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124 WORLD DEVELOPMENT REPORT 2016 Figure 2.16 Employment is becoming more intensive in the use of digital technologies Change in the ICT intensity of employment, 2000–12 Percent 35 30 25 20 15 10 5 0 –5 –10 Moldova South Africa Costa Rica Romania Lithuania Samoa West Bank and Gaza India Philippines Latvia Malta Russian Federation Average, low- and middle-income countries Jamaica Malaysia Namibia Turkey Barbados Mauritius Macedonia, FYR Cambodia Mexico Panama Bulgaria Average, high-income countries Peru El Salvador Croatia Bahamas, The Ukraine Thailand Source: WDR 2016 team, based on Monroy-Taborda, Moreno, and Santos, forthcoming, for the WDR 2016, using ILO Laborsta (various years). Data at http://bit .do/WDR2016-Fig2_16. Note: ICT (information and communication technology) intensity of employment is based on an index between 0 (no use of technology at work) and 19 (most use of technology at work), averaged by occupation (at the three-digit level) and weighted by employment. Figure 2.17 Nonroutine skills are becoming more important over time Employment composition by type of occupation according to skills requirements, 2000–12 Percent of total employment 45 40 35 30 25 20 15 10 5 0 2000 2001 a. High-income countries 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Percent of total employment higher earnings, even after accounting for educational attainment. Across a sample of eight developing countries, the return associated with using ICT at work is around 40 percent. 122 In Brazil, and focusing on workers most similar to one another, returns to internet use are about 10 percent. 123 60 50 40 30 20 10 0 2000 2001 b. Low- and middle-income countries Nonroutine cognitive or interpersonal Routine cognitive or manual Nonroutine manual Source: WDR 2016 team, based on ILO Laborsta (various years). Data at http://bit.do/WDR2016-Fig2_17. Note: Data are simple cross-country averages. Classification of occupations according to skills requirements follows Autor 2014 and reflects the types of skills most intensely used in each occupation. 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 High-order cognitive and socioemotional skills are more important in the new economy Technological progress is redefining the nature and content of jobs. Some of today’s jobs are new and require new skills—software publishers, data scientists,
EXPANDING OPPORTUNITIES 125 enterprise mobile developers. Others have long existed but have been transformed. Consider, for example, the job description of an accountant in the 1970s and today. Specialized softwares have automated many of the accountant’s original tasks, shifting her job toward more advisory services and critical thinking. Employers now demand more “new economy” skills: that is, highorder cognitive and socio emotional skills, as evidenced in countries as diverse as Brazil, Malaysia, and FYR Macedonia (figure 2.21). At the aggregate level and within firms, new technologies substitute for workers performing routine tasks, while making skilled workers who execute nonroutine abstract tasks more productive. 124 Across 28 studies, more than half of the top five skills demanded by employers are socioemotional, another 30 percent are higher-order cognitive, and 16 percent are technical. 125 High-order cognitive skills include reasoning, problem solving, and critical thinking, while socioemotional skills refer to behavior, personality traits, and attitudes, such as grit, teamwork, selfdiscipline, dependability, and leadership. These are things that are still hard for technology to replicate. These new economy skills pay off. Workers with strong cognitive and socioemotional skills in Armenia, Georgia, the Kyrgyz Republic, Tajikistan, and Vietnam are more likely to be employed and have better-quality jobs. 126 In Vietnam, within a given industry, performing nonroutine analytical tasks carries a 23-percent earnings premium, and interactive (that is, interpersonal) tasks a 13-percent premium, whether combined with routine or nonroutine tasks (figure 2.22). In Armenia and Georgia, the premium for problem solving and learning new things is close to 20 percent. 127 More generally, in 12 of 16 mostly developing countries, wages in nonroutine occupations increased significantly more than wages in routine occupations between 2005 and 2011. 128 In addition to technological change, other factors help explain these global labor market trends. Trade, urbanization, structural transformation, and globalization fundamentally shape labor markets and in a number of cases are likely to be even more important than technology. In some Latin American countries, for example, commodity-driven economic booms have boosted low-wage earnings and show no polarization at the aggregate level. Moreover, distinguishing among factors is more difficult because they are related to one another. 129 Yet technological change seems to be an important part of the explanation. First, occupations most intensive in the use of digital technologies are also most intensive in nonroutine cognitive and interpersonal skills (figure 2.23). Second, globalization and trade do not fully explain the observed polarization. 130 Given Figure 2.18 In developing countries, one-third of urban workers use digital technology at work Urban workers who use a computer at work, conditional on working Percent 50 40 30 20 10 0 Men Women 15–29 30–49 50+ Upper 60% Gender Age group Average Source: WDR 2016 team, based on STEP household surveys (World Bank, various years). Data at http:// bit.do/WDR2016-Fig2_18. Note: “Average” refers to the average use of technology among all urban workers in 11 countries where the STEP survey was conducted. “Upper 60%” and “Bottom 40%” refer to asset distribution of individuals’ households. the weight of China in manufacturing supply chains, the decline in routine labor in the rest of the world could simply be the result of a shift of routine labor to China’s manufacturing sector. Between 2000 and 2010, the share of employment in routine occupations Bottom 40% Income distribution Figure 2.19 Employment becomes more intensive in ICT use as economies grow Share of employment in high–ICT-intensity occupations, circa 2013 Percent 60 50 40 30 20 10 0 CZE EST MKD SVK KOR POL GEO ARM UKR VNM BOL COL RUS KEN LKA GHA LAO NLD GBR BEL DNK CAN FIN SWE DEU AUT USA ESP FRA ITA JPN IRL Source: Monroy-Taborda, Moreno, and Santos, forthcoming, for the WDR 2016, based on STEP (World Bank, various years), PIAAC household surveys, and World Development Indicators (World Bank, various years). Data at http://bit.do/WDR2016-Fig2_19. Note: GDP = gross domestic product; ICT = information and communication technology; PIAAC = Programme for the International Assessment of Adult Competencies. NOR 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 GDP per capita (constant U.S. dollars)
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A World Bank Group Flagship Report
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Contents xiii xv xix Foreword Ackno
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CONTENTS vii Boxes O.1 5 Frequently
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CONTENTS ix O.24 35 Digital safegua
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CONTENTS xi B3.8.1 178 Autocratic g
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Foreword We find ourselves in the m
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Acknowledgments This Report was pre
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ACKNOWLEDGMENTS xvii Karl Chua, Mas
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xx ABBREVIATIONS GDP GIS GNI GPS GS
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xxii ABBREVIATIONS BFA Burkina Faso
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Inclusion Efficiency Innovation
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OVERVIEW 3 Figure O.1 Digital techn
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OVERVIEW 5 Box O.1 Frequently asked
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OVERVIEW 7 Map O.1 The internet is
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OVERVIEW 9 Figure O.6 The digital d
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OVERVIEW 11 This mechanism operates
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OVERVIEW 13 Figure O.10 The size of
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OVERVIEW 15 Box O.3 Bridging the di
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OVERVIEW 17 sector is thus challeng
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OVERVIEW 19 skills that help them b
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OVERVIEW 21 Figure O.15 Labor share
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OVERVIEW 23 Figure O.18 From a tech
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OVERVIEW 25 governments and citizen
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OVERVIEW 27 Box O.6 Nailing Jell-O
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OVERVIEW 29 as well as higher secur
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OVERVIEW 31 Figure O.22 Policy prio
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OVERVIEW 33 Figure O.23 The types o
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OVERVIEW 35 Box O.12 Can continuous
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OVERVIEW 37 Box O.13 European Union
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OVERVIEW 39 29. Data for 2014 of ne
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OVERVIEW 41 OECD (Organisation for
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HOW THE INTERNET PROMOTES DEVELOPME
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D
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ACCELERATING GROWTH 51 varies with
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ACCELERATING GROWTH 53 Map 1.1 Many
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ACCELERATING GROWTH 55 Figure 1.6 L
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ACCELERATING GROWTH 57 Figure 1.7 I
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ACCELERATING GROWTH 59 Box 1.3 Is t
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ACCELERATING GROWTH 61 Map 1.2 Chin
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ACCELERATING GROWTH 63 Box 1.5 The
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ACCELERATING GROWTH 65 is selling c
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ACCELERATING GROWTH 67 goods tradin
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ACCELERATING GROWTH 69 competition
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ACCELERATING GROWTH 71 it to manage
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e-HEALTH 191 Figure F3.1 Sequencing
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4. Sectoral policies 5. National pr
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SECTORAL POLICIES 201 Box 4.1 Polic
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SECTORAL POLICIES 203 Box 4.1 Polic
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SECTORAL POLICIES 205 is independen
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SECTORAL POLICIES 207 Box 4.3 Fragi
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SECTORAL POLICIES 209 role for the
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SECTORAL POLICIES 211 subscriptions
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SECTORAL POLICIES 213 Box 4.5 The l
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SECTORAL POLICIES 215 Box 4.6 Guate
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SECTORAL POLICIES 217 Figure 4.1 Pr
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SECTORAL POLICIES 219 Box 4.7 How b
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SECTORAL POLICIES 221 mandating tha
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SECTORAL POLICIES 223 the internet
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SECTORAL POLICIES 225 Protecting pe
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SECTORAL POLICIES 227 grown since t
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SECTORAL POLICIES 229 Box 4.9 Tech
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SECTORAL POLICIES 231 Box 4.10 Isra
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SECTORAL POLICIES 233 US$74 million
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SECTORAL POLICIES 235 has been clas
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SECTORAL POLICIES 237 Kende, Michae
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242 WORLD DEVELOPMENT REPORT 2016 i
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THE DATA REVOLUTION 245 Figure S5.1
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THE DATA REVOLUTION 247 A journalis
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NATIONAL PRIORITIES 249 • Rising
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NATIONAL PRIORITIES 251 schools, ho
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NATIONAL PRIORITIES 253 Figure 5.3
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NATIONAL PRIORITIES 255 requiring f
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NATIONAL PRIORITIES 257 around the
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NATIONAL PRIORITIES 261 Box 5.3 The
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NATIONAL PRIORITIES 263 Box 5.5 Kha
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NATIONAL PRIORITIES 265 Box 5.7 Eme
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NATIONAL PRIORITIES 267 Box 5.8 Bui
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NATIONAL PRIORITIES 269 Box 5.9 Bui
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NATIONAL PRIORITIES 271 • Explore
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NATIONAL PRIORITIES 275 identify gh
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NATIONAL PRIORITIES 277 Table 5.7 T
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NATIONAL PRIORITIES 279 Box 5.13 Es
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NATIONAL PRIORITIES 281 experiences
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NATIONAL PRIORITIES 283 dence.” N
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NATIONAL PRIORITIES 285 Kremer, Mic
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290 WORLD DEVELOPMENT REPORT 2016 A
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CHAPTER 6 Global cooperation Data,
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ENVIRONMENTAL MANAGEMENT 323 Map F6
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326 WORLD DEVELOPMENT REPORT 2016 E
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