Title page 1

Contents 7

Foreword 13

Acknowledgments 15

About the Authors 17

Overview 19

Abbreviations 37

1. Stylized Facts about EAP Labor Markets 39

Introduction 39

Overall employment and earnings 39

Employment and earnings across sociodemographic groups 42

Trends in jobs and structural transformation 52

Notes 58

References 58

2. Technology and the Labor Market: Conceptual and Empirical Framework 60

Introduction 60

Technical feasibility: Tasks and job exposure to technology 61

Economic viability: Drivers of technology adoption 65

The technical feasibility and economic viability of technology 69

Notes 74

References 74

SPOTLIGHT 2.1. Measuring the Task Content of Jobs 76

3. Automation in Manufacturing: Industrial Robots 84

Introduction 84

Technical and economic drivers of the adoption of robots 84

Labor market impacts of robot adoption 90

Robots and jobs in Viet Nam 96

Notes 103

References 103

SPOTLIGHT 3.1. Technology, Agricultural Productivity, and Jobs in EAP and the World 108

4. Artificial Intelligence and Jobs 114

Introduction 114

Exposure to AI 114

AI exposure and labor market outcomes 125

Note 127

References 127

5. Working with Digital Technologies 129

Introduction 129

Digital jobs 129

Digital platforms 145

References 151

6. Technology, Jobs, and Structural Transformation: An Integrated View 157

Introduction 157

Summary of the empirical evidence 157

Cross-sectoral impacts of technology adoption on jobs 159

References 166

7. Policy Implications 168

Introduction 168

Skills 168

Facilitating labor and capital mobility 178

Removing factor price distortions 181

Expanding social protection to the informal sector 183

References 185

APPENDIX: Supplementary Data 191

Tables 12

TABLE 6.1. Linking stylized facts about EAP labor markets and the implications of technology adoption 158

Figures 9

FIGURE O.1. The task structure of jobs, EAP and advanced economies 21

FIGURE O.2. Correlation between labor costs and robot prices and labor costs and robot adoption, EAP and the world 23

FIGURE O.3. The stock of industrial robots and trends in robot adoption, EAP, 2000-22 24

FIGURE O.4. Relative labor costs and employment, by routine task intensity and country 26

FIGURE O.5. Effects of robot adoption on employment, wages, and informality, Viet Nam, 2014-20 27

FIGURE O.6. Estimated effects of robot adoption on district employment and wages, by age group, Viet Nam 28

FIGURE O.7. Exposure to AI: Correlation with sex, educational attainment, and wages, EAP, circa 2022 29

FIGURE O.8. Wages and the digital intensity of jobs, by formality and work experience, Indonesia, 2023 30

FIGURE O.9. Agricultural mechanization, robot adoption, and employment in agriculture and industry, EAP and the world, 1991-2021 32

FIGURE 1.1. Share of the working-age population in the total population and ratio of employment to working-age population, by country or grouping, 2010-23 40

FIGURE 1.2. Hourly wage and labor productivity growth, EAP, circa 2010-22 41

FIGURE 1.3. Unemployment rates and labor force participation rates, by age group, circa 2023 43

FIGURE 1.4. Wages: Youth and workers over age 50 relative to prime-age workers, five countries, 2010 or 2011 and 2019 44

FIGURE 1.5. Labor force status and changes in female participation rates, by sex, EAP 45

FIGURE 1.6. Changes in the gender wage gap in salaried jobs, five EAP countries, 2010 or 2011 and 2019 47

FIGURE 1.7. The educational attainment of the working-age population, East Asian countries and the Pacific Islands, circa 2010 and 2022 49

FIGURE 1.8. Wage premiums in secondary and tertiary education relative to primary education, five countries, 2010 or 2011 and 2019 51

FIGURE 1.9. Changes in employment share and real wages, by sector, EAP, 2010-19 53

FIGURE 1.10. Changes in the informal employment rate, by country and region, 2010-22 55

FIGURE 1.11. Changes in employment, by formal and informal status and type of work, five ASEAN countries, 2010-19 56

FIGURE 1.12. Real wage growth, by sector, five ASEAN countries, 2010-circa 2019 56

FIGURE 1.13. Average real wage growth, by occupation, EAP, 2010-19 57

FIGURE 2.1. The effects of new technologies on routine and nonroutine tasks: An integrated view 63

FIGURE 2.2. Employment by job task content, EAP and other regions 65

FIGURE 2.3. Economic viability of technology: Robot prices, labor costs, and robot adoption, the world 66

FIGURE 2.4. Jobs and technology in the EAP region: Technical susceptibility and economic viability 70

FIGURE 2.5. Relative labor costs and employment routine task intensity, by country 73

FIGURE 3.1. Adoption trends and the composition of industrial robots, EAP, 2000-22 89

FIGURE 3.2. Robot adoption and employment growth across industries, EAP, 2010-20 91

FIGURE 3.3. Total employment and average wage effects of robot adoption, five ASEAN countries 92

FIGURE 3.4. Industry composition of the stock of robots, Viet Nam, 2010-22 96

FIGURE 3.5. Estimated effects of robot adoption on employment and wages, by educational attainment, Viet Nam, 2014-20 98

FIGURE 3.6. Estimated effects of robot adoption on formal employment and the informality rate, Viet Nam, 2014-20 100

FIGURE 3.7. Estimated effects of robot adoption on district employment and wages, by sex, Viet Nam, 2014-20 101

FIGURE 3.8. Estimated effects of robot adoption on district employment and wages, by age group, Viet Nam, 2014-20 102

FIGURE 4.1. Exposure and complementarity with AI, by routine task intensity of physical and cognitive jobs, EAP and advanced economies 118

FIGURE 4.2. Exposure and complementarity with AI, EAP and other country groups 124

FIGURE 4.3. Exposure to AI: Correlation with sex, educational attainment, and sector of employment, EAP 125

FIGURE 4.4. Exposure to automation and AI, by age group, five EAP countries 126

FIGURE 4.5. The correlation of exposure to AI with earnings and employment growth, five countries in EAP 127

FIGURE 5.1. The share of employment in digitally intensive occupations, EAP and other selected economies 134

FIGURE 5.2. Earnings premiums and employment growth associated with digitally intensive occupations, five EAP countries 139

FIGURE 5.3. The effect of education and digital intensity on earnings, five EAP countries 140

FIGURE 5.4. Growth in earnings and employment, by sex, five EAP countries, 2010-19 141

FIGURE 5.5. Digital intensity and computer use among workers, by age group, five EAP countries 145

FIGURE 5.6. Top 100 digital platforms worldwide and the market value of the EAP digital economy 146

FIGURE 5.7. Growth in user traffic on digital platforms, the Philippines and Viet Nam 147

FIGURE 5.8. The effects of platform diffusion on firm productivity, value added, and employment, the Philippines and Viet Nam 148

FIGURE 5.9. Own-sector effects of platforms on enterprise and labor force composition and firm performance, Viet Nam 149

FIGURE 6.1. The structure of employment and economic development in EAP and the world, circa 1991-2023 162

FIGURE 6.2. Technology adoption, changes in employment structure, and economic development, EAP and the world, 1991-2021 163

FIGURE 6.3. Trends in the level and the share of employment in manufacturing, EAP and the world, 1990-2022 165

FIGURE 7.1. Meta-analysis of socioemotional learning programs: Average impacts 172

FIGURE 7.2. The supply of STEM graduates, EAP region, circa 2020 175

FIGURE 7.3. Correlation coefficient with engineering density, selected indicators, United States 176

FIGURE 7.4. Share of workers employed in agriculture in total employment, by birth cohort, 1999 and 2019 179

FIGURE 7.5. Robot adoption and the relative taxation of capital and labor, 2018 182

FIGURE 7.6. Likelihood of choosing a social insurance package over no insurance, Malaysia 185

Maps 12

MAP 3.1. Robot penetration and employment share of foreign-owned manufacturers, Viet Nam, annual averages, by district, 2014-20 97

Boxes 8

Box 2.1. Estimating robot prices across manufacturing industries 67

Box 3.1. Empirical evidence on the determinants of the adoption of robots 85

Box 3.2. The employment effects of industrial robots across the world: A literature review 93

Box 4.1. Who is adopting artificial intelligence? The correlates of AI adoption by individuals and firms 115

Box 4.2. AI exposure and differences in the tasks within occupations 120

Box 5.1. The creation of digital jobs in China 130

Box 5.2. The literature on employment and the labor impacts of digital connectivity 131

Box 5.3. Measuring the digital intensity of occupations 135

Box 5.4. Digital jobs, informality, and female labor force participation in Indonesia 141

Box 5.5. Income effect of ride-sharing platforms 150

Box 6.1. General equilibrium impacts of technology adoption on jobs 160

Box 7.1. Policy responses to the emergence of artificial intelligence in the Philippines 170

Box 7.2. Fostering the socioemotional skills of children 173

Box 7.3. Building advanced technical skills to harness digital technologies 177

Box 7.4. Innovative approaches to fostering social insurance for gig and self-employed workers 183

Box Tables 12

TABLE B2.3.1. Estimation of global-average robot prices, by robot type 68

TABLE B5.1.1. Examples of newly added digital occupations, China 130

TABLE B5.3.1. Digital intensity score and the share of occupations, by countries 136

Box Figures 10

FIGURE B3.1.1. Robot adoption: Determinants and correlation with sectoral wage 85

FIGURE B3.1.2. Correlation between robot adoption per worker and population aging 88

FIGURE B3.2.1. Meta-analysis of estimates on the employment effects of robotization 95

FIGURE B4.1.1. The correlates of AI adoption, by the characteristics of firms and individuals 116

FIGURE B4.2.1. A comparison of AI exposure estimates, by country 121

FIGURE B4.2.2. Decomposition of the differences in average AI exposure, by country 122

FIGURE B5.3.1. The digital intensity score and the share of workers using digital technologies, by occupations, Viet Nam, 2021 138

FIGURE B5.4.1. Share of workers using digital technologies, by sex and formal or informal status, Indonesia, 2018-23 142

FIGURE B5.4.2. The digital premium, by formal and informal status and job tenure, Indonesia 143

FIGURE B5.4.3. Share of workers who have insurance or pensions, by digital work and formal or informal status, Indonesia, 2023 144

FIGURE B5.5.1. The effects of ride-hailing platform entry on the earnings of motorbike and car drivers, Viet Nam 151

Spotlight Figures 10

FIGURE S2.1.1. Occupational structure by the task intensity of jobs, EAP and advanced economies 77

FIGURE S2.1.2. Routine task intensity, survey versus O*NET measures, EAP and other economies 80

FIGURE S2.1.3. The drivers of differences in routine task intensity across economies 82

FIGURE S3.1.1. Log agricultural machinery versus log gross domestic product per capita, EAP and the world, 1991 109

FIGURE S3.1.2. Trends in agricultural machinery and farm labor productivity, EAP, 1991-2022 110

FIGURE S3.1.3. Trends in farm employment and the mechanization effect 111

Appendix Tables 12

TABLE A.1. Regression results: Agricultural mechanization, employment, and productivity 204

Appendix Figures 12

FIGURE A.1. Task intensity and artificial intelligence exposure, EAP 192

FIGURE A.2. Unit price of technology, 1971-2023 199

FIGURE A.3. Change in robot adoption and wages, 2014-19 200

FIGURE A.4. Trends in employment in agriculture and services, 1990-2022 205

Appendix Boxes 9

Box A.1. Exposure to artificial intelligence and complementarity 201

Appendix Box Figures 12

FIGURE A1.1. AI exposure and complementarity among routine and nonroutine cognitive tasks, by occupation 202