(p. 20) in Section 3.1 into countries’ indus___Contribution share90
try origins. In each industry contribution,
Sources: Official national accounts in each country, including author adthe top eight countries are presented. The
justments.
top four industries in terms of contributions to regional growth were manufacturing (29%), wholesale and retail trade (15%), finance, real estate, and business activities (13%), andcommunity, social, and personal services (14%). A total of 29% of Asian economic growth originatedfrom the expansion of its manufacturing sector, two-thirds of which was accounted for by China. In
other words, China’s manufacturing sector alone accounted for nearly 17% of the region’s economic
growth. This was followed by China’s community, social, and personal services (7.3%) and wholesale
and retail trade, hotels, and restaurants (6.4%).

90: The average growth rate of the Asian economy for 2000–2012 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) ∑ j (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 x 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©2014 Asian Productivity Organization

Over a period of four decades there has been a noticeable shift in the industry origins of economic
growth (Figure 82). For the ROC and Korea, manufacturing has been a clear driving force behind6 Industry Perspective

3. Manufacturing (28.7%)
17.3

0

5
China

India

2.7

10

15

Korea

Indonesia

1.3

1.3 1.0

5.1

20

25
Japan

30 %
Rest of the world

6. Wholesale and retail trade, hotels, and restaurants (14.5%)
6.4

0

3.0

2

4

China

India

6

8

Indonesia

Iran

0.9

0.6 0.4

3.1

10

12

14 %

Saudi Arabia

Rest of the world

2.0

1.2

3.0

8

10

9. Community, social, and personal services (14.3%)
7.3

0

2

4

China

6

India

Japan

0.5 0.4

Indonesia

12

14 %

Korea

Rest of the world

8. Finance, real estate, and business activities (13.4%)
5.0

0

3.4

2

4

China

0.6 0.5 0.5

6

India

8

Iran

3.3

10

12

Indonesia

Korea

0.7

2.4

14 %
Rest of the world

7. Transport, storage, and communications (9.6%)
3.5

0

2.1

2

4

China

India

0.5 0.4

6

8

Indonesia

Japan

10
Iran

12 %
Rest of the world

5. Construction (6.1%)
3.5

0

1

1.4

2

China

India

3

0.5

4

Indonesia

0.2 0.2

5

Saudi Arabia

0.3

6%

Iran

Rest of the world

1. Agriculture (5.6%)
2.5

0

1.3

1
China

2
India

0.5

3

Indonesia

0.2 0.2

4Pakistan

0.8

5
Iran

6%
Rest of the world

2. Mining (5.0%)
2.8

0

0.7

1
China

2

0.4

3

Saudi Arabia

Qatar

0.2 0.2

0.7

4
Kuwait5India

6%Rest of the world

4. Electricity, gas, and water supply (2.6%)©2014 Asian Productivity Organization

1.6

0

0.5
China

0.3

1
India

Iran

0.1 0.1 0.1

1.5

2

Korea

Thailand

0.4

2.5

Figure 81 Industry Origins of Asian Economic Growth, 2000–2012___Contribution to regional growth of GDP at constant prices, using 2011 PPP
Sources: Official national accounts in each country, including author adjustments.

102

3%

Rest of the world

6.3 Labor Productivity by Industry

economic growth on the whole. In the decade between the mid-1980s and the mid-1990s, however,
the importance of manufacturing retreated in the ROC temporarily while the economy developed its
service sector. Since the mid-1990s, the role of manufacturing in the ROC has increased again, although compared to its heydays of the 1970s and 1980s its impact in terms of percentage points ismuch reduced. In Singapore, finance, real estate, and business activities, as well as wholesale and retail trade, hotels, and restaurants are important drivers alongside the manufacturing sector. Working
within the data constraints, Hong Kong appears a clear service-driven economy in recent years. Whilethe lack of diversification of the oil-exporting countries cannot be missed; historically, the dominanceof the mining sector influenced the economic volatility of these countries. In recent years the GCC
countries have been making efforts in diversifying, especially into the service sector, with different
degrees of success. Bahrain and Oman 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 the Philippines, construction was driving economic growth in the firsthalf 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.

6

6.3 Labor Productivity by Industry
Section 5.1 discusses per-worker measures of labor productivity performance in level terms, and identifies a large gap between Asia as a whole and the US. In 2012, Singapore and Hong Kong were thecountries that had labor productivity levels comparable to the US. Besides these two, the best performers in Asia achieved productivity levels that were at least 40% of the US. However, Asia collectively was dragged down by a long tail of countries with labor productivity of less than 20% of the US
level. This pulled down the average performance to 19% of the US for the APO20 and 18% for Asia23(Table 8, p. 59). In growth terms, however, Asia’s performance far exceeded the US, allowing the countries to gradually close the gap with the US over time. Labor productivity growth in Asia23 was 5.2%
per year on average between 2005 and 2012, compared to 1.3% in the US (Table 9, p. 61).

91: Labor productivity growth in Table 16 is defined simply as per-worker GDP at constant prices by industry (vj). The industry decomposition of labor productivity growth for the whole economy (v) in Figure 83 (industry contribution in Table16) is based on theequation v = ∑ jwjvj* where the weight is the two-period average of value-added shares. In this decomposition, the number ofworkers 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.
92: 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.

103©2014 Asian Productivity Organization

Table 16 presents cross-country comparisons in labor productivity growth by industry91 for the period
2000–2012.92 Positive labor productivity growth was achieved across all sectors for Asia23. If one
focuses on the regional economy, 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 are no significant differences between manufacturing and some
services in Asia23; i.e., manufacturing (at 5.0% on average per year), electricity (4.2%), transport, storage, and communications (4.1%), and agriculture (4.0%). Construction was the sector with the slowest
productivity growth at 0.7%.

6 Industry Perspective

Bahrain%50
40

Bangladesh

%
12
9

30

10

6

20

0

3

10

−10

0

0

−20

−3

−10
−20

1971 1976 1981 1986 1991 1996 2001 2006 2011

Cambodia%15−61971 1976 1981 1986 1991 1996 2001 2006 2011

China

%
15

−30

12

12

9

9

9

6

6

6

3

3

3

0

0

0

1971 1976 1981 1986 1991 1996 2001 2006 2011

Hong Kong

%
12

−3

1971 1976 1981 1986 1991 1996 2001 2006 2011

India

%
9

−3

6

5

4

3

0

0

0

−5

−4

−3

−10

1971 1976 1981 1986 1991 1996 2001 2006 2011

Iran

%
20

−6

1971 1976 1981 1986 1991 1996 2001 2006 2011

Japan

%
10
8

10

6
3

Kuwait

%
60
40

−8

Korea

0

−4

1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

%
15

0

−3

−6
−30

−15

2

−2

−20

Indonesia

9

4

−10

1971 1976 1981 1986 1991 1996 2001 2006 2011

12

6

0

ROC

%
10

8

−8

1971 1976 1981 1986 1991 1996 2001 2006 2011

%
15

12

−3

Brunei%20

1971 1976 1981 1986 1991 1996 2001 2006 2011

Lao PDR%
15−6

1971 1976 1981 1986 1991 1996 2001 2006 2011

Malaysia

%
12

10

8

5

4

0

0

−5

−4

20
0
−20
−40
−60

1971 1976 1981 1986 1991 1996 2001 2006 2011

Mongollia

1971 1976 1981 1986 1991 1996 2001 2006 2011

Myanmar

−8

%
15

12

10

6

5

4

4

1971 1976 1981 1986 1991 1996 2001 2006 2011

Nepal

%
8

16

8

©2014 Asian Productivity Organization

−10

0

2

−5

0

−8

−10

−2

−12

−15

0
−4

1971 1976 1981 1986 1991 1996 2001 2006 2011

1971 1976 1981 1986 1991 1996 2001 2006 2011

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 2011

3. Manufacturing
7. Transport, storage, and communications
Real GDP

4. Electricity, gas, and water supply
8. Finance6.3 Labor Productivity by Industry

%
30

Oman

Pakistan

%
10
8

20

6

6
10

4

0

2

3
0
−3

0
−10
−20

%
25

Qatar

−4

18

15

12

10

6

5

0

0

−6

−5

−12

−10

−18

−15

−24

1971 1976 1981 1986 1991 1996 2001 2006 2011

Sri Lanka

1971 1976 1981 1986 1991 1996 2001 2006 2011

Saudi Arabia

%
24

20

%
9

−6

−2
1971 1976 1981 1986 1991 1996 2001 2006 20110
−3
1971 1976 1981 1986 1991 1996 2001 2006 2011

Thailand

%
16

%
9

Vietnam−61971 1976 1981 1986 1991 1996 2001 2006 2011

UAE

%
100
80
60
40
20

−4

1971 1976 1981 1986 1991 1996 2001 2006 2011

6

3

0

−3

Singapore

%
15

6

4

0

1971 1976 1981 1986 1991 1996 2001 2006 2011

9

8

3

−9

12

12
6

Philippines

%
9

−8

0

−12

−20

1971 1976 1981 1986 1991 1996 2001 2006 2011

US

%
8

1971 1976 1981 1986 1991 1996 2001 2006 2011

Australia

%
8

6

6

4

4

2

2

6

3

0

0

−2

−2

0

−3

%
10

1971 1976 1981 1986 1991 1996 2001 2006 2011−41971 1976 1981 1986 1991 1996 2001 2006 2011−41971 1976 1981 1986 1991 1996 2001 2006 2011

Turkey

8
6
4
2
0
−2
−4
−6

1971 1976 1981 1986 1991 1996 2001 2006 2011

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, 1970–2012
Sources: Official national accounts in each country, including author adjustments.

105©2014 Asian Productivity Organization___Industry decomposition: Average annual growth rate of GDP at constant prices

6 Industry Perspective

Figure 83 shows the industry origins of average labor productivity growth per year in two periods:
1990–2000, and 2000–2012.93 In the past two decades, the role played by agriculture (both positive
and negative) has been diminishing in Asian countries. While the importance of manufacturing has
never waned in some countries (e.g., Korea, the ROC, China, and Thailand), it has not been a major
contributor in India in its recent development process, or in Hong Kong and Sri Lanka in the 2000s.

Table 16 Labor Productivity Growth by Industry, 2000–2012

3.3
5.0
4.9
5.3
5.5
2.3
2.6
4.7
2.1

(0.8)
(1.4)
(1.4)
(1.7)
(0.9)
(0.9)
(0.9)
(1.3)
(0.3)

1.3
4.2
4.3
3.6
6.3
1.6
2.0
1.5
5.2

−2.4
−6.0
−2.0

(0.0)
(0.2)
(0.0)

4.3
1.2
2.3

(0.5) 1.2 (0.0) −1.4 (−0.1)(0.1) −3.4 (−0.0) 3.0 (0.2)(0.4) −0.8 (0.1) 2.8 (0.1)(0.1) −3.1 (−0.2)(0.1) 0.7 (0.0)(0.1) 4.5 (0.0)(0.2) 2.2 (0.1)(0.1) −1.7 (−0.0)(0.1) 4.1 (0.0)(0.1) 0.7 (0.0)(0.2) 0.4 (0.2)(0.1) −1.7 (−1.0)

2. Mining

Total economy

(0.1)
(0.2)
(0.3)
(0.3)
(0.1)
(0.1)
(0.0)
(0.2)
(1.0)

9. Community,social, andpersonal services

0.3
3.3
2.1
7.6
4.4
−3.4
−4.5
2.5
−2.0

8. Finance, realestate, andbusiness activities−6.9 (−1.7)−0.6 (0.3)−5.7 (−1.3)−3.6 (0.3)
7.3 (0.4)−0.5 (−0.0)−7.0 (−0.3)
0.3 (0.0)−1.8 (−0.0)
1.1 (0.3)−2.1 (−0.5)−0.7 (0.0)
0.2 (0.0)
1.3 (−0.4)
0.3 (−0.2)
1.9 (−0.1)−1.0 (0.1)−1.0 (−3.9)−1.4 (−0.2)
0.8 (0.1)
2.6 (−5.1)−3.3 (−0.9)
0.0 (−0.3)
6.0 (0.5)−0.9 (−0.1)
5.8 (−0.2)−0.3 (0.1)

7. Transport,
storage, andcommunications

5. Construction

19.4 (0.2)
6.9 (0.1)
0.4 (0.0)−3.3 (0.0)
7.7 (0.3)
2.8 (0.0)−3.1 (−0.2)
2.6 (0.0)
8.0 (0.1)
3.8 (0.1)
4.9 (0.1)−2.2 (−0.0)
3.5 (0.1)
7.6 (0.1)−4.4 (0.0)
2.6 (0.0)
5.1 (0.1)−2.1 (0.0)−0.5 (0.0)
1.8 (0.1)
2.6 (0.1)
7.6 (0.1)
1.1 (0.1)
11.8 (0.2)
7.0 (0.2)
0.9 (0.1)
2.6 (0.3)−2.3 (−0.9) −3.6 (−0.4) 6.4 (1.8) 0.3 (−1.8)
3.1 (0.4) 2.1 (0.4) −4.7 (0.3) 4.6 (0.9)−0.8 (−0.8) −0.5 (−0.1) 3.5 (0.2) 5.0 (1.2)
0.2 (0.1) 1.3 (0.4) 1.3 (0.6) 0.9 (0.3)
8.0 (0.9) 7.0 (0.6) 8.5 (1.0) 7.7 (1.0)
1.9 (0.3) 2.9 (0.2) −0.2 (0.2) 0.1 (0.0)
0.0 (0.0) 1.8 (0.3) −2.4 (0.2) 1.6 (0.3)
4.8 (1.1) 2.4 (0.2) 1.7 (1.2) −0.2 (−0.2)
4.2 (0.9) 7.5 (0.7) 5.4 (1.4) 5.9 (0.8)
4.3 (0.5) 10.9 (0.7) −2.7 (0.3) 0.4 (−0.1)
2.6 (0.4) 3.9 (0.2) 1.6 (0.8) 3.5 (0.5)
0.0 (0.0) 0.8 (0.1) 0.2 (0.0) 0.3 (0.0)
2.9 (0.3) 2.6 (0.3) −0.8 (0.2) −0.8 (−0.2)
1.0 (−0.2) 6.1 (0.5) −7.2 (−0.2) −2.5 (−3.4)
1.7 (−0.2) 0.6 (0.1) −1.1 (0.3) 4.3 (0.4)
7.6 (0.6) 6.5 (1.1) 6.2 (0.8) 0.5 (−0.2)
1.5 (0.3) 1.5 (0.5) 0.9 (0.5) 7.8 (0.9)
1.6 (−0.0) 2.5 (0.2) 0.3 (0.4) 0.4 (−0.9)−0.4 (0.0) −0.2 (0.2) −2.5 (0.3) 5.3 (0.8)
0.2 (−0.2) 3.3 (0.2) −1.6 (0.8) 3.2 (0.4)
3.2 (−0.7) 3.5 (−0.1) 8.6 (1.3) 1.9 (−1.2)
5.2 (−0.2) 7.3 (0.3) −0.4 (0.3) 0.3 (−1.0)
1.8 (0.3) 0.6 (0.2) −0.3 (1.0) −0.1 (−1.0)
2.6 (0.8) 5.2 (0.8) −0.1 (0.5) 3.0 (0.2)
1.4 (0.2) 6.1 (0.4) 2.3 (0.6) −0.5 (0.0)−2.1 (−0.4) 0.4 (0.1) −8.3 (−0.1) −1.4 (−2.4)
2.6 (0.5) 4.7 (0.2) −4.3 (0.6) −0.4 (0.1)

−3.1
2.5
−1.9
4.0
9.1
2.5
0.9
2.6
5.0
3.3
2.6
0.7
2.6
−1.7
1.5
4.4
1.1
−3.5
1.2
2.1
−1.6
0.0
1.3
3.9
2.5
−2.6
3.9

6. Wholesale andretail trade, hotels,
and restaurants

4. Electricity,gas, and watersupply4.3 (−0.3) 2.2 (0.1)
6.4 (0.1) 1.7 (0.6)−4.8 (−0.9) 0.6 (0.0)
13.6 (0.1) 3.3 (1.2)
8.4 (0.5) 7.6 (2.9)
5.9 (0.0) 5.5 (1.5)−0.3 (0.1) 1.7 (0.3)
0.0 (0.0) 4.4 (0.2)
4.5 (0.1) 6.9 (1.0)−4.3 (0.1) 2.2 (0.9)
1.1 (0.2) 6.1 (0.8)−2.0 (−0.0) 3.0 (0.6)−0.2 (−0.0) 5.9 (1.7)−1.6 (1.7) 0.5 (0.2)−8.9 (−0.1) 3.4 (1.0)−2.0 (0.9) 6.5 (0.5)−2.9 (0.0) 1.0 (0.1)−1.9 (0.1) 5.9 (0.6)−4.3 (0.1) 1.8 (0.5)
2.5 (0.1) 2.9 (0.8)−6.2 (4.3) 1.5 (0.1)
1.5 (1.0) 3.6 (0.5)
0.0 (0.0) 3.7 (1.0)
11.6 (0.2) 2.2 (0.4)
0.5 (0.1) 3.4 (1.2)−4.8 (0.3) −0.8 (−0.0)
1.7 (0.2) 4.0 (1.1)

1. Agriculture©2014 Asian Productivity Organization

Bahrain−4.9 (−0.1)
Bangladesh 1.0 (−0.6)
Brunei−4.4 (−0.1)
Cambodia
3.8 (1.0)
China
7.0 (1.6)ROC
3.0 (0.2)Fiji
2.1 (0.2)
Hong Kong −2.4 (−0.0)India
1.9 (−0.1)
Indonesia
3.8 (0.6)
Iran
2.3 (0.1)Japan
0.4 (0.1)
Korea
4.1 (0.3)
Kuwait7.5 (0.0)
Malaysia
2.7 (0.2)
Mongolia
2.7 (0.6)
Nepal−0.3 (−1.3)
Oman
0.0 (0.0)
Pakistan
0.1 (−0.6)
Philippines
1.5 (−0.1)
Qatar−1.5 (−0.2)
Saudi Arabia −1.5 (−0.1)
Singapore −6.3 (−0.0)
SriLanka
3.2 (0.4)
Thailand1.5 (−0.1)
UAE−1.2 (0.0)
Vietnam
3.7 (0.8)(regrouped)
APO20
1.7 (−0.2)
Asia234.0 (0.6)
Asia294.0 (0.6)
East Asia
6.4 (1.3)
South Asia
1.5 (−0.2)
ASEAN
3.4 (0.4)
ASEAN6
2.8 (0.2)
CLMV
5.0 (1.4)
GCC−1.1 (−0.0)(reference)US
2.3 (0.0)
Australia
3.7 (0.1)
Turkey3.6 (0.8)

3. Manufacturing___Average annual growth rate of industry labor productivity

1.5 (0.3)
3.0 (0.5)
3.0 (0.5)
3.2 (0.5)
3.3 (0.8)
2.4 (0.3)
2.5 (0.3)
2.8 (0.1)
2.1 (−0.2)

2.7
4.1
4.2
3.9
5.1
5.8
5.9
6.6
3.4

(0.3) 0.1
(0.4) 1.9(0.4) 1.8(0.4) 2.7(0.6) 4.0(0.5) −1.5(0.5) −1.4(0.5) 3.5(0.2) −2.9(0.6) 1.5 (0.4)2.0(0.7) 2.9 (0.5)
4.6(0.7) 2.9 (0.5)
4.5(0.6) 2.7 (0.5)5.5(1.2) 5.5 (0.8)
4.3(0.5) 0.7 (0.0)2.9(0.5) 1.0 (0.0)2.7(0.1) −0.2 (0.1)
4.2(0.3) −0.4 (−1.5) −0.8

1.7
1.5
1.5

4.6
2.0
3.8

(0.3) 1.7(0.2) 0.9(0.8) −1.4

(0.6)
(0.5)
(0.5)

(0.2)
(0.0)
(0.2)

0.1 (−0.1)
0.0 (−0.3)
1.3 (0.2)

Unit: Average annual growth rate (percentage), contribution in parentheses.
Source: APO Productivity Database 2014.01.

93: Not all Asian countries are included, as employment by industry sector is not available for some countries.

106

1.4
0.9
3.0

6.3 Labor Productivity by Industry%

10

1990−2000

8

2000−2012

6
4
2
0
−2

6

Japan
Fiji
Australia
Nepal
Pakistan
Singapore
US
Malaysia
Philippines
ROC
ThailandBangladesh
Hong Kong
Iran
Korea
TurkeyIndonesia
Sri Lanka
Vietnam
Cambodia
Mongolia
India
China

Mongolia
Fiji
Philippines
Hong Kong
Japan
Indonesia
Nepal
US
TurkeyIranPakistan
Bangladesh
Australia
Myanmar
Sri Lanka
India
Cambodia
Thailand
Malaysia
Singapore
Korea
ROC
VietnamChina−4

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

3. Manufacturing

Real GDP

Figure 83 Industry Origins of Labor Productivity Growth, 1990–2000 and 2000–2012___Industry decomposition: Average annual growth rate of GDP at constant prices
Source: APO Productivity Database 2014.01.

The manufacturing sector has been a major driving force behind productivity growth in most Asian
countries, as shown in Figure 84. In the 1990s, manufacturing accounted for a significant part of laborproductivity growth in Hong Kong (83%), Indonesia (63%), and China (49%). Nevertheless, its role haslessened in 2000–2012 to 7%, 28%, and 32%, respectively. In contrast, contributions from manufacturing strengthened from 56% to 64% in Korea, from 28% to 61% in the ROC, and from 55% to 80% inJapan between the two periods. In other economies, however, like Sri Lanka, Nepal, and Mongolia, inthe 2000s manufacturing played a negligible role.

Figure 85 presents the contribution of services in labor productivity growth by country. In 2000–2012,services were contributing at least one-third or more to labor productivity growth in most Asian countries. The contribution was predominant in Hong Kong and India, accounting for 91% and 77% oflabor productivity growth, respectively. It also accounted for around two-thirds or more of labor productivity growth in the US, Sri Lanka, and Singapore. Korea had the lowest share from the service
sector, accounting for one-fifth of labor productivity growth. There is an expansion of the role playedby services in China between these two periods, from 26% to 38%. The contribution of services was
also highly significant in South Asian countries like Bangladesh, India, Nepal, and Pakistan over thesame term. Finance, real estate, and business activities made the largest contribution of 1.4 percentage points in India and 1.0 percentage point in Singapore, respectively.

107©2014 Asian Productivity Organization

Traditionally, it has been difficult for the service sector to realize productivity growth, but modern
advancements in information and communication technology have changed this. Many 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, andcommunications; and finance, real estate, and business activities.

6 Industry Perspective

1990−2000
5.0 4.0 3.0 2.0 1.0 0.0 −1.0 %
China
Korea
Singapore
Cambodia
Malaysia
Vietnam
ROC
Indonesia
ThailandHong Kong
Bangladesh
TurkeyUS
Sri Lanka
Japan
Pakistan
Philippines
Australia
India
Iran
Myanmar
Nepal
Fiji
Mongolia

4.3
2.4
1.7
1.4
1.4
1.3
1.3
1.1
1.0
0.8
0.8
0.7
0.7
0.6
0.6
0.5
0.4
0.3
0.3
0.3

0.0
−0.2
−0.2
−0.4

2000−2012−30

Contribution

0

30

60 %

3.0

49

2.9

2.0

56

0.0 %

1.0

1.7

41

1.5

39

1.2

33

1.2

26

1.1

28

1.0

63

1.0

24

1.0

83

0.9

35

0.8

35

0.8

37

0.6

22

0.6

55

0.5

21

0.5

46
14

0.5

9

0.4

12

0.4
0.3

−1

0.2

−9

0.1

−558

0.1

20

Contribution share toaggrergate labor productivity

0

China
Korea
ROC
ThailandCambodia
Vietnam
India
Malaysia
Singapore
Indonesia
Philippines
Iran
Bangladesh
Japan
Mongolia
PakistanUS
TurkeySri Lanka
Fiji
Hong Kong
Australia
Nepal

20

40

60

80 %

32
64
61
48
29
29
21
66
75
28
38
30
25
80
12
42
32
14
10
34
7
14
6

Contribution

Contribution share toaggrergate labor productivity

Figure 84 Contribution of Manufacturing to Labor Productivity Growth, 1990–2000 and
2000–2012
Source: APO Productivity Database 2014.01.

1990−2000
3.0

2.0

1.0

0.0 −1.0 %

2.9
2.3
2.2
2.0
1.9
1.9
1.8
1.4
1.4
1.3
1.2
1.2
1.1
1.1
1.0
0.8
0.7
0.5
0.4
0.3
0.2
0.2
−0.1
−0.5

Contribution

ROC
India
China
Malaysia
VietnamSingapore
Cambodia
Australia
Sri Lanka
IranPakistan
Nepal
US
Bangladesh
Korea
ThailandTurkeyMyanmarJapan
Hong Kong
Mongolia
Philippines
IndonesiaFiji2000−2012

−30

0

30

60 %

4.0

63

3.9
73

26

3.0

2.0

1.0

0.0 %

3.5
2.4

48

2.3

38

2.3

45

2.2

51
63

2.0
1.8

51

1.6

61

1.5

56

1.4

68

1.4

59

1.3

48

1.3

24

1.2

20

1.0

38

0.8

20

0.8

42

0.6

29

0.5

−9

0.5

19

0.4

−4
−1362

Contribution share toaggrergate labor produtcivity

0.1

Contribution

India
China
Mongolia
Hong Kong
Sri Lanka
Nepal
Bangladesh
Iran
TurkeyCambodia
Indonesia
Vietnam
PakistanThailandPhilippines
US
Fiji
ROC
Singapore
Korea
Malaysia
Australia
Japan

0

20

40

60

80 100 %
77

38
55
91

58
198
80
71
54
36
43
35
108
51
56
69
91
31
42
21
35
40
16

Contribution share toaggrergate labor productivity©2014 Asian Productivity Organization

Figure 85 Contribution of Service Sector to Labor Productivity Growth, 1990–2000 and
2000–2012
Source: APO Productivity Database 2014.01.

108

6.3 Labor Productivity by Industry

Energy Productivity and CO2 Emission

In 2011, in order to produce
40% of the world output in
Asia, 43% of world energy
was consumed and 51% ofworld CO2 was emitted (Figure B6.1). This implies that
Asia has lower energy productivity (output per energy
consumption) and higher
carbon intensity of energy at
the aggregate level (mainly
due to a larger consumptionof coal). It is key to improveenergy productivity and carbon intensity in the growing
economies of Asia, in orderto reduce CO2 emissions in
the world in the long run.

Energy Consumption
Japan

Japan

India
APO20
19 %

Others27 %CO2 Emission

Asia
43 %

Asia 29
40%

EU27
13 %

EU15
11 %

US
17 %

Other
Asia
3%

China

EU27
11 %

Others
22 %

India
APO20
18 %

Asia
51 %

Asia 29
47 %

EU15
9%
US
16 %

Other
Asia
3%

China

6

Figure B6.1 Shares of Asia in World Energy Consumption
and CO2 Emission, 2011
Sources: IEA, CO2 Emissions from Fuel Combustion 2013; IEA, Energy Balances of OECDCountries 2013; IEA, Energy Balances of non-OECD Countries 2013.

The average level of energy
productivity in Asia was inferior to the EU27 by 27% inLabor Productivity(US dollars/hours worked)
2011. There is a large diver­70
sity however, reflecting the differences in industrial structureUS60
and energy efficiency among
countries. Figure B6.2 placed
Singaporecountries on the two partial
50
EU15
Australia
productivity indicators of laEU27
bor and energy, measured
40
ROC
Japan
in 2011. Less-developed countries with lower labor producIran30
tivity (such as the Philippines,
TurkeyKorea
Sri Lanka, Myanmar, andMalaysia
20
Bangladesh) tend to havehigher energy productivity.
ThailandSri Lanka
To improve labor produc10
Indonesia
China
Pakistan
Philippines
tivity in such countries, an efIndia
Vietnam
Cambodia
fective strategy is to to expand
Bangladesh
0
0
5
10
15
20
25
the manufacturing sector (FigEnergy Productivity
ure 68). This frequently fol(Thousands of US dollars/toe)lows the deterioration in energy
productivity, as in China,
Thailand, and Korea. As a next
Figure B6.2 Labor Productivity and Energy Productivity,
stage of economic growth,2011well-developed countries will
Sources: IEA, Energy Balances of OECD Countries 2013; IEA, Energy Balances of nonbe able to pay more attention­
OECD Countries 2013; APO Productivity Database 2014.01.
to improve energy productivity
by abolishing implicit or explicit subsidies on energy prices and levying heavier taxes on energy consumptions. The C-shape relationship found between labor and energy productivities corresponds to the so-called Environmental Kuznets
curve, as an inversed U-shape relationship between environmental quality (at the y-axis) and economic
development (at the x-axis).

continued on next page >109©2014 Asian Productivity Organization

Box 6

6 Industry Perspective> continued from previous page

Figure B6.3 decomposes the sources of CO2 emission growth (from fuel combustion) in Asian countries
during 2000–2011, based on the so-called Kaya identity. The growth in CO2 emissions is decomposed tothree components: changes in real GDP, carbon intensity of energy, and energy intensity of GDP (the inverse of energy productivity). In many countries, the production expansion (real GDP growth) is the mostsignificant factor to explain the growth of CO2 emissions. With an exception of Singapore, energy productivity has been improved in many Asian countries in this period, but it has a minor effect to offset an expansion of energy consumption. Singapore realized a large improvement in carbon intensity of energy by theshift from oil to LNG in electricity power generation. This helped offset the deterioration in energy productivity. Decoupling in the growths of GDP and CO2 emission was realized in only a few developed countries,
like Japan (regardless of very low operation of nuclear power due to Fukushima Daiichi nuclear disaster in2011), the US, and EU. Improvements in energy productivity and carbon intensity of energy are focused asa policy target for sustainable growth of the world economy in the long run.

%

14
12
10

8

2.4
2.6

3.8

6
4
2
0
−2
−4

1.7

2.7

7.0

1.1

0.9 0.6

9.9
5.7

7.7 7.3
4.7 4.7

1.0
5.7

4.1

7.2

3.1

1.8

2.3

0.4 0.8
5.2 5.3

4.2 4.1

5.6

1.4

0.2
4.3 3.6 4.0 3.8 4.6

0.1
3.1

0.7 1.5 1.4 1.3
0.7−1.1−0.4−0.5−0.5−0.9−0.8−0.8−1.0−0.3−1.1−1.9−1.8−1.9−2.7−1.4−1.4−2.0−1.4−1.8−1.6−1.6
−0.6
−1.1
−3.6
−3.6
−3.8−3.4
−4.6
−4.7
−1.7
−5.9

−0.5

−6
EU15
EU27
US
Japan
Australia
Philippines
ROC
Hong Kong
Nepal
Pakistan
Singapore
Korea
TurkeySri Lanka
Indonesia
Mongolia
ThailandIran
KuwaitMalaysia
India
Cambodia
Bangladesh
China
Vietnam−8

GDP

Carbon intensity of energy

Energy intensity of GDP

CO2

Figure B6.3 Sources of CO2 Emission Growth, 2000–2011©2014 Asian Productivity Organization

Sources: IEA, Energy Balances of OECD Countries 2013; IEA, Energy Balances of nonOECD Countries 2013; IEA, CO2 Emissions from Fuel Combustion 2013; Official national
accounts in each country, including author adjustments.

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 (therelative prices of a country’s exports to imports), unambiguously raises real income and in turn welfare.94 In many ways, a favorable change in the terms of trade is synonymous with technological progress, making it possible to get more for less. That is, for a given trade balance position, a country caneither 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.95 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). Meanwhile, there has been no significant difference between real income
growth and real GDP growth in Myanmar, which is a relatively closed economy (Figure 92). 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,96 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 the amount of domestic expenditurethat can be purchased with the current income flow.97 As such, real income captures the purchasing
power of 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 fromabroad. Applying the method proposed by Diewert and Morrison (1986), the annual growth rate ofreal 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),98 andthe effect of net income transfer.99

94: See Diewert and Morrison (1986) and Kohli (2004).
95: 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.”
96: The weight for import price changes is negative. Thus, if import prices decrease, this tends to raise the GDP deflator.
97: 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).
98: The term “trading gain” is used by some authors (Kohli, 2006). This term is adopted in this report.
99: 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©2014 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.100 The findings presented in Table 17 confirm thisobservation. Excluding the oil-exporting countries, the trading gain effect in 16 out of 21 economies
compared, fell within the margin of ±10% of real GDP growth on average for the long period of
1970–2012. Movements in terms of trade have been consistently unfavorable to Japan and the ROC.
Table 17 Real Income and Terms of Trade, 1970–2012, 1995–2000, 2000–2005, and 2005–2012___Average annual growth rate of real income, real GDP, trading gain, and net primary income transfer from abroad©2014 Asian Productivity Organization

Bahrain5.84 4.84
Kuwait5.71 0.94
Oman
8.12 6.42
Qatar
6.67 6.21
Saudi Arabia 7.45 4.95
UAE
10.58 10.03

−0.35
0.34
−0.38
−0.97
−0.21
−0.42
0.00

Bahrain
7.84
Kuwait
11.10
Oman
8.23
Qatar
11.94
Saudi Arabia 8.76
UAE
6.37
Brunei8.01(reference)
US
2.39
EU15
2.05
EU27
2.10
Australia
4.25
Turkey4.67(reference)US
EU15

2.71 2.76 −0.07
2.11 2.16 −0.04

Australia
Turkey3.51 3.29 0.25 −0.03
4.16 4.34 −0.15 −0.03

0.02
0.00

2.87
4.41
3.90
5.83
2.02
1.87
3.59

4.20 0.08
0.00
2.88 −0.09
0.07
2.85 −0.12
0.09
3.74 0.12
0.15
4.37 −0.31 −0.08

6.52
7.63
3.58
9.71
4.28
4.70
2.85

1.33
4.64
4.44
4.55
4.55
1.75
5.15

−0.02
−1.18
0.21
−2.32
−0.07
−0.08
0.00

2.36 −0.04
0.08
1.80 0.08
0.17
1.87 0.07
0.16
3.30 1.18 −0.23
4.59 0.27 −0.19

Trading gain

3.51
1.63
4.03
8.63
2.65
6.57
1.81

Net primary income
from aboad

Bahrain
6.04
Kuwait
6.38
Oman
7.54
Qatar
13.49
Saudi Arabia 4.47
UAE
8.03
Brunei5.39(reference)
US
4.27
EU15
2.87
EU27
2.82
Australia
4.01
Turkey3.98

Real GDP

1.32 −0.32
4.40
0.38
1.60
0.10
0.53 −0.08
1.59
0.89
0.22
0.32

12.24 12.24 0.00
0.00
10.94 10.28 0.56
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
8.15 8.59 −0.34 −0.09
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
5.22 5.40 −0.45
0.27
4.63 4.77 −0.80
0.65
4.62 5.15 −0.01 −0.52
3.96 4.55 −0.96
0.37
3.71 4.47 −0.84
0.08
3.71 4.82 0.14 −1.25
2.94 3.46 −0.59
0.07
2.89 4.00 −1.00 −0.11
2.36 3.60 −1.47
0.22
1.58 1.77 0.34 −0.52
1.04 1.18 −0.34
0.21Real income

Myanmar
China
Cambodia
Mongolia
Iran
Vietnam
India
Malaysia
Sri Lanka
Philippines
Bangladesh
PakistanThailandIndonesia
Korea
Singapore
Nepal
Hong Kong
ROC
Fiji
Japan

Trading gain

−0.26
0.08
−0.27
1.62
0.01
−0.03
0.15
−0.31
−0.77
−0.61
−0.15
0.12
1.00
−0.02
−0.37
−0.04
−0.81
0.09
−0.01

2005–2012
Net primary income
from aboad

7.41 0.21
7.67 −0.79
6.46 0.23
3.62 1.15
5.59 −0.17
5.47 −0.11
2.72 2.32
5.44 0.04
5.37 0.41
5.47 0.04
5.04 −0.07
4.14 −0.20
3.66 −1.12
4.98 −1.89
3.14 −0.02
2.38 0.37
1.30 0.65
0.83 −0.16
0.36 −1.20

Real GDP

Vietnam
7.37
China
6.96
Singapore
6.43
Philippines
6.39
India
5.42
ROC
5.34
Iran
5.19
Cambodia
5.17
Malaysia
5.02
Myanmar
4.90
Sri Lanka
4.82
Bangladesh 4.06
Fiji
3.55
Korea
3.07
Pakistan
2.74
Hong Kong
2.71
Indonesia
1.13
Japan
0.76
Thailand−0.84

Real income

Net primary income
from aboad

−0.01
−0.08
−0.06
−0.02
−0.03
0.08
−0.07
0.05
−0.01
−0.10
0.10
−0.09
0.12
0.69
0.19
0.21
0.08

2000–2005
Trading gain

Net primary income
from aboad

8.65 −0.01
7.26 −0.07
6.35 0.46
6.94 −0.47
5.73 0.62
6.92 −0.91
5.74 0.06
5.64 −0.07
5.45 0.00
5.74 −0.43
3.39 1.62
5.37 −0.26
4.60 −0.25
3.66 −0.03
2.34 0.52
3.13 −0.30
2.64 −0.31

Real GDP

Trading gain

8.63
7.11
6.75
6.45
6.32
6.09
5.73
5.61
5.44
5.21
5.12
5.02
4.47
4.32
3.06
3.04
2.41

Real income

Real GDP

China
Singapore
Malaysia
Korea
Indonesia
ROC
MyanmarHong Kong
India
ThailandIran
Sri Lanka
Pakistan
Philippines
Fiji
BangladeshJapan

1995–2000

Real income

1970–2012

China
11.03 11.05 −0.06
0.03
Myanmar10.92 10.91 0.01
0.00
Mongolia
10.55 9.75 1.88 −1.09
India
8.00 7.91 0.16 −0.07
Cambodia7.76 6.83 1.00 −0.07
Vietnam
6.77 6.18 0.96 −0.37
Sri Lanka
6.37 6.73 −0.26 −0.11
Bangladesh 6.01 5.97 −0.57
0.61
Singapore
5.45 5.99 −1.20
0.65
Philippines
5.21 4.95 −0.33
0.60
Malaysia
5.04 4.48 0.47
0.09
Indonesia
5.03 5.63 −0.88
0.28
Nepal
3.97 3.32 0.69 −0.04
Pakistan
3.93 4.12 −0.60
0.40
Thailand3.28 3.66 −0.43
0.05
Hong Kong
3.09 3.59 −0.71
0.21
Korea
2.65 3.49 −0.93
0.09
Iran
2.23 2.09 0.04
0.10
ROC
1.44 3.69 −2.35
0.10
Fiji
0.31 0.08 0.14
0.09
Japan
−0.05 0.36 −0.52
0.12
Bahrain7.49 5.34 3.68 −1.53
Kuwait6.02 2.64 4.15 −0.77
Oman
8.21 3.90 4.68 −0.37
Qatar
14.45 12.39 1.26
0.81
Saudi Arabia 7.16 4.53 2.44
0.19
UAE
5.88 3.21 2.89 −0.22
Brunei5.52 −1.11 6.56
0.08
(reference)US
1.16 1.13 −0.09
0.12
EU15
0.42 0.63 −0.20 −0.01
EU27
0.52 0.77 −0.20 −0.06
Australia
3.80 2.84 0.73
0.22
Turkey3.23 3.88 −0.65
0.01

Unit: Percentage.
Sources: Official national accounts in each country, including author adjustments.
Note: See footnote 99 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 1970–2012: Brunei (1989–), Cambodia (1993–), Mongolia (2000–), Nepal (2000–), and Vietnam (1989–).

100: 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 Trade

In the short term, 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
terms of trade have been turning strongly in its favor. The trading gain effect in Australia has therefore
been rising from 3% on average per year in 1995–2000, to 36% in 2000–2005, and 26% in 2005–2012
of its real GDP growth. In terms of percentage points, the trading gain added 0.12, 1.18, and 0.73
percentage 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 arise in purchasing power with little real GDP growth in countries, such as Brunei, Kuwait, and UAE
in 2005–2012.

7

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 27 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 (during the late 1990s), net primary income from abroad played aneven greater role in cushioning the real income of Filipinos. Over the past four decades, net primary
income from abroad augmented real GDP growth by 3.0% and 0.8% on average per year in Japan andthe US, respectively. This has grown to be more significant (33% and 10%, respectively), in both countries as real GDP growth slowed from 2005–2012.
Figure 86 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. It has held positive in the ROC, oscillating around +2% of GDP, since 1980. Singapore’s net primary income from abroad displayed the largest fluctuations, ranging from +1.9% in1997 to –7.1% in 2004, but on the whole, it has been more negative than positive. In Japan and thePhilippines, net primary income from abroad has risen strongly, albeit at different magnitudes. In Japan, it rose from 0.7% of GDP in 1990 to 3.2% in 2012, compared with 1.4% in 1990 and 31.4% in 2012
in the Philippines. In the US, it has always been positive, fluctuating within +1.7% of GDP, whereas in
the EU15 it was marginally negative for the three decades between 1975 and 2005 before turning
mildly positive.

%

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 86 Effect of Net Income Transfer on GDP, 1970–2012
Sources: Official national accounts in each country, including author adjustments.

113©2014 Asian Productivity Organization−2

7 Real Income

Combining both the trading gain
effect and net primary income fromabroad, real income growth formost of the countries compared fellwithin the margin of ±20% of real
GDP growth (Figure 87). Kuwait andBrunei appear to be the outliers,
with real income growth being 6.1
times and 3.4 times their respective
long-term dismal real GDP growthof 0.9% and 1.4%.101% Real income growth12(+20%)
UAE

10
China
8

(−20%)

Oman
Saudi Arabia Vietnam
Singapore
Malaysia
Qatar Korea
Bahrain
ROC
KuwaitIndia
Hong Kong
Thailand
Iran
Brunei
Sri Lanka
Pakistan
Philippines
TurkeyAustralia
Fiji
Bangladesh
US
Japan
EU15
Indonesia
Myanmar6

4©2014 Asian Productivity Organization

Unlike the oil-exporting countries,
at any one time roughly half of the2
Asian countries compared sustained a negative trading gain effect, albeit to variable extents,
0
whereas the impact from net pri0
2
4
6
8
10
12 %
Real GDP growthmary income from abroad was relatively less pronounced. The period
Figure 87 Real Income and Real GDP Growth, 1970–2012___Average annual growth rate of GDP at constant prices and realof 1995–2000 reflects the impact ofincomethe Asian financial crisis. For Thailand, the trading gain effect more
Sources: Official national accounts in each country, including author adjustments.
Note: The starting years for some countries are different due to data availability
than outweighed the small positive
during 1970–2012: Brunei (1989–), Cambodia (1993–), Mongolia (2000–), Nepal
average real GDP growth per year
(2000–), and Vietnam (1989–).
(0.4%), giving rise to a marginal fallin real income of –0.8%. In Korea,
the negative trading gain also shaved 38% off real GDP growth of 5.0%, producing real income growthof 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 to be 41%
lower than real GDP growth in the period 2000–2005. However, in the period 2005–2012 it wiped out
64% of the handsome 3.7% real GDP growth on average per year, leaving real income to grow at 1.4%.
Similarly, in Korea the trading gain effect caused real GDP growth to overestimate real income growthby 19% in the first half of the 2000s, which increased to 27% in the years 2005–2012 (Table 17 andFigure 88). In Japan, the negative trading gain effect more than wiped out the 0.5 percentage pointsof real GDP growth, leaving real income to actually fall by 0.1% per year on average in the period
2005–2012.
In contrast, the trading gain worked to counterbalance falling real GDP in Brunei, leaving it with a robust, real income growth of 6.6%, despite its contracting real GDP of 1.1% in the latest period (Table
17). In Saudi Arabia, real income growth was more than 170% faster than its real GDP growth. Thistakes place against the backdrop of strong oil prices, which spiked in mid-July 2008 to USD 145 perbarrel. After dropping sharply to USD 30 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 per barrel

101: 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 Tradesince 2010 (Figure 89). In the US, the trading gain effecthas 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 2005–2012, the trading gain effect shaved 8.0% off real
GDP growth. It was counterbalanced by the positive effectfrom net primary income from abroad, which added 10.4%
to real GDP growth, leaving real income growth slightly
lower than real GDP.

6.6
4.7
4.2
3.7
2.9
2.4
1.9
1.3
1.0
1.0
0.7
0.7
0.5
0.2
0.1
0.0
0.0

BruneiOman
KuwaitBahrain
UAE
Saudi Arabia
Mongolia
Qatar
Cambodia
Vietnam
Australia
Nepal
Malaysia
India
Fiji
Iran
Myanmar
China
US
EU27
EU15
Sri Lanka
Philippines
ThailandJapan
Bangladesh
Pakistan
TurkeyHong Kong
Indonesia
Korea
Singapore
ROC

7

Figure 90 provides the results of further decomposition of
−0.1
−0.2
the trading gain into the terms-of-trade effect and the real
−0.2
exchange rate effect in Asian countries for the period
−0.3
102
−0.3
1970–2012. The terms-of-trade effect is the part of real
−0.4
income growth attributed to the change in the relative
−0.5
−0.6
price between exports and imports. The real exchange−0.6
rate effect refers to the part of real income growth attrib−0.7−0.7
uted to changes in the relative prices of traded goods and
−0.9
−0.9
domestically consumed goods. By applying this result, real
−1.2
income growth can be decomposed into real GDP growth,−2.4
terms-of-trade effect, real exchange rate effect, and net
−3
0
3
6%
primary income from abroad. The first chart in Figure 90
applies this break-down to Asian countries for the period
Figure 88 Trading Gain Effect, 2005–
1970–2012. It shows that the real exchange rate effect is
2012___Average percentage points
generally much smaller than the terms-of-trade effect, implying that the relative prices of traded versus domestiSources: Official national accounts in each country,
including author adjustments.
cally consumed goods have been largely stable in mostcountries. The exceptions are Kuwait and Brunei where thereal exchange rate effect accounted for 30% and 18% ofreal income growth. This might have reflected the weight of oil in the composition of their traded
goods. The second chart shows the decomposition for the most recent period 2000–2012. It showsthat the trading gain, particularly the terms-of-trade effect, is highly significant and favorable for theoil-exporting countries, but is significant and negative in a handful of Asian economies such as Hong
Kong, the ROC, Indonesia, Korea, Malaysia, and Pakistan.
−0.1

Dollars per barrel

150

145.3
109.4

125

113.4

106.8
110.2

100
77.1

75
41.1

50

68.0

25

30.3
10.8

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

Jan 02,2014

Figure 89 Price of Crude Oil, 1986 January–2014 June
Source: US Energy Information Administration, WTI spot prices FOB (Cushing, Oklahoma).

115©2014 Asian Productivity Organization0
Jan 02,
1986

75.4

7 Real Income

EU15
Japan
US
Bangladesh
Fiji
Australia
TurkeyPhilippines
Pakistan
Sri Lanka
IranThailandIndia
Hong Kong
KuwaitMyanmarBahrain
ROC
Indonesia
Korea
Qatar
Malaysia
Singapore
Saudi Arabia
Oman
China
UAE

1970–2012%
Figure 91 shows the decomposi12tion of average annual real in9
come growth covering two peri­
ods of major economic shocks
1.2 0.9
6
1.0
1.1
faced by the Asian economies:
10.0
1.7
0.7
1.4
8.6
6.9
7.3
during 1973–1979, which in5.7
3
6.3 6.2
5.7 6.9
5.7
6.4
2.7 5.6 5.5
4.8
5.4 4.6 3.7 4.3
4.9
3.4
3.3
cludes the two oil price hikes in
2.3 3.1 2.8 2.6 2.2
0.9
0
−0.8
1974 and 1979, and 1996–1998
to capture the impact of the−3
Asian financial crisis. High oil
prices improved the terms for oilexporting countries, such as Iranand Indonesia, and worsened the
2000–2012%15
terms of trade for oil-importing
2.3
countries. During the Asian finan12
2.2
cial crisis, the terms-of-trade ef9
1.0
0.9
fect was still the predominant
2.4
3.3
6 11.3
2.8
1.6
3.7
0.9
factor in determining the dif­
2.3
1.0
11.5 10.7
1.0
8.7 8.3
7.5 7.2
0.9
5.7
5.8
3
5.9
4.4
ference between real income
4.6
4.7 4.2 5.5 5.2 4.4
4.3 4.2 3.4 3.9 3.8 3.7
3.8
3.8 4.7 4.4
3.0
1.6 1.1
growth and real GDP growth. In
0.8 0.7
0−0.9 −0.9−0.8−0.9−0.8−2.0Brunei, the terms-of-trade effect−3
further reinforced the negative
real GDP growth of –6.3%, reducing its real income growth a further 8.2 percentage points. In
Real exchange rate effectTerms-of-trade effect
Real GDPNet primary income from abroad
Real income
Iran, the negative terms-of-tradeeffect counteracted the 0.9% real
Figure 90 Decomposition of Real Income Growth, 1970–
GDP growth, giving real income
2012 and 2000–2012
growth of –1.5%. In Indonesia,
Sources:
Official national accounts in each country, including author adjustments.
the trading gain effect worked tocounterbalance the contraction
in real GDP, whereas in Thailand,
it reinforced the negative real GDP growth. In the Philippines, although the strong favorable terms-oftrade effect was moderated by the negative real exchange rate effect, the resulting real income
growth more than tripled the real GDP growth.103
Japan
Fiji
EU15
US
ROC
Hong Kong
Korea
Nepal
TurkeyThailandAustralia
PakistanIndonesia
Singapore
Iran
Philippines
Bangladesh
Malaysia
Sri Lanka
UAE
BruneiVietnamIndia
BahrainSaudi Arabia
KuwaitOman
Cambodia
Mongolia
China
Myanmar
Qatar

Figure 92 shows this decomposition of real income in each Asian country, along with the US, EU15,
Australia, and Turkey104 from 1970, or the year of first data collection for the country in question. The

102: 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)()©2014 Asian Productivity Organization(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 effect103: 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%.

116

7.1 Real Income and Terms of Trade

1973–1979

%

10

3.2

1.1

5
7.3

3.3

1.2

7.5

5.1 7.3 5.3

5.2 8.9

8.0 7.1

7.3
4.2 4.6

0

1.3

5
2.3

9.8

1996–1998

%

10

1.5
−0.8

−1.1

5.8

0
5.4 4.3 4.4 4.7
3.6 3.8 3.8 2.9 2.9
−0.7

2.3

−0.7

7.2

6.3 7.0
−1.6

1.1

1.1
3.1 1.0

4.6

3.1 4.3−1.8

1.1
4.3 3.5 4.5 2.9 1.5 1.4 1.0
1.4 1.3 1.2−0.8−1.1 −0.7
6.0

−5

1.2
0.9
1.9
1.6 −2.6−0.7−1.1 −1.5−5.2 −5.0 −6.3
−1.4−0.9
−0.7

−0.7

−10
−5

−8.1

−15

Terms-of-trade effectBruneiThailandIndonesia
Korea
Iran
Fiji
Japan
Malaysia
Hong Kong
Pakistan
EU15Australia
Singapore
US
Cambodia
India
Philippines
ROC
MyanmarBangladesh
China
TurkeyVietnam
Sri Lanka

Bangladesh
EU15
US
Japan
Australia
India
TurkeyPhilippines
Myanmar
Sri Lanka
China
Thailand
PakistanFiji
Singapore
Hong Kong
ROC
Iran
Malaysia
Korea
Indonesia
Real exchange rate effect

Real GDPNet primary income from abroad

7

Real income

Figure 91 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.

104: 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©2014 Asian Productivity Organization

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 true
in 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
40

Bangladesh

%
15

%
24
18

10

12

20

5

0

6
0

0

−20

−6

−5

−40

−12

−60

−10

−80

−15

1971 1976 1981 1986 1991 1996 2001 2006 2011

Cambodia

%
21
18

−18
1971 1976 1981 1986 1991 1996 2001 2006 2011

−24

China

%
15

%
18

9

6

9

6

3

6

3

0

3

0

−3

0
1971 1976 1981 1986 1991 1996 2001 2006 2011

Hong Kong

%
16

−6

−3

9

8

6

4

3

−6

1971 1976 1981 1986 1991 1996 2001 2006 2011

India

%
12

12

ROC

12

9

12

1971 1976 1981 1986 1991 1996 2001 2006 2011

15

12

15

−3

Brunei%20

1971 1976 1981 1986 1991 1996 2001 2006 2011

Indonesia

15
10

0

0

−4

−3

−8

−6

5
0
−5
−10

1971 1976 1981 1986 1991 1996 2001 2006 2011

Iran

%
45

−15
1971 1976 1981 1986 1991 1996 2001 2006 2011

Japan

%
8

36

−20

%
18

10

4

6

2

9

2

0

0

−2

−9
−18
−27

1971 1976 1981 1986 1991 1996 2001 2006 2011

Kuwait

%
90

−2

−6

−4

−10

1971 1976 1981 1986 1991 1996 2001 2006 2011

Malaysia

%
20

%
25

1971 1976 1981 1986 1991 1996 2001 2006 2011

Mongolia

20

15

60

15
10

30

10

5
0

5
0

0

−5

−30
−60

Korea

14

6

27
18

1971 1976 1981 1986 1991 1996 2001 2006 2011−51971 1976 1981 1986 1991 1996 2001 2006 2011

Myanmar

%
15

−10

−10
1971 1976 1981 1986 1991 1996 2001 2006 2011

−15

Nepal

%
8

%
45

1971 1976 1981 1986 1991 1996 2001 2006 2011

Oman

12
9
6

6

30

4

15

2

0

0

−15

©2014 Asian Productivity Organization

3
0
−3
−6
−9

1971 1976 1981 1986 1991 1996 2001 2006 2011

Real GDP118−21971 1976 1981 1986 1991 1996 2001 2006 2011

Trading gain

−30

Net primary income from abroad

1971 1976 1981 1986 1991 1996 2001 2006 2011

Real income

7.1 Real Income and Terms of Trade%
10

Pakistan

Philippines

%
15

%
40

8

10

30

6

5

20

4

0

10

2

−5

0

0

−10

−10

−2

−15

−20

−4

−20

%
60

1971 1976 1981 1986 1991 1996 2001 2006 2011

Saudi Arabia

45
30
15

1971 1976 1981 1986 1991 1996 2001 2006 2011−30

Singapore

%
20

%
20

16

15

12

10

8

5

4

0

0

−5

−15

−4

−10

−30

−8

0

%
15

1971 1976 1981 1986 1991 1996 2001 2006 2011

Thailand

UAE

%
100

0
−5

4

20

2

US

−40

0
−4
1971 1976 1981 1986 1991 1996 2001 2006 2011

EU15

%
6

−6

%
8

4

6

4

2

4

2

0

2

0

−2

0

−2

−4

−2

%
12

1971 1976 1981 1986 1991 1996 2001 2006 2011

−6

Vietnam

−2

6

−4

7
1971 1976 1981 1986 1991 1996 2001 2006 2011

6

40

−20
1971 1976 1981 1986 1991 1996 2001 2006 2011

Sri Lanka

8

0

−10

%
12

1971 1976 1981 1986 1991 1996 2001 2006 2011

10

60

5

%
8

−15

80

10

−15

1971 1976 1981 1986 1991 1996 2001 2006 2011

Qatar

1971 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

8
4
0
−4
−8

1971 1976 1981 1986 1991 1996 2001 2006 2011

Real GDP

Trading gain

Net primary income from abroad

Real income

Figure 92 Sources of Real Income Growth, 1970–2012

119©2014 Asian Productivity Organization

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

7 Real Income

7.2 Trading Gain and Productivity Growth% Trading gain effect3

KuwaitBrunei©2014 Asian Productivity Organization

When the trading gain is highly
2favorable, it can breed a sense ofcomplacency with productivity
performances suffering as a reIran
Omansult. Resource-rich economies are
Bahrain1
susceptible to this pitfall because
Saudi Arabia
Indonesia
they are poised to reap some exFiji
Vietnamtremely positive trading gains
Australia Malaysia
UAE
Qatar
Singapore
Cambodia
when commodity prices turn inHong Kong
India
0
EU15
their favor over a sustained period
Myanmar China
Philippines US
TurkeySri Lankaof time. While commodity prices
Korea
Bangladesh
Thailandcan rise, they can also fall. This is
Pakistan
Japan
ROC
when countries’ real income
−1
−4.5
−3.0
−1.5
0.0
1.5
3.0
4.5
6.0
7.5 %
growth could suffer if fundamenLabor productivity growthtals for real GDP growth are weak.
Over the past four decades, only
Figure 93 Trading Gain Effect and Labor Productivity
five countries have enjoyed a faGrowth, 1970–2012
vorable trading gain effect of over
Sources: Official national accounts in each country, including author adjustments.
1% per year. They are Kuwait, BruNote: The starting years for some countries are different due to data availability during 1970–2012: Brunei (1989–), Cambodia (1993–), Myanmar (1977–), Turkey (1988–),
nei, Iran, Oman, and Bahrain (alland Qatar (1975–).
oil-exporting countries). Only Iranamong them could achieve a significant positive growth in laborproductivity (Figure 93). Australia is a rising economy that has benefited from recent hikes in commodity prices. These are likely to stay for a period of time, as a response to the vibrant growth in theemerging 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.105 This was just at the stage when they wereenjoying an all-time-high positive trading gain effect, with real income growth faster than real GDP
growth by 38% during 2005–2012 (Table 17). A resource-rich country 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 can easily 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 (see Section 6.2 and Figure 76, p. 96).
Figure 93 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.
Meanwhile, 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 better positioned than before their development took off, and without
productivity improvements.

105: The Economist, 28 May 2011, “Special Report on Australia: No worries?”120

7.2 Trading Gain and Productivity Growth

Box 7

Resource-Rich Countries and the Possible Dutch Disease

Resource price hikes are certainly blessings for resource-exporting economies when prices are increasing.
Figure B7 illustrates trading gain effects (average annual growth rates due to trading gains in 1970–2012)and value-added shares of the mining sector in 1970 and 2012 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 B7 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 93 shows% Trading gain effect, 1970−2012that labor productivity growth
5.0
rates in these countries after
1990 remained low, or even
Kuwaitnegative. Even if they wanted
4.0
to start industrialization, theirhigh income and strong local
Bruneicurrency would not easily
3.0
allow them to develop a manufacturing sector or an internationally competitive service
industry. Another concern is
2.0
Irantheir heavy dependence on
Oman
Bahrainforeign workers, both skilled
and unskilled.
Saudi Arabia
1.0

0.0

Indonesia

Qatar

Malaysia
Vietnam
Australia
0

10

20

UAE
30

40

50

60

70

80

90 %

Value-added shares in Mining, 1970 and 2012

Figure B7 Trading Gain Effect and Value-added Share in Mining Sector, 1970–2012
Note: The starting years for some countries are different due to data availability during
1970–2012: 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©2014 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.

77 Real Income

Box 8

Quarterly Economic GrowthTimely analysis of the current economic situation is beyond the scope of this Databook, which presents
results based on annual data, with 2012 as the latest year covered. In the meantime, for an insight into thecurrent economic growth, for example, one has to rely on countries’ quarterly national accounts (QNA).
Although they are more timely, the QNA are often less precise, and subject to frequent revisions as morereliable 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 there are three constant-price measures of quarterly growth. The first is the quarterly output
compared with the same quarter in the previous year – 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 theannualized quarter-on-quarter growth rate, which is also often used in economic analyses of the current
economic situation. The first two measures are presented in the AQGM (with year-on-year growth displayed as a default).

©2014 Asian Productivity Organization

The current version includes 22 Asian countries that publish QNA: China, Hong Kong, India, Indonesia, Iran,Japan, Korea, Malaysia, Mongolia, the Philippines, Qatar, the ROC, Singapore, Sri Lanka, Thailand, Vietnam,
Armenia, Cyprus, Georgia, Israel, Jordan, and Turkey. For the purpose of international comparisons, the current version includes 51 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
per month to reflect revisions and capture newly available data. Based on the AQGM, Figure B8.2 presents
year-on-year quarterly GDP growth, as well as available quarter-on-quarter GDP growth for Asian countries, the US, and EU15 from 2012Q1 to 2014Q1.

Figure B8.1 Views of Quarterly Economic Growth in Asian Countries by the AQGM
Source: Asian Quarterly Growth Map, June 2014.

continued on next page >

122

6

6
2

4

4
1

1

2

2
0

0

0

0
−1

−1

−2

−2

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

3

3

6

15

6
2

2

4

10

4
1

1

2

5

2
0

0

0

0

0
−1

−1

−2

−5

−2

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

6
4

4
2

2

−2

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

%
8

%
4

%
4

%
4

CanadaGermany

%
4
6

3

3

3

3
4

2

2

2

2

2

1

1

1

1

0

0

0

0

0

−2

−1

−1

−1

−1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

%
4

%
4

%
4

%
4

United Kingdom
Spain

%
4

2

2

2

2

2

0

0

0

0

0

−2

−2

−2

−2

−2

−4

−4

−4

−4

−4

7
2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q10−2−2

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q100

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1

2014Q1
2013Q4
2013Q3
2013Q2
2013Q1
2012Q4
2012Q3
2012Q2
2012Q1Compared to previous quarter
Compared to the same quarter in previous year

62

Portugal
Italy
Ireland%
8
4

FranceUS
Turkey%86Australia
VietnamThailandSri Lanka
Singapore

%
20
16
12
8
4
0
−4
%
10
8
6
4
2
0
−2
%
8

3
2

Philippines%
8

Mongolia%
20

Malaysia
%
8

Korea
%
4

Japan
%
4

3

Indonesia
%
8

India
%
8

Hong Kong
%
4

ROC
%
4

China
%
10
8
6
4
2
0
−2

123

©2014 Asian Productivity Organization
7.2 Trading Gain and Productivity Growth> continued from previous page

Figure B8.2 Quarterly Economic Growth in Asian Countries, 2012Q1 – 2014Q1

Source: Asian Quarterly Growth Map, June 2014.

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, Pakistan and Korea newly publishedtheir national accounts based on the 2008 SNA in April 2013 and March 2014, respectively, following
Malaysia and Hong Kong, who published the 2008 SNA based national accounts in 2012, and the Philippines, who published its new national accounts based on the 1993 SNA, incorporating some elements of the 2008 SNA. While there are movements towards upgrading the SNA, Indonesia has still
not fully introduced the 1993 SNA. The different statuses of 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 anddefinitions to provide harmonized estimates for international comparison. The APO Productivity
Database 2014 largely follows the concepts and definitions of 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 the estimates of GDP. Procedures for allthese adjustments are explained below.

App.

1) FISIM

Among the 20 APO member economies, six countries – Bangladesh, Cambodia, Indonesia, the Lao
PDR, Nepal, and Sri Lanka – 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 thesecountries 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 overperiods, 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 with the average ratios
observed in the countries in which data is available. Figure 94 describes the countries and methods
to adjust FISIM. As described, in instances where both value added data are not available, the trendof the FISIM share on GDP is applied to extrapolate past estimates (although the impacts on GDP
are minor).
Figure 95 plots per capita GDP levels in 2012 and the FISIM share in GDP in the 2000–2012 (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.

125©2014 Asian Productivity Organization

FISIM is an indirect measure of the value of financial intermediation services provided, but for which
financial institutions do not charge explicitly (United Nations, 1993: para. 6.124). It represents a significant 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).

Appendix

2) Software©2014 Asian Productivity Organization

The 1993 SNA also recommends
the capitalization of intangible
assets, which changes not only
the size of GDP but also the sizeof capital input. One intangible
asset is computer software, which
includes pre-packaged software,custom software, and ownaccount software. Among APO
member economies, only nine
have capitalized all three types ofsoftware. Another three countries
exclude own-account software in
their capitalization, in one country only pre-packaged software iscapitalized, 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
1981 1985
1970

1955
1960

1974

1964
1960
1946

1967
1959
1951

1972
1970

1955

1986
1970 1974

1958

1990
1970

1975
1982

1962
1970
1970 19751970
1970 1975
1960

Adjustment using value added of imputed bank service charge
Adjustment using value added of financial intermediation
Using the average trend of FISIM share in GDP

Figure 94 Adjustment of FISIM%

3.5

FISIM share in GDP (average in the 2000−2012)

Hong Kong
Among the countries studied, the3.0data for software investment isavailable for the ROC, Japan, Korea, Mongolia, the Philippines,
2.5
Singapore, Thailand, and China.
To harmonize data, a country’s
India
2.0
Philippines
Singapore
GDP is adjusted to include softJapanUS
Fijiware investment (through its softThailand
Korea
1.5
ware industry) by using the ratio
Malaysia
China
ROC
Pakistan
Australia
Indonesia Turkey
between software investment andMongolia
1.0 Nepal
Iran
GDP (software ratio) and the tanBrunei
Vietnamgible GFCF to GDP ratio (GFCF
Lao PDR
0.5
ratio). Data from the OECD ProBangladesh
Cambodiaductivity Database (Schreyer, BigThousands of US dollar(as of 2012)
Sri Lanka
Myanmarnon, and Dupont, 2003) and the
0.0
0
10
20
30
40
50
60
70
80
APO Productivity Database sugPer capita GDP in 2012 (using 2011 PPP, reference year 2012)
gest an inverse relationship beOffical national accounts in each country, including author adjustment
tween these two ratios (Figure
Our estimates using value added in financial intermediation
Our estimates using value added in imputed bank service charge
96). Countries with a low GFCF ratio tend to be those with high per
Figure 95 FISIM Share in GDP in the 2000–2012
capita GDP, and the observed
Sources: Official national accounts in each country and author estimates.
data suggest that IT tends to playa more important role in thesecountries than in less developed
countries. Furthermore, it is observed from the OECD and APO software data that the software ratio
has been gradually increasing over the past 25 years.

126A.1 GDP Harmonization% Software Investment/GDP
The Databook applies the inverse
2.5
relationship between these two ratios observed from the OECD counSweden
2.0
tries and national accounts in Asian
USJapan
Denmark
non-OECD countries to estimate
Finland
Korea
Hong Kongthe software ratio in 2006 for those
New ZealandFrance
1.5
APO member economies that do
United Kingdom
ROC
not capitalize software investment.
Netherlands
CanadaSwitzerland
The estimated ratios for individual
1.0
countries in 2006 gradually taper
Singapore
Australia
Germany
AustriaSpain
off as one move back in time. HowItaly
ever, there is an exception. CounIndonesia
Vietnam
0.5
Fiji
Sri Lanka
Cambodiatries at the very early stage ofMalaysia
PortugalChina
economic growth are found to have
Ireland
Philippines
India
Nepal
ThailandBangladesh Mongoliaa GFCF ratio as low as countries
Iran
Pakistan0.0with high per capita GDP, but for a
13
18
23
28
33
38
43 %
Tangible GFCF/GDP
different reason. The low GFCF ratio
Countries in which software is included
is explained by the fact that theseCountries in which software is excluded
Countries in which own account is excluded
countries have not experienced
Countries in which custom and own account software are excluded
economic development yet, and inCountries in which pre-package and own account software are excluded
turn this does not imply an important role for software investment. In
Figure 96 Software Investment Ratio and GFCF Ratio tothis report, Cambodia, the Lao PDR,
GDP, 2005
and Nepal are regarded as counSources: OECD Productivity Database and author estimates.
tries 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.

App.

Another problem arises from partial software capitalization. There are three types of software: prepackaged software, custom software, and own-account software. Countries may have capitalized one
or two types of software, but software investment data is often not available separately. The Databook
attempt’s to adjust for the varied level of capitalization across countries by adding the type of software not capitalized to countries’ GDP.

Valuables are defined as “goods of considerable value that are not used primarily for purposes of production or consumption but are held as stores of value over time” (United Nations, 1993: para. 10.7).
They are held under the expectation that their prices will not deteriorate and will rise in the long run.
Valuables consist of precious stones and metals such as diamonds; art-works such as paintings andsculptures; and other valuables such as jewelry made from stones and metals. In 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 1.4% of GDP for India on average during 1999–2012. The current decision is toharmonize the data by excluding net acquisition of valuables from GDP in the APO Productivity
Database 2014.

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’127©2014 Asian Productivity Organization

3) Valuables

Appendix

prices), but this is not true for GDP at factor cost and GDP at basic prices. International comparisons in
Chapter 3 (on economic scale and growth) and Chapter 4 (on final demand) are based on GDP at market prices. However, by valuing output and input at the prices that producers actually pay and receive,
GDP at basic prices is a more appropriate measure of countries’ output than GDP at market prices 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.

©2014 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,and Pakistan, at basic prices for Cambodia, Hong Kong, India, Korea, the Lao PDR, Mongolia, Nepal,
and Singapore, at producers’ prices for Iran, 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.

128

A.2 Capital Stock

A.2

Capital StockAt present, half of APO member economies publish estimates of capital stocks in their systems ofnational accounts. Even where estimates are available, users must be mindful of differences in methodologies and assumptions used to estimate capital stock, and a large diversity in the treatment ofquality adjustment in price statistics among countries. In the APO Productivity Database 2014, a harmonized methodology has been applied in estimating capital stock and capital services, covering 18
Asian economies: Bangladesh, 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 a reference 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 2014.01.
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 and 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 (2006–2012)tion is sometimes used in an attempt to controlFiji1972, 1982, 2005
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
Iran1999, 2001
that individual countries’ price data fails to capJapan
1960, 1965, 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005
Benchmark (1960, 1963, 1966, 1970, 1975, 1980, 1985, 1990,
ture quality improvements. Assuming that the
Korea
1995, 2000, 2005, 2010) Updated (1973, 1978, 1983, 1986-1988,
relative price of IT to non-IT capital in the coun1993, 1998, 2003, 2006–2011)
tries compared is set equal to the IT to non-IT
Malaysia
1978, 1983, 1987, 1991, 2000, 2005
Mongolia
1970, 1977, 1983, 1987, 2000, 2005
prices relative in the reference country, the harX
X
Pakistan
1975/1976, 1984/1985, 1989/1990, 1990/1991
monized price is formulated as: ∆ ln P̃IT = ∆ ln PnlT
Philippines 1969, 1975, 1985, 1988, 1990, 1995, 2000refref+ (∆ ln PIT − ∆ ln PnlT ), where the superscript X
Singapore 1973, 1978, 1983, 1988, 2000, 2005, 2007
Sri Lanka
2006
denotes the country included in the compariThailand
1975, 1980, 1985, 1990, 1995, 1998, 2000, 2005
sons, PIT is the price of IT capital, and PnIT is theVietnam
1996, 2000, 2007
price of non-IT capital. The price of IT capital in
China
1987, 1992, 1997, 2002, 2007
country X, P̃ITX , is computed by the observed
Brunei2005
refTurkey1973, 1979, 1985, 1990, 1998, 2002
in the reference country andprices PITref and PnlT

129

©2014 Asian Productivity Organization

9. computer software
10. other intangible assets

Appendix

%

4.5

1980

4.0

3.8

3.5
3.0

3.2

2.5

3.0

3.0

3.2
2.9

2.7

2.7 2.72.6

2.3
2.0

2.0

2012

3.6

2.9

1.8

2.5

2.4 2.42.3
2.3

1.8

2.3
1.8

2.2 2.22.2
1.9

2.4
1.9
1.8

1.1

1.0

1.9
1.4

1.4

Pakistan

1.5

2.2
1.8

Bangladesh

1.7

1.5
0.5
0.0

Sri Lanka

Philippines

India

Malaysia

Vietnam

US

Singapore

Mongolia

Iran

Fiji

Hong Kong

Thailand

ROC

China

Indonesia

Korea

Japan

X
PnlT
in X. Schreyer (2002) and
Schreyer, Bignon, and Dupont (2003) applied priceharmonization to OECD capital services, with the US as areference country, since thepossible error due to usinga harmonized price index
would be smaller than thebias arising from comparing
capital services based on national deflators.

Figure 97 Capital-Output Ratio, 1980 and 2012___Ratio of the beginning-of-period net capital stock to GDP at current
In this Databook, the same
price harmonization method
pricesis applied to adjust the qualSource: APO Productivity Database 2014.01.
ity improvement for IT hardware and communications
equipment in countries where the appropriate 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 someassets were not available, to estimate missing data based on the relative price of these assets to total
GFCF. In measuring capital services, this Databook largely follows the framework of the OECD Productivity Database (see Schreyer, Bignon, and Dupont, ibid.). The OECD assumes the truncated normal
distribution as profiles for asset discarding (retirement) and the hyperbolic distribution as profiles for
asset decaying. The age-efficiency profile is defined as a combined distribution of discard and decayof assets. The age-efficiency 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 (nodecay 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).

©2014 Asian Productivity Organization

Figure 97 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 3.8. 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, Pakistan, and Iranhave an increasing trend of capital-output ratio, unlike the ratio in the US, which is stable.

130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.

Bangladesh

%
50

China

%
50

ROC

%
50

40

40

40

40

30

30

30

30

20

20

20

20

10

10

10

10

1970 1980 1990 2000 2010

1970 1980 1990 2000 2010%
50

Hong Kong

%
50

India

1970 1980 1990 2000 2010%
50

Indonesia

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

1970 1980 1990 2000 2010

%
50

Japan

%
50

Korea

Malaysia

1970 1980 1990 2000 2010

%
50

40

40

40

40

30

30

30

30

20

20

20

20

10

10

10

10

1970 1980 1990 2000 2010

1970 1980 1990 2000 2010%50

Pakistan%
50

Philippines1970 1980 1990 2000 2010%50

Singapore1970 1980 1990 2000 2010

%
50

40

40

40

40

30

30

30

30

20

20

20

20

10

10

10

10

1970 1980 1990 2000 2010

1970 1980 1990 2000 2010%
50

Thailand%100

Vietnam1970 1980 1990 2000 2010

%
50

80

40

30

60

30

20

40

20

10

20

10

0

0

40

1970 1980 1990 2000 2010

Sri Lanka

0

0

0

0

Mongolia

0

0

0

0

Iran

0
1970 1980 1990 2000 2010

%
50

App.

0

0

0

0

Fiji

1970 1980 1990 2000 2010US01970 1980 1990 2000 2010

1970 1980 1990 2000 2010

Figure 98 Ex Post Real Rate of Return in Asia, 1970–2012
Source: APO Productivity Database 2014.01.

131©2014 Asian Productivity Organization%50Appendix

This Appendix outlines the methodology of the user cost of capital estimation and presents the estimated results of endogenous rate of return for Asian countries in the APO Productivity Database 2014.
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 18 Asian
countries and the US are shown in Figure 98. 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 1970–2012. In 2005–2012,
the real rate of return ranged from 5.1% for Japan to 20.2% in Indonesia and 26.0 for Iran. Using theseex post estimates, the aggregate capital services are measured in this report. The difference caused by
the ex ante and ex post approaches may provide a modest difference in the growth measure of capital
services, regardless of the substantial differences in the rates of return and capital compensations(Nomura, 2004).
Table 20 Average Ex Post Real Rate of Return in Asia

©2014 Asian Productivity Organization

1970–1974 1975–1979 1980–1984 1985–1989 1990–1994 1995–1999 2000–2004 2005–2012
Bangladesh
China
ROC
Fiji
Hong Kong
India
Indonesia
Iran
Japan
Korea
Malaysia
Mongolia
Pakistan
Philippines
Singapore
Sri Lanka
Thailand
Veitnam
US

7.9
21.5
30.7
11.3
19.5
18.3
34.3
24.9
15.0
28.2
27.1
12.3
19.7
9.6
25.3
24.5
13.4
20.7
11.3

10.0
16.6
20.9
12.5
23.4
20.3
32.3
21.7
7.4
23.0
27.6
14.0
21.8
13.6
17.7
32.9
9.9
12.6
9.5

Unit: Percentage
Source: APO Productivity Database 2014.01.

132

8.0
14.3
15.1
5.0
16.9
15.3
30.8
10.1
6.2
12.1
17.0
13.6
17.9
10.4
14.5
16.3
4.3
34.4
6.4

11.9
13.3
19.3
2.6
22.0
13.7
17.3
7.9
8.4
15.5
14.3
16.8
21.6
11.6
12.6
10.3
10.1
13.5
7.9

13.3
15.1
16.6
15.3
13.4
11.9
15.3
21.0
6.8
12.3
16.0
−5.5
18.0
8.8
15.0
9.8
11.4
24.3
8.2

11.2
10.8
15.0
7.0
11.0
10.0
18.7
13.2
4.7
8.4
16.8
22.0
9.0
13.8
12.3
7.8
10.0
13.6
10.9

9.3
12.9
17.1
7.2
9.4
11.6
18.2
24.3
5.1
8.0
17.6
−1.0
10.7
19.9
11.1
9.1
9.1
15.1
11.4

8.0
13.1
13.7
3.1
13.0
11.2
20.2
26.0
5.1
7.0
21.2
5.7
5.5
16.3
15.3
10.1
10.1
11.2
10.0

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, isdata 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 recollectionof the respondents concerning work patterns and pay during the reference week. Another source oferrors 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 the reliability ofdata 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.

133©2014 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.

©2014 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, Population 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
Singapore
Malaysia
Vietnam
PakistanThailandHong Kong
Bangladesh
China
India
ROC
Philippines
Indonesia
Sri Lanka
TurkeyJapan
Australia
EU15 −4

47
44
44
40
40
39
39
37

The APO Productivity Database 2014 defines
37
35
labor inputs as the simple sum of hours
32
worked. Hours worked are defined in this Data30
30
book as the economy-wide hours worked by26
employees, the self-employed, and contribut23
ing family workers. Japanese and US’s national
20
15
accounts publish estimates of the total hours
6
worked. Other Asian countries do not publish
3
hours worked in their national accounts. For−50
5 10 15 20 25 30 35 40 45 50 %these countries the procedure of constructing
economy-wide annual hours worked consists
Figure 99 Average Annual Hours Worked Perof two steps; for many Asian countries first, an
Worker Relative to the US, 2000–2012
average weekly hours worked is obtained andSources: Official national accounts and labor force survey in eachthe number of workers collated from official
country, including author adjustments.
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 of134

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 99 presents a cross-country comparison of average annual hours worked per worker for 2000–
2012, 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 difference in 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. An exception is Japan. Workers in Japan are likely to work much shorter hours than those inother Asian countries. However, compared with EU15, hours worked by workers in Japan is still about
10% longer.

A.5

App.

Other Data

For China, multiple data sources have 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 1952–2012 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.106
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.

106: Holz (2006) provides a useful reference on Chinese official statistics.

135©2014 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. The data forenergy consumptions and CO2 emissions is based on IEA’s CO2 Emissions from Fuel Combustion, Energy
Balances of OECD Countries, and Energy Balances of non-OECD Countries.

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

B - Fishing05

1

Fishing, operation of fish hatcheries, and fish farms; service activities incidental to fishingC - Mining and quarrying

10
11

2
2

12
13
14
15
16
17
18
19
20

2
2
2
3
3
3
3
3
3

21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
40
41

3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
4
4

Mining of coal and lignite; extraction of peat
Extraction of crude petroleum and natural gas; service activities
incidental to oil and gas extraction excluding surveying
Mining of uranium and thorium ores
Mining of metal ores
Other mining and quarrying
Manufacture of food products and beverages
Manufacture of tobacco products
Manufacture of textiles
Manufacture of wearing apparel; dressing and dyeing of fur
Tanning and dressing of leather; manufacture of luggage, handbags, saddlery, harness, and footwear
Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles ofstraw and plaiting materials
Manufacture of paper and paper products
Publishing, printing, and reproduction of recorded media
Manufacture of coke, refined petroleum products, and nuclear fuelManufacture of chemicals and chemical products
Manufacture of rubber and plastics products
Manufacture of other non-metallic mineral products
Manufacture of basic metals
Manufacture of fabricated metal products, except machinery and equipment
Manufacture of machinery and equipment n.e.c.
Manufacture of office, accounting, and computing machinery
Manufacture of electrical machinery and apparatus n.e.c.
Manufacture of radio, television, and communication equipment and apparatus
Manufacture of medical, precision, and optical instruments, watches, and clocks
Manufacture of motor vehicles, trailers, and semi-trailers
Manufacture of other transport equipment
Manufacture of furniture; manufacturing n.e.c.
RecyclingF - Construction

45

5Construction

G - Wholesale and retail trade; repair ofmotor vehicles, motorcycles, andpersonal and household goods

50
51
52

6
6
6

Sale, maintenance, and repair of motor vehicles and motorcycles; retail sale of automotive fuelWholesale trade and commission trade, except of motor vehicles and motorcycles
Retail trade, except of motor vehicles and motorcycles; repair of personal and household goods

H - Hotels and restaurants

55

6

Hotels and restaurants

I - Transport, storage, andcommunications

60
61
62
63
64

7
7
7
7
7

Land transport; transport via pipelines
Water transport
Air transport
Supporting and auxiliary transport activities; activities of travel agencies
Post and telecommunications

J - Financial intermediation

65
66
67

8
8
8

Financial intermediation, except insurance and pension funding
Insurance and pension funding, except compulsory social security
Activities auxiliary to financial intermediation

K - Real estate, renting, and businessactivities

70
71
72
73
74

8
8
8
8
8

Real estate activities
Renting of machinery and equipment without operator and of personal and household goods
Computer and related activities
Research and development
Other business activities

L - Public administration and defence;compulsory social security

75

9

Public administration and defence; compulsory social security

M - Education80

9

Education

N - Health and social work

85

9

Health and social work ther community, social, andO-O
personal service activities

90
91
92
93

9
9
9
9

Sewage and refuse disposal, sanitation, and similar activities
Activities of membership organizations n.e.c.
Recreational, cultural, and sporting activities
Other service activities

P - Private households with employedpersons

95

9

Private households with employed persons

Q - E xtra-territorial organizations andbodies99

9Extra-territorial organizations and bodies

D - Manufacturing©2014 Asian Productivity Organization

E - Electricity, gas, and water supply

1
1

Agriculture, hunting, and related service activities
Forestry, logging, and related service activities

3.1
3.1
3.2
3.2
3.2
3.3
3.4
3.4
3.5
3.5
3.5
3.6
3.7
3.8
3.8
3.8
3.8
3.8
3.8
3.8
3.8
3.9
3.9

Note: “n.e.c.” represents “not elsewhere classified.”

136

Electricity, gas, steam, and hot water supply
Collection, purification, and distribution of water

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