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date: 05 July 2022

(p. 1) Introduction: Structural Transformation—Overcoming the Curse of Destiny

(p. 1) Introduction

Structural Transformation—Overcoming the Curse of Destiny

Some words, concepts, and phrases are unlucky throughout their history. They struggle more than others to establish their true meanings, and to claim their fate. ‘Structural transformation’ or ‘structural change’, used interchangeably in this volume, is one of these hapless phrases that have suffered decades of benign neglect, discontent, and outright abuse, before regaining glory and yet falling again into incomprehension and suspicion. Such a trajectory is puzzling, for structural transformation, which refers to the movement of a country’s productive resources (natural resources, land, capital, labour, and know-how) from low-productivity to high-productivity economic activities, is arguably the single most significant concept and social goal in the global quest for prosperity and world peace. As noted by some researchers decades ago, ‘[I]t is impossible to attain high rates of growth of per capita or per worker product without commensurate substantial shifts in the shares of various sectors’ (Kuznets 1979: 130).

Structural transformation is the mysterious process through which societies push (or incentivize their productive resources) into higher-performing and dynamically-growing sectors, industries, and branches.1 Once ignited and sustained, this process can generate both static and dynamic economic benefits to human societies. Static gains are usually defined as the rise in economy-wide labour productivity, as workers in a given country or region are increasingly employed in more productive sectors. Dynamic (p. 2) gains, which follow over time, accrue from skill upgrading and the positive externalities resulting from workers having access to better technologies and accumulating capabilities (McMillan and Rodrik 2011). As noted by an UNCTAD report, ‘Structural transformation can be particularly beneficial for developing countries because their structural heterogeneity—that is, the combination of significant inter-sectoral productivity gaps in which high-productivity activities are few and isolated from the rest of the economy—slows down their development’ (UNCTAD 2017).

Before the First Industrial Revolution, there was little growth in the world economy and the income gap between countries was extremely small. For example, even in 1820, the between-country income differences represented less than 15 per cent of income equality across people in the world, whereas the between-country share rose to well over half of global inequality by 1950, and the richest countries’ per capita income was only just less than four times higher than the poorest (Lin and Rosenblatt 2012). The most recent period of world economic history (roughly since the mid-1990s) has offered a sharp reversal from a pattern of divergence to convergence—particularly for a few developing countries such as China, Vietnam, or Indonesia. The latter phenomenon is being fostered by increasing economic ties among developing countries, and on the intellectual scale, increased learning and knowledge-sharing opportunities among the developing countries. The patterns and dynamics of global economic progress have been transformed in recent years across many dimensions. While economic divergence is still the main reality, the experience of the handful of success stories, and the emergence of the multi-polar growth world justify the rethinking of development economics and policy. This historical record provides a challenge for economists attempting to fully understand the success of the rising economic powers and re-think the traditional views on economic development. Three major questions emerge: (i) Why was there so much divergence during the twentieth century? (ii) Why has the pattern changed recently and can it be sustained? (iii) What is the role of development institutions in facilitating sustained convergence?

This introductory chapter briefly chronicles and assesses the idea of structural economic transformation. It starts with a brief discussion of some of the pervasive narratives of despair, which marked human societies everywhere for centuries. It then highlights the shift to new economic possibilities which occurred after the First Industrial Revolution and the Enlightenment period—and were reflected in the debate on the very idea of economic convergence among nations. The chapter then analyses the determinants and mechanics of structural change and gets into the ‘black box’ to examine the role of industrialization, defined more broadly and across the three traditional sectors (agriculture, industry, and services). The topics of deindustrialization, automation, and the future of work are then discussed, as they relate to structural transformation in times of the Fourth Industrial Revolution. Because Africa is the region of the world where structural change through economic diversification into the most productive sectors and industries has been occurring at the slowest pace, the chapter includes a section on meta-economic issues there. A summary of the contents of this volume concludes.

(p. 3) Transformations: Narratives of Despair

Economists, philosophers, artists, and writers have always enjoyed predicting the future. Their conjectures have tended to be rather pessimistic, perhaps because doom and gloom tend to make for better stories. Homer famously suggested God may have afflicted humans with misfortune so that future generations would have tales to sing about. In the period known in the Western world as the Middle Ages, a time of pervasive poverty and violence, many popular works of art and fiction offered dark chronicles of what life was about, and the almost teleological dim fate that lay ahead for humans. Dante’s Divine Comedy, the most famous fourteenth-century poem on sin and redemption, was still mainly about the travails of human life. Its sober vision of mankind’s eternal fate offered no perspective or prescription for generating economic prosperity on earth.

Even during the Renaissance, known in Western history as a period of rejuvenation, enthusiasm, and experimentation, branded as a period marked by extraordinary levels of optimism, a lot of powerful literature and works of art were also often chronicles of economic misery, emotional suffering, deep despair, collective self-doubt, and habituation to pain and evil. Leonardo Da Vinci’s views illustrate this paradox: he could paint both the Mona Lisa, an unsettling portrait of a Florentine woman with an enigmatic expression, elegant and aloof, and The Last Supper, his visual interpretation of Jesus Christ’s last night on earth, foretelling his unavoidable betrayal by one of his disciples——the painting specifically depicts the moment after Christ dropped the bombshell that one of his devotees around the table would betray him before sunrise, and all twelve of them react to the stunning news with shock, horror, and anger. Yes, even in times of optimism, influential artistic works tended to recount stories which epitomize the sad fate of men.

Throughout the Enlightenment, economists did not stand out as voicing the democratization of economic well-being—what may be termed social positivism. They were not overly preoccupied with generating wealth and prosperity for the whole of society—not just the ruling classes favoured by mercantilist theorists. Fighting poverty, which was prevalent for millennia, and finding innovative ways and policies for improving the standard of living and the quality of life of the bottom deciles were not the focus of their work. Collective well-being, redistribution, and equity as the main public policy goal did not seem to be important topics of research. In that context, Adam Smith’s (1776) vigorous criticism of mercantilism and his belief in the need for and possibility of inquiring into the nature and causes of the wealth of nations, and for the blueprint for a just society that concerns itself with the well-being its least well-off members, sounds messianic, if not naïve. But Smith was not an economist: he was a moral philosopher.

True, Smith’s masterpiece was preceded by the inspirational ethics of David Hume and paved the way to reflections by John Stuart Mill and David Ricardo, who seriously (p. 4) considered the need for societies to set human well-being as an important goal. But despite its richness and brilliance, Hume’s work was dominated by his taste for empiricism and his scepticism. Mill’s and Ricardo’s brilliance did not lead them to focus on the common economic good or the plight of the poor. Great economists who carried the torch after them (from F. Y. Edgeworth to David Riccardo, Alfred Marshall or notable members of the Austrian School such as Carl Menger, Eugen Böhm Ritter von Bawerk, Friedrich Hayek, or Ludwig von Mises), developed new intellectual frameworks for increasing production and generating wealth but focused little on the issues of distribution. This seems even more surprising that during their time, the Western world was experiencing major sociopolitical transformations often fueled by mass poverty, exclusion, and sociopolitical conflicts. On purely moral grounds, famous literary works such as Victor Hugo’s Les misérables or Emile Zola’s Germinal were well ahead of the sophisticated theories produced by economists from various political and philosophical backgrounds.

The veil of naturalist indifference about mass poverty and social change, which had covered much of the intellectual landscape for centuries, started to be lifted with the rise of Marxism, which brought the desire for economic change centre stage. Still, in the first half of the twentieth century, a period of major political transformations, social upheavals, and international tensions—culminating in two ignominious World Wars—the general intellectual mood was dominated by narratives of despair. No wonder that the post-World War II period, which witnessed the emergence and rise of macroeconomics as a discipline, still largely left the issues of mass poverty and income distribution on the fringe. Even the thinkers who conceptualized social transformations tended to do so in the darkest and most pessimistic terms. Orwell’s iconic 1984 is an illustration of such negative and pessimistic progressivism.

Why did economic pessimism remain so well entrenched for so long? And why did economists ignore issues of collective well-being even as some of them studied the creation of national wealth through trade and finance? Looking at human history from an economic perspective, one can understand this long benign neglect: the potential for radical, transformational economic changes just seemed too remote and too improbable. For thousands of years indeed, there was little growth in the world economy and the income gap between countries was extremely small. Data compiled by Maddison (1982) shows that for some 1,400 years, the entire world was poor. For several centuries, income per capita in the city known today as Abidjan was identical to income per capita in the cities known today as Douala, London, Paris, Washington, Mexico, Tokyo, or Beijing. While there were a few relatively rich people in each of these places (the so-called aristocratic classes), most people everywhere on earth were poor. The quality of life then, even for the rich people, was bad: they died early of diseases that can now be prevented by a simple pill or a vaccine, and their life expectancy was very low.

During the period known as Agrarianism (500–1500), estimates of what later became gross domestic product (GDP) grew by only 0.1 per cent on average—the same rate as the world’s population. Things improved marginally in the next couple of (p. 5) centuries (1500–1700) when the world recorded an annual GDP growth rate of 0.4 per cent. Economies were largely based on agriculture and scientific progress was mainly divorced from technological innovation in production (Lin 1995). Agricultural productivity was also similar across nations and, as a result, the largest poles of economic production were in fact the largest population centres. China and India together contributed about half of world GDP during the seventeenth and eighteenth centuries.

Then, something quite dramatic happened in the eighteenth century, which brought prosperity to some places and abruptly changed the course of human history: the Industrial Revolution. Scientific progress began to be applied to the means of production as machines were developed that both increased productivity, and also dramatically reduced transportation costs. This created the possibility for the countries that developed those technologies, or those that adapted the technologies first, to grow much faster than less technologically advanced countries.

The Industrial Revolution marked a dramatic turning point in the economic progress of nations. Technological innovation introduced new tools that created the potential for a dramatic increase in productivity and living standards. Whereas per capita GDP growth worldwide was negligible in 1500–1820, it was about 1.5 per cent per annum following 1820. During the nineteenth century, several technological leaders and early adapters leapt ahead of the rest of the world, while others lagged behind.

The result of this process was that (at least prior to the year 2000) the global economy was dominated by the few industrialized economies that existed in the world, and most of these few economies had become industrialized either as leaders or earlier followers of the nineteenth-century Industrial Revolution. There was a major caveat: Historical data dramatically reveal the divergent pattern of growth across country groupings: in the late nineteenth century, the Western European countries and their colonial ‘offshoots’ began to experience an historic take-off in incomes per capita. This was later matched by Japan in the middle of the twentieth century. The world economy was driven by several large Western European countries (Germany, France, Italy, the United Kingdom) and Anglophone-offshoots (Australia, New Zealand, the United States, and Canada), plus Japan. Many other countries, including the former Soviet Union, could rise to middle-income status and experience levels of average economic welfare that far surpassed prior centuries; however, their standard of living still lagged substantially behind the leading countries. In sum, the global economy was dominated by the so-called G7. During the twentieth century, the G7 maintained a large and stable share of global GDP.

The twentieth century could have been a period in which technology spread across the entire world—allowing lagging economies to catch up with advanced economies. The predominant neo-classical paradigm in economic thinking suggested that this would be the case. Economic convergence might have been achieved through trade and capital flows based upon continued progress in transportation and communication technology. In principle, one would expect, and certainly hope, that the poorer countries in the world could catch up with the richer countries in the world. Instead, the twentieth century was an unfortunate period of continued and accelerated (p. 6) divergence in living standards. Few countries have experienced convergence on a sustained basis. One approach to measuring relative progress is to look at per capita GDP relative to the United States, which has been the symbol of advanced industrialized countries since World War II. Pritchett (1997) analysed global economic performance during the twentieth century and concluded that it was marked by ‘Divergence, Big Time’.

Lin and Rosenblatt’s (2012) historical overview of both the evolution of the economic performance of the developing world and the evolution of economic thought on development policy is by and large a sobering story. They confirm that the twentieth century actually accentuated divergence between high-income countries and the developing world, with only a limited number (less than 10 per cent of the economies in the world) managing to progress out of lower- or middle-income status to high-income status. Persistently, over 80 per cent of the countries in the world have GDP per capita levels that are half or less than half of the level in the United States.

A few countries reached high-income status before falling back for a prolonged period into middle-income status. Argentina is a well-known example. In the forty-three years leading up to 1914, its GDP grew at an annual rate of 6 per cent, the fastest recorded in the world. It ranked among the ten richest in the world, ahead of Germany, France, or Italy. Its income per capita was 92 per cent of the average of the world’s sixteen richest economies. A century later, the income figure was 43 per cent of those same sixteen rich economies, trailing Chile or Uruguay. Russia is also an intriguing case: it was considered a middle-income country for some 200 years.

Many African countries went from lower middle-income status at independence around 1960 to low-income in the 1980s. Since then, some have climbed back up to middle-income status. With a few exceptions (typically oil rich nations), the small number of developing economies that have recorded a substantial increase in income per capita are generally located in East Asia. They achieved sustained growth through rapid industrialization strategies underpinned by a comparative advantage in export dynamism and they also benefited enormously from the facilitating role of the state.

The great divergence seen during the twentieth century may have been due, in part, to an interruption in trade and capital flows during the World Wars and the inter-war Great Depression that marked the first half of the twentieth century. Protectionism also persisted in many countries following World War II. It was only with the Uruguay Round of negotiations in the 1980s, leading to the eventual establishment of the World Trade Organization in 1995, that a clear institutionalized path towards opening up trade was established. Meanwhile, technological progress in communications and transport—but especially communications—facilitated the acceleration of global trade and capital flows in the last quarter of the twentieth century.

Fortunately, the twenty-first century global economic landscape provides new possibilities for countries to catch up. While a general economic divergence is still the dominant story, there has been strong growth in the developing world, especially in several large developing countries, such as Brazil, China, India, Indonesia, and the Russian Federation. In some cases—most notably China and India—the high growth (p. 7) period extends back some twenty or thirty years. In addition, there are numerous other countries that are taking advantage of growing trade and financial links—both with developed and developing countries—to accelerate economic growth. The global economy now exhibits a multi-polar system, with large developing countries leading the way as the new and most dynamic growth poles.

In sum, there are opportunities out there for social and economic transformations, even in the most unlikely places (Lin and Monga 2017). Not too long ago, most countries in the world were poor. Yet some have managed to break out of the poverty trap, begin a sustained dynamic growth and become middle-income or even high-income economies, sometimes in a matter of just one or two generations. The governments in the small group of successful countries where positive change took place over the past century must have drawn valuable policy lessons or at least inspiration from the successful countries before them in the formulation of policies that unleashed their growth potentials. For economists engaged in research on poverty reduction, perhaps the biggest questions should consider why and how some countries succeeded whilst others failed to make it out of poverty. The countries that remain trapped in poverty might then be able to draw policy insights from those successful experiences and so avoid making mistakes, successfully initiating sustained, dynamic growth in their own countries.

What did this elite group of successful countries do? How did they transform their economies and what lessons can the still lagging economies of the world draw from such experiences? These are perhaps the most important question in economics today.

The Signifying Monkeys—What Drives Structural Change

India’s modern mythology is rich with delicious parables which help make important points. A popular one is that of a poor nomadic merchant who travelled from one village to the other across the country, selling hats. On the road one evening, he was so exhausted that he fell asleep in an open field. On waking he was realized that his load of hats had disappeared. A group of monkeys sitting on neighbouring trees had picked up the hats and were wearing them and visibly mocking him from above. The merchant could not climb the trees to chase the monkeys. Desperate, he angrily threw his own hat on the ground. The monkeys observing him were so amused by his nervous gesture that they did the same: they all imitated him, took off the hats they were wearing and threw them on the ground. The hat seller couldn’t be happier: pleasantly surprised by the unexpected turn of events, he quickly collected his goods and continued his journey. Happy ending.

The story does not end there.

Some forty years later, his grandson who has become a hat seller too finds himself on the same route, going from one small town to the other to sell his goods. A similar (p. 8) problem occurs: one day, as he is exhausted travelling, he drops his pile of hats and falls asleep. When he wakes up all the hats are gone. He looks up and, lo and behold, sees a group of monkeys wearing his hats, chanting and mocking him, having a good time. The hat seller does not panic. Remembering the lessons from his grandfather’s story, he purposely throws his own hat on the ground with the expectation that the monkeys will imitate him. To his surprise, nothing happens. The monkeys just stare at him. Then, one monkey comes down the tree, picks up the hat thrown on the ground, slaps the man on the cheek, and asks him the following question: ‘You think only you have a grandfather?’

The story of the Indian ‘signifying monkeys’,2 told by Basu (2010), provides a game-theoretic metaphor for the need to take intergenerational learning and knowledge seriously. It also stresses the importance of understanding the many ways in which people learn and use knowledge—and warn about the risks of underestimating the ability to process information by other actors in the game. It is therefore a useful tale as we reflect on the reasons why societies evolved from being poor for centuries to generating prosperity for large sections of their populations.

Studies about the Industrial Revolution—the event that changed the economic history of the world—have sparked some challenging questions, which eventually pointed to the importance of learning and knowledge: How did it occur (or manifested itself so obviously) at a particular time and place? Why did it take place in the Western world even though many other regions of the planet had recorded the rise and fall of great civilizations before then? Were some countries in the Western world blessed with enormous luck while those in Asia, Africa, or Latin America were cursed with poverty and sentenced to eternal poverty? Was it an unplanned, magical and random process? What major factors stimulated it? What was the role of past knowledge, perhaps transmitted silently across generations as in the case of the monkeys’ story?

At first glance, there seem to be four interconnected sources of the post-nineteenth century growth acceleration (Fardoust 2006), although the sequencing and relative importance for each of them has long been the subject of debate: (i) improvements in transportation and communication technologies; (ii), trade liberalization and the intellectual doctrine of trade, as articulated by the likes of Adam Smith and David Ricardo; (iii) the peacefulness and stability (relative to earlier times) in Europe, where the likes of Metternich, Bismarck, and Castlereagh maintained the Concert of Europe and Britain assured a balance of power in its Pax Britannica; and (iv) an increase in ‘equity’ in European institutions beginning in the late seventeenth century and continuing through the early twentieth century.

Economic historians and development theorists have struggled to explain the mystery of the Industrial Revolution and decipher its drivers and dynamics. The first set of possible explanations has centred on materialistic causes. Early economists such as Adam Smith and Thomas Malthus thought, erroneously, that the determinants of the (p. 9) prosperity of nations were to be found in physical objects and capital. Their analyses of the process of wealth creation was therefore dominated by notions of scarcity. For a long while, growth theories focused on how an economy transforms scarce resources like iron ore into machinery and so forth. It was all about capital and labour, with their combination leading to diminishing returns and to the steady state. Little attention was devoted to the underlying process of technological change (or to the possibility of increasing returns). A country or region or firm had a plot of land or an amount of capital that could be used only by them and there was a finite number of those basic sources of wealth. Some researchers have suggested that a combination of cheap energy costs at the time and high wages incentivized business people to devote more resources into technological innovation.

Economists eventually recognized that other factors besides physical objects were important (things like institutions, rules, or recipes for how to rearrange physical objects and make them more valuable). A second set of explanations of the causes of the Industrial Revolution shed light on the benefits of colonial resource extraction, or on the social and political institutions that encouraged entrepreneurship. But researchers simply did not develop the rigorous analytical tools to integrate them into mainstream growth theory. The easy solution was to lump together all the possible elements other than capital and labour as ‘technological change’, and to treat them as exogenous—coming from outside the economic system.

Then came John Maynard Keynes, who may not have heard the Indian monkeys’ story but had the right intuition when he stressed the importance of ideas in the very last pages of his General Theory:

the ideas of economists and political philosophers, both when they are right and when they are wrong, are more powerful than is commonly understood. Indeed, the world is ruled by little else. Practical men, who believe themselves to be quite exempt from any intellectual influences, are usually the slaves of some defunct economist. Madmen in authority, who hear voices in the air, are distilling their frenzy from some academic scribbler of a few years back.…It is ideas, not vested interests, which are dangerous for good or evil.

(Keynes 1936: 383)

The traditional arguments about capital, labour, and institutions, sound convincing but they are, at best, insufficient. Material and political conditions alone could not have done it. The Industrial Revolution was primarily the result of ideas. People and business leaders found innovative ways of adopting technology and making it commercially viable so that it could boost productivity. Some great inventions had been sitting on shelves for many decades. It took some wise and very practical people to design the institutions that would create the appropriate incentives and conditions for their broader use by firms and households, to bring benefits and rewards to all stakeholders, and to stimulate economic growth.

As Azariadis and Stachurski (2005) point out, ‘While the scientific achievements of the ancient Mediterranean civilizations and China were remarkable, in general there was little attempt to apply science to the economic problems of the peasants. Scientists (p. 10) and practical people had only limited interaction.’ Lin (1995) argues that the transition from innovation based on the experiences of artisan/farmers in the pre-Industrial Revolution period to innovation based on controlled experiments guided by science after the Industrial Revolution was the key factor. Societal incentives in pre-modern China did not favour the move toward the human capital accumulation needed for the new system of innovation. In fact, the significant waves of invention that occurred in China and the Islamic world prior to the Industrial Revolution did not snowball into a world-changing industrial revolution. Great inventions are rare and often potentially transformative for nations. But making them widely accepted and used by economic agents throughout society is really just the conditions for them to positively impact productivity and growth and to generate prosperity.

McCloskey, who built on the analytical insights from Keynes, devoted a trilogy to refute these materialistic explanations (2006, 2010, and 2016). Slavery, imperialism, investment, coal, foreign trade, property rights, climate, genetics, or education, were not the root causes of the Industrial Revolution. Instead, he stresses the importance of the immaterial causes, including what he calls ‘bourgeois equality’—the idea that ordinary economic agents from all walks of life were emboldened to try innovative ways of doing things. It follows that the important questions are not just how innovations come about, but how they are adopted and translated into everyday improvements in living standards. Examples abound of great inventions that never turned out to become real innovations—or required time to do so. A well-known example is that of electricity, a discovery that dates to at least the late nineteenth century. Yet it took many decades before it could be used widely by firms and households and before researchers could estimate resulting improvements in the national productivity figures (David 1990). Besides designing and implementing the appropriate economic, financial, and marketing strategies and incentive systems to ensure the diffusion of innovations, nations also must undergo some social changes that allow for their large-scale adoption. Human history shows that such processes are not obvious or may not occur spontaneously.

In his search for the specific conditions that turned the inventions of the late eighteenth and early nineteenth centuries into sustained, modern economic growth in Western Europe, Mokyr (2016) reexamines how the Enlightenment also created the right conditions for the emergence of a ‘Republic of Letters’, and sustained new forms of public debate and innovation that resembled what is now called ‘open science’. In Mokyr’s words, a culture of growth emerged that made everything possible during the Industrial Revolution. Thanks to that environment, knowledge could be converted from abstract scientific insights into practical technological know-how and readily useable common tools and processes. This process of a ‘democratization of knowledge’ often occurred simply because leading scientists and thinkers corresponded with their counterparts across Europe—a continent whose political fragmentation led ambitious rulers to compete in attracting the most prominent intellectual stars to their own territories. As Coyle (2014) puts it, ‘Competition among states to attract the best craftsmen, engineers and scientists spread knowledge, as did publishers vying for (p. 11) new markets. This culture of public science, which had great prestige, paved the way for entrepreneurs to begin turning ideas into industrialisation and growth.’

Modern growth theorists such as Robert Solow and Joseph Schumpeter have indeed demonstrated quite convincingly that countries move from being low- to middle- and high-income not by accumulating more capital but through technological progress—that is, by learning how to do things better. In a world where labour and capital are quite mobile, the main explanation of the economic differences between rich and poor countries is not money: it is the difference in their ability to generate or borrow and use the best ideas available. ‘While some of the productivity increase reflects the impact of dramatic discoveries, much of it has been due to small, incremental changes. And if that is the case, it makes sense to focus attention on how societies learn, and what can be done to promote learning—including learning how to learn’ (Stiglitz and Greenwald 2014). In fact, formerly poor countries—especially those in East Asia—that have been able to converge toward the incomes of advanced economies have generally done so through learning.

Economic development is therefore the process of technological diffusion and industrial upgrading. It involves making knowledge available to the largest number possible of economic agents and fostering constant learning. Then, the question becomes how good ideas emerge in any society, how they spread, are sorted out and validated, used, and shared widely enough to create a demand for them. Knowledge can be accumulated by some economic agents while others miss out. So, the production or underproduction of knowledge compounds over time, creating either positive or negative externalities for economic development. Kenneth Arrow’s work on ‘learning by doing’ showed, once learning starts, that it can be built dynamically and at scale. The dynamic nature and effects of learning can then far outweigh any short-term static losses in efficiency. Some economic sectors—manufacturing, above all—have greater learning spillovers than others. That justifies shaping policies to promote them over others, which would not occur randomly in any country environment.

Yet knowledge is different from conventional goods. It is, in a sense, a public good. It is not excludable: people cannot be excluded from using it once it comes into being. Nor is it rivalrous: one person’s consumption of knowledge does not preclude another person’s consuming it. So, the marginal cost for another person or firm to enjoy the benefits of knowledge—beyond the cost of transmission—is zero. But markets—anywhere, whether in developed or developing countries—are not efficient at producing and distributing public goods.

Producing, acquiring, sharing, and diffusing knowledge—through complex processes of social learning—make it the public good that is subject to the greatest market failures. In all societies, especially in low-income countries, knowledge brings many externalities, as gaps in production and acquisition by economic agents produce gaps between social and private returns. Producing knowledge is costly. Because individuals and firms do not always capture the full returns from their investments in learning (when they can afford such investments), knowledge is generally underproduced.

The world has changed many times since the (first) Industrial Revolution. There is much to learn from the experiences of the few developing economies that have (p. 12) managed to break out of the vicious cycle of poverty. Their stories, development strategies, and policy frameworks offer good news for other developing countries. In an increasingly globalized world economy where capital, labour, technology, and ideas are very mobile, it is still possible for countries at very low-income levels to borrow relevant knowledge from more advanced economies and use it at minimum costs to enrich their analytical and policy frameworks. But this process cannot be spontaneous or left just to market forces. Institutions must be in place to create incentives and to stimulate the process of learning across firms (even as they compete against each other) and across industries. International development agencies whose primary role is to facilitate the production and sharing of global public goods are best placed to stimulate and facilitate the process of sharing clever ideas, to foster the production and distribution of ideas in African countries, and to highlight the importance of meta-ideas (‘an idea that helps us get better at discovering ideas,’ as Paul Romer puts it).

Debating Structural Change Processes: How they Occur

In their long quest to convert their discipline from a conjectural field of the social sciences into a hard science, economists have generally shied away from topics and issues that seemed difficult to grasp with rigorous, logical, and formal analytical tools. With the emergence and gradual dominance of mathematical models in economics during the second half of the twentieth century, some topics perceived as hard to model suffered from benign neglect. Krugman (1995) observed that this methodological shift, which caught some researchers off-guard, might have been the main reason for the reluctance of mainstream economists, for several decades, to tackle the important but challenging issues of development. Krugman’s conjecture may also explain the ups and downs of research on structural transformation, and the general intellectual shyness that kept it away from much of economics roughly from the 1960s to the late 1980s.

Knowledge has emerged as the main driver of sustained structural transformation. Oxford dictionaries define it broadly as ‘facts, information, and skills acquired through experience or education; the theoretical or practical understanding of a subject’. Knowledge is also defined tautologically as the ‘sum of what is known’. But what exactly is structural transformation, and how has the economic research devoted to it evolved in recent decades?

The general idea underlying the process has remained straightforward: structural transformation has always been understood as the process whereby the resources (labour, capital, and technology) in any economy are shifted out of traditional agriculture and other low-productivity primary activities into ‘modern’, higher productivity sectors (including non-traditional agriculture). This shift of resources (transformation), and the expansion of modern sectors, have been at the core of the sustained (p. 13) productivity gains that characterize economic development. Indeed, there is ample consensus that rising productivity accounts for the bulk of long-term growth. Sustained economic growth is essentially about structural and technological upgrading.

The specific elements underpinning structural transformation processes are difficult to identify and measure consistently. In fact, the economic notion of ‘structures’3 has evolved over time to cover both macro and micro issues, and to hold different meanings (Lin and Monga 2013). In the 1940s, a first wave of researchers working on low-income countries conceived development to be an interrelated set of long-run processes. Early development economists4 borrowed the notion of ‘structures’ from other social scientists and used it to design a first set of theories for growth and prosperity. While numerous variants of early economic structuralism5 can be traced to a very diverse body of work that spans over a century (from Karl Marx, David Ricardo, and Keynes to Michal Kalecki, Joan Robinson, Richard Nelson, and Sidney Winter), the fundamental assumption of all its various schools of thought is that ‘an economy’s institutions and distributional relationships across its productive sectors and social groups play essential roles in determining macro behavior’ (Taylor 2004: 1).

Early structuralists argued that due to structural rigidities and coordination problems in developing country markets, modern heavy industries were unable to develop spontaneously there. They suggested that the virtuous circle of development essentially depended on the interaction between economies of scale at the level of individual firms and the size of the market. Specifically, they assumed that modern methods of production could only be made more productive than traditional ones if the market were large enough for their productivity edge to compensate for the necessity of paying higher wages. Yet the size of the market itself depended on the extent to which these modern techniques were adopted. Therefore, if the modernization process could be started on a very large scale, then the process of economic development would be (p. 14) self-reinforcing and self-sustaining. If not, countries would be trapped into poverty indefinitely (Rosenstein-Rodan 1943).

The focus of the first wave of economic structuralism was therefore not on knowledge and the transfer of ideas but rather on structural change in production structure and on economy-wide phenomena such as agricultural transformation, industrialization, urbanization, and ‘modernization’. Early structuralists identified economic activities of a very different nature that existed side by side in the ‘periphery’ (developing countries), with an export sector of relatively high productivity of labour, and a subsistence agricultural sector of very low productivity. They hypothesized that poor economies had to specialize in the production of a few commodities whose exploitation could not generate any forward or backward linkages. They conjectured that poor economies were trapped in an external disequilibrium and could only occupy a marginal space on the international scene (especially given the long-term trend of declining terms of trade). As a result, they argued, these peripheral economies would not undergo the kind of transformation process that leads to modernization and prosperity. Leading that group, Kuznets (1966) studied the genesis and patterns of evolution of modern economic growth in high-income countries and approached structural analysis mainly through the lens of sectoral changes—that is, the evolution overtime of the relative contributions of agriculture, industry, and services to gross domestic product (Syrquin 1988).

A second wave of development thinking dominated policy making in low-income countries in the 1980s and 1990s and tackled structural analysis only indirectly. Economists in that group approached structural change almost inadvertently through a broad examination of the general functioning of economies, their markets, institutions, mechanisms for allocating resources, regulatory and incentives systems, etc. The proponents of the ‘stuctural’ adjustment programmes implemented in many developing countries viewed the restoration of external and domestic balances as an essential precondition for launching the process of economic transformation and change. Throughout these two major waves of research, there was no consensus among researchers on its key features into the increasingly formal models of mainstream economic theory. Moreover, the definition and scope of structural transformation have been gradually broadened, making it even more challenging for economists to account for it consistently with the rigorous tools of mathematics.

The dominant framework used to study the growth in output associated with the development process has been the one-sector neo-classical model, also used for as the basis for development accounting exercises. Under some assumptions, the model predicts a balanced growth path, which is viewed as providing a good description of the long-run behaviour of advanced economies. Despite its elegance and simplicity, the one-sector model typically only describes static, repetitive features of a balanced growth path in which economies become richer by doing the same things, with output, consumption, investment, or the capital stock all growing at the same constant rate, and with the interest rate and factor shares held constant while the real wage also grows at the same rate as output (the so-called Kaldor Facts). Yet the balanced growth path is (p. 15) not the story of most economies. Thus, the need to build models that simultaneously generate outcomes that mimic balanced growth at the aggregate level while also generating structural transformation.

A third and more recent wave of the development literature has sought to refine structural analysis.6 At the theoretical level, economists have developed multi-sector extensions of the one-sector growth model and made them consistent with the new theories of structural transformation (Ngai and Pissarides 2007; Herrendorf at al. 2014). They have also focused on building models that can quantitatively account for the properties of structural transformation and at the same time assess the importance of various economic mechanisms. The quest to the standard three-sector focus is felt more acutely in the case of advanced economies, which are increasingly dominated by distinct types of services; this constantly changing structure makes it necessary to disaggregate services. It has been noted, for example, that education and health care are very different activities than construction, in that they both represent an investment and tend to use very different skill intensities for the labour that they employ. Authors such as Jorgenson and Timmer (2011) and Duarte and Restuccia (2016) have pioneered work in this direction.

The third wave of development thinking aims at reexamining the importance of knowledge in the process of structural transformation. Its main theoretical foundations can be found in a large corpus of interrelated topics of economic knowledge that includes: (i) the economics of information; (ii) the economics of ideas and diffusion of knowledge; (iii) the problem of agglomeration; and, perhaps most important, (iv) the problems of coordination and externalities.

Stiglitz, who pioneered the economics of information, explained in his Nobel lecture how his encounter with developing country issues forced him to reassess his own views: ‘My first visits to the developing world in 1967, and a more extensive stay in Kenya in 1969, made an indelible impression on me. Models of perfect markets, as badly flawed as they might seem for Europe or America, seemed truly inappropriate for these countries. But while many of the key assumptions that went into the competitive equilibrium model seemed not to fit these economies well, the ones that attracted my attention was the imperfection of information, the absence of markets, and the pervasiveness and persistence of seeming dysfunctional institutions’ (Stiglitz 2001). It was not just the discrepancies between the standard neo-classical competitive model and its predictions that were being questioned. The model was not robust—even slight departures from the underlying assumption of perfect information had major analytical and policy consequences. In many areas of public policy (such as education, wage determination), the notion that had underlain much of traditional competitive equilibrium analysis—that markets had to clear—was simply not true if information were imperfect.

(p. 16) Since the nineteenth century, the most dominant idea in mainstream economics, which provided both the rationale for the reliance on free markets, and the belief that issues of distribution can be separated from issues of efficiency, was that competitive economies lead, as if by an invisible hand, to a (Pareto) efficient allocation of resources, and that every Pareto efficient resource allocation can be achieved through a competitive mechanism—provided only that the appropriate lump sum redistributions are undertaken. That big idea, still the fundamental theorem of welfare economics, also allowed the economist the freedom to push for reforms which increase efficiency, regardless of their seeming impact on distribution. As Stiglitz (2001) noted, ‘the economics of information showed that neither of these results was, in general, true’. Moreover, asymmetries of information have been shown to be related to absent or imperfect markets. They help explain why markets for used cars—as famously shown by Akerlof (1970)—or for credit or labour tend to work imperfectly. Information imperfections are pervasive in the economy and neither sustained economic growth nor structural change is possible without a reliable mechanism to address them (Greenwald and Stiglitz 1986). The fact that when there are asymmetries of information, markets are not, in general, constrained Pareto efficient implies there is a potentially vital role for government (Stiglitz 1997).

That insight also opens up an avenue to discuss the economics of ideas and diffusion of knowledge. But what exactly is knowledge?

Knowledge is typically considered a peculiar form of information, and many of the issues that are central to the economics of information and to the process of structural transformation—such as the problems of appropriability, the fixed costs associated with investments in research which give rise to imperfections in competition, and the public good nature of information—also point to a crucial role for government. An important conclusion from economic analysis is that the market economies of high-income countries (in which research and innovation play a vital role) are not well described by the standard neo-classical competitive model, and that the market equilibrium, without government intervention, is often not efficient. That conclusion also holds for developing countries where there is even less public and private funding available to generate knowledge. But these countries can learn by borrowing ideas and expertise from other more advanced economies.

‘Nations are poor because their citizens do not have access to the ideas that are used in industrial nations to generate economic value,’ Romer observed (1993a: 543). Developing countries remain trapped in poverty because households and firms there have not been able to improve their productivity levels by either inventing innovative ways of making better goods and services or by copying and use new industrial and technological tools available elsewhere. ‘In a world with physical limits, it is discoveries of big ideas, together with the discovery of millions of little ideas, that make persistent economic growth possible. Ideas are the instructions that let us combine limited physical resources and arrangements that are ever more valuable’ (Romer 1993b: 64).

(p. 17) Another theoretical justification for the role that governments must play to foster development—is the economics of agglomeration. Balassa (1966) made a puzzling observation on the rise of intra-industry trade in Europe in the 1950s. Balassa noted each country produced only part of the range of potential products within each industry, importing those goods it did not produce. This trade allowed specialization in narrower ranges of machinery and intermediate products, permitting the exploitation of economies of scale through the lengthening of production runs. New trade theorists have consequently highlighted the fact that unexhausted economies of scale at the firm level necessarily imply imperfect competition. They have shown that increasing returns have been a powerful force shaping the world economy, and developed general equilibrium models of imperfect competition that confirm Marshall’s trinity of reasons for industry localization: knowledge spillovers, labour market pooling, and specialized suppliers.7 For developing countries that must rely on trade as their main source of growth in an increasingly globalized world, the policy implications of this are clear: it is essential that their governments are capable of solving the coordination and externalities issues that prevent the agglomeration of firms and activities from taking place (Rodrik 2007; Harrison and Rodriguez-Clare 2009).

A third wave of structural transformation research has also been geared towards the specific experience of developing economies, seeking to highlight the dynamics of change and the factors that differentiate their experiences from those of advanced economies (Lin and Monga 2011, 2017; Lin 2012a, 2012b). Policy questions are being addressed systematically, covering the distribution of roles between the government and the private sector; the strategic selection of competitive industries according to the comparative advantage of developing countries; the determinants of the dynamics of sectoral contributions to growth; the evolution of the capital intensity of sectors over time—within and across countries; the processes that allow economies to move up the value chain; the various ways of organizing and fostering the adaptation and adoption of new technologies in poor countries; the determinants of a country’s ability to create employment; and the institutional arrangements that are necessary to support structural transformation, especially in the context of low-income countries where infrastructure, skills, and long-term financing are scarce.

At the policy level, however, the big question remains: what exactly needs to be done to ignite, stimulate, or support processes of structural economic change, both from the macro and micro perspectives? Which sectors are more likely to record the highest productivity growth rates, and therefore contribute more effectively to positive social transformation? Theoretical and empirical economic research has long reached consensus: industrialization is key (UNCTAD 2017). But what type of industrialization? And has the very idea of industrialization become a moving target in a world of constantly changing production structures?

(p. 18) Getting into the Black Box: Industrialization, Unavoidable, and Evolving Feature of Change

One big idea seems to have survived the various waves of development thinking on structural transformation: industrialization. At times, it has been celebrated, revered, feared, and even challenged, but it has never been absent from the successive intellectual and policy frameworks seen as the essential feature of economic change. In fact, there is wide consensus among economists that industrialization is the single most important driver of structural change. The two concepts are indeed closely linked: structural transformation is the phenomenon whereby a society’s resources are moved from the sectors where they yield little economic benefit to those where the payoffs are the highest—and this occurs through industrialization. Indeed, prosperity is achieved in any country only when a country’s resources (human, natural, and capital) are shifted from subsistence and informal activities into high-productivity activities.

Industrialization dynamics is therefore an unavoidable feature of structural transformation. It has long been recognized as one of the main engines of sustained economic growth, especially in the early stages of development.8 Its essential characteristics include: (i) an increase in the proportion of the national income derived from manufacturing activities and from secondary industry in general, except perhaps for cyclical interruptions; (ii) a rising trend in the proportion of the working population engaged in manufacturing; and (iii) an associated increase in the income per head of the population (Bagchi 1990). Few countries have been economically successful without industrializing. Only in circumstances such as an extraordinary abundance of natural resources or land have countries been able to do so (Unido 2009).

The economic development of today’s industrialized countries was almost universally accompanied by an increase in agricultural productivity in the initial stages of development. Sustained economic development typically requires that agriculture, through higher productivity, provides food, labour, and even savings to the process of urbanization and industrialization. A dynamic agricultural sector raises labour productivity in the rural economy, pulls up wages, and gradually eliminates the worst dimensions of absolute poverty.

Agricultural growth also stimulates growth in non-farm sectors, thus driving structural transformation and industrialization processes. The development of a competitive industrial sector yields an even higher payoff. Economists have established at least since the early1960s that manufacturing has always played a larger role in total output in (p. 19) richer countries, and that countries with higher incomes are typically those with a substantially bigger economic contribution from the transport and machinery sectors. The countries that manage to pull out of poverty and get richer are those that can diversify away from agriculture and other traditional products.

Industrialization is an ever more powerful engine for economic and social change in the context of globalization, as it provides an almost infinite potential for growth—especially for many low-income countries. It has always played a key role in growth acceleration processes that are sustained over time and eventually transforms economies from ‘poor’ to ‘rich’.

Whereas economic growth based on the exploitation of natural resources or agricultural land eventually faces the constraint of shortages of quantity, a development strategy based on producing manufactured goods for the global market benefits from economies of scale due to increasingly lower unit costs of production.

In the early phases of modern economic growth, which started with the Industrial Revolution, manufacturing played a larger role in the total output of successful countries and their higher incomes were associated with a substantially greater role of transport and machinery sectors. Throughout the nineteenth and twentieth centuries, countries in North America, Western Europe, and Asia could transform their economies from agrarian to industrial powers, which included a rapidly growing services sector fuelled in large part by the multiplier effect of manufacturing. As a result, they built prosperous middle classes and raised their standards of living.

In addition to the generally much higher levels of productivity in industry (especially manufacturing) than in traditional agriculture, the main reason for the growth of industrialization is the fact that its potential is virtually unlimited, especially in an increasingly globalized world. As agricultural or purely extractive activities expand, they usually face shortages of land, water, or other resources. In contrast, manufacturing easily benefits from economies of scale: thanks to new inventions and technological development, and to changes in global trade rules, transport and the unit costs of production have declined substantially during the past decades, which also facilitates industrial development. Several decades ago, low-income countries faced the constraints of their limited market size, high transportation costs, and trade barriers, and could not take advantage of the opportunities offered by manufacturing. With globalization, virtually any country can identify products for which it has overt or latent comparative advantage, facilitate the entrance of its firms into global value chains, and scale up production almost without limit, thereby creating its own niche in world markets. Today, almost any small country can access the world market, find a niche, and establish itself as a site of global manufacturing. For example, Qiaotou and Yiwu, two once small Chinese villages, have become powerhouses, producing more than two-thirds of the world’s buttons and zippers, respectively!

Industrialization also promotes inclusive development by expanding the fiscal space for social investments. In such a context, fiscal revenues are likely to increase due to: exports of higher value added; the rising profits of companies; and better incomes earned by a more productive and innovative labour force. Within the industrial sector, (p. 20) manufacturing has evolved and changed the dynamics of the world economy. Profound changes in geopolitical relations among world nations, the widespread growth of digital information, the decline of transportation costs and the development of physical and financial infrastructure, computerized manufacturing technologies, and the proliferation of bilateral and multilateral trade agreements have all contributed to the globalization of manufacturing. These developments have permitted the decentralization of supply chains into independent but coherent global networks that allow transnational firms to locate various parts of their businesses in various places around the world. The creative design of products, the sourcing of materials and components, and the manufacturing of products can now be done more cheaply and more efficiently from virtually any region of the planet while final goods and services are customized and packaged to satisfy the needs of customers in faraway markets.

The globalization of manufacturing has thus allowed developed economies to benefit from lower-cost products driven by the lower wages used for production in developing countries such as China, India, Bangladesh, Costa Rica, Mexico, or Brazil while creating employment and learning opportunities in these formally poor nations. The intensity of these exchanges has led to new forms of competition and co-dependency.9

Yet, despite its importance, mainstream development economics paid only limited attention to industrialization for long decades. Several factors explain this benign neglect or even reluctance by researchers to think seriously about industrialization. First, tackling industrialization posed serious analytical challenges for a long time. In 1995 Krugman wrote about the intellectual shyness of early development economists when faced with the need to formalize ideas and concepts with the unsuitable mathematical toolbox available in the 1960s and 1970s. Following his intuition, it can be noted that issues of market size and economies of scale, central to the analytics of structural transformation as studied by some of the leading voices in the first generation of development economists (mainly Paul Rosenstein Rodan and Albert Hirschman) were not presented in formal models.

A second reason for the long neglect of structural change in mainstream economic analysis was the intellectual shift from the type of deep, transformative long-term questions that had preoccupied economists since the eighteenth century, to a narrower focus on short-term, business cycles topics that dominated headlines. The quest for the sources and mechanisms for prosperity and social change, which started with classical economists such as Adam Smith, Alfred Marshall, or Allyn Young, slowed down after the Great Depression, as researchers turned their interest to short-run issues. Indeed, with the notable exception of the pioneering work of Robert Solow, for much of the twentieth century and certainly through the 1960 and 1970s, macroeconomists tended to study business cycle issues that characterized the post-war period. As they tried to better understand stabilization policies—monetary and fiscal measures to avoid (p. 21) disruptive and costly inflation—few resources were devoted to the analysis of the long-run determinants of growth and transformation.

Several waves of growth research produced valuable insights (Monga 2011). On the theoretical front, the analysis of endogenous technical innovation and increasing returns to scale has provided economists with a rich general framework for capturing the broad picture and the mechanics of economic growth. From Solow’s work, we know the importance of the role of capital accumulation (both physical and human) and technical change in the growth process. From contributions by Becker, Heckman, Lucas,10 and many others, we have also learned about the importance of human capital through the diffusion of new knowledge or on-the-job learning, often stimulated by trade, and the so-called college wage premium. From work by North (1981), with supporting theoretical and empirical analyses exemplified by the works of Greif (1993) and Acemoglu et al. (2001), we have learned that growth is in large part driven by innovation and institutions that have evolved in countries where innovative activity is promoted and conditions are in place for change to take place. From Romer and endogenous growth theorists, we have understood the need to change the focus of growth theory from accumulation to knowledge creation and innovation. In sum, we know quite a lot about some of the basic ingredients of growth.

On the empirical side, the availability of standardized data sets—especially the Penn World tables—have stimulated interest in cross-country work that highlight systematic differences between high-growth and low-growth countries with regard to initial conditions (such as productivity levels, human capital, demographic features, infrastructure, financial development, and inequality), institutional variables (such as the rule of law, protection of property rights, and governance indicators), and policy variables (such as macroeconomic stability, financial regulation, or trade openness). However, growth research still faces significant challenges in identifying actionable policy levers to sustain and accelerate growth in specific countries.

In recent years, growth researchers have confronted three types of challenges: the explanation of a lack of convergence among countries; the identification of robust determinants of economic performance; and the design of the supporting institutions for innovation and technological change, which are widely acknowledged to be the foundations for structural change and prosperity. The disappointments of growth research—most notably from the perspective of policy makers seeking specific action plans to generate prosperity—have led to a reassessment of the validity and usefulness of existing knowledge, and to a return to structural transformation. An important study by the World Bank (2005), focusing on lessons of the 1990s, highlighted the complexity of economic growth and noted that the reforms carried out in many developing countries in the 1990s focused too narrowly on macroeconomic stabilization and the efficient use of resources, not on the expansion of capacity for growth. While they enabled better use of existing capacity, thereby establishing the basis for (p. 22) sustained long-run growth, they did not provide sufficient incentives for expanding that capacity.11 The report concluded that there is no unique, universal set of rules to guide policy makers. It recommended less reliance on simple formulas and the elusive search for ‘best practices’, and greater reliance on deeper economic analysis to identify the one or two most binding constraints on growth in each country.

The rethinking of economic development—beyond growth theories—has brought attention back to the deeper issues of structural transformation and its key feature, industrialization.12 However, economists have continued to debate the role and significance of industrialization in a world economy that has changed considerably since the days of Adam Smith and even Simon Kuznets.

Deindustrialization and Automation: Threats or Opportunities?

To many researchers, industrialization’s role has become marginally important in the global quest for economic prosperity. They cite as the most obvious piece of evidence the dramatic decline in employment in manufacturing as a share of total employment in the world’s most advanced economies, a phenomenon widely referred to as ‘deindustrialization’. This trend was first observed in the United States and Europe. Some critics saw deindustrialization as resulting from the rapid growth of North–South trade (trade between the advanced economies and the developing world) and explained that it was caused by the fast growth of labour-intensive manufacturing industries in the low-wage developing world. Viewing it as a threat to workers in the advanced economies, they branded it as a negative consequence of the globalization of markets, which generated fierce political debates in the Western world. Political leaders across the ideological spectrum seized on deindustrialization as the main explanation to widening income inequality in the United States and high unemployment in Europe.

These popular explanations were inaccurate. Empirical research showed that when measured in real terms, the share of domestic expenditure on manufactured goods had been comparatively stable for decades in advanced economies. Thus, that round of deindustrialization was essentially the result of higher productivity in some capital-intensive manufacturing sectors rather than in services. The pattern of trade specialization among the advanced economies explained why some countries deindustrialize faster than others (Rowthorn and Ramaswamy 1997). In sum, deindustrialization was primarily a reflection of successful economic development and effective industrial (p. 23) upgrading strategies, and North–South trade has very little to do with it. This became even more apparent in Japan and in the successful Four Tiger economies of East Asia (Hong Kong, China, Korea, Singapore, plus Taiwan Province of China), which also experienced deindustrialization.

Most recently, deindustrialization has emerged again as a concern not just for advanced economies but also for low-income countries. Rodrik’s (2016) seminal work on this topic has highlighted the changes in the relationship between industrialization (measured by employment or output shares) and incomes not just in advanced, post-industrial economies, but also in developing countries. He concludes that countries are running out of industrialization opportunities sooner and at much lower levels of income compared to the experience of early industrializers. In other words, industry’s share of employment in some developing countries seems to be peaking at a lower level than it used to, and at an earlier point in their development. Advanced economies have indeed lost considerable employment in some industries (especially of the low-skilled type), but they have done surprisingly well in terms of manufacturing output shares at constant prices. Rodrik’s analysis confirms that advanced economies have lost considerable employment (especially of the low-skilled type), but they performed well in terms of manufacturing output shares at constant prices. Surprisingly, Asian countries and manufacturing exporters appear to have been largely insulated from deindustrialization trends, while Latin American countries have suffered the most.

Other empirical research examining developing countries as whole has shed light on the mystery of deindustrialization. Haraguchi et al. (2017) have analysed several decades of employment data on over 100 developing countries, going back to 1970. They explore whether the low levels of industrialization in developing countries are attributable to long-term changes in opportunities available to the sector around the globe. They find that manufacturing employment became geographically more concentrated after 1990, but no less important. Their study’s findings show that the manufacturing sector’s value added and employment contribution to world GDP and employment, respectively, have not changed significantly since 1970. The declining manufacturing value added and manufacturing employment share in many developing countries has not been caused by changes in the sector’s development potential but has instead resulted from a shift of manufacturing activities to a relatively small number of populous countries, thus resulting in a concentration of manufacturing activities in specific developing countries.

While the average of each country’s manufacturing–employment ratio has indeed declined since the early 1990s, as observed by Rodrik (2016), the aggregate of manufacturing employment in developing countries is actually higher than in earlier decades. This counter-intuitive finding can be explained by the fact that the workforce in some developing countries—such as China—is so large that a stagnation or even a decline in the percentage of manufacturing in the labour force does not translate into a decline in the absolute, aggregate number of workers in that sector.

Still, worries about deindustrialization and about the importance of industrialization in modern growth and structural transformation processes have been compounded by (p. 24) the lacklustre global trade climate, which has characterized the world economy in the wake of the 2008 financial crisis.13 This new trade scepticism has led many researchers and policy makers to wonder whether today’s low-income countries could benefit from the same export opportunities that allowed rapid industrialization in Asia in the 1970s–90s—even if they could adopt the right policy frameworks and develop their manufacturing production bases. While it is indeed true that global trade grew at a lower rate than global GDP in the decade following the 2018 financial crisis, over the long term, the trade–GDP relationship is usually not a static one.

Despite the resurgence of the protectionist discourse in some advanced economies, and the persistence of non-trade measures, the general, long-term trend of global trade is still a very positive one for developing countries. Moreover, the declining general trend in average tariffs around the world since World War II is unlikely to be rolled back given the structural changes they have induced in the global production system and the enormous win–win opportunities they have created for advanced and developing economies. The best indicator of that evolution is that many goods are now manufactured in several countries at the same time. Global trade is therefore no longer a series of transactions between countries producing individual goods and services within their national boundaries and exchanging them in international markets. It is often about collaboration and partnerships, even in an intensively more competitive world. Manufacturing is increasingly a network of global supply chains in which the various production stages take place in the most cost-efficient locations—regardless of where they are in the world (Lin and Monga 2017: ch. 7).

Some researchers have observed that manufacturing is not the only driver of growth. In the words of Ghani and O’Connell (2014) and Enache et al. (2016), there is an ongoing Third Industrial Revolution led by services, which may now contribute substantially to output growth, productivity growth, and job growth in low-income countries. Services are invalidating some long-held tenets of economic development: for centuries, the service trade was limited because it required proximity and face-to-face interaction between the buyer and the seller. However, this is no longer the case, as technology and innovation allow services to be produced and traded just like manufactured goods. Moreover, the cost of trading services that can be digitized has fallen dramatically, as services do not have to confront customs and other logistical barriers. And service-led growth is also greener and more gender-friendly. These observations have led Ghani and O’Connell (2014) to suggest that the services sector, branded as a ‘growth escalator for low-income countries’, be given priority in the design of structural transformation strategies. They conclude: ‘Unlike the goods sector, where developing countries already have a large market share, making it difficult for new entrants to become large-scale exporters, services appear to be steadily expanding, with catch-up (p. 25) opportunities continuing to rise and entry for all.…A service-led growth can be sustained because the current globalization of services is only the tip of the iceberg, and service is the largest sector in the world, accounting for more than 70% of global output’ (Ghani and O’Connell 2014: 20 and 21).

Today’s global economy certainly offers infinite opportunities for growth and transformation in the services sector but not to countries at all levels of development. Therefore, one should be careful not to draw swiping policy recommendations from the fact that an increasingly large services sector is driving global growth. First, there is a semantic issue to be addressed: manufacturing no longer means the type of old, capital-intensive industries that spurred the First Industrial Revolution in the eighteenth and nineteenth centuries. With the advent of the Second Industrial Revolution, manufacturing has become a continuum of activities that are interlinked. As noted by Schwieters and Moritz (2017), ‘One key indicator is that conventional boundaries between industries are eroding. It’s getting harder to tell the difference between, say, a telecommunications company and an entertainment producer, or between a retail bank and a retail store. The relationships among suppliers, producers, and consumers are also blurring, more rapidly than many business decision makers are prepared for.’ The definitions of ‘agriculture’, ‘manufacturing’, and ‘services’, should therefore evolve to reflect the constantly changing boundaries of these sectors. In its current meaning, manufacturing should be understood in its broadest sense as all trade based on the fabrication, processing, or preparation of all kinds of products from raw materials and commodities to chemicals, textiles, machines, equipment, and even modern services and virtual goods.

The second reason why policy recommendations cannot necessarily follow from the increasing services sector growth is that even in developing countries where there has been a boom in the services sector without industrialization, a lot of these services are low-productivity, subsistence level, and sometimes even informal activities that may help households escape poverty but are not sustainable sources of growth. The type of high-productivity services that offer long-term growth prospects to nations (in sectors such as informational technology or banking and finance) are skill-intensive. Yet by definition, low-income countries have a weak skills base. That is certainly the case in most African and South Asian countries where the demographic structure and limited fiscal base do not allow for the rapid build-up of the kind of human capital necessary to sustain economic transformations driven by high-productivity modern services. Even developing countries such as India, Sri Lanka, Kenya, Cameroon, or Egypt, where substantial amounts of public funding have been devoted to the creation of strong education systems, too often end up exporting much of their skilled labour. Consistent with the basic rationale for structural transformation, which is to constantly move labour and capital into higher-productivity sectors, it is logical that advances in the modern service sector, rather than in traditional manufacturing, will drive the growth of living standards in the advanced economies in the future and also in the middle-income countries that successfully manage their industrial upgrading process. However, for low-income countries, low-skilled labour-intensive employment will still offer (p. 26) sizeable growth opportunities—especially with the upcoming ‘graduation’ of large middle-income countries like China or Indonesia, which is freeing up substantial quantities of industrial employment (Lin 2011).

Finally, there is the perceived threat of automation on industrialization. Improvements in the design of robots, and their increasing use in many industries around the world, have made economists wonder whether the long-held prescriptions for structural transformation are becoming obsolete. If sophisticated and smart robots, not people, can fill the factories and therefore lower production costs, would that not invalidate the Simon Kuznets insight that modern economic growth requires moving resources out of agriculture into industry, then out of industry into services?

The question of whether robots hamper industrialization’s central development role is indeed important. However, the potential adverse employment and income effects of robots are being overestimated—most commentators neglect to consider that what is technically feasible is not always also economically profitable. For instance, it would be technically possible (if not necessarily economically sensible) to automate about two-thirds of manufacturing employment in countries like India, Indonesia, or Thailand (McKinsey 2017). But the economic and social returns for doing this in the decades ahead are unclear, at best. The countries currently most exposed to robot-based automation are those with a large and well-paying manufacturing sector (UNCTAD 2017). While routine tasks in well-paid manufacturing and service jobs are being replaced by robots, low-wage manufacturing jobs in areas such as clothing factories are left largely unaffected by automation (UNCTAD 2017). So far, robotization has had a small effect on most developing countries, where mechanization continues to be the predominant form of automation. Despite the hype surrounding the potential of robot-based automation, today the use of industrial robots globally remains quite small and amounts to less than 2 million units.14 Industrial robots are concentrated in the automotive, electrical, and electronics industries, and only then in a small number of countries.15

Deindustrialization and automation need not to be viewed as worrisome phenomena. The appropriate response to the perceived or real threats that they pose is for developing countries to implement digital industrial policies to ensure that robotics supports—rather than threatens—inclusive development. This will require that countries at various levels of development constantly design and implement proactive upgrading strategies that are suited to their evolving endowments and comparative advantages.


(p. 27) The importance of structural transformation as a process for generating prosperity and as the mechanics for improving the quality of lives around the world cannot be underestimated: since World War II, only two economies out of more than 200 have moved from low-income to high-income status: South Korea and Taiwan, China.

Few countries have experienced economic convergence on a sustained basis. One approach to measuring relative progress is to look at per capita GDP relative to the United States, which has been the symbol of advanced industrialized countries since World War II. Persistently, over 80 per cent of the countries in the world have GDP per capita levels that are half or less than half of the level in the United States. There has also been some ‘churning’, with countries not only converging up the ladder, but also diverging down the ladder. This is the case of some former colonies in Africa: many have gone from being lower middle-income (MIC) economies at independence to low-income in the 1980s. Since then, some have climbed back up to MIC status. Even some natural resource rich countries failed to diversify their economic base and, as a result, have experienced large declines in their relative income per capita.

There are also countries at the high-income end of the distribution that have fallen back to MIC status, by this measure—most notably Argentina. Historical data on long-run growth compiled by Angus Maddison also suggests that many countries have remained stuck in the so-called middle-income trap: Russia, for instance, remained there for some 200 years. And in the most dynamic current middle-income countries (Vietnam, Thailand, Indonesia, Brazil, Peru, Mexico, Mauritius, South Africa, Botswana, etc.), there is the constant fear that they may not necessarily climb to high-income status and remain there.

In sum, only a handful of developing countries have succeeded in reaching high levels of prosperity, and many of them are in Western Europe. The few developing economy success stories—with the exception of a few small oil rich countries—are generally located in East Asia and achieved rapid industrialization by following comparative advantage export dynamism, helped by the facilitating role of the state. This small group of exceptional examples of catching-up has not been studied systematically. Yet, their unique experience and the recent rise of the multi-polar growth world deserve scrutiny, especially with the adoption of the Sustainable Development Goals by the international community. Failure to understand the mechanics and policies for structural transformation is costly, not just for individual economies but for the world, as poverty is often associated with instability, conflicts, and mass migrations.

This brings us to this Oxford Handbook of Structural Transformation. The existing academic literature on structural change lacks an in-depth, comprehensive compendium in which researchers and policy makers can find both a critical assessment of the major theories of the determinants of structure and its change, and a discussion of strategies, policies, and country experiences (best and worst practices) from which to learn. This volume tries to fill that gap.

The Handbook is organized as follows: Part I discusses theories and frameworks of structural change. Part II focuses on the drivers, channels, and policy instruments for structural transformation. Part III discusses the empirics of structural change while (p. 28) Part IV sheds lights on a number of country and regional experiences. Part V provides some concluding thoughts. The contributors have tried to strike a balance between academic literature and policy issues, between economic theory and practice, and between past knowledge and the unexplored ideas that remain for future research.

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(1) UNCTAD’s International Standard Industrial Classification (ISIC), Revision 4 uses the word ‘sector’ to refer to agriculture, industry, and services. The economic literature also refers to them, respectively, as the primary, secondary, and tertiary sectors. Sectors are further disaggregated into ‘industries’. For example, the industrial sector includes manufacturing, mining, utilities, etc. Within most of these industries, the disaggregation goes one step further into branches. For example, within manufacturing, one can distinguish branches such as food processing, garments, textiles, chemicals, metals, machinery, and so on.

(2) We borrow this phrase from Gates (1988).

(3) The concept of ‘economic structure’ refers to ‘the composition of production activities, the associated patterns of specialization in international trade, the technological capabilities of the economy, including the educational level of the labour force, the structure of ownership of the factors of production, the nature and development of basic state institutions, and the degree of development and constraints under which certain markets operate (the absence of certain segments of the financial market or the presence of a large underemployed labour force, for example) (Ocampo et al. 2009: 7).

(4) The long list of these early development economists includes Rosenstein-Rodan (1943); Singer (1950); Lewis (1954); Nurkse (1956); Myrdal (1957); Prebisch (1959); Chenery and Bruno (1962), and Furtado (1964).

(5) Dutt and Ross (2003) provide a comprehensive review of the main and often overlapping currents of early economic structuralism. They suggest that the first phase, which occurred from 1945 to the mid-1950s, was launched by Rosenstein-Rodan, Lewis, and Nurske. A second sub-group working in this area from roughly the mid-1950s to the late 1960s and was dominated by contributions from Myrdal, Hirschman, Chenery and Bruno, and Furtado. A third sub-group, called ‘neo-structuralism’ or ‘late structuralism’, emerged in the early 1980s to respond to criticism from neo-classical economists and to modify and enrich development economics with lessons drawn from economic analysis and the actual experience of poor countries. It is represented by contributions from Taylor (1983, 1991), Ocampo and Taylor (1998), and Ocampo et al. (2009).

(6) This section draws on Lin and Monga (2013) ‘Evolving Paradigms of Structural Change’.

(7) For a quick intellectual history of the importance of increasing returns on economics and a review of progress on theoretical analysis, see Krugman (2008).

(8) Earlier analyses of the process, dating back to the 1950s and 1960s (Datta 1952; Kuznets 1966), found that manufacturing specifically tends to play a larger role in total output in richer countries—a pattern corroborated by the UNIDO report (2009)—and that higher incomes are associated with a substantially bigger role of transport and machinery sectors.

(9) In recent decades, innovation, technological developments and new sources of economic growth have led some economists to question whether manufacturing still matters. See Monga (2014) for a critical assessment of the arguments in that debate.

(10) See, in particular, Becker (1992); Lucas (2004); Heckman (2006).

(11) Pritchett (2006) suggests that economists abandon the quest for a single growth theory and focus instead on developing a collection of growth and transition theories tailored to countries’ circumstances.

(12) Influential works include Ngai and Pissarides (2007); Rogerson (2008); Timmer and Akkus (2008); Rodrik (2008); Lin (2012a); Herrendorf et al. (2014); and Timmer (2014).

(13) In the words of Davies, ‘world trade has lost its mojo’, and global trends support his observation. From 1990 to 2008 global real GDP expanded at an annual rate of 3.2 per cent, while world trade volume grew at 6.0 per cent. Since 2008, however, world trade has grown slightly slower than GDP, so the share of exports in GDP fell after a 25-year uptrend (Davies 2013).

(14) Of the 1.63 million industrial robots in operation worldwide in 2015, only 1,580 were in textiles, apparel, and leather. Of all the industrial robots shipped that year, a third ended up in middle-income countries. Source: International Federation of Robotics (

(15) Almost half of operational industrial robots are in Germany, Japan, and the United States of America, but China has quadrupled its robot stock since 2010, and the Republic of Korea has the highest number of robots per worker globally (UNCTAD 2017).