The Information Revolution changed the nature of work and the economy because it has

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Abstract

Examines three possible impacts of technology on jobs, including (1) robots replacing workers; (2) robots enhancing worker productivity; or (3) technology creating jobs as it shapes demand for new goods and services. These disparate effects of technology render economic predictions of technology-induced job losses useless. Predictions sensationalize the impact of technology and stir fears, especially among middle-skill workers in routine jobs. Technology does change the demand for skills. Since 2001, the share of employment in occupations heavy in nonroutine cognitive and sociobehavioral skills has increased from 19 to 23 percent in emerging economies and from 33 to 41 percent in advanced economies. The pace of innovation will determine whether new sectors or tasks emerge to counterbalance the decline of old sectors and routine jobs as technology costs decline. Meanwhile, whether the cost of labor remains low in emerging economies in relation to capital will determine whether firms choose to automate production or move elsewhere.

From their beginning, robots were intended to replace humans in the workplace. In fact, Karel Čapek, the Czech writer who invented the word robot in 1920, used the Slavic-language word for work, robota, to make it clear what these machines would be used for. Over the last century, machines have replaced workers in many tasks. On balance, however, technology has created more jobs than it has displaced. Technology has brought higher labor productivity to many sectors by reducing the demand for workers for routine tasks. And yet in doing so, it has opened doors to new sectors once imagined only in the world of science fiction.

As technology advances, firms adopt new methods of production, markets expand, and societies evolve. Firms rely on new technologies to better use capital, overcome information barriers, outsource, and innovate. New technologies allow for more efficient management of the operations of firms: firms hire workers in one location to produce parts, in another location to assemble, and in a third location to sell. Meanwhile, consumers enjoy a wider range of products at lower prices.

In today’s economy, market opportunities are growing for all participants. Some platform firms1 are creating new marketplaces to trade goods or services. Even small firms are global. And they are growing faster. The firms selling on eBay in Chile, Jordan, Peru, and South Africa are younger than the firms in offline markets.2 In China, start-ups are dominant on the Alibaba platform.3 Societies benefit as technology increases the options for service delivery and for citizens to hold their governments accountable.

Workers, firms, and governments are building new comparative advantages as conditions change. For example, by being the first to adopt 3-D technologies, Danish firms strengthened their hold on the global market for hearing aid products in the 2000s.4 The Indian government invested in technical universities across the country, and subsequently India became a world leader in high-tech sectors. By integrating into global value chains, Vietnamese workers developed their foreign-language abilities, building additional human capital that allows them to expand into other markets.

Notwithstanding the opportunities, however, there are still disruptions. The declining cost of machines especially puts at risk those workers in low-skill jobs engaged in routine tasks. These are the occupations most susceptible to automation. Displaced workers are likely to compete with (other) low-skill workers for jobs with low wages. Even when new jobs are created, retooling is costly, and often impossible.

The resulting displacement of workers generates anxiety, just as in the past. In 1589, Queen Elizabeth I of England was alarmed when clergyman William Lee applied for a royal patent for a knitting machine: “Consider thou what the invention would do to my poor subjects,” she pointed out. “It would assuredly bring them to ruin by depriving them of employment.”5 In the 1880s, the Qing dynasty fiercely opposed constructing railways in China, arguing that the loss of luggage-carrying jobs might lead to social turmoil.6 Earlier in the 19th century, the Luddites sabotaged machines to defend their jobs in England, despite the overall economic growth fueled by steam power.

Fears of robot-induced unemployment have dominated discussions about the future of work. Nowhere are these fears more evident than in the industrial sector. The decline in industrial employment in some high-income economies over the last two decades is an established trend. The Republic of Korea, Singapore, Spain, and the United Kingdom are among the countries in which the share of industrial employment dropped more than 10 percentage points. But this trend mainly reflects a shift in employment from manufacturing to services as those countries grow. By contrast, millions of industrial jobs have been created in developing countries since the late 1980s. Indeed, the share of industrial employment has increased significantly in a few emerging markets such as Cambodia and Vietnam. On average, the share of industrial employment has remained stable in developing countries, despite the many predictions of job losses resulting from technology.

That said, technology is disrupting the demand for skills. Globally, private returns to education—about 9 percent a year—remain high despite the significant expansion in the supply of skilled labor. Returns to tertiary education are almost 15 percent a year. Individuals with more advanced skills are taking better advantage of new technologies to adapt to the changing nature of work. For example, returns to primary schooling in India increased during the Green Revolution of the 1960s and 1970s, with more educated farmers adopting new technologies.

Technology has the potential to improve living standards, but its effects are not manifesting themselves equally across the globe. The process of job creation works societywide—and not just for the few—only when the rules of the game are fair. Workers in some sectors benefit handsomely from technological progress, whereas those in others are displaced and have to retool to survive. Platform technologies create huge wealth but place it in the hands of only a few people.

Irrespective of technological progress, persistent informality continues to pose the greatest challenge for emerging economies. Informal employment remains at more than 70 percent in Sub-Saharan Africa and 60 percent in South Asia and at more than 50 percent in Latin America. In India, the informal sector has remained at around 90 percent, notwithstanding fast economic growth and technology adoption. Both wages and productivity are significantly lower in the informal sector. Informal workers have neither health insurance nor social protection. Technology may prevent Africa and South Asia from industrializing in a manner that moves workers to the formal sector.

Progress in the context of the formal–informal worker divide must be reevaluated because of the changing nature of work. Economic growth depends on human capital accumulation and infrastructure that responds to the needs of education, health, and business. Enhanced social protection that applies no matter the form of labor contract is also ripe for consideration.

Technology generates jobs

“They’re always polite, they always upsell, they never take a vacation, they never show up late, there’s never a slip-and-fall, or an age, sex, or race discrimination case,” said Andrew Puzder, then chief executive of Hardee’s Food Systems Inc., a restaurant chain headquartered in Tennessee. He was talking about swapping employees for machines.7 Statements like these give workers reason to worry.

The advent of a jobless economy raises concern because tasks traditionally performed by humans are being—or are at risk of being—taken over by robots, especially those enabled with artificial intelligence. The number of robots operating worldwide is rising quickly. By 2019, 1.4 million new industrial robots will be in operation, raising the total to 2.6 million worldwide.8 Robot density per worker in 2018 is the highest in Germany, Korea, and Singapore. Yet in all of these countries, despite the high prevalence of robots, the employment rate remains high.

Young workers may be more affected by automation than older workers. Although the adoption of robots did not have any substantial net effect on employment in Germany, it reduced the hiring of young entrants.9 For this reason, the effects of automation can be different in countries that are aging compared with those that have young populations and anticipate large numbers of new labor market entrants.

Yes, robots are replacing workers, but it is far from clear to what extent. Overall, technological change that replaces routine work is estimated to have created more than 23 million jobs across Europe from 1999 to 2016, or almost half of the total increase in employment over the same period. Recent evidence for European countries suggests that although technology may be replacing workers in some jobs, overall it raises the demand for labor.10 For example, instead of hiring traditional loan officers, JD Finance, a leading fintech platform in China, created more than 3,000 risk management or data analysis jobs to sharpen algorithms for digitized lending.

Technological progress leads to the direct creation of jobs in the technology sector. People are increasingly using smartphones, tablets, and other portable electronic devices to work, organize their finances, secure and heat their homes, and have fun. Workers create the online interfaces that drive this growth. With consumer interests changing fast, there are more opportunities for people to pursue careers in mobile app development and virtual reality design.

Technology has also facilitated the creation of jobs through working online or joining the so-called gig economy. Andela, a U.S. company that specializes in training software developers, has built its business model on the digitization of Africa. It has trained 20,000 software programmers across Africa using free online learning tools. Once qualified, programmers work with Andela directly or join other Andela clients across the world. The company aims to train 100,000 African software developers by 2024. Ninety percent of its workers are in Lagos, Nigeria, with other sites in Nairobi, Kenya, as well as Kampala, Uganda.

Technology increases proximity to markets, facilitating the creation of new, efficient value chains. In Ghana, Farmerline is an online platform that communicates with a network of more than 200,000 farmers in their native languages via mobile phone. It provides information on the weather and market prices, while collecting data for buyers, governments, and development partners. The company is expanding to include credit services.

During this process of technology adoption some workers will be replaced by technology. Workers involved in routine tasks that are “codifiable” are the most vulnerable. The examples are numerous. More than two-thirds of robots are employed in the automotive, electrical/electronics, and metal and machinery industries. Based in China, Foxconn Technology Group, the world’s largest electronics assembler, cut its workforce by 30 percent when it introduced robots into the production process. When robots are cheaper than the existing manufacturing processes, firms become more amenable to relocating production closer to consumer markets. In 2017 3-D printing technologies enabled the German company Adidas to establish two “speed factories” for shoe production: one in Ansbach, Germany, and the other in Atlanta in the United States, eliminating more than 1,000 jobs in Vietnam. In 2012 the Dutch multinational technology company Philips Electronics shifted production from China back to the Netherlands.

Some service jobs are also vulnerable to automation. Mobileye of Israel is developing driverless vehicle navigation units. Baidu, the Chinese technology giant, is working with King Long Motor Group, China, to introduce autonomous buses in industrial parks. Financial analysts, who spend much of their time conducting formula-based research, are also experiencing job cuts: Sberbank, the largest bank in the Russian Federation, relies on artificial intelligence to make 35 percent of its loan decisions, and it anticipates raising that rate to 70 percent in less than five years.11 “Robot lawyers” have already replaced 3,000 human employees in Sberbank’s legal department. The number of back-office employees will shrink to 1,000 by 2021, down from 59,000 in 2011. Ant Financial, a fintech firm in China, uses big data to assess loan agreements instead of hiring thousands of loan officers or lawyers.

Nevertheless, it is impossible to put a figure on the level of job displacement that will take place overall. Even the most well-known economists have experienced little success with this exercise. In 1930 John Maynard Keynes declared that technology would usher in an age of leisure and abundance within a hundred years. He mused that everyone would have to do some work if they were to be content, but that three hours a day would be quite enough.12 The world in 2018 is far from this kind of reality.

Although quantifying the impact of technological progress on job losses continues to challenge economists, estimates abound. Those estimates vary widely (figure 1.1). For Bolivia, job automation estimates range from 2 to 41 percent. In other words, anywhere from 100,000 to 2 million Bolivian jobs may be automated in 2018. The range is even wider for advanced economies. In Lithuania, from 5 to 56 percent of jobs are at risk of being automated. In Japan, from 6 to 55 percent of jobs are thought to be at risk.

The wide range of predictions illustrates the difficulty of estimating technology’s impact on jobs. Most estimates rely on automation probabilities developed by machine learning experts at the University of Oxford. The experts were asked to categorize a sample of 70 occupations taken from the O*NET online job database used by the U.S. Department of Labor as either strictly automatable or not (1–0).13 Relying on these probabilities, initial estimates placed 47 percent of U.S. occupations at risk of automation. Basing probabilities on the opinion of experts is instructive but not definitive. Moreover, using one country’s occupational categories to estimate possible job losses from automation elsewhere is problematic.

Job loss predictions do not accurately incorporate technology absorption rates, which are often painstakingly slow and differ not only between countries but also across firms within countries. The absorption rate therefore affects the potential for technology to destroy jobs. The use of mobile telephony, for example, spread faster than earlier technologies, but the Internet has been comparatively slow to take hold in many cases, particularly among firms in the informal sector. The uptake of mechanization in agriculture presents a similar picture. Persistent trade barriers, the relatively low cost of labor compared with that of agricultural machinery, and poor information all contribute to the low rates of mechanization in low-income and some middle-income countries. Even for the textile industry’s spinning jenny, the relatively low cost of labor delayed its introduction in France and India—in 1790 France had only 900 spinning jennies compared with 20,000 in Great Britain.14 The prevalence of automation versus labor continues to vary across and within countries, depending on the context.

How work is changing

It is easier to assess how technology shapes the demand for skills and changes production processes than it is to estimate its effect on job losses. Technology is changing the skills being rewarded in the labor market. The premium is rising for skills that cannot be replaced by robots—general cognitive skills such as critical thinking and sociobehavioral skills such as managing and recognizing emotions that enhance teamwork. Workers with these skills are more adaptable in labor markets. Technology is also disrupting production processes by challenging the traditional boundaries of firms, expanding global value chains, and changing the geography of jobs. Finally, technology is changing how people work, giving rise to the gig economy in which organizations contract with independent workers for short-term engagements.

Technology is disrupting the demand for three types of skills in the workplace. First, the demand for nonroutine cognitive and sociobehavioral skills appears to be rising in both advanced and emerging economies. Second, the demand for routine job-specific skills is declining. And, third, payoffs to combinations of different skill types appear to be increasing. These changes show up not just through new jobs replacing old jobs, but also through the changing skills profile of existing jobs (figure 1.2).

Since 2001, the share of employment in occupations intensive in nonroutine cognitive and sociobehavioral skills has increased from 19 to 23 percent in emerging economies and from 33 to 41 percent in advanced economies. In Vietnam, within a given industry workers performing nonroutine analytical tasks earn 23 percent more than those performing tasks that are nonanalytical, noninteractive, and nonmanual; those undertaking interpersonal tasks earn 13 percent more.15 In Armenia and Georgia, the earnings premium for problem solving and learning new skills at work is close to 20 percent.16

Robots may complement workers who engage in nonroutine tasks that require advanced analytical, interpersonal, or manual skills requiring significant dexterity—for instance, teamwork, relationship management, people management, and caregiving. In these activities, people must interact with one another on the basis of tacit knowledge. Designing, producing art, conducting research, managing teams, nursing, and cleaning have proven to be hard tasks to automate. Robots have for the most part struggled to replicate these skills to compete with workers.

Machines replace workers most easily when it comes to routine tasks that are codifiable. Some of these tasks are cognitive, such as processing payrolls or bookkeeping. Others are manual or physical, such as operating welding machines, assembling goods, or driving forklifts. These tasks are easily automated. In Norway, the adoption by firms of information and communications technologies benefited skilled workers in executing nonroutine abstract tasks but replaced unskilled workers.17

Payoffs for combinations of different skill types are also increasing. The changing nature of work demands skill sets that improve the adaptability of workers, allowing them to transfer easily from one job to another. Across countries, both higher-order cognitive (technical) skills and sociobehavioral skills are consistently ranked among the skills most valued by employers. Employers in Benin, Liberia, Malawi, and Zambia rank teamwork, communication, and problem-solving skills as the most important set of skills after technical skills.18

Even within a given occupation, the impact of technology on the skills required to perform a job is changing—but not always in the direction one might expect. In Chile, the adoption of sophisticated computer software for client management and business operations between 2007 and 2013 decreased the demand for workers to complete abstract tasks and increased the demand for workers to complete routine manual tasks. As a result, there was a reallocation of employment from skilled workers to administrative, unskilled production workers.19

In advanced economies, employment has been growing fastest in high-skill cognitive occupations and low-skill occupations that require dexterity. By contrast, employment has shifted away from middle-skill occupations such as machine operators. This is one of the factors that may translate into rising inequality in advanced economies. Both middle- and low-skill workers could see falling wages—the former because of automation; the latter because of increased competition.

Few studies have been made of emerging economies, but some of those that have been made reveal similar changes in employment. In middle-income European countries such as Bulgaria and Romania, the demand for workers in occupations involving nonroutine cognitive and interpersonal skills is rising, while the demand for workers in lower-skill nonroutine manual occupations has remained steady.20 The use of routine cognitive skills has also increased in Botswana, Ethiopia, Mongolia, the Philippines, and Vietnam.21 Studies observe that the demand for nonroutine cognitive and interpersonal skills is largely rising much faster than for other skills. High-skill workers are gaining with technological change, whereas low-skill workers—especially those in manual jobs—seem to be losing out.

Other studies show that changes in employment have been positive. In Argentina, the adoption of information and communications technologies in manufacturing increased employment turnover: workers were replaced, occupations were eliminated, new occupations were created, and the share of unskilled workers fell. However, employment levels increased across all skill categories.22

Technology is also disrupting production processes, challenging the traditional boundaries of firms and expanding global value chains. In doing so, technology changes the geography of jobs. Other waves of technological change have done the same. The Industrial Revolution, which mechanized agricultural production, automated manufacturing, and expanded exports, led to the mass migration of labor from farms to cities. The advent of commercial passenger planes expanded tourism from local holiday destinations in Northern Europe to new foreign resorts on the Mediterranean Sea. Thousands of new jobs were created in new locations.

Improvements in transcontinental communications technologies, along with the fall in transportation costs, have expanded global value chains toward East Asia. But many other factors beyond technology also matter for outsourcing. The Philippines overtook India in 2017 in terms of market share in the call center business at least in part because of the country’s lower taxes.

Meanwhile, technology is enabling clusters of business to form in underdeveloped rural areas. In China, rural micro e-tailers began to emerge in 2009 on Taobao.com Marketplace. Owned by Alibaba, it is one of the largest online retail platforms in China. These clusters—“Taobao Villages”—spread fast, from just 3 in 2009 to 2,118 across 28 provinces in 2017. In 2017 490,000 shops were online. Although sales have been strongest in traditional goods such as apparel, furniture, shoes, luggage, leather goods, and auto accessories, sellers are diversifying their offerings to include high-tech goods such as drones.

Online work platforms are eliminating many of the geographical barriers previously associated with certain tasks. Bangladesh contributes 15 percent to the global labor pool online by means of its 650,000 freelance workers.23 Indiez, founded in 2016 in India, takes a team-based approach to online freelancing. The platform provides a remotely distributed community of talent—mainly from India, Southeast Asia, and Eastern Europe—that works together on tech projects for clients anywhere in the world. Clients include the pizza restaurant chain Domino’s India, as well as the Indian multinational conglomerate Aditya Birla Group. Wonderlabs in Indonesia follows a similar model.

Finally, technology is changing how people work and the terms under which they work. Instead of the once standard long-term contracts, digital technologies are giving rise to more short-term work, often via online work platforms. These so-called gigs make certain kinds of work more accessible on a more flexible basis. More widespread access to digital infrastructure—via laptops, tablets, and smartphones—provides an enabling environment in which on-demand services can thrive. Examples range from grocery delivery and driving services to sophisticated tasks such as accounting, editing, and music production. Asuqu in Nigeria connects creatives and other experts with businesses across Africa. Crew Pencil works in the South African movie industry. Tutorama, based in the Arab Republic of Egypt, connects students with local private tutors. In Russia, students work as Yandex drivers whenever they can fit it in to their university schedules. They identify peak hours in different locations to achieve the highest level of passenger turnover.

It is difficult to estimate the size of the gig economy. Where data exist, the numbers are still small. Data from Germany and the Netherlands indicate that only 0.4 percent of the labor force of those countries is active in the gig economy. Worldwide, the total freelancer population is estimated at around 84 million, or less than 3 percent of the global labor force of 3.5 billion.24 A person counted as a freelancer may also engage in traditional employment. In the United States, for example, more than two-thirds of the 57.3 million freelancers also hold a traditional job, using freelancing to supplement their income.25 The best estimate is that less than 0.5 percent of the active labor force participates in the gig economy globally, with less than 0.3 percent in developing countries.

Changes in the nature of work are in some ways more noticeable in advanced economies where technology is widespread and labor markets start from higher levels of formalization. However, emerging economies have been grappling with many of the same changes for decades. As noted earlier, informality persists on a vast scale in emerging economies—as high as 90 percent in some low- and middle-income countries—notwithstanding technological progress. With some notable exceptions in Eastern Europe, informality has been hard to tackle. In countries such as El Salvador, Morocco, and Tanzania only one out of five workers is in the formal sector. On average, two out of three workers in emerging economies are informal workers (figure 1.3).

The prevalence of informality predates the new millennium wave of technological change. Various programs for reducing informality, inspired by Hernando de Soto’s The Other Path: The Economic Answer to Terrorism (2002), have yielded limited progress. The reason is the onerous regulations, taxes, and social protection schemes that give businesses no incentive to grow.

Because recent technological developments are blurring the divide between formal and informal work, there is something of a convergence in the nature of work between advanced and emerging economies. Labor markets are becoming more fluid in advanced economies, while informality is persisting in emerging economies. Most of the challenges faced by short-term or temporary workers, even in advanced economies, are the same as those faced by workers in the informal sector. Self-employment, informal wage work with no written contracts or protections, and low-productivity jobs more generally are the norm in most of the developing world. These workers operate in a regulatory gray area, with most labor laws unclear on the roles and responsibilities of the employer versus the employee. This group of workers often lacks access to benefits. There are no pensions, no health or unemployment insurance schemes, and none of the protections provided to formal workers.

This type of convergence is not what was expected in the 21st century. Traditionally, economic development has been synonymous with formalization. This is reflected in the design of social protection systems and labor regulations. A formal wage employment contract is still the most common basis for the protections afforded by social insurance programs and by regulations such as those specifying a minimum wage or severance pay. Changes in the nature of work caused by technology shift the pattern of demanding workers’ benefits from employers to directly demanding welfare benefits from the state. These changes raise questions about the ongoing relevance of current labor laws.

A simple model of changing work

Will robots turn the old Luddite fears of machines replacing workers into reality? Will massive automation mean that the old path of prosperity-through-industrialization, once taken by China, Japan, and the United Kingdom, is closing? How can public policy ensure that the evolution of work produces a world that is both more prosperous and more equitable?26

High labor costs in relation to capital—beyond a certain level—push firms to automate production or to move jobs to lower-cost countries (figure 1.4). This reduction in costs is achieved explicitly within a firm or implicitly through competition within a market. The relative cost of labor, not income, is emphasized because countries may have labor costs that do not align with their income level. This is the case, for example, in countries where low levels of human capital render workers unproductive, reducing exporting potential, or in countries where regulations significantly raise labor costs for formal employers.

A response to globalization is a greater shift in jobs to developing country cities, thereby reducing the overall relative costs of labor (and shifting the curve in figure 1.4 leftward). Automation leads to less demand for manufacturing workers everywhere (shifting the curve downward). Automation also changes the overall relationship between industrial employment and labor costs because it occurs more quickly in locations with high labor costs, assuming the incentive to reduce labor costs trumps other differences between locations (changing the shape of the curves in figure 1.4 from left-skewed to right-skewed).

Keynes understood that employment in the traditional sectors, especially agriculture, would decline enormously in the 20th century, but he failed to anticipate the explosion of new products that 21st-century workers would produce and consume. Most important of all, he failed to foresee the vast service economy that would employ workers in most wealthy countries. Digital technologies are enabling firms to automate, replacing labor with machines in production, and to innovate, expanding the number of tasks and products. The future of work will be determined by the battle between automation and innovation (figure 1.5). In response to automation, employment in old sectors declines. In response to innovation, new sectors or tasks emerge. The overall future of employment depends on both. It also depends on the labor and skills intensity of the new sectors or tasks that emerge. These forces in turn affect wages.

For most of the last 40 years, human capital has served as a shield against automation, in part because machines are less adept at replicating more complex tasks. Low-skill and middle-skill workers have benefited less from technological change either because of higher susceptibility to automation or because of lower complementarities with technology.27

What is the result? Automation has disproportionately reduced the demand for less skilled workers, and the innovation process has generally favored the more educated. A big question is whether workers displaced by automation will have the required skills for new jobs created by innovation. This study focuses on the importance of human capital for the workforce of the future. Yet it is worth remembering that many innovations, such as Henry Ford’s assembly lines, increased the demand for less skilled workers, while others, such as quartz watches, disproportionately destroyed jobs for higher-skill workers.

Automation and innovation are largely the unexpected by-products of a single breakthrough, such as the advent of the Internet, or the result of more targeted investments by companies that are seeking to either reduce labor costs or increase profits in new markets. If public regulations limit innovation, employment is more likely to fall.

In the mid-20th century, automation in the form of dishwashers and washing machines revolutionized homemaking, enabling millions of women to work outside the household. Women often found jobs in the service economy, which grew by providing yet more products and services, from caffe lattes to financial planning, and enabling an even finer division of labor such as personal trainers and financial market traders. A major question for this century is whether more of these services will become tradable and whether service workers will locate in the same metropolitan area as their clients.

The battle between innovation and automation is raging not just in the U.S. and European rust belts. Even though low-wage countries may not invest in the development of labor-saving innovations, they import labor-saving ideas from advanced economies. In fact, the mechanization of agriculture in emerging economies represents the largest global shift in work. Cities in emerging countries must generate abundant new jobs to employ the farmers displaced by the industrialization of agriculture. The declining costs of transportation and connectivity (so-called globalization) enable these urban job markets to expand, as long as connectivity spreads more quickly than the automation of tradable goods production. So, although the growth of employment in emerging economies is supported by global value chains, automation may mean that African countries never experience mass industrialization.

The dramatic economic growth experienced by China, Japan, Korea, and Vietnam started with the fruits of globalization: manufacturing exports that competed effectively because of low labor costs. These countries chose to invest in infrastructure, special economic zones, and, above all, human capital, which generated a high-quality labor force connected to the outside world.

The transition of Shenzhen, China, from labor-intensive, low-cost manufacturing to high-skilled, technologically intense production illustrates the challenge that later industrializers are facing. They must compete not only with the high labor cost, capital-intensive producers of the wealthy West, but also with the moderate labor cost, technology-intensive producers of Asia and Eastern Europe. If robust global connections arrive too slowly in Africa, then industrialization may no longer be a plausible path to job creation. This threat strengthens the case for investing promptly in the precursors of globalization: education and transportation infrastructure.28

If African cities maintain the current model, employment will remain in the low-wage informal service sector. Changing the model depends significantly on investments in human capital (figure 1.6). In that case, Africa may urbanize as a services-producing economy, moving away from export earnings based on natural resources and agriculture.

Globalization increases the returns to human capital through higher labor productivity; some workers participate in export industries, and the shift of workers to those industries increases the demand for all kinds of labor (figure 1.6). This positive shift is meant to capture the positive experience of a poorer nation that has suddenly gained access to significant foreign direct investment. Of course, globalization may not always raise productivity across the board.

Likewise, the benefits of globalization will not accrue evenly. Globalization causes the variance in labor productivity to increase. Although productivity for subsistence farmers is low and relatively homogeneous, the returns to participating in a globalized economy are far more mixed. By investing strongly in raising the human capital of their citizens, governments increase their citizens’ chances of success in global markets.

The vertical lines in figure 1.6 denote the minimum productivity level at which firms find it optimal to employ workers formally before the move toward globalization. A minimum wage, required benefits, and other taxes and regulations ensure that informality is appealing for all but the most productive workers before the economy grows. If regulations remained constant, globalization and automation would in many cases pull more workers into the formal sector by increasing their productivity. Yet this formal employment effect may be reduced if development prompts countries to impose more requirements on firms. Globalization raises incomes, but it may not do much to reduce informality if regulatory aspirations increase along with global connections. Indeed, informality could even rise if globalization sufficiently increases regulation.

Finally, policy makers have to think about risk management because of the predominance of informality in developing countries and the higher uncertainty associated with the changing nature of work. The large continuing presence of a vast informal service sector challenges risk management systems that function through employers. Financing pensions and other forms of insurance through payroll taxes levied on formal workers does little good if these workers represent only a small share of the workforce. Strong requirements also deter formalization.

This study emphasizes the importance for social inclusion for all workers regardless of how or where they work. Governments could try to strengthen social protection and reduce inequality through requirements or subsidies for employer-provided support such as a minimum wage, employer-provided health care, or protection against dismissal. Alternatively, governments could pursue the same goals through direct, state-provided support in the form of social assistance programs and subsidized universal social insurance or public jobs for, say, community health workers.

Both types of social policy promote equity. And both have costs. From the state’s perspective, different combinations of regulations and public aid generate the same level of equity. Direct public aid generates implementation costs through waste and higher tax rates. Employer requirements deter hiring and could, if too stringent, raise inequity by increasing the share of workers who are either unemployed or in the informal sector.

Many developing countries initially chose to redistribute primarily through labor market regulations because the costs of distorting labor markets were low and the public capacity for social programs was limited. If automation pushes up the cost of distorting labor markets, and development improves the efficacy of the public sector, government should move away from regulation-based redistribution to direct social welfare support.

The future world of work is uncertain. Innovation may outpace automation. Globalization may move quickly enough that industrialization allows Africa to grow and prosper. Yet, given the considerable uncertainty about the future of employment, governments should rethink policies that deter job creation, and emphasize policies that protect the vulnerable while still encouraging employment.

Notes

1. Many Internet businesses or services use a platform or “two-sided market” model. The platforms match buyers with sellers or a service user with a provider. See World Bank (2016).

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