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No.1 | The Inclusive Sustainable Transformation Index (ISTI)


Content introduction:


The Inclusive Sustainable Transformation Index

Justin Yifu Lin, Célestin Monga and Samuel Standaert


Executive summary

The adoption of the Sustainable Development Goals (SDGs) by the United Nations General Assembly and the successful conclusion of theClimate SummitCOP 21 in 2015 were hailed as historic milestones in the global pursuit of shared prosperity in a peaceful and stable world. However, the monitoring of progress towards these goals has become a significant challenge, especially given that economies around the world are at different levels of development and have different production structures. This paper proposes the Inclusive Sustainable Transformation (IST) index as contribution to the monitoring of these global objectives.

The IST outcome index captures the extent to which the country has developed a modern industry or services-based economy that protects the environment and is gender inclusive.It considers the strength of the manufacturing and export sector and the technological expertise embedded in the economy and weighs this against the structure and inclusiveness of the labor market. This is combined with its environmental outcome tracking the lack of pollution, the structure of the energy market and the protection of environmental resources.

The most important way in which this index distinguishesitself from other indicators of (industrial) development is that the level of development is taken into account the structural characteristics of different countries are compared. New Structural Economics (Lin 2012a, 2012b) highlights the idea that a countries best strategy and its desired characteristics change depending on its development status. Simply put, it should not be expected of relatively poor countries such as Burundi or Ethiopia to have same environmental, institutional and economic characteristics as rich countries like Denmark or Japan. To that end, the indicators included in the IST outcome indexare first transformed such that they express the country’sperformance on a certain topic relative to its peers at that point in time. These transformed scorerepresent the fraction of countries with a similar level of development that performs worse: a score of one meansthat country outperforms all of its peers, and vice versa for zero. The IST indexis then computed as the simple average of all transformed indicators.

In addition to monitoring the progress made towards the establishment of an inclusive and environmental-friendly modern economy, the indexcan serve as a useful tool for policy makers and analysts. By decomposing the score back into its components, the areas that are leading can be disentangled from those that are lagging and specific policy areas that require more attention can be targeted. Subsequent cross-country comparisons of the index and constituent indicators can help identify “best practice” policies that take the level of development into account.

  1. 1. Introduction

A century or two from now, when future historians analyze and chronicle the story of economic development on planet Earth and try to identify its defining and foundational moments (the conceptual points in time when the world decided to establish some baselines of commonality), it is very likely that they will pick 2015, the year of the adoption of the Sustainable Development Goals (SDGs) and of the Paris Agreement on climate change, as a major inflexion point. These global rendezvous were indeed major milestones in the long struggle for building global consensus on international priorities, and setting objectives that the human community of nations should strive for. Not surprisingly, even the most ambitious and transformational global objectives always generate a (healthy) dose of incredulity: why should anyone believe in the promises of a better world when such goals have often been stated in the past, to little results, and are predicated on the assumption that the global consensus that led to the signing of these two major international covenants will hold in countries at all levels of economic development?

There are indeed a few major puzzling issues about the SDGs and the Paris Accord: first, almost every single commitment made appears to be voluntary. Second, monitoring mechanisms are uncertain, which makes enforcement highly problematic. It is therefore important that the underlying mechanisms and dynamics that allow economies and societies to reach their noble goals be monitored carefully. It is necessary to measure how well each country and region in the world will address issues of economic production, employment generation, and the protection of the environment. Without steady and well-organized economic transformation that can occur only through responsible industrialization, the widely shared global goals of creatingopportunities and improving human life would remain elusive.

Achieving all SDGs by 2030 will be costly. Estimates by The Economist suggest that meeting them would cost $2-3 trillion a year of public and private money over 15 years. That is the equivalent of about 15 percent of global annual savings, or 4 percent of global GDP. It should be noted that while many industrialized countries have promised to deliver 0.7 percent of their GDP to aid, none has actually managed to do so.[1] Therefore, it would be unrealistic to expect that after the adoption of the SDGs by the international community in September 2015, there will be real resources to consistently carry out the monitoring of progress.

Measurement of any global goal can be costly, hard, and frustrating.[2] In December 2014 UN Secretary-General Ban Ki-moon called for a “comprehensive program of action on data.” However, because the Open Working Group has recommended 169 targets for the proposed 17 SDGs, it would unrealistic to expect adequate funding to carry out all the necessary data collection exercise.[3] Under such circumstances, it is best to adopt more focused approaches, which are still based on objective data analysis and monitoring but cover only the factors and elements considered to be most important indicators of progress towards the SDGs.

Structural change is the foundation of sustained and inclusive growth (Monga, 2013) and the condition for achieving the SDGs. Rarely has a country evolved from a low- to a high-income status without sustained structural transformation from agrarian or resource-based economy towards an industry- or services-based economy. Industrialization in particular is essential for lifting people out of poverty, creating jobs, advancing technology, and generating prosperity around the world.  However, industry is also the largest single sector that emits greenhouse gas (GHG) with almost 30 percent of the global share. Fortunately, it is possible to transform conventional industrial development patterns to prevent dangerous anthropogenic interference with the atmosphere.[4] The global community needs monitoring tools that provide incentives to governments, the private sector, and other development stakeholders to promote climate resilient industrialization.

This paper proposes the inclusive sustainable transformation (IST) index, which focuses on the critical elements of successful economic development strategies. They are based on New Structural Economics (Lin 2012a, 2012b) and differentiate the outcome based on the level of development of each country. In an era where there is no shortage of development indices, the ISTindexset itselfapart by measuring performance towards the SDGs not in a generic fashion but by accounting for specific country status (high- middle- or low-income).

The remainder of this paper is organized as follows. The next section discusses the need for an index of structural transformation. Section 3surveys the theoretical challenges for building development indices, and presents the IST methodology. Finally, section 4 discusses the indicators chosen and the resulting values of the IST index and its subcomponents.

  1. 2. Why the Need for an Index of Structural Transformation?

The importance of structural transformation as a process for generating prosperity and as the mechanics for improving the quality of life around the world cannot be underestimated: rarely has a country evolved from a poor to a rich one without sustained structural transformation from agrarian or resource-based towards an industry or services-based economy. Ideally, that process involves changes in the agricultural sector, through higher productivity, in order to provide food, labor, and even savings, to the process of urbanization, industrialization, and the gradual development of a high-performing service sector that can also absorb an increasingly large fraction of an educated workforce. Sustained growth and economic prosperity require the shift of resources out of traditional agriculture and other low-productivity primary activities, into more productive sectors of manufacturing and services in both urban and rural areas. The ensuing expansion and upgrading of “modern” sectors (including non-traditional agriculture) are at the core of the sustained productivity gains that characterize economic development. Indeed, there is ample consensus that rising productivity accounts for the bulk of long-term growth.

Structural transformation (or structural change) is therefore central focus of economic policy for countries at all levels of development. It involves five main features: i) a steadily declining share of agriculture in economic output and employment; ii) a rising share of urban economic activity in industry and modern services; iii) an increasingly sophisticated share of manufactured goods in production and exports; iv) migration of rural workers to urban settings; v) and a demographic transition that always leads to a spurt in population growth before a new equilibrium is reached. Sustaining high economic performance, improving living standards for the largest segments of society, and sharing prosperity widely to maintain social cohesiveness and peace, eventually require not only constant movement of resources to new, more productive industries, sectors, and firms, but also continuous infrastructure and institutional improvement, which becomes increasingly challenging as an economy approaches the technological frontier and can no longer rely on imitation to create value.

Structural differences between developed and developing countries reflect the differences in their endowment structure. A given economy’s structure of factor endowment -- defined as the relative composition of natural resources, labor, human capital and physical capital – is innately different at each level of development. Because of this, for any given economy, its comparative advantage and optimal industrial structure will be different at different levels of development. To move from one level to another smoothly and quickly, the government needs to provide or coordinate the improvement in hard and soft infrastructure (Lin 2012a, 2012b).

What is the sectoral dynamics of structural change? The modernization of agriculture and sustainable industrialization are essential features of the structural transformation process. Prosperity is achieved only when a country’s resources (human, natural, and capital) are shifted from subsistence and informal activities into high-productivity activities. The economic development of today's industrialised countries was almost universally accompanied by an increase in agricultural productivity in the early stages of development. Sustained economic development typically requires that agriculture, through higher productivity, provides food, labor, and even savings to the process of urbanization and industrialization. “A dynamic agriculture raises labor productivity in the rural economy, pulls up wages, and gradually eliminates the worst dimensions of absolute poverty (Timmer and Akkus, 2008, p. 3-4).Investments in agriculture aimed at promoting growth and generating an investable surplus are now widely viewed as necessary for industrial growth and for the benefits of development to reach the poor.

Agricultural growth stimulates growth in non-farm sectors, thus driving structural transformation and industrialization processes through various channels:

  • Higher farm incomes generate more demand for non-food consumables (e.g.  commercially-manufactured goods), creating growth linkages into the rural non-farm economy and further afield.
  • Increased demand in the agricultural sector for agricultural inputs, capital and services stimulates production of inputs such as fertiliser, machinery and tools.
  • As farm productivity increases and marketable surplus grows, demand for commercial distribution and processing infrastructure and services increases.
  • Increased productivity of agricultural labour means that labour can be released for employment in industrial and related sectors without damaging agricultural output.
  • Increased profits from rising agricultural productivity generates capital that can be invested in other sectors of the economy.

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 the total output of 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 are able to diversify away from agriculture and other traditional products. “As labor and other resources move from agriculture into modern economic activities, overall productivity rises and incomes expand. The speed with which this structural transformation takes place is the key factor that differentiates successful countries from unsuccessful ones.” (McMillan and Rodrik 2011, p. 1). In fact, only in circumstances such as extraordinary abundance of land or resources have countries succeeded in developing without industrializing.

Industrialization has always played a key role in growth acceleration processes that are sustained over time and eventually transform economies from “poor” to “rich.” In the early phases of modern economic growth, which started with the Industrial Revolution, manufacturing in particular played a larger role in the total output of successful countries and their higher incomes were associated with a substantially bigger role of transport and machinery sectors. Throughout the nineteenth and twentieth centuries, countries in North America, Western Europe and Asia were able to transform their economies from agrarian to industrial powers, which included a rapidly growing services sector fueled in large part by the multiplier effect of manufacturing. As a result, they built prosperous middle classes and raised their standards of living.

Besides the generally much higher levels of productivity in industry (especially manufacturing) than in traditional agriculture, the main reason for the growth in 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 unit costs of production have declined substantially during the past decades, which also facilitates industrial development. Today, almost any small country can access the world market, find a particular niche, and establish itself as a global manufacturing place. 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: i) exports of higher value added, ii) rising profits of companies and iii) better incomes earned by more productive and innovation labor force.[5]Figure 1illustrates the positive relationship between the level of industrialization (horizontal axis) and a number of measures of social inclusiveness such as the non-poor ratio, the HDI and the inverse of the Gini coefficient.

Within the industrial sector, 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 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 different 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.


Figure 1 - Inclusiveness indices by share of manufacturing in total employment, 1970-2010

Source: UNIDO (2015)

Note: Sample of almost 100 countries. Each dot represents the average value of each country for a 5-year sub period. In all cases a quadratic trend is also included in the figures to indicate the general trend of inclusiveness.


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

Successful transformation is not necessarily a linear process. In fact, few developing economies have experienced successful structural transformation: historical data on long-run growth compiled by Angus Maddison show that since World War II (WWII), only 2 economies out of more than 200 have moved from low-income to high-income status: South Korea and Taiwan, China. Few countries have also been able to achieve economic convergence with the most advanced countries on a sustained basis. One approach to measuring progress is to look at per capita GDP relative to the United States, which has been the benchmark of advanced industrialized countries in the post-WWII era. Persistently, over 80 percent 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 countries that have gone from being lower middle-income economies (MIC) at the time of their political independence to low-income in the 1980s. Since then, a few (mainly in Africa) 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.

Some countries that used to be at the high-income end of the distribution have fallen back to MIC status—most notably Argentina. Others remained stuck in the so-called middle income trap for a long period of time—Russia, for instance, remained there for some 200 years. This explains why policymakers around the world—especially in the most dynamically-growing emerging countries—are concerned with the middle-income trap.

Figure 2shows changes in income levels in African and Less Developed Countries (LDCs) relative to the United States between 1970 (horizontal axis) and 2014 (vertical axis). Nine areas are distinguished depending on the position of each country above or below two thresholds: a low-income threshold (defined as a relative income of 7 percent compared to the US), and a middle-income threshold (defined as a relative income of 45 percent compared to the US).

  • Catching-up economies are those that have managed to move from low to middle-income ranges or from middle-income to high-income ranges between 1970 and 2014.
  • Falling-behind economies are those that fell to a lower income range during the period. All of them are economies that in 1970 were considered middle-income but ended up in the low-income range in 2014.
  • The Poverty trap group includes the economies that remained in the low-income range during the period.
  • The Middle-income trap group includes those that remained in the middle-income range during the period.

Figure 2 - GDP per capita relative to the United States in 9 boxes, log of percent

Source: Elaboration based on PWT 8.1 and United Nations Statistical Division.

Note: Thresholds based on Gill and Kharas (2015). 12 LDCs are not included because data for 1970 was not available.[6] The estimates are based on figures of per capita GDP at 2005 international dollars


The performance of most African and LDCs in Figure 2 reflects 50 years of missing opportunities. With only a few exceptions, they show a negative performance. For the 53 countries of this group for which data is available, 22 can be characterized as being in the poverty trap,[7] 13 in the middle-income trap[8] and 12 have actually lagged further behind during the period, moving from the middle- to the low-income range.[9] Six countries, however, have managed to move up one income category during the period: Bhutan, Botswana, Cabo Verde, Egypt, Equatorial Guinea and Lao PDR.

In recent decades, innovation, technological developments and new sources of economic growth have led some economists to question whether “manufacturing still matters”. Manufacturing’s share of global value added has steadily declined over the past nearly 30 years as the global value added of services has grown. In 1985, manufacturing’s share of global value added was 35 percent. By the late 2000s, it had declined to 27 percent. Services grew from 59 percent to 70 percent over the same period (UNIDO, 2009). However, these trends are mainly observed in high-income countries and can be explained by several factors. Firstly, productivity increases and rising standards of living in advanced economies have pushed up wages and forced many industries to delocalize their production in lower-costs nations. Secondly, increasing levels of efficiency in the world economy have reduced the relative prices of consumption goods while at the same time the demand for services such as healthcare, security, or transportation has increased. Finally, and perhaps even more important, manufacturing jobs have a multiplier effect on jobs in services as the development of industries everywhere automatically generates a wide variety of new economic activities, from transportation to housing, from restaurant to entertainment.[10]

Concerns about the future of manufacturing as a viable source of economic growth have been investigated empirically by Hausmann, et al. (2011) with a measure of the sophistication of an economy based on how many products a country exports successfully and how many other countries also export those products. The results are striking: over 70 percent of the income variations among nations can still be explained by differences in manufactured product export data alone (Hausman et al. 2011). The analysis of the composition and quantity of a nation’s manufacturing reveals that sophisticated economies export a large variety of “exclusive” goods that few other countries can produce. To do this, these economies have typically accumulated productive knowledge and developed manufacturing capabilities that others do not have. It therefore appears that national income and economic sophistication (“economic complexity”) tend to rise in tandem. Furthremore, the linkage between manufacturing, economic complexity and prosperity is highly predictive, with economic complexity being much better at explaining the variation in incomes across nations compared to any other leading indicators. This is exemplified in Figure 3that contrasts the link between sectoral shares in GDP and income level of OECD countries with that of the least developed countries.In other words, even basic manufacturing expertise and capabilities can gradually breed new knowledge and capabilities and lead to new, more advanced products, provided that the right strategic and business decisions are made on industrial and technological upgrading. In the words of Hausmann and Hidalgo (2012, p. 13), economic development is “a social learning process, but one that is rife with pitfalls and dangers. Countries accumulate productive knowledge by developing the capacity to make a larger variety of products of increasing complexity. This process involves trial and error. It is a risky journey in search of the possible. Entrepreneurs, investors and policy-makers play a fundamental role in this economic exploration. Manufacturing, however, provides a ladder in which the rungs are more conveniently placed, making progress potentially easier.” In sum, manufacturing still generates economies of scale, sparks industrial and technological upgrading, fosters innovation, and has big multiplier effects.

Other researchers have wondered whether services should be considered the main engine of structural change as they contribute more to GDP growth, job creation, and poverty reduction than industry in many developing countries (Ghani and Kharas 2010). It is true that services now account for more than 75% of the global economy (45% in developing economies), and services are the fastest growing sector in global trade. As noted by Ghani et al. (2011), “the average growth of service exports from poor countries has exceeded that of rich countries during the last two decades. Their service exports are growing faster than goods exports. In brief, the globalisation of services has enabled developing countries to tap into a new, dynamic source of growth.”

Figure 3 - Sectoral shares in GDP and income level

Source: Own elaboration based on PWT 8.1 and United Nations Statistical Division.

Note: Unweighted averages. GDP shares are based on data at current dollars. Income levels are based on data at 2005 international dollars.

While productivity growth in poor countries in services is accelerating and appears to have outstripped productivity growth in industry, sustainable services are expanding fast mainly in upper middle-income developing countries. More important: the aggregation of very different types of low- and high-productivity activities under the label “services” can be highly misleading. One should distinguish modern services from traditional services. The former are information communication technology (ICT) intensive and can be unbundled, disembodied, and splintered in a value chain just like manufacturing goods (Bhagwati 1984), whereas the latter are typically low-productivity activities, often in the informal sector. Modern services can be electronically transported internationally through satellite and telecom networks. Traditional services are often not ICT-intensive and lack the potential for generating the income levels that can lift large segments of populations out of poverty.

It is modern services that are developing rapidly thanks to growing tradability, more sophisticated technology (including specialization, scale economies and off-shoring) and reduced transport costs (Ghani 2010). This raises serious questions on the viability of an economic development strategy that relies on services as the main sources of growth: first, blindly recommending the promotion of the services sector without making it explicit that only a fraction of it (modern services) can actually generate structural change can be deceptive. Second, the tradable services sector activities that are sustainable (IT, banking, insurance, etc.) require years of training, which most developing countries cannot afford. And even when they do, they often end up training good people who then leave the country to pursue better employment opportunities elsewhere if the country’s production structure cannot absorb their skills.

Building and retaining a sizeable workforce to support modern services takes time and is costly. Yet the payoff of that development strategy may not necessarily outweigh the costs, even when factoring in the expected benefits from the remittances sent home by well-trained migrants. A good example of this problem is the economic story of India, often considered the Mecca of the IT sector and by extension, a prime example of the promises and limitations of a development strategy relying primarily on modern services. India trains and exports quite a large number of highly educated people. India President Pranab Mukherjee recently made the following intriguing observation: With over 700 universities including 44 central universities and around 36,000 colleges, India at present has one of the largest higher education systems anywhere in the world. It is equally, however, a matter of concern that till very recently we did not have a single university figuring in the global top 200. It is only now, after concerted efforts and policy interventions that two of our institutions - Indian Institute of Science Bangalore and IIT Delhi- have broken into the top 200 globally in September [2015].[11] President Mukherjee concluded that the need of the hour, therefore, is to focus not only on education per se, but more importantly on the quality of education.

President Mukherjee could find some comfort in the fact that in 2015 India received $38 billion in foreign direct investment (FDI) inflows and nearly the double ($72 billion) in remittances. Remittances are obviously an excellent source of financing for the current account, and when they are stable they are also sources of growth. However, remittances do not have the transformative power of FDI (Drieffield and Jones 2013; de Mello 1997). India excellent performance in gaining remittances has not yet translated into sustained, double-digit growth rates—the country still has a GDP per capita of only $1,600. A benefit-cost analysis of devoting the country’s limited fiscal resources to building human capital for a modern services sector that is still too small for a workforce of about $600 million people highlights the importance of strategic choices for structural transformation. Unlike India, China has relied much less on remittances from migrants whose education was funded by taxpayers’ money, and more on FDI, channeled into labor-intensive industries, and creating employment opportunities that can absorb its workforce. Learning lessons from past strategic mistakes, the Indian government has launched the Make in India Initiative that aims to stimulate industrialization and employment generation.[12]

In sum, structural transformation is essential to sustained growth and prosperity. But economists and policymakers around the world have struggled to come up with viable strategies to ignite it, or to facilitate and foster the process. The adoption of the Sustainable Development Goals (SDGs) by the United Nations General Assembly and the successful conclusion of theClimate SummitCOP 21 in 2015, hailed as historic milestones in the global pursuit of shared prosperity in a peaceful and stable world, provide a good opportunity for researchers to bring new ideas on how best to implement policy agendas that are conducive to structural change. Both international covenants require all signatories (sovereign governments) to constantly assess