Chapter 2. New currents for shifting wealth

The 2010 Perspectives on Global Development (PDG) report argued that global wealth in the world had shifted, changing the course of development for lower- and middle-income countries. This chapter syntheses findings of the previous PGD editions and regional economic outlooks. It updates the trend towards the transformation of economic geography and economic convergence, focusing on its sustainability, in light of the fact that the People’s Republic of China (hereafter “China”) has begun rebalancing its economy in the context of its 2030 strategy. In addition, it takes stock of developments with respect to economic growth and the roots of the shifting wealth phenomenon. It further assesses the domestic and international drivers behind these developments.

    
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Since its inception in 2010, the OECD Development Centre’s Perspectives on Global Development series has investigated the increasing economic weight of developing countries in the world economy, a phenomenon referred to as “shifting wealth” (OECD, 2010[1]) (Box 2.1).

The global macroeconomic effects emanating from shifting wealth run deep throughout the developing world and crucially determine how poor countries deal with reducing poverty. Consequently, the transformation of economic geography has redefined development strategies and partners for poor countries. It has changed output linkages between emerging and developing countries, wages and terms of trade, and not least the geography of development finance.

With appropriate strategies, low-income developing countries could grow faster, lifted by the weighty fast-growing emerging economies. The initial opening of the People’s Republic of China (hereafter “China”) and India has hurt some middle-income countries in the short term. However, the sustained growth of these two emerging economic giants improves the long-term prospects of both low- and middle-income countries.

This sixth edition of the series, Rethinking Development Strategies, picks up on the shifting wealth theme by examining the rise of emerging economies and the implications for international relations. It pays particular attention to China’s evolving role.

The following chapter contains three main messages:

  • Since the 1990s, shifting wealth has evolved in three distinct phases: an opening up phase (1990-2000), a phase of pervasive convergence (2001-08), and a post global financial crisis (GFC) phase (2009-present).

  • Although shifting wealth has slowed down since the GFC, largely due to China’s domestic economic transformation, economic convergence continues.

  • This continuation is buoyed by growth in India, new low-cost labour manufacturing hubs and strong South-South linkages between developing economies.

Box 2.1. Earlier editions of the PGD examining shifting wealth

The five earlier editions of the series each examined shifting wealth from a particular policy focus:

  • The inaugural 2010 PGD, introduced the theme of Shifting Wealth, describing the new geography of development finance and the economic gravity shift towards the East and South, focusing on the increasing potential of South-South linkages.

  • The 2012 edition, Social Cohesion in a Shifting World, examined social cohesion in fast-growing developing countries and provided policy makers with recommendations for ways to strengthen it.

  • The 2013 edition, Industrial Policies in a Changing World, shed light on the renewed interest in industrial policies in developing countries.

  • The 2014 edition, Boosting Productivity to Meet the Middle-Income Challenge, argued that for sustained convergence developing countries needed to boost competitiveness and narrow their significant productivity gap with advanced economies.

  • The 2017 edition, International Migration in a Shifting World, described the evolution of international migration globally. It examined how the transformation of economic geography has impacted migration flows, focusing on the role of migration and non-migration policies in developing countries of origin and destination. It argued for the need for better national and global governance on migration policy to maximise the impact of migration on development.

Three phases of shifting wealth

Since the 1990s, China and India have grown much faster than OECD economies. Several large emerging economies began shaping the global macroeconomic landscape. Combined with very large populations, these growth differences have translated into a new world economy: the countries with the largest economic size are no longer also the richest countries in terms of gross domestic product (GDP) per capita. China has become the world’s largest economy with GDP measured in purchasing power parity (PPP) terms and the second largest behind the United States when measured in nominal values. The year 2008 was a watershed in global development as the weight of developing and emerging economies in the global economy tipped over the 50% mark (expressed in PPPs) for the first time (Figure 2.1).

Figure 2.1. Shifting weight in global economic activity is likely to continue, but at a slower pace, mostly because of the slowdown in China
Share in global GDP (in percentage, 1992-2022)
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Note: The next ten largest economies after Brazil, the Russian Federation (hereafter “Russia”), India, Indonesia, China, South Africa (BRIICS) and the OECD are: Saudi Arabia, Iran, Viet Nam, Nigeria, Thailand, Egypt, Argentina, Pakistan, Malaysia and the Philippines. Projections start in 2017.

Source: IMF (2017[2]), World Economic Outlook 2017 (database), GDP based on PPP share of world total, https://www.imf.org/external/pubs/ft/weo/2017/02/weodata/index.aspx (accessed in December 2017).

 StatLink https://doi.org/10.1787/888933856606

Three different periods of shifting wealth can be distinguished: an initial opening up phase, a convergence and spillover period, and a “new normal” or post-crisis phase (Figure 2.2). Each of these three phases differs importantly. Consequently, the entire globalisation period since 1990 may entail structural breaks that are often ignored. Distinguishing three phases of shifting wealth provides a richer menu for the formulation of strategies by developing countries; ignoring them might lead to costly strategic mistakes.

The 1990s represent a highly volatile period, particularly for the impact of several financial crises on emerging and developing economies. Conversely, the 2000s can be considered a more tranquil period for developing countries. The latter period was marked by enhanced integration of the global economy, the rising profile of China in the world economy (joining the World Trade Organization [WTO] in 2001) and high global liquidity. This configuration explains that the weight of OECD member countries in global economic activity held steady at roughly 60% throughout the 1990s, with the residual non-OECD weight at 40%. From the 2000s, the shift in global activity started to move in favour of the non-OECD world, which caught up with OECD member countries in 2009. From then, the non-OECD countries have extended their weight of global GDP: their relative share now assumes 60%, with the OECD at 40%. Within three decades of shifting wealth, we have witnessed a reversal in PPP-adjusted GDP weights in the world economy in favour of non-OECD countries. The weight of China and India’s output in the global economy has grown consistently throughout the three decades (Figure 2.2).

The emergence of the new global economic geography – shifting wealth – is thus best explained in three distinct periods of growth performance. Over the course of nearly three decades, starting in 1990, the global economy underwent structural transformation that shifted the world’s economic centre of gravity eastwards and southwards, from OECD countries to emerging economies.

Figure 2.2. The three phases of shifting wealth
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Opening up (1990-2000)

After years of relative isolation from the global economy, the initial “opening up” phase is best exemplified by three developments. These comprise China’s cautious market reforms in agriculture and foreign investment in 1978, India’s gradual economic liberalisation in 1991 and the dissolution of the former Soviet Union (FSU) in the same year. However, with China embarking on a second stage of more robust privatisation reforms in the late 1980s, the initial opening of China, India and the FSU to world markets was really felt from the 1990s onwards.

The world market economy experienced a significant supply shock through the tripling of the effective labour supply. The entry of many new workers into the global labour force, following the opening of formerly closed large economies, created a big wage shock. In the first years of the 1990s, the integration of China, India and the FSU brought new labour forces of 750 million, 450 million and 300 million respectively to the world economy. Along a core model of economic development, the Lewis (1945) or surplus labour model, the modern sector – and by extension the world economy – temporarily faced an unlimited supply of labour at near subsistence wages. As predicted by the Stolper-Samuelson theorem, the labour supply shock led to a drop in the price of wage-intensive goods. This, in turn, caused a reduction in the equilibrium wage; alternatively, low wage flexibility led to job losses.

The arrival of 1.5 billion workers doubled the number of people working in open, market-oriented economies, which halved the global capital-labour ratio (OECD, 2010[1]). Large emerging countries opening to trade increased the share of global workers with basic education. This, in turn, lowered the world average land/labour ratio. The relative endowments of other countries thus shifted in opposite directions, which tended to move their comparative advantage from labour-intensive manufacturing (Wood and Mayer, 2011[3]). Industrialisation and urbanisation in the emerging giants stimulated demand and prices of fossil energy and industrial metals, which in turn transferred wealth to their exporters.

During the 1990s, the convergence of developing countries relative to the Group of Seven (G7) average was mixed. Figure 2.3 shows that Brazil, South Africa and especially the Russian Federation (hereafter “Russia”) underperformed in the BRIICS group of countries (Brazil, Russia, India, Indonesia, China and South Africa). The three Asian BRIICSs – China, India and Indonesia – enjoyed growth rates sufficiently high to help their incomes converge towards G7 levels. For Latin America and sub-Saharan Africa in particular, the decade proved to be yet another period of disappointment after the “lost decade” – the debt-crisis prone 1980s. For countries of the FSU, long and deep recessions dominated the early years of the decade. Transitioning towards a market economy proved anything but easy, and some countries experienced major setbacks in human development.

Concerns that the entry of China into world markets would lead to deindustrialisation of other developing (and advanced) countries were confirmed (Rodrik, 2016[4]). While Asian countries and manufacturing exporters have been largely insulated from “premature deindustrialisation” – manufacturing activity, in part, even shifted to China’s neighbours – Latin American countries were especially hard hit. In addition, disruption in Russia and financial crises in some emerging countries of Asia and Latin America initially delayed output and welfare gains expected from liberalisation during the 1990s. Meanwhile, Africa suffered from a protracted debt crisis before debt was relieved at the end of the decade.

Pervasive convergence (2001-08)

The second phase of shifting wealth, from 2000 to the 2008 GFC, saw pervasive convergence of poor countries largely due to increasingly China-centric growth. Rapid urbanisation and industrialisation in Asia, in particular, led to rising raw material prices for fossil fuels and industrial metals. While oil and metal producers benefited, most OECD member countries as net commodity importers suffered depreciating terms of trade and losses in purchasing power.

Figure 2.3. Mixed convergence during the opening up phase
GDP per capita relative to average GDP in the G7 (1990-2000)
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Note: GDP per capita of developing countries relative to the G7 average for the years 1990 compared to 2000. The 45-degree line represents stagnation of per capita income in relative terms; the diamonds above the line indicate relative convergence of developing countries; those below the line are falling behind.

Source: IMF (2017[2])World Economic Outlook 2017 (database), (GDP per capita, constant prices (PPP, 2011 international dollars), http://www.clio-infra.eu (accessed in December 2017).

 StatLink https://doi.org/10.1787/888933856625

Simultaneously, net foreign assets positions turned in favour of China and oil producers whereas the United States’ net foreign debt position bulged, as a result of growing current account deficits. As global trade became increasingly imbalanced, China became singled out with respect to their currency management. In some circles, deindustrialisation in OECD member countries was attributed to external deficits. However, and in contrast, current account surpluses of around 100 countries had largely risen in response to the US current account deficit – the excess of US domestic investment over US national savings – during the 2000s (OECD, 2010[1]).

While large countries with very high growth, such as China and Russia, tended to attract the headlines, important economic acceleration also occurred among smaller countries. Every continent shared in this phenomenon. The new millennium saw the resumption – for the first time since the 1970s – of a trend towards strong convergence in per-capita incomes with the high-income countries. Converging countries are defined as those countries doubling the average per-capita growth of the high-income OECD countries.

In the 2000s, convergence became pervasive. The number of converging countries increased by nearly seven times, from 12 to 83, during the period. Meanwhile, the number of poor low-income countries more than halved from 55 to 25 (Figure 2.4).

Figure 2.4. Pervasive convergence largely due to China-centric growth
GDP per capita relative to average GDP in the G7 (2001-08)
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Note: GDP per capita of developing countries relative to the G7 average for the years 2001 compared to 2008. The 45-degree line represents stagnation of per capita income in relative terms; the diamonds above the line indicate relative convergence of developing countries; those below the line are falling behind.

Source: IMF (2017[2])World Economic Outlook 2017 (database), GDP per capita, constant prices (PPP, 2011 international dollars, http://www.clio-infra.eu (accessed in December 2017).

 StatLink https://doi.org/10.1787/888933856644

Apart from strong domestic economic growth and improving human development in emerging economies, shifting wealth forged the direct channels of interaction – mainly trade, lending and foreign direct investments – between the emerging giants and poor countries. These links between the largest converging economies and the rest of the developing world intensified throughout the pre-crisis period. The realignment of the global economy accelerated, including during the crisis years 2007 and 2008 as large converging countries remained in recession only briefly.

Around 2000, China’s influence also began to expand beyond goods and commodity markets into global financial markets. Seen initially as a producer of cheap consumer goods, China became the world’s biggest holder of US government debt. This accumulation by the Chinese government of foreign assets raised the country’s global, financial and macroeconomic importance. This had a dampening effect on US and hence world interest rates. This, in turn, added to lower interest rates caused by global wage pressures. China’s output gap, the difference between actual and potential growth, would henceforth have repercussions on key global interest and exchange rates. Moreover, many emerging economies moved from being net debtors to net creditors, due to high domestic saving rates and rapidly increasing foreign reserves through exports, particularly in Asia.

Backed by a growing surplus on the current account in their balance of payments and by high raw material prices, the oil-rich countries – as well as China – accumulated large foreign exchange reserves and increasingly real assets held in sovereign wealth funds. The switch of many emerging countries from net debtor to net creditor position stimulated both South-South trade and capital flows, further fuelling growth. A new geography of development finance had emerged, with emerging donors and lenders complementing the traditional donors (OECD Development Assistance Committee, DAC).

Post global financial crisis (2009-present)

In the third phase during the 2010s, the shifting wealth process has shown signs of a temporary slowdown. This was driven by both the global recession in the aftermath of the GFC and China’s economic transformation from a manufacturing and export-led economy to one based on services and consumption. Both the GFC and China’s transition implied a slump in oil and metals prices. This burdened commodity exporters, but also stimulated growth in commodity-importing countries.

Figure 2.5. Convergence slowed post-GFC
GDP per capita relative to average GDP in the G7 (2009-16)
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Note: GDP per capita of developing countries relative to the G7 average for the years 2009 compared to 2016. The 45-degree line represents stagnation of per capita income in relative terms; the diamonds above the line indicate relative convergence of developing countries; those below the line are falling behind.

Source: IMF (2017[2])World Economic Outlook 2017 (database), GDP per capita, constant prices (PPP, 2011 international dollars), http://www.clio-infra.eu (accessed in December 2017).

 StatLink https://doi.org/10.1787/888933856663

The growth differential between OECD and non-OECD countries began to narrow after its peak in 2009 during the crisis. Ten years since the 2008 tipping point, the pace of shifting wealth has slowed after the heady times of the 2000s. This change has taken place against a backdrop of fading external tailwinds, the rebalancing in China and depressed raw material prices that have affected commodity exporters. Although it is still very integrated in world trade, China’s participation in global value chains (GVCs) is no longer its main trade driver since the GFC. As Figure 2.5 shows, however, convergence has still occurred in the 2010s in many poorer countries towards the average of the G7 countries.

The economic growth regime that prevailed until the end of the 2000s, in which external demand played a leading role, is no longer in place. Thus, the dynamics of China’s foreign trade changed. Domestic demand and domestic capacity are now the major factors influencing the evolution of China’s foreign trade with important consequences for the geographic orientation of China’s exports and imports (Lemoine and Unal, 2017[5]).

Figure 2.6. China's trade rebalances towards developing economies
Chinese exports and imports across regions (1992-2016)
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Note: Regional trade is expressed in percentage terms of total trade.

Source: Authors' calculations based on World Bank (2018[6]), World Integrated Trade Solution (database), https://wits.worldbank.org/ (accessed in April 2018).

 StatLink https://doi.org/10.1787/888933856682

Simultaneously, the dominance of high-income countries in China’s trade has steadily been reduced as trade has been rebalanced towards developing economies (Figure 2.6). In Africa, for example, growth shifted from West to East as a result. Meanwhile, new global projects were undertaken such as China’s Belt and Road Initiative (BRI). They have fostered infrastructure finance and thus helped to start removing a central growth bottleneck in low- and middle-income countries. Finally, on the back of reform and favourable demography, India has joined China’s high growth path.

Developing countries may well enjoy a twin-turbo growth engine in the coming years. While China’s growth has been coming down from unsustainable levels, India’s growth has been rising – erratically so, however, given the impact of extreme weather. Consequently, the process of shifting wealth is not over. Instead, it has changed shape, becoming based on a broader foundation of actors and a reinforcement of mutual economic interdependencies.

The benefits and costs of shifting wealth to OECD member countries

The benefits of shifting wealth, including to the OECD, are well known. North and South, the rising living standards that came with globalisation initially lent widespread support to the view of trade as a key engine of economic growth. The expansion of GVCs became a strong driver of productivity, boosting intermediate trade – a boon for OECD producers of equipment goods. Exports from formerly poor countries translated into higher consumption and thus imports, not least OECD-based luxury brands. Intensified specialisation meant an improved allocation of resources also in OECD member countries. Consequently, capital and jobs shifted away from their least competitive uses and lowest added value towards higher-income sectors. Consumers in the OECD benefited from a higher purchasing power of wages with the drop in prices of low-skilled goods. They also enjoyed more product choice. The deterioration of China’s terms of trade through the mid-2000s indicates that its exports made the world better off (Wolf, 2006[7]). Improvements in the range and quality of exports, greater technological dynamism, better prospects for doing business and a larger consumption base all generated substantial welfare benefits for OECD countries. Overall, shifting wealth is a win-win phenomenon.

Nonetheless, the term “shifting wealth” has been criticised for conveying the dangerous notion of winners and losers. Consequently, the rise of protectionism and nationalism in some OECD member countries risks bringing the emergence of developing countries and the corresponding rapid reduction of global poverty to an end.

The challenge consists in an uneven distribution of shifting wealth benefits. Many major economic trends – globalisation, digitalisation and robotisation – are good for society on average, but not automatically good for everyone; they also generate losers, especially in the labour market. Besides mass immigration, these losers can play a decisive role in the rise of populism. An appropriate policy answer in advanced countries requires a sound diagnosis.

Global economic development brings unprecedented business opportunities and new jobs, including to the OECD. Rather than taking satisfaction in the movement, however, some view economic growth in the South as a threat. In contrast to the conventional “win-win” view of globalisation, recent studies on the “China shock” focus on how surging imports from China are costing jobs and have caused poverty to rise in the United States and elsewhere.

Autor, Dorn and Hanson (2016[8]) trace the substantial adjustment costs and distributional consequences of trade. These are most discernible in the local US labour markets in which industries exposed to foreign competition are concentrated. They also find adaptation in local labour markets to be slow. Specifically, they show wages and labour-force participation rates remaining depressed and unemployment rates remaining elevated for at least a full decade after the commencement of the China trade shock.

In the former mainstream consensus, trade could be strongly redistributive in theory, but was relatively benign and frictionless in practice. Evidence from the United States and elsewhere has challenged this view (Beyer and Stemmer, 2016[9]). Wood (2018[10]) has calculated (for 2011) trade estimates of the impact on labour demand in all OECD member countries of exports of manufactures and services from the South (all non-OECD countries). The base case shows that imports from the South reduced demand for labour in manufacturing by 18 million jobs.

The “elephant graph” of Lakner and Milanovic (2016[11]) demonstrates how the distribution effects of globalisation and technological change have put a strain on the OECD middle-class. The graph depicts income gains at each point of the global income distribution for the 20 years spanning the fall of the Berlin Wall to the 2008 financial crisis. Alvaredo et al. (2018[12]) updated the graph for the World Inequality Report 2018 for 1980 to 2016. The trough of low growth is identified with the bottom 90% in the United States and Western Europe (the global 50-95 income percentile). Higher income growth has been appropriated by the Asian middle class and the global top 1% income group (Sandefur, 2018[13]). The 50-95 income percentile mostly located in the OECD constitutes many frustrated voters.

The “China shock” literature does not suggest protectionism, but it risks being exploited by those who favour this policy response. Lower employment in certain sectors or regions in OECD member countries has resulted largely from technological changes rather than from trade (Dauth, Findeisen and Suedekum, 2017[14]). However, the two drivers are not always easily disentangled. Labour-displacing improvements in technology stimulated by trade and offshoring of technology have been suggested as further channels by which globalisation has harmed manufacturing jobs. In the OECD, both globalisation and technological change affect a middle class that is often marked by employment in industrial sectors, which has lost its good jobs or is afraid of imminent job losses.

Yet job losses from import competition alone do not provide the full picture. In fact, while the manufacturing share in aggregate employment in the US has been decreasing for decades, the share in real output remained roughly constant, largely due to improvements in productivity (Baily and Bosworth, 2014[15]). Moreover, by focusing on job gains from China-enhanced globalisation instead, Feenstra, Ma and Xu (2017[16]) show that the net manufacturing job impact was negative between 1991 and 2007, but balanced for an extended observation period 1991-2011. A positive net job effect exists for the United States since 2009 as Figure 2.7 suggests.

Analysis of globalisation often misses the three distinct phases that emerging countries have experienced and are still going as described above. Policy makers forgo the benefits of globalisation if their protectionist responses are only informed by the first opening phase of the 1980-90s. Changes in the global labour supply and of China’s fast transition to a “new normal” are reversing important wage and price trends.

Since the third phase of shifting wealth (from 2009 onwards), China has been transforming its production and trade patterns towards consumption, away from investment and intermediate GVC trade. The growth of global labour has peaked as China’s labour supply has been largely absorbed and its population begun to age rapidly, and as India’s fertility rate has come down (Goodhart and Pradhan, 2017[17]). A slowing working-age population will increasingly be mirrored by a rising middle-class consumer population. This stimulates “ordinary” global trade based mainly on local inputs and domestic demand fuelled by higher consumption, whereas intermediate processing trade has begun to stagnate (Lemoine and Unal, 2017[5]). Asia-driven wage pressures felt in the OECD are thus probably a thing of the past, with China’s wages rising rapidly in both dollar and yuan terms due to a shrinking labour force and increasing domestic productivity (Figure 2.8).

Figure 2.7. Since the start of China’s economic transformation, US manufacturing jobs have started to rebound
US manufacturing jobs (1975-2017)
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Note: The shaded area represents the shifting wealth period.

Source: US Bureau of Labor Statistics (2018[18]), Employment, Hours, and Earnings from the Current Employment Statistics survey (National) (database), All employees, manufacturing, seasonally adjusted, https://data.bls.gov/timeseries/CES3000000001 (accessed in May 2018).

 StatLink https://doi.org/10.1787/888933856701

Figure 2.8. Wages in China are rising rapidly
Manufacturing wages in China, expressed in annual averages over time (RMB, 1978-2017)
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Note: The shaded area represents the shifting wealth period.

Source: CEIC (2018[19])China Average Annual Wage: Manufacturing, China average annual wage: Manufacturing (annual averages over time in RMB, https://www.ceicdata.com/en/china/average-wage-by-industry-urban-nonprivate/avg-annual-wage-manufacturing (accessed in May 2018).

 StatLink https://doi.org/10.1787/888933856720

Why shifting wealth matters for the South

Shifting wealth has had a profound effect on global development since 1990. First, it re-drew the map of economic relations in terms of trade, financial flows and migration. Second, it boosted global growth, lifting millions out of poverty during the process. Third, it changed the global governance context, which meant that developing countries assumed new roles, but also needed to craft new strategies.

Global linkages

From the perspective of poor countries, the most important consequence of China and India’s entry into the global economy operated through both global and direct linkages (see the section on “Shifting wealth – a driver for South-South integration” below). The global impact has been visible in the contribution of the Asian giants to global growth (Figure 2.9). This is apparent both through their impact on the global terms of trade (Figure 2.10) and in the shift in net foreign asset positions towards emerging surplus countries (Figure 2.11) that subsequently financed development loans, grants and direct investment.

Figure 2.9. China and India have increasingly contributed to global economic growth, yet at a slower pace during the last decade
Contributions to global growth (percentage)
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Note: Advanced economies consist of currently 39 countries as defined by the IMF.

Source: IMF (2017[2])World Economic Outlook 2017 (database), GDP, current prices (PPP, international dollars), https://www.imf.org/external/pubs/ft/weo/2017/02/weodata/index.aspx (accessed in December 2017).

 StatLink https://doi.org/10.1787/888933856739

Growth in low- and middle-income economies from 2000 onwards has depended more on growth in China than on the G7. This constituted a reversal from the traditional OECD dominance in determining non-OECD growth (Garroway et al., 2012[20]). China’s growth impact was not limited to oil-exporting developing countries, but pertained to non-oil exporting countries as well.

China and India’s high growth has boosted global growth in recent years. From 2011 to 2016, China’s relative contribution to global growth was on par with advanced countries. This occurred despite per capita GDP growth falling in China from a top rate of 13.6% to 6.1% over 2007-16. India’s contribution to global growth has also risen since the early 2000s, on the back of a per capita income growth rate oscillating between 8.8% and 5.9% over 2010-16. However, China has contributed almost 30% to global growth in recent years, approximately 20 percentage points more than India.

As India is more closed and still considerably poorer than China, it cannot yet offset the impact of China’s slowdown on global growth and trade. Meanwhile, India has taken the lead over China in terms of GDP growth (but not growth in GDP per capita), with favourable demographics that encourage domestic savings and investment. In future decades, shifting wealth may well benefit from the China and India twin-turbo.

Figure 2.10. Shifting wealth reversed the decade-long deterioration in terms of trade for many developing economies exporting commodities
Terms of trade measured as the ratio between the oil price average relative to G7 manufacturing producer prices (1990-2016)
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Note: Global terms of trade are expressed as the ratio between crude oil price average and the G7 producer price index (PPI) for manufacturing. This ratio shows that (net barter) terms of trade of non-oil exporting developing countries suffer when oil prices go up relative to manufacturing prices.

Sources: Authors' calculations based on World Bank (2017[21]), Commodity Markets Outlook, Crude oil ($/bbl), http://pubdocs.worldbank.org/en/817261508960786112/CMO-October-2017-Data-Supplement.xlsx (accessed on  February 2018); and OECD (2017[22]), OECD Data (database), Producer price indices (PPI), https://data.oecd.org/price/producer-price-indices-ppi.htm (accessed in February 2018).

 StatLink https://doi.org/10.1787/888933856758

Shifting wealth reversed the decade-long decline in terms of trade for countries exporting raw materials. Until about 2000, continuing technological advances promoted the widely shared view that each unit of output required fewer units of raw-material input to produce; in other words, it was believed GDP was becoming “lighter”. Demand for commodities was perceived to remain subdued even in the face of robust economic growth. In fact, after 2000, demand for commodities was strong, on the back of high urbanisation rates in Asia. By the onset of the GFC in 2008, oil prices had quadrupled and prices for metals had almost doubled from 1995 levels. The changing terms of trade had major strategic implications for poor countries, framing the design of policies covering, for example, aid, foreign investment, trade negotiations and industrial strategies. For instance, whereas South Africa’s garment and textile industry came under tremendous pressure, Angola, a net oil exporter, benefited from strong rents from oil extraction.

Figure 2.11. Shifting wealth has triggered a shift in net wealth from advanced economies towards China and other large emerging economies
External wealth expressed in net foreign assets in percentage of GDP (1990-2014)
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Source: Authors' calculations based on Lane and Milesi-Ferretti (2018[23]), “The External Wealth of Nations Revisited: International Financial Integration in the Aftermath of the Global Financial Crisis”, https://doi.org/10.1057/s41308-017-0048-y.

 StatLink https://doi.org/10.1787/888933856777

Shifting wealth also created a new geography of development finance. A central feature has been the shift in net wealth from advanced economies towards China, Brazil, Russia and the Gulf States during the 2000s. Data demonstrate the switch in net foreign assets as a percentage of GDP for China and the United States (Figure 2.11). Driven by growing current account surpluses (mostly reflecting US deficits), these emerging countries accumulated assets worth trillions of US dollars. The focus was initially on financial assets (foreign reserves) at their central and national development banks. Increasingly, it concerned real assets held by sovereign wealth funds and other public savings vehicles. More recently, the rise of assets in development banks owned or founded by China and other large emerging countries such as Brazil and the Gulf States has boosted development finance.

Low-income countries could thus increasingly source capital flows from cash-rich emerging countries rather than from mostly OECD-country sources as they had before. The switch from advanced country to converging country sources of finance brought with it a higher share of state-sponsored capital as opposed to purely private sector sources. The diversification of capital sources brought benefits, unsurprisingly welcomed by recipients since they expanded their policy options.

Figure 2.12. Emerging partners boosted policy options for Africa
Based on a survey of perceived competitive advantage of development partners
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Note: The stakeholder survey was conducted in 40 out of 51 African countries covered in the report.

Sources: OECD et al. (2011[24]), African Economic Outlook 2011: Africa and its Emerging Partners, http://dx.doi.org/10.1787/aeo-2011-en; Reisen and Stijns (2011[25]), How emerging donors are creating policy space for Africa, https://voxeu.org/article/how-emerging-donors-are-creating-policy-space-africa (accessed in May 2018).

 StatLink https://doi.org/10.1787/888933856796

Emerging partners boosted new sectors and finance mechanisms. Aid is only one element of their toolbox, reflecting striking differences in engagement philosophies with traditional donors. Emerging donors offer broader sources of finance; more appropriate technology and training; low-cost and speedy infrastructure; and cheap generics, machinery and consumer goods. China has a perceived comparative advantage in building infrastructure, India in providing cheap generics, as well as skills and services, and Brazil in helping agriculture and agro-processing. To Africa, the emerging partners offered new opportunities to trade goods, knowledge and models. A survey on 40 African countries in 2011 found that emerging partners were relatively well perceived in the realms of infrastructure and innovation (Figure 2.12).

Growth expansion and poverty reduction

China became a global growth engine that was an additional driving force behind the growth performance in converging countries. Given the positive link between economic growth and poverty reduction (provided that economic inequality is sufficiently low), China’s growth likely translated into poverty reduction in poor countries. Estimates for 52 low- and middle-income countries from 1990 to 2000 had put the elasticity of poverty to growth at around minus two (Chhibber and Nayyar, 2008[26]). A rise of one percentage point in China’s annual per capita income growth, given the poor-country growth elasticity of 0.34 estimated by Garroway et al. (2012[20]) would thus translate into a 0.68% reduction in poverty in poor countries. In this sense, China may have been the most potent poverty reduction engine outside its borders during the first decade of the 21st century.

The World Bank defines extreme poverty as living with less than 1.90 international USD per day. Measured by this benchmark, extreme poverty in China, which affected 88% of its one billion people in 1981, had all but been eliminated by 2013. According to the World Bank, extreme poverty stood at 1.9% by 2013 in China, affecting 26 million Chinese.

Figure 2.13. China's economic growth helped diminish the share of global population living in extreme poverty
Extreme poverty defined as living below 1.90 international USD per day
picture

Note: The shaded area represents the shifting wealth period.

Source: World Bank (2018[27]), World Development Indicators (database), China share of world poverty, http://databank.worldbank.org/data/source/world-development-indicators (accessed in February 2018).

 StatLink https://doi.org/10.1787/888933856815

However, the substantial decline of global poverty was not only due to the poverty decline in China. According to Roser and Ortiz-Ospina (2018[28]), the world share of people living in extreme poverty outside China had fallen from 29% to 12% between 1981 and 2013 (Figure 2.13). During that period, world population grew from 4.5 billion to 7 billion. Despite rapid global population growth, the number of people outside China affected by extreme poverty had diminished from more than 1 billion to 743 million over 1981-2013. The decline in extreme poverty occurred despite growing inequality within countries.

Figure 2.14. Income inequality rose in both China and India
Inequality expressed as the top 1% and the bottom 50% of the income distribution (1990-latest)
picture

Note: Latest data for China are 2015 and for India are 2013.

Source: World Inequality Lab (2018[29]), World Inequality Database, Top 1% share, Bottom 50% share, https://wid.world/data/ (accessed in February 2018).

 StatLink https://doi.org/10.1787/888933856834

As an indicator of (rising) income inequality of the two Asian giants, Figure 2.14 presents, the percentage share of the top 1% (solid) and the bottom 50% (dotted) of pre-tax national income for both China (1990-2015) and India (1990-2013). Until the third sub-period of shifting wealth (post GFC, 2009-present), income inequality deteriorated continuously in China. Nonetheless, this trend has subsided since 2007; instead, income shares have stabilised. By contrast, income inequality in India – already higher than in China – continued to rise until 2013, the last year of observation. Comparable data from the World Inequality Report 2018 for the observation period since 1990 are not available for the other BRIICS.

Data for Brazil indicate unbroken income inequality: the top 1% reaps almost 30% of national income, the bottom half not even 15%, on a flat trend during the 2000s. Russia in the 1990s suffered a steep rise of the national income share appropriated by the top 1%, from egalitarian levels (around 5%) to 26.9% in 2007. Since then, the income share of the top 1% has come down to around 20%.

Wealth inequality within countries has recently experienced mounting interest in research (Piketty, 2014[30]). World wealth inequality, however, also depends on the rise or fall of wealth across countries and regions. The role of the fast-growing developing economies is an important element in the evolution of wealth inequality.

The 2001-08 phase of rapid income convergence of low- and middle-income countries in the wake of China’s commodity-hungry growth spurt has not only lowered global income inequality. It also helped lower global wealth inequality, despite higher within-country income and wealth inequality. Median and mean household wealth rose in all developing regions. Shifting wealth seems to have contributed – as it did for global income equality – to slightly more global wealth equality (Table 2.1).1

Table 2.1. Net household wealth
Expressed in percentage of world total

2000

2010

2017

Africa

0.9

1.2

0.9

Asia-Pacific (excluding Japan)

7.3

11.1

11.2

China

4.1

7.5

10.3

India

1.0

1.7

1.8

Latin America

3.0

3.7

2.9

Total South

16.3

25.2

27.1

Europe

29.6

33.7

28.4

Japan

17.0

10.7

8.4

North America

37.1

30.4

36.0

Total North

83.7

74.8

72.8

Note: Net household wealth is defined as the marketable value of financial assets plus non-financial assets (principally housing and land) less debts. World total net household wealth has risen from USD 117 trillion at the end of 2000 (a mean of USD 31 415 and a median of USD 1 867 for the 3.7 billion adults, defined as older than 20 years) to USD 280.3 trillion by mid-2017 (a mean USD 56 541 and a median of USD 3 582 for 5 billion adults).

Sources: Credit Suisse Research Institute (2017[31]), Global Wealth Databook 2017, http://publications.credit-suisse.com/index.cfm/publikationen-shop/research-institute/global-wealth-databook-2017-en/ (accessed in March 2018); Davies, J., R. Lluberas and A. Shorrocks (2010[32]), Global Wealth Databook 2010, https://publications.credit-suisse.com/tasks/render/file/index.cfm?fileid=88DC07AD-83E8-EB92-9D5C3EAA87A97A77 (accessed in March 2018).

Over the period 2000-17, net household wealth shifted East and South. Consequently, global household wealth inequality has been reduced during the 2000s. Most of the shift towards the South occurred during the first decade of the new millennium when income convergence was rapid, not least due to booming raw material prices. In the 2010s, by contrast, gains in the percentage share of world household wealth were given back by Africa and Latin America; only China kept gaining a higher relative share in world wealth.

Table 2.2 reveals the first decade of the 21st century lowered global wealth inequality, and also generated remarkable gains in median wealth.2 Broadly, median net wealth per adult doubled in all non-OECD regions listed in Table 2.2 during 2000-10. Since then (post GFC), however, median wealth kept rising only in China, dropping sharply in Africa. Despite being shown in constant US dollars, the numbers may indicate that sharp real depreciation of local currencies in countries with net raw material exports have dented mean household wealth and inflated household debt. This may also be the result of a lower demand for commodities in China.

Table 2.2. Median net wealth per adult
Expressed in constant USD

2000

2010

2017

Africa

499

939

438

Asia-Pacific

1 322

3 400

2 997

China

2 349

4 628

6 689

India

704

1 301

1 295

Latin America

3 099

6 388

5 159

World

1 867

3 709

3 582

Note: Asia-Pacific including Japan.

Sources: Credit Suisse Research Institute (2017[31]), Global Wealth Databook 2017, http://publications.credit-suisse.com/index.cfm/publikationen-shop/research-institute/global-wealth-databook-2017-en/ (accessed on  March 2018); Davies, J., R. Lluberas and A. Shorrocks (2010[32]), Global Wealth Databook 2010, https://publications.credit-suisse.com/tasks/render/file/index.cfm?fileid=88DC07AD-83E8-EB92-9D5C3EAA87A97A77 (accessed in March 2018).

Diverse regional growth dynamics

Aggregating countries across regions often disguises underlying heterogeneous growth dynamics. Strong economic growth episodes are not confined to certain periods or regions. In fact, many economies have experienced this growth at some point and increasingly so during the shifting wealth period. Volatility persisted throughout the 1990s, but has come down in the shifting wealth sub-periods since the early 2000s.

Figure 2.15 takes a longer perspective on economic growth and presents growth break estimates across economies on GDP per capita data. Breaks are defined as growth accelerations or upbreaks if average growth after the break exceeds the average growth rate during the previous period; downbreaks are defined as rapid growth slowdowns. Results obtained on the period prior to shifting wealth are comparable with earlier findings in the literature such as, for instance, Berg, Ostry and Zettelmeyer (2012[33]) and Kar et al. (2013[34]).

Developing countries observe more upbreaks than downbreaks in per capita GDP growth. Positive growth spurts have particularly dominated since the inception of shifting wealth, which produced an almost equal amount of upbreaks between 1990 and 2017 than in the previous four decades. Africa and Asia, with respectively 65% and 45% of total growth accelerations during shifting wealth, profited the most from this period of global prosperity. Judging by the number of rapid growth slowdowns, the GFC seems to have affected developing economies less. This picture stands in stark contrast to the experience of OECD countries. In this latter group, sustained growth decelerations predominate, and break patterns coincide with the major productivity slowdowns in the 1970s, as well as during and after the recent financial crisis. In turn, growth accelerations in developing countries tend to coincide with productivity rises (De Gregorio, 2018[35]).

Figure 2.15. During shifting wealth, growth accelerations appeared predominantly in developing economies
Growth accelerations and rapid slowdowns by region (1950-2017)
picture

Note: The break analysis is based on the Bai and Perron (2006[36]) algorithm computed through a Stata routine provided by Kerekes (2011[37]): 26 OECD member countries with a total of 37 breaks, 97 non-OECD countries with 122 breaks; minimum growth spell length of 8 years. The shaded area represents the shifting wealth period.

Source: IMF (2017[2])World Economic Outlook 2017 (database), GDP per capita, constant prices (PPP, 2011 international dollars), http://www.clio-infra.eu (accessed in December 2017).

 StatLink https://doi.org/10.1787/888933856853

Growth performance and development in transition

Shifting wealth has on balance supported sustained growth transitions to higher income status, especially in the 2000s. It continues to do so in the 2010s despite a slowdown in growth rates. Many low-income and middle-income countries crossed to higher income brackets, while reversals were extremely rare. Likewise, many countries graduated from International Development Association (IDA) eligibility, while returns to IDA eligibility were the exception. For low-income countries, measured economic vulnerability declined markedly, especially in the wake of multilateral debt relief in the 2000s (but some debt stress returned recently).

Still, a country’s growth does not necessarily go hand in hand with increased well-being for its citizens. Unless policies to counteract such trends are put in place, significant development vulnerabilities often remain. In fact, inequality can grow, even as countries become more prosperous. This is particularly relevant for countries with limited economic diversification, or those more exposed to the adverse impacts of climate change, rendering them more fragile. Therefore, GDP and other income-focused indicators are not all that matter. Further metrics to measure sustainable development are required. These need to trace vulnerabilities such as poverty, fragile middle classes, economic instability, regional disparities, insecurity, and unequal access to education and health services.

There are several ways to measure economic performance and transition. Among the most common measures are the World Bank’s country income status and a country’s IDA eligibility (i.e. aid dependence). A third, broader, measure of transition is the United Nations’ Least Developed Country (LDC) categorisation.

Table 2.3 presents country income classifications for 25 “converging” countries that managed to exceed average G7 growth rates during 1990-2016. While not all countries shown managed to cross income-classification thresholds, those that have converged in relative terms can be identified in all three developing regions. The table identifies 20 transitions from low- to lower-middle to upper-middle or to high-income status as defined by the World Bank. China climbed two income categories, from low- to upper-middle income status. Chile, Uruguay and Panama reached high-income status, the only “converging” countries leaving the “middle-income trap” behind during the period of shifting wealth.

However, climbing the economic ladder is by no means automatic and reversals of fortunes often occur. For instance, Argentina and Russia were downgraded from high to upper-middle income in 2014. And although convergence in income levels may have been achieved, development challenges and pockets of fragility remain across income levels.

Since the establishment of IDA in 1960, there have been 44 transitions from IDA eligibility. Several countries have transitioned more than once as they had to return to IDA eligibility. Eleven countries suffered such reversals in IDA eligibility, with most transitioning during the 1980s and particularly exposed to commodity prices, political instability and debt stress (Sumner, 2016[38]).

Table 2.3. Transitions in World Bank income status
GNI (Gross national income) per capita classification

Country

Initial Income Level

1990s

2000s

2010s

Africa

Burkina Faso

Low-income

Low-income

Low-income

Low-income

Egypt

Low-income

Lower middle-income

Lower middle-income

Lower middle-income

Mauritius

Lower middle-income

Upper middle-income

Upper middle-income

Upper middle-income

Mozambique

Low-income

Low-income

Low-income

Low-income

Lesotho

Low-income

Low-income

Lower middle-income

Lower middle-income

Uganda

Low-income

Low-income

Low-income

Low-income

Asia

 

 

 

 

Bangladesh

Low-income

Low-income

Low-income

Lower middle-income

Cambodia

Low-income

Low-income

Low-income

Lower middle-income

China

Low-income

Lower middle-income

Lower middle-income

Upper middle-income

India

Low-income

Low-income

Lower middle-income

Lower middle-income

Indonesia

Low-income

Low-income

Lower middle-income

Lower middle-income

Lao PDR.

Low-income

Low-income

Low-income

Lower middle-income

Malaysia

Lower middle-income

Upper middle-income

Upper middle-income

Upper middle-income

Nepal

Low income

Low-income

Low-income

Low-income

Pakistan

Low-income

Low-income

Lower middle-income

Lower middle-income

Sri Lanka

Low-income

Lower middle-income

Lower middle-income

Lower middle-income

Thailand

Lower middle-income

Lower middle-income

Upper middle-income

Upper middle-income

Turkey

Lower middle-income

Upper middle-income

Upper middle-income

Upper middle-income

Viet Nam

Low-income

Low-income

Lower middle-income

Lower middle-income

Latin America

 

 

 

 

Chile

Lower middle-income

Upper middle-income

Upper middle-income

High-income

Costa Rica

Lower middle-income

Lower middle-income

Upper middle-income

Upper middle-income

Dominican Republic

Lower middle-income

Lower middle-income

Upper middle-income

Upper middle-income

El Salvador

Lower middle-income

Lower middle-income

Lower middle-income

Lower middle-income

Mexico

Lower middle-income

Upper middle-income

Upper middle-income

Upper middle-income

Panama

Lower middle-income

Upper middle-income

Upper middle-income

High-income

Peru

Lower middle-income

Lower middle-income

Upper middle-income

Upper middle-income

Uruguay

Upper middle-income

Upper middle-income

Upper middle-income

High-income

Note: The country income classifications are derived from the World Bank and represent income thresholds as of 1 July 2018. Only countries with a continuous G7-relative per capita improvement throughout the entire shifting wealth period are presented.

Sources: Authors’ calculations, based on World Bank (2018[39])World Bank Country and Lending Groups, Historical classification by income, https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups (accessed in August 2018).

Focusing on countries from Africa, Asia and Latin America, Table 2.4 presents the recent history of IDA graduation and reversals for the three sub-periods of shifting wealth – the 1990s, 2000s and 2010s. The volatile 1990s had nine episodes of reversals – a return to IDA eligibility – but only four graduation episodes. This was a result of debt overhangs and slumping commodity exports, which in turn triggered capital flight. The Heavily Indebted Poor Countries (HIPC) initiative of the World Bank and International Monetary Fund (IMF) was rolled out in 1996; the Multilateral Debt Relief Initiative followed in 2005. Unsurprisingly, the debt relief initiatives stopped the trend towards IDA reversals in the 1990s. However, the decade of “pervasive convergence” – the 2000s up to the GFC – failed to leave marks in the IDA graduation process as only Indonesia graduated from IDA eligibility. During the 2010s, India – IDA’s most important client – graduated (with several other countries). This triggered intense debate about the future of IDA and other multilateral concessional windows (Garroway and Reisen, 2014[40]). The 2010s saw only one reversal back to IDA eligibility: conflict-ridden Syria.

Table 2.4. IDA eligibility and LDC graduation/reversals

1990s

2000s

2010s

IDA graduates

The Philippines (1993)

Indonesia (2008)

Angola (2014)

China (People’s Republic of) (1999)

Azerbaijan (2011)

Egypt (1999)

Bolivia (2017)

Equatorial Guinea (1999)

India (2014)

Sri Lanka (2017)

Viet Nam (2017)

IDA reversals

Cameroon (1994)

Papua New Guinea (2003)

Syrian Arab Republic (2017)

Republic of the Congo (1994)

Côte d’Ivoire (1994)

Egypt (1991)

Honduras (1991)

Indonesia (1998)

Nicaragua (1991)

Nigeria (1989))

Zimbabwe (1992)

LDC graduates

Botswana (1994)

Cabo Verde (2007)

Maldives (2011)

Samoa (2014)

Equatorial Guinea (2017)

Sources: IDA Graduates, World Bank (2018[41]), IDA Graduates, http://ida.worldbank.org/about/ida-graduates (accessed in April 2018); and UN (2018[42])List of Least Developed Countries (as of March 2018), https://www.un.org/development/desa/dpad/wp-content/uploads/sites/45/publication/ldc_list.pdf (accessed in March 2018).

Graduating from LDC status

A third measure of economic transition, the LDC status, is more concerned with a multidimensional range of factors than the World Bank country income status and IDA eligibility. The United Nations has designated 47 countries as LDCs, which together have more than a billion people. The LDCs comprise a category of states that are deemed highly disadvantaged in their development process, for structural, historical and geographical reasons. These countries are also characterised by their vulnerability to external economic shocks, natural and human-made disasters, and communicable diseases. The United Nations Economic and Social Council reviews the list of LDCs every three years in light of recommendations by the Committee for Development Policy (CDP). The CDP uses poverty (per capita gross national income), human assets (nutrition, health, school enrolment and literacy) and economic vulnerability (e.g. exports and agricultural production, see below) to determine LDC status.

To graduate out of LDC status, a country must reach certain thresholds in two of the three indicators over two reviews. Since its inception in 1971, more countries have been given such a status than have graduated from it. In fact, from 1972 to 1991, 23 countries were added to the LDC list, joining the original 24 countries. The first country to graduate was Botswana in 1994, during the first phase of shifting wealth. However, in contrast to the transitions based on mere economic performance, only one country (Cabo Verde) graduated in the first decade of the 2000s. Since then, the Maldives (2011), Samoa (2014) and Equatorial Guinea (2017) have graduated, with Vanuatu and Angola expected to leave the LDC status soon. The lower transition count, compared to the two measures above, reflects the importance of the multidimensionality of development and that social outcomes do not always piggyback economic development. The absence of returns to LDC status also suggests the UN measure is a more appropriate indicator of sustainable development.

The Fourth United Nations Conference on the LDCs adopted the Istanbul Programme of Action (IPoA) in May 2011 for the decade 2011-20. It reflects a common vision and strategy for the sustainable development of LDCs with a strong focus on developing their productive capacities. A broad range of actors is expected to contribute to IPoA implementation, including donor countries, developing countries, parliaments, the private sector, civil society, the UN system, and international and regional financial institutions. LDC IV Monitor, a partnership established by eight organisations (including the OECD Development Centre) aims to help deliver commitments to the LDCs more effectively in order to help them meet the criteria for graduation. This is closely related to the objective to achieve sustained, equitable and inclusive economic growth in LDCs to at least a level of 7% annually. The IPoA focuses on reducing vulnerabilities of LDCs and addresses new challenges to development. This includes the effects of the interlinked food, fuel and economic crises and climate change, with a strong focus on structural transformation through increasing productive capacity.

To be sure, there is tentative evidence that LDCs have made progress on two accounts: a) in reducing economic vulnerability; and b) in shifting resources from low-productivity to high-productivity areas. But global warming increasingly raises LDC physical (rather than economic) vulnerability. Higher physical shock exposure undermines resource shifts into promising high-productivity areas such as horticulture and tourism. Both shifts are connected prerequisites for a sustained transition for LDCs.

Assessing LDCs’ shock exposure beyond policy shortcomings has produced two kinds of vulnerability indices (Guillamont, 2011[43]). These have recently been used for allocation of European Union (EU) development funds:

  • Structural economic vulnerability (as measured by the UN Economic Vulnerability Index, EVI). EVI is a composite split evenly between “exposure” (size, location, agricultural share) and “shock intensity” (both natural and trade). EVI would be used for the allocation of development assistance.3

  • Physical Vulnerability to Climate Change Index (PVCCI). PVCCI is split evenly between “risks related to progressive shocks” (flooding due to sea-level rise; increasing aridity) and “risks related to the intensification of recurrent shocks” (rainfall; temperature). PVCCI could be used for the allocation of adaptation resources.

Structural economic vulnerability measured by the EVI is significantly higher in LDCs than in non LDCs on average over 1990-2013. Although average EVI has decreased in both categories of countries, it has decreased faster in LDCs than in non-LDCs in recent years. This is especially the case since 2003-04 when debt relief had been granted to 145 countries, as shown in Figure 2.16, for 1990-2013 countries (Feindouno and Goujon, 2016[44]).

Figure 2.16. Evolution of the economic vulnerability index
Expressed as annual averages across country groups
picture

Note: The index is constructed using eight different vulnerability components: population size, remoteness from world markets, export concentration, share of agriculture, forestry and fisheries in GDP, share of population living in low elevated coastal zones, export instability, instability of agricultural production, victims of natural disasters. The higher the index, the more economically vulnerable the country or region.

Source: Feindouno and Goujon (2016[44]), The retrospective economic vulnerability index, 2015 update.

 StatLink https://doi.org/10.1787/888933856872

The EVI indicator seems to be blind to looming debt problems, although LDCs have a low degree of debt tolerance. While their official sovereign (Paris Club) and multilateral debt was relieved by debt relief in the mid-2000s, private-sector debt and emerging-partner (mostly China) debt has risen fast in some countries. Debt burdens and vulnerabilities have risen significantly since 2013 in many developing countries. This reflects a mix of factors, including exogenous shocks and loose fiscal policies (Diao, McMillan and Rodrik, 2017[45]). At the end of 2017, 68% of LDCs were assessed as under severe or moderate debt distress; two were in default (IMF, 2018[46]). Two-fifths of LDCs (most of them in sub-Saharan Africa) faced significant debt challenges in 2017, up from one-fifth in 2013/14. Most debt-distress LDCs were classified as “diversified exporters” (rather than simply fuel or copper), reflecting weaker fiscal revenues and spending overruns, but also higher capital spending.

Whether sustained development requires higher industrialisation or whether “premature deindustrialisation” will stop development underway is open to debate (Sumner, 2018[47]). First, a sustained development process requires a shift of resources from low-productivity to high-productivity sectors (Lewis, 1954[48]). Second, it requires a larger share of resources devoted to sectors with potential for rapid productivity growth.

Diao, McMillan and Rodrik (2017[45]) confirm the importance of Lewis-type structural change for recent growth acceleration in low-income countries. However, in contrast to earlier East Asian experiences, rapid industrialisation does not seem to have driven recent growth accelerations in middle-income countries. The industry share (expressed as value added in percentage of GDP) in both the upper- and lower-middle income groups has reverted from peaks of the mid-2000s (Figure 2.17).

Figure 2.17. Industry share in GDP has reverted from peaks in upper- and middle-income countries, but recently picked up in low-income countries
Expressed in percentage of GDP
picture

Source: World Bank (2018[27])World Development Indicators (database), Industry (incl. construction), value added (% of GDP), http://databank.worldbank.org/data/source/world-development-indicators (accessed in February 2018).

 StatLink https://doi.org/10.1787/888933856891

Stalled manufacturing globally has worried many development experts that African LDCs have lost the opportunity to emulate East Asia's economic trajectory. Yet Africa has performed relatively well. Low-income countries saw their industry share slowly but steadily rise, especially in the 1990s and 2010s. This was not merely a reflection of commodity cycles, as illustrated by the spectacular case of Ethiopia.

However, Africa seems to owe structural transformation not only to traditional industries, but to new developments in tradable services and agro-industries that resemble traditional industrialisation (Coulibaly, 2018[49]). Aside from horticulture and agro-business, these new industries include information and communication technology-based services and tourism.

Shifting wealth – a driver for South-South integration

South-South integration has also supported development in transition. In fact, the dynamism of South-South economic ties has been an essential element of shifting wealth since the 1990s.

In his 1979 Nobel Prize lecture, Sir Arthur Lewis (1979[50]) had already envisaged the important role of South-South trade for sustained GDP convergence of the southern world:

The real problem is whether LDCs will persist in rapid growth despite the slowdown of the MDCs [More developed countries]. If the economy is still dependent, the balance of payments will pull it down; but if it has attained self-sustaining growth, the weakness in the foreign exchanges merely launches a drive to export to other LDCs, and the weakness in the balance of payments is then only transitional. If a sufficient number of LDCs has reached self-sustaining growth we are into a new world. For this means that instead of trade determining the rate of growth of LDC production, it will be the growth of LDC production that determines LDC trade, and internal forces that will determine the rate of growth of production. (Lewis, 1979[50])

Are we into that new world imagined by Arthur Lewis 40 years ago? The answer is yes and no.

Yes, because the non-OECD countries have increased their share in world output, merchandise trade and finance (including remittances). The corresponding trends will be documented in the following sections. Yes, because the relative shift in net foreign assets positions (the shift in net wealth) away from the group of OECD member countries has helped fund the creation of a new geography of development finance, not least the Belt and Road Initiative (BRI) by the Chinese government.

No, because China dominates the respective non-OECD shares in world output, merchandise trade and finance. This holds in a directly observable sense, but also indirectly as China’s rise and development cycles have impacted global factors. This, in turn, has (temporarily) raised non-OECD shares in the aggregate, especially during the second period (2000-09) of shifting wealth. The most striking example is the temporary rise of oil and metal prices that led to rising shares of non-OECD raw material exporters in world trade.

Much of South-South integration was driven by raw materials, especially during the 2001-08 phase of pervasive convergence:

  • Higher prices for raw materials boosted export values for net commodity exporters and the import bills of net commodity importers, including China, which boosted South-South trade value.

  • Higher resource rents filled foreign exchange reserves and assets of sovereign wealth funds in oil- and copper-producing countries, which were reinvested in and lent to developing countries.

  • Immigration into the Gulf States was stimulated by higher oil earnings, boosting remittances especially to South Asia.

  • Swaps – where revenues from the export of natural resources are used as collateral for a loan to finance infrastructure development – stimulated South-South co-operation in new ways not accounted for by conventional official development assistance (ODA).

Subsequently, developing economies met the strong decline in commodity prices with generally deeper integration on both the trade and financial sides. Policy initiatives by the Chinese government have thereby turned out to be key in fostering this shift to deeper South-South integration.

South-South trade

By 2010, developing countries accounted for around 42% of global merchandise trade, with South-South flows making up about half of that total (UNCTAD, 2013[51]). South-South trade has risen fast both as part of extended global production networks and to satisfy the demands of a growing middle class. The dollar value of South-South trade multiplied more than 13 times to USD 4 trillion in 2016 since China joined the WTO in early 2001 (Figure 2.18). In contrast to a drop in North-North trade and stagnation in South-North trade, South-South trade remained dynamic even in the post-crisis period.

The impressive headline development of South-South trade, however, disguises quite an uneven pattern, as will be shown below in some detail:

  • South-South trade has remained dynamic even post GFC, thanks to China and the LDCs.

  • Correcting for China and LDCs, South-South trade shares have declined as a percentage of “southern” exports over the past two decades, reflecting lower South-South shares in the exports of middle-income countries.

  • As South-South trade has been increasingly China-centric, there are doubts whether it can still offer a developmental promise absent in North-South trade. It is reassuring, though, that LDCs managed to double their share in intra-South trade since 1995.

Much developmental hope has been attached to the rise in South-South trade, resonating with the former structuralist literature, inspired by the 1950 Prebisch-Singer hypothesis. The structuralist school had argued that North-South trade would leave the South in a constant state of underdevelopment, because of deteriorating terms of trade, slow technology transfer and concentration on low-end products. South-South trade, by contrast, would benefit developing countries by stimulating the product and geographical diversification of their exports, thus reducing vulnerability to output cycles in the North (Didier, 2017[52]). The PGD 2010 (OECD, 2010[1]) pointed to further benefits of South-South relative to North-South trade: more trade creation than trade diversion in practice; better learning-by-doing effects; intermediate technology transfer; proximity; and eased integration into global value chains.

The outstanding role of China driving South-South trade and the role of booming oil and metal prices have often been obfuscated (see e.g. Aksoy and Ng, (2014[53])). However, China has largely driven the surge in South-South trade, directly and indirectly, accounting for almost half of South-South exports. China’s directly measurable impact is clearly indicated by the right column in Figure 2.18, which depicts South-South trade excluding China: excluding China’s (direct) share from the trade data shows stagnation of South-South trade from 2008. While that trade was virtually nil in 1990, it had reached USD 1.9 trillion by 2008, thanks to rising raw material prices and Chinese infrastructure building. As it is difficult to disentangle raw material prices and capacity building from the trade data, these are China’s indirect drivers of South-South trade. In addition to its importance in Southeast Asia, China became Africa’s biggest commercial partner in 2009 (AfDB/OECD/UNDP, 2017[54]), while expanding commercial ties with Latin America too (OECD/CAF/UN ECLAC, 2015[55]).

Figure 2.18. South-South trade is still dynamic, but China-centric
Expressed in USD trillion
picture

Note: North refers to developed countries and South refers to developing countries, according to the classification in the UNCTAD Handbook of Statistics, i.e. excluding transition economies.

Source: Authors' calculations based on UNCTAD (2018[56]), International trade in goods and services (database), Merchandise: Intra-trade and extra-trade of country groups by product, annual, http://unctadstat.unctad.org/wds/ReportFolders/reportFolders.aspx (accessed in April 2018).

 StatLink https://doi.org/10.1787/888933856910

Figure 2.19 (Panel A) indicates the percentage shares in total southern exports of total South-South trade, South-South trade excluding China, and LDC-South trade. South-South trade clearly got a boost from China’s WTO accession and booming raw material prices, particularly from 2001 (42.3%) to 2013 (58.5%). Excluding China from the trade data, however, indicates a flat trend in southern intra-group trade shares during the observation period, oscillating around 30%. This trend in South-South trade is particularly driven by middle-income countries (excluding China). LDC-South trade shares have increased over this period (Figure 2.19, Panel B). Finally, the cyclical upswing of advanced (northern) countries may explain the recent drop in total South-South trade shares.

With South-South trade being China-centric and China’s economy increasingly resembling advanced economies, it is an open question whether South-South trade can still offer a developmental promise that might be missing in North-South trade. Therefore, Figure 2.19 (Panel B) zooms in on LDC-South trade shares 1995-2016 (as percentage of total southern exports). That share doubled from 2% to 4% during the past two decades, particularly since China’s WTO accession in 2001. The continuous rise of the poorest countries’ share in South-South trade – through peaks and troughs of the commodity cycle – should be indicative of positive development factors. Most likely it reflects improved infrastructure that helps facilitate trade, but also regional integration (such as in West Africa) and other South-South free trade agreements (Wignaraja and Lazaro, 2010[57]). With China’s transitioning to the “new normal”, developing economies may increasingly profit from a transferral of manufacturing activities to low-cost destinations.

Figure 2.19. While South-South trade has expanded and become more China-centred, the LDCs have doubled their trade share with the South
Trade shares between specific groups of countries (1995-2017)
picture

Note: Trade shares are expressed as percentages of total southern exports.

Source: Authors' calculations based on UNCTAD (2018[56]), International trade in goods and services (database), Merchandise: Intra-trade and extra-trade of country groups by product, annual, http://unctadstat.unctad.org/wds/ReportFolders/reportFolders.aspx (accessed in April 2018).

 StatLink https://doi.org/10.1787/888933856929

The role of China in South-South trade

Since the GFC, Chinese imports have been the driving force for South-South trade. World imports determine the export potential for developing countries, but were almost flat between 2008 and 2016 as a result of cyclical and structural factors. Chinese imports, by contrast, continued to grow. The percentage share of China’s imports in world imports has surged since China’s WTO accession, from 2.3% the year before to 9.7% in 2016, the latest year for which comparable trade data are available. Table 2.5 presents world trade as trends in imports over 1990-2016.

Table 2.5. Imports of goods and services
World imports expressed in current USD trillion

1990

2000

2008

2016

World imports

4 304

7 893

19 455

20 139

China’s share (in percentage)

1.1.

2.3

5.9

9.7

South (excluding China) (in percentage)

21.3

22.7

26.8

28.0

Source: Authors' calculations based on UNCTAD (2018[56]), International trade in goods and services (database), Merchandise: Intra-trade and extra-trade of country groups by product, annual, http://unctadstat.unctad.org/wds/ReportFolders/reportFolders.aspx (accessed in April 2018).

The fast growth of China’s market share in the world can be explained through several transforming factors. Until the mid-2000s, China’s export performance was based on strong price competitiveness due to two reasons. First, rural surplus kept labour costs down. Second, the yuan stayed competitive despite surpluses in the balance of payments. China’s import growth expanded fast during the 2000s (Table 2.5).

China’s position in world trade continues to rise. However, this situation no longer seems to stem primarily from its participation in global GVCs (Lemoine and Unal, 2017[5]). While processing activities have declined rapidly, China’s ordinary trade has proved relatively resilient. It has become the most dynamic component of China’s international trade. The sectoral and geographical characteristic of ordinary trade is quite different from that of processing trade. Ordinary imports are primarily intended to be marketed or used domestically.

Figure 2.20 presents pie charts on China’s import composition for the years 2000 (pre-WTO), 2008 (GFC) and 2016 (latest). Manufactured goods (consisting mostly of electronics) and chemicals declined steadily as a share of China’s imports. Meanwhile, miscellaneous manufactures and food imports rose. The cyclical component machinery and transport equipment remained China’s most important import category. Its share of fuel- related imports has come down quite markedly since 2008.

Figure 2.20. China's imports became more balanced towards domestically used and marketed goods
Goods imported (percentage of total imports)
picture

Source: Authors' calculations based on UN (2018[58]), Comtrade (database), Imports of goods (percentage of total Chinese imports), https://comtrade.un.org/data (accessed in June 2018).

 StatLink https://doi.org/10.1787/888933856948

The relatively lower importance of fuel and metals also explains why the share of developing regions came back overall between 2008 and 2016. The continuous slide in the import share from East Asia indicates the relatively lower importance of processing GVC trade in China’s foreign trade (Figure 2.21). In the years before, notably Latin America and sub-Saharan Africa had enjoyed growing shares in China’s imports until the GFC.

Figure 2.21. China increasingly imports from regions other than East Asia
Regional trade shares (percentage of total imports, 2000; 2008; 2016)
picture

Source: Authors' calculations based on UN (2018[58]), Comtrade (database), Regional trade shares (percentage of total Chinese imports), https://comtrade.un.org/data (accessed in June 2018).

 StatLink https://doi.org/10.1787/888933856967

Complex cross-border production-sharing activities related to GVCs were the most important force driving globalisation and the growth of global GDP during 1995-2000 and 2000-08 before declining during 2012-15 (WTO, 2017[59]). GVCs create new opportunities for developing countries, increase their participation in global markets and enable them to diversify exports. However, they have apparently not been inclusive enough to foster South-South links. Proximity to the world’s three major production hubs and high-income markets – the United States, Asia and Europe – is highly important (WTO, 2017[59]). It also matters for developing countries to which degree trade partners are integrated within regional GVCs.

Many developing countries are increasingly involved in GVCs, carrying out different steps in partitioned production processes (Cadestin, Gourdon and Kowalski, 2016[60]). Southeast Asian economies and those in Europe and Central Asia show the highest degrees of participation, while Middle East and North African countries also have relatively high participation rates. South Asia, along with regions in sub-Saharan Africa, trail behind. Southeast Asia – the region with some of the most comprehensive and deepest regional integration agreements among developing countries – has the highest average share of intra-regional GVC participation. In the rest of the developing world, the share of intra-regional GVC participation is lower than the share of extra-regional links (Kowalski et al., 2015[61]).

WTO (2017[59]) reports a reduction in cross-country production-sharing in complex GVC during the economic recovery since 2011, contrasting with patterns in three previous recovery periods over the past 20 years. Indeed, the structure of value-added creation (pure domestic production, traditional trade production, simple GVC and complex GVC) during the economic recovery since 2011 reverses previous patterns. Unlike the rapid globalised production driven by the growth of complex GVC activities in previous periods, the economic recovery since 2011 has less cross-border production-sharing activities in complex GVCs. This may also mean the China-centric growth of middle- and low-income countries observed during the 2000s has been lower since 2011.

A new geography of South-South development finance

Especially since the early 2000s, large emerging countries have become important providers of development funds. Shifting wealth has allowed governments to tap a bigger pool of “transformative infrastructure finance” and to choose from more financing options (Xu and Carey, 2015[62]). From a long-term development perspective, infrastructure finance is arguably the most important prerequisite to close the infrastructure gap. This gap has been identified as the major bottleneck for delivering on growth and on the Sustainable Development Goals (SDGs), notably in Africa. Much of the new funding supply is through official bank credit outside the Paris Club framework, however. This, in turn, has amplified concerns that a new debt overhang might be building in the absence of a concerted mechanism for debt prevention and resolution.

The rise in South-South finance is being channelled through three major vehicles: i) increased remittances within the non-OECD area, often resulting from commodity riches; ii) growing corporate equity participation via mergers and acquisitions (M&A), as well as greenfield foreign direct investment (FDI) by emerging multilateral companies; and iii) an extension of bilateral and multilateral bank credit supply, notably by China. The overall rise of development funds has occurred despite a downward trend of ODA as a fraction of recipient countries’ rising GDP. Western donors, including private ones, had reduced investment in infrastructure in the past decades. Instead, they devoted more attention to poverty reduction, health, good governance and climate change mitigation.

Total external development finance to all developing countries more than doubled between 2003 and 2012 to USD 269 billion (Prizzon, Greenhill and Mustapha, 2016[63]). In 2012, development finance flows beyond ODA by DAC donors – excluding FDI, portfolio equity and remittances – accounted for USD 120 billion, or around 45% of total development finance; 13% of this USD 120 billion was from so-called emerging donors, such as Brazil, China, the Gulf States, India, Malaysia, Russia and Thailand.

Over recent years, remittance flows – funds sent by migrants living and working abroad to their home countries – have been increasing in line with expanding developing countries’ GDP (Figure 2.22). Booming oil prices translated in higher demand for immigrants in the construction and other service sectors of the Gulf States and Russia. While private capital mainly flows to emerging countries, remittances are particularly important in poorer countries where they can represent up to a third of national GDP. India, China, the Philippines and Mexico receive the largest remittances in the world by amount. As a share of GDP, however, smaller countries such as Tajikistan (42%), Kyrgyzstan (30%) and Nepal (29%) were the largest recipients.

Figure 2.22. Remittances have been increasing with developing economies’ GDP
External financial receipts (percentage of developing economies' GDP in PPPs, 2000-15)
picture

Note: The figure presents three-year moving averages, scaled by developing economies' GDP based on PPPs.

Sources: Authors' calculations based on World Bank (2017[64])Migration and Remittances Data, http://www.worldbank.org/en/topic/migrationremittancesdiasporaissues/brief/migration-remittances-data (accessed in  July 2018); OECD (2018[65])International Development Statistics (IDS) online databases, Total net ODA disbursements from all donors to developing countries, https://stats.oecd.org/qwids/#?x=1&y=6&f=3:51,4:1,5:3,7:1,2:262&q=3:51+4:1+5:3+7:1+2:262+1:1,2,25,26+6:2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015 (accessed in July 2018).

 StatLink https://doi.org/10.1787/888933856986

The top five immigration countries, relative to population, are outside the high-income OECD member countries (World Bank, 2016[66]): Qatar (91%), United Arab Emirates (88%), Kuwait (72%), Jordan (56%) and Bahrain (54%). Due to an upsurge in migration, remittance flows into developing countries sprang up in the 1990s, becoming another important financial resource for developing countries. During 1970-2000, workers’ remittances to sub-Saharan Africa only reached 2.6% of GDP. This inflow was clearly lower than its official inflows that added up to 11.5% of sub-Saharan Africa’s GDP (Buch and Kuckulenz, 2010[67]). This trend contrasted to North Africa and the Middle East, which received almost 9% of GDP through remittances over that period. By 2015, remittances represented the largest source of external finance for many developing countries, ahead of ODA and FDI. At that time, worldwide remittance flows were estimated to have exceeded USD 601 billion. Of that amount, developing countries were estimated to have received about USD 441 billion, nearly three times the amount of ODA.

Table 2.6. Developing country FDI outflows and inflows
Expressed in USD billion

1990

2000

2008

2016

FDI outflows

LDCs

0.0

2.1

18.4

11.9

China

0.8

0.9

55.9

183.1

Total South

13.1

90.0

288.6

383.4

FDI inflows

LDCs

0.6

5.3

32.3

37.9

China

3.5

40.7

108.3

133.7

Total South

-

233.8

592.7

646.0

Source: Authors’ calculations based on UNCTAD (2018[68])Foreign direct investment (database), Foreign direct investment: Inward and outward flows and stock, annual, http://unctadstat.unctad.org/wds/TableViewer/tableView.aspx?ReportId=96740 (accessed in May 2018).

FDI flows have increasingly turned into a two-way street since the GFC. Traditionally, and until the late 1990s, developing countries have hosted FDI rather than being the source of FDI flows. While inward FDI has plateaued for many emerging economies in the 2010s, much of the dynamism is now in outward FDI. Table 2.6 provides evidence on FDI outflows and inflows for the years 1990, 2000, 2008 and 2016. Up to the GFC, Latin American companies used to spearhead outward investment from emerging economies. Since then, China raised its percentage share in developing-country FDI outflows from 1% in 2000 to almost 50% by 2016. Chinese multinationals have increasingly taken the M&A route for their overseas expansion, particularly after the GFC of 2008-09.

Greenfield investment, i.e. investments in new assets, is an important mode of entry for Indian and Malaysian multinationals compared to M&A. Indeed, India and Malaysia are the only other emerging countries besides China listed among the top 15 countries for greenfield FDI in 2016. Emerging countries continue to primarily invest South-South in other emerging and developing economies, as most emerging economies’ regional markets serve as the primary destination for their outward greenfield FDI flows. The share of outward FDI projects of the largest 20 emerging countries (in value) directed to the Asia-Pacific region has declined, but has increased to Africa, Latin America and especially North America (Casanova and Miroux, 2017[69]).

The poorest countries classified by UNCTAD as the LDC group have started to participate at last in hosting considerable FDI inflows as a proportion of their GDP. South-South FDI contributed to that new trend, with growing activity from many firms in China, Brazil, India and South Africa.4

Intricately linked to FDI are Special Economic Zones (SEZs) that have proven to be a key element of economic development and strategic planning in many developing countries. Initially set up as export processing zones for rather labour-intensive manufacturing, contemporary SEZs have begun incorporating higher value-added components.

Since the inception of shifting wealth, the numbers of SEZs in developing economies have increased from only 176 zones in 47 countries in 1986 (Boyenge, 2007[70]) to over 4 300 in more than 130 countries in 2015 (The Economist, 2015[71]). Zones in East Asia early on led the climb up the value chain.5 Elsewhere, countries such as the Dominican Republic are shifting towards technology-intensive sectors such as the automotive industry through settling a variety of upstream suppliers (WTO, 2017[59]).

China has been establishing SEZs at home since 1979. Building on this experience abroad, China has been setting up “overseas zone programmes” since 2000 either to establish value chains or profit from economic co-operation and mutual learning through joint zones. This engagement, however, is still regionally concentrated. By 2014, out of the initial 50 foreign zones supported by the Chinese Ministry of Commerce, 44 were built in Asia and only six in Africa (Bräutigam and Tang, 2014[72]).

In the 2000s, China became a global leader in official bank credit for infrastructure funding. This funding benefited Africa above all, building roads, dams, bridges, railways, airports, seaports and electricity grids. Meanwhile, China established several bilateral and multilateral funds across the world, in addition to two policy banks, the China Development Bank and the Export Import Bank of China. Figure 2.23 suggests (for Africa) that in recent years multilateral flows have substituted for bilateral official lending flows. Despite steady growth in private sector funding in the past decade, official development finance backs 80% of Africa’s infrastructure funding (ECN, 2015[73]). China has also pioneered a host of bilateral and regional development funds in the wake of founding the Belt and Road Initiative (BRI) in 2013 (see the section on China’s Belt and Road Initiative below). These funds add upwards of USD 100 billion in development finance. A major portion of these Chinese investments is in Asia; the largest is the USD 40 billion Silk Road Fund established in 2014 (Gallagher, Kamal and Wang, 2016[74]).

Figure 2.23. In Africa, multilateral flows have substituted for official bilateral lending flows
Bilateral and multilateral disbursements and amortisation (USD billion, 2004-17)
picture

Note: Values for 2017 are based on projections.

Source: Authors’ calculations based on World Bank (2018[75])International Debt Statistics (database), Various indicators, http://databank.worldbank.org/data/reports.aspx?source=International%20Debt%20Statistics (accessed in March 2018).

 StatLink https://doi.org/10.1787/888933857005

In 2015, two new multilateral financial institutions of consequential size and scope became legal entities. China led the creation of the Asian Infrastructure Investment Bank (AIIB), while the BRICS nations (Brazil, Russia, India, China and South Africa) championed and owned the New Development Bank (NDB). The NDB aimed to strengthen co-operation among the BRICS and beyond. The advent of these new multilateral development banks reflects a decentralisation of power from the Bretton Woods system and a shift in terms of soft power distribution beyond the G7. Their potential role and influence stems from: i) the size of their lending activity, even relative to long-established institutions such as the World Bank and the Asian Development Bank (ADB); ii) their relatively high capitalisation; and iii) their focus on infrastructure – a sector vital for growth and development. AIIB and NDB are expected to add significant financing capabilities with combined loan portfolios estimated at USD 230 billion (Reisen, 2015[76]).

Staying outside the relatively transparent DAC framework, China does not disclose comprehensive or detailed information about its international development finance activities. Aid Data (Dreher et al., 2017[77]) constructed a dataset with a new methodology for tracking underreported financial flows. According to these new data, the scale and scope of China’s overseas infrastructure activities now rival or exceed that of other major donors and lenders. Between 2000 and 2014, the Chinese government committed more than USD 350 billion in official finance to 140 countries and territories in Africa, Asia and the Pacific, Latin America and the Caribbean, the Middle East, and central and eastern Europe. Transport and power generation are the two main sectors financed. Chinese co-operation also invests significantly in health, education, water and sanitation, agriculture, and other social and productive sectors.

Chinese official finance consists of ODA, which is the strictest definition of aid used by OECD-DAC members, and other official flows. China provides relatively little aid in the strictest sense of the term (development projects with a grant element of 25% or higher). A large proportion of the financial support that China provides to other countries comes in the form of export credits and market or close-to-market rate loans. Table 2.7 provides a calculation of the weighted average of China’s development finance that was extended at concessional ODA terms: 24.5% for 2000-14.

Table 2.7. Recipients of Chinese official finance (2000-14)

World region

Total (in USD billion)

ODA terms (in %)

Number of projects

Africa

118.1

58

2 345

Eastern Europe

56.7

3

171

Latin America

53.4

12

317

South Asia

48.8

10

423

Southeast Asia

39.2

7

507

Other Asia

28.5

6

183

Middle East

3.1

1

93

Pacific

2.8

3

265

Total/Average

350.6

24.5

4 304

Source: Authors’ calculations based on AidData (2017[78]), AidData's Global Chinese Official Finance Dataset, 2000-2014, Version 1.0https://www.aiddata.org/data/chinese-global-official-finance-dataset (accessed in March 2018).

Africa benefited most from Chinese development finance during 2000-14 – in terms of amounts, degree of concessionality (percentage share at ODA terms) and number of projects (Table 2.7). Zimbabwe, Angola, Sudan, Tanzania, Ghana, Kenya and Ethiopia headed the ranking of Africa’s recipients in number of projects. Africa has received more Chinese ODA-like finance than all other developing regions in the world combined.

Infrastructure funding has risks for low-income countries with low debt tolerance, however, despite its transformative nature. China and other emerging creditors supply much of their new funding through official bank credit outside the Paris Club framework. International organisations and private institutions in Washington, DC, however, have voiced concerns that the absence of a concerted mechanism for debt prevention and resolution might lead to a new debt overhang. Greater borrowing opportunities have provided more room to expand development-oriented spending and address infrastructure gaps. However, long-term growth is enhanced only if borrowed funds are used productively, yielding a high economic rate of return that exceeds borrowing costs. Unfortunately the IMF (2018[46]) has noted that higher budgetary borrowing levels have been associated with a drop in public investment in many low-income and developing countries.

The IMF is particularly worried by the rise of debt since 2013 and by its composition in several post-HIPC countries now judged at high risk of, or in, debt distress. Those countries are all African: Cameroon, Chad, Democratic Republic of the Congo, Ethiopia, Ghana, Mauritania, Mozambique and Zambia. Their rise in debt levels has been financed by an increasingly fragmented composition of emerging bilateral creditors, commercial external creditors and the domestic financial system. By contrast, the contribution of traditional creditors (the multilateral development banks and Paris Club creditors) has been modest; they tend to limit provision of loans to such high-risk countries, or are more likely to provide grant finance in such cases.

China’s Belt and Road Initiative

China’s Belt and Road Initiative (BRI) is deepening South-South integration in the post-GFC period. Officially announced in September 2013 and incorporated into the Chinese constitution in October 2017, the initiative envisions the establishment of the Silk Road Economic Belt and the 21st Century Maritime Silk Road. It intends to promote connectivity and economic co-operation along the proposed Belt and Road routes, encompassing large areas of the Association of Southeast Asian Nations region, Central Asia, the Middle East and Eastern Europe.6

The BRI has both economic and political goals for China, but low-income countries may receive the greatest benefits. From an economic perspective, China hopes that new trade routes, markets and energy resources will help develop its own infrastructure capabilities and reduce cyclical input and output dependencies. In addition, the BRI is meant to help China take a leading role in establishing a multipolar world order. However, low-income countries participating in the BRI could reap the biggest developmental benefits, provided some prerequisites are met. For instance, China has placed political emphasis on developing links with countries along the China-Pakistan Economic Corridor and pledged to deepen economic ties with Viet Nam, Sri Lanka, Cambodia, Lao People’s Democratic Republic, Myanmar and several eastern African countries.

Upon completion in 2049, the BRI envisages to reach more than 60% of world population and cover over 50% of global trade. This scale makes it the largest and most ambitious geo-economic vision in recent history. Although the BRI officially covers 87 countries, China’s trade and investment links are so far concentrated on a relatively narrow number of Southeast Asian countries. By either providing new trade connections or upgrading existing ones, trade time reductions across regions are estimated to range for individual countries somewhere between 26% (Republic of Moldova) and 63% (Myanmar). Improved connectivity also results in an increase in bilateral trade of at least 15% on average (World Bank, 2018[79]). To date, Chinese investment in transportation alone has resulted in about 2 100 infrastructure projects, (CSIS, 2018[80]). Whether the BRI will provide deeper economic and political integration of the countries concerned remains to be seen from a historical perspective.

Capital needs for fully implementing the BRI are estimated from USD 1 trillion to USD 8 trillion (Hurley, Morris and Portelance, 2018[81]).7 By the end of 2016, China’s big commercial banks and policy banks had shouldered 97% of the (debt) financing (Deloitte, 2018[82]). In addition, the BRI has been accompanied by the foundation of BRICS-centred multilateral lending institutions, the AIIB and the NDB. Chinese officials also have encouraged participation by traditional multilateral institutions like the World Bank, the ADB and the African Development Bank (AfDB). The Silk Road Fund provides financing to predominantly Chinese state-owned enterprises – from State Grid to shipping companies such as COSCO. The Chinese development banks, in turn, grant financial support to infrastructure projects in countries along the BRI economic corridors. Despite sometimes rivalling other development finance institutions from the West in granting concessional loans, there is no zero-sum competition as projects are often co-funded or China takes credit risks that other Western institutions do not.

The economic logic of connectivity and increasing economic integration on a trans-continental scale pursued by the BRI is strong. This is especially true given that globalisation appears to be in retreat in the face of rising protectionism and economic nationalism. In a widely quoted study, ADB (2017[83]) asserts that in USD 26 trillion in infrastructure investments are needed over 2016-30 in Asia alone to maintain 3% to 7% economic growth, eliminate poverty and respond to climate change. The economic benefits for participating countries from economically viable projects under the BRI would flow from the fact that infrastructure projects tend to relieve the most binding growth constraints. To be sure, the employment of Chinese labour and construction materials during BRI development may help slightly alleviate China’s industrial overcapacities at home (Dollar, 2015[84]).

BRI corridors will entail higher benefits if partner countries lower cross-border transaction costs and import tariffs (Ramasamy et al., 2017[85]). A 30% decline in both impediments would generate, for instance, economic gains of 1.8% growth in GDP for China and anywhere from 5.3% to 16.9% of GDP for other participating member countries. Improving the quality of infrastructure in countries with less efficient trade regimes and border administration may result in only limited export gains.

Not all projects under the BRI seem economically viable at first glance, particularly if they are undertaken in less solvent economies (OECD, 2018[86]). This suggests they have been included for either geo-political reasons or to determine the better security-cost trade-off by testing multiple and potentially competing routes (Pomfret, forthcoming[87]). Passages such as the China-Pakistan Economic Corridor or the China-Iran train link are to traverse some of the most conflict-ridden and politically unstable parts of the world (Menon, 2017[88]). The risks to large-scale investments are considerable unless issues of security for investments, infrastructure, freight and transport are properly addressed.

Washington-based institutions, such as the IMF and World Bank, are also worried about prospective debt distress in connection with the BRI. A Center for Global Development (CGD) paper identified a subset of 23 countries to be significantly or highly vulnerable to debt distress, of which ten are Asian and four African. The CGD analysis finds in general, however, that the BRI is unlikely to cause a systemic debt problem in the regions of focus. While the aggregate numbers look large, they should be assessed against the size of the economies likely to benefit from BRI investments. In these cases, amounts are consistent with current levels of infrastructure investment. In addition, some of the China-sourced financing will likely substitute for other debt sources.

Notwithstanding such concerns for the debt potential of the BRI, the CGD analysis seems unfair to China. First, by its very nature, the debt potential of China’s just-started initiative is virtually impossible to quantify. Second, expansive OECD monetary policies since the GFC have provided strong incentives for the recent debt build-up in developing countries, yet that major policy incoherence is often taken as a given. Third, these debt sustainability concerns seem to neglect the rise in debt service capacity that may result from China’s “transformative” infrastructure funding, which will be increasingly enshrined in the BRI.

Outlook

The outlook for shifting wealth is uncertain, depending more than ever on conducive policy implementations at the global and local level. Most developing countries will enjoy favourable demographics and urbanisation to both stimulate investment and productivity. China’s more balanced economy will favour exports of consumer goods from low-income countries, including agricultural, and the relocation of manufacturing. As the BRI is implemented, infrastructure bottlenecks to growth will gradually subside.

Development in transition will have to deal with slower convergence speed, the middle-income trap, labour-reducing technology, and protectionism and relocation trends in advanced economies, and financial stress from key currency fluctuations and tightening global liquidity.

References

[83] ADB (2017), Meeting Asia's infrastructure needs, Asian Development Bank, http://dx.doi.org/10.22617/FLS168388-2.

[54] AfDB/OECD/UNDP (2017), African Economic Outlook 2017: Entrepreneurship and Industrialisation, OECD Publishing, Paris, http://dx.doi.org/10.1787/aeo-2017-en.

[78] AidData (2017), AidData's Global Chinese Official Finance Dataset, 2000-2014, Version 1.0, AidData, https://www.aiddata.org/data/chinese-global-official-finance-dataset (accessed on 01 March 2018).

[53] Aksoy, A. and F. Ng (2014), Increased export performance and competitiveness of developing countries: Mainly a China story?, European University Institute.

[12] Alvaredo, F. et al. (2018), World Inequality Report 2018, World Inequality Lab, https://wir2018.wid.world/files/download/wir2018-full-report-english.pdf.

[8] Autor, D., D. Dorn and G. Hanson (2016), “The China shock: Learning from labor-market adjustment to large changes in trade”, Annual Review of Economics, Vol. 8, pp. 205-240, https://dx.doi.org/10.1146/annurev-economics-080315-015041.

[36] Bai, J. and P. Perron (2006), “Multiple structural change models: A simulation analysis”, in Corbae, D., S. Durlauf and B. Hansen (eds.), Econometric Theory and Practice: Frontier of Analysis and Applied Research (Essays in Honor of Peter Phillips), Cambridge University Press, https://doi.org/10.1017/CBO9781139164863.010.

[15] Baily, M. and B. Bosworth (2014), “US manufacturing: Understanding its past and its potential future”, Journal of Economic Perspectives, Vol. 28/1, pp. 3-26, http://dx.doi.org/10.1257/jep.28.1.3.

[33] Berg, A., J. Ostry and J. Zettelmeyer (2012), “What makes growth sustained?”, Journal of Development Economics, Vol. 98/2, pp. 149-166, https://dx.doi.org/10.1016/j.jdeveco.2011.08.002.

[9] Beyer, R. and M. Stemmer (2016), “Polarization or convergence? An analysis of regional unemployment disparities in Europe over time”, Economic Modelling, Vol. 55/June, pp. 373-381, https://dx.doi.org/10.1016/j.econmod.2016.02.027.

[70] Boyenge, S. (2007), ILO database of export processing zones, revised, http://www.ilo.org/public/libdoc/ilo/2007/107B09_80_engl.pdf.

[72] Bräutigam, D. and X. Tang (2014), “Going global in groups: Structural transformation and China's special economic zones overseas”, World Development, Vol. 63/C, pp. 78-91, https://doi.org/10.1016/j.worlddev.2013.10.010.

[67] Buch, C. and A. Kuckulenz (2010), “Worker remittances and capital flows to developing countries”, International Migration, Vol. 48/8, pp. 89-117, https://doi.org/10.1111/j.1468-2435.2009.00543.x.

[60] Cadestin, C., J. Gourdon and P. Kowalski (2016), “Participation in Global Value Chains in Latin America: Implications for Trade and Trade-Related Policy”, OECD Trade Policy Papers, No. 192, OECD Publishing, Paris, http://dx.doi.org/10.1787/5jlpq80ts8f2-en.

[69] Casanova, L. and A. Miroux (2017), Emerging Markets Multinationsl Report 2017, https://www.johnson.cornell.edu/Portals/32/EMI%20Docu/EMR/Emerging%20Multinationals%20in%20a%20Changing%20World.pdf.

[19] CEIC (2018), China Average Annual Wage: Manufacturing, https://www.ceicdata.com/en/china/average-wage-by-industry-urban-nonprivate/avg-annual-wage-manufacturing (accessed on 01 May 2018).

[26] Chhibber, A. and G. Nayyar (2008), “Pro-poor growth: Explaining the cross-country variation in the growth elasticitiy of poverty”, International Journal of Development Issues, Vol. 7/2, pp. 160-176, https://doi.org/10.1108/14468950810909123.

[49] Coulibaly, B. (2018), Africa's alternative path to development, https://www.project-syndicate.org/commentary/africa-industries-without-smokestacks-by-brahima-coulibaly-2018-05 (accessed on  May 2018).

[31] Credit Suisse Research Institute (2017), Global Wealth Databook 2017, Credit Suisse Research Institute, http://publications.credit-suisse.com/index.cfm/publikationen-shop/research-institute/global-wealth-databook-2017-en/ (accessed on 01 March 2018).

[80] CSIS (2018), BRI Projects (database), Center for Strategic & International Studies, https://reconnectingasia.csis.org/ (accessed on 01 April 2018).

[14] Dauth, W., S. Findeisen and J. Suedekum (2017), “Trade and manufacturing jobs in Germany”, American Economic Review: Papers and Proceedings, Vol. 107/5, pp. 337-342, https://doi.org/10.1257/aer.p20171025.

[90] Davies, J., R. Lluberas and A. Shorrocks (2018), Global Wealth Report 2018, http://publications.credit-suisse.com/tasks/render/file/index.cfm?fileid=37226D89-C511-95F3-3960988EEA61FB88.

[89] Davies, J., R. Lluberas and A. Shorrocks (2017), “Estimating the level and distribution of global wealth, 2000-2014”, The Review of Income and Wealth, Vol. 63/4, pp. 731-759, https://doi.org/10.1111/roiw.12318.

[32] Davies, J., R. Lluberas and A. Shorrocks (2010), Global Wealth Databook 2010, Credit Suisse Research Institute, https://publications.credit-suisse.com/tasks/render/file/index.cfm?fileid=88DC07AD-83E8-EB92-9D5C3EAA87A97A77 (accessed on 01 March 2018).

[35] De Gregorio, J. (2018), Productivity in emerging market economies: Slowdown or stagnation?, Peterson Institute for International Economics, https://piie.com/system/files/documents/wp18-12.pdf.

[82] Deloitte (2018), Embracing the BRI ecosystem in 2018: Navigating pitfalls and seizing opportunities, Deloitte China, https://www2.deloitte.com/content/dam/insights/us/articles/4406_Belt-and-road-initiative/4406_Embracing-the-BRI-ecosystem.pdf.

[45] Diao, X., M. McMillan and D. Rodrik (2017), The recent growth boom in developing economies: A structural change perspective, https://www.nber.org/papers/w23132.pdf.

[52] Didier, L. (2017), “South-South trade and geographical diversification of intra-SSA trade: Evidence from the BRICs”, African Development Review, Vol. 29/2, pp. 139-154, https://doi.org/10.1111/1467-8268.12246.

[84] Dollar, D. (2015), “China's rise as a regional and global power: The AIIB and the 'one belt one road'”, Horizons, Vol. Summer 2015/4, pp. 162-172, https://www.brookings.edu/wp-content/uploads/2016/06/China-rise-as-regional-and-global-power.pdf.

[77] Dreher, A. et al. (2017), Aid, China, and Growth: Evidence from a New Global Development Finance Dataset, http://docs.aiddata.org/ad4/pdfs/WPS46_Aid_China_and_Growth.pdf.

[73] ECN (2015), Spanning Africa's infrastructure gap: How development capital is transforming Africa's project build-out, The Economist Corporate Network, http://ftp01.economist.com.hk/ECN_papers/Infrastructure-Africa.

[16] Feenstra, R., H. Ma and Y. Xu (2017), US exports and employment, National Bureau of Economic Research, https://www.nber.org/papers/w24056.pdf.

[44] Feindouno, S. and M. Goujon (2016), The retrospective economic vulnerability index, 2015 update, Fondation pour les études et recherches sur le développement international, http://www.ferdi.fr/sites/www.ferdi.fr/files/publication/fichiers/p147-ferdi-goujeon_et_feindouno_-_evi_2015.pdf.

[74] Gallagher, K., R. Kamal and Y. Wang (2016), Fueling growth and financial risk: The benefits and risks of China's development finance in the global energy sector, https://www.bu.edu/pardeeschool/files/2016/05/Fueling-Growth.FINAL_.version.pdf.

[20] Garroway, C. et al. (2012), “The Renminbi and Poor-country Growth”, The World Economy, Vol. 35/3, pp. 273-294, https://doi.org/10.1111/j.1467-9701.2011.01408.x.

[40] Garroway, C. and H. Reisen (2014), The future of multilateral concessional finance, Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), http://star-www.giz.de/fetch/3dQ00u3Xc0001Qgm0f/giz2014-1668en-mulilateral-concessional-finance.pdf.

[17] Goodhart, C. and M. Pradhan (2017), Demographics will reverse three multi-decade global trends, Bank for International Settlements, https://www.bis.org/publ/work656.pdf.

[43] Guillamont, P. (2011), The concept of structural economic vulnerability and its relevance for the identification fo the least developed countries and other purposes (Nature, Measurement, and Evolution), United Nations Department of Economic and Social Affairs, https://www.un.org/development/desa/dpad/wp-content/uploads/sites/45/publication/CDP-bp-2011-12.pdf.

[81] Hurley, J., S. Morris and G. Portelance (2018), Examining the Debt Implications of the Belt and Road Initiative from a Policy Perspective, https://www.cgdev.org/publication/examining-debt-implications-belt-and-road-initiative-a-policy-perspective.

[46] IMF (2018), Macroeconomic developments and prospects in low-developing countries, https://www.imf.org/~/media/Files/Publications/PP/2018/pp021518-macroeconomic-developments-and-prospects-in-low-income-developing-countries.ashx.

[2] IMF (2017), World Economic Outlook 2017 (database), https://www.imf.org/external/pubs/ft/weo/2017/02/weodata/index.aspx (accessed on 01 December 2017).

[34] Kar, S. et al. (2013), “Looking for a break: identifying transitions in growth regimes”, Journal of Macroeconomics, Vol. 38, pp. 151-166, https://doi.org/10.1016/j.jmacro.2013.09.022.

[37] Kerekes, M. (2011), Analyzing Patterns of Economic Growth: A Production Frontier Approach, http://www.wiwiss.fu-berlin.de/fachbereich/vwl/corneo/dp/PoG_V02_Main.pdf.

[61] Kowalski, P. et al. (2015), “Participation of Developing Countries in Global Value Chains: Implications for Trade and Trade-Related Policies”, OECD Trade Policy Papers, No. 179, OECD Publishing, Paris, http://dx.doi.org/10.1787/5js33lfw0xxn-en.

[11] Lakner, C. and B. Milanovic (2016), “Global income distribution: From the fall of the Berlin Wall to the Great Recession”, World Bank Economic Review, Vol. 30/2, pp. 203-232, https://doi.org/10.1093/wber/lhv039.

[23] Lane, P. and G. Milesi-Ferretti (2018), “The External Wealth of Nations Revisited: International Financial Integration in the Aftermath of the Global Financial Crisis”, IMF Economic Review, Vol. 66/1, pp. 189-222, https://doi.org/10.1057/s41308-017-0048-y.

[5] Lemoine, F. and D. Unal (2017), “China's foreign trade: A "new normal"”, China & World Economy, Vol. 25/2, pp. 1-21, https://doi.org/10.1111/cwe.12191.

[50] Lewis, A. (1979), The slowing down of the engine of growth: Lecture to the memory of Alfred Nobel.

[48] Lewis, A. (1954), “Economic development with unlimited supplies of labour”, The Manchester School, Vol. 22/2, pp. 139-191, https://doi.org/10.1111/j.1467-9957.1954.tb00021.x.

[88] Menon, S. (2017), The Unprecedented Promises – and Threats – of the Belt and Road Initiative, https://thewire.in/external-affairs/the-unprecedented-promises-and-threats-of-the-belt-and-road-initiative (accessed on 01 July 2018).

[65] OECD (2018), International Development Statistics (IDS) online databases, OECD, https://stats.oecd.org/qwids/#?x=1&y=6&f=3:51,4:1,5:3,7:1,2:262&q=3:51+4:1+5:3+7:1+2:262+1:1,2,25,26+6:2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015 (accessed on 01 July 2018).

[86] OECD (2018), OECD Business and Finance Outlook 2018, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264298828-en.

[22] OECD (2017), OECD Data (database), https://data.oecd.org/price/producer-price-indices-ppi.htm (accessed on 01 February 2018).

[1] OECD (2010), Perspectives on Global Development 2010: Shifting Wealth, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264084728-en.

[24] OECD et al. (2011), African Economic Outlook 2011: Africa and its Emerging Partners, OECD Publishing, Paris, http://dx.doi.org/10.1787/aeo-2011-en.

[55] OECD/CAF/UN ECLAC (2015), Latin American Economic Outlook 2016: Towards a New Partnership with China, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264246218-en.

[30] Piketty, T. (2014), Capital in the Twnety-First Century, Harvard University Press.

[87] Pomfret, R. (forthcoming), The Central Asian Economies in the Twenty-first Century: Paving the New Silk Road, Princeton University Press.

[63] Prizzon, A., R. Greenhill and S. Mustapha (2016), An age of choice for development finance: Evidence from country case studies, https://www.odi.org/publications/10390-age-choice-development-finance-evidence-country-case-studies.

[85] Ramasamy, B. et al. (2017), Trade and trade facilitation along the Belt and Road Initiative corridors, https://www.unescap.org/resources/trade-and-trade-facilitation-along-belt-and-road-initiative-corridors.

[76] Reisen, H. (2015), “Will the AIIB and the NDB help reform multilateral development banking?”, Global Policy, Vol. 6/3, pp. 297-304, https://doi.org/10.1111/1758-5899.12250.

[25] Reisen, H. and J. Stijns (2011), How emerging donors are creating policy space for Africa, https://voxeu.org/article/how-emerging-donors-are-creating-policy-space-africa (accessed on 01 May 2018).

[4] Rodrik, D. (2016), “Premature deindustrialization”, Journal of Economic Growth, Vol. 21/1, pp. 1-33, https://link.springer.com/article/10.1007/s10887-015-9122-3.

[28] Roser, M. and E. Ortiz-Ospina (2018), Global Extreme Poverty, https://ourworldindata.org/extreme-poverty (accessed on 01 June 2018).

[13] Sandefur, J. (2018), Chart of the week #1: Is the elephant graph flattening out?, https://www.cgdev.org/blog/chart-week-1-elephant-graph-flattening-out (accessed on 01 May 2018).

[47] Sumner, A. (2018), What is premature deindustrialisation and does it matter?, https://www.gpidnetwork.org/wp-content/uploads/2018/03/Brief_9.pdf.

[38] Sumner, A. (2016), Global poverty: Deprivation, distribution, and development since the Cold War, Oxford University Press.

[71] The Economist (2015), Not so special, https://www.economist.com/leaders/2015/04/04/not-so-special (accessed on 01 May 2018).

[58] UN (2018), Comtrade (database), United Nations Department of Economic and Social Affairs, https://comtrade.un.org/data (accessed on 01 June 2018).

[42] UN (2018), List of Least Developed Countries (as of March 2018), United Nations Committee for Development Policy, https://www.un.org/development/desa/dpad/wp-content/uploads/sites/45/publication/ldc_list.pdf (accessed on 01 March 2018).

[68] UNCTAD (2018), Foreign direct investment (database), United Nations Conference on Trade and Development, http://unctadstat.unctad.org/wds/TableViewer/tableView.aspx?ReportId=96740 (accessed on 01 May 2018).

[56] UNCTAD (2018), International trade in goods and services (database), United Nations Conference on Trade and Development, http://unctadstat.unctad.org/wds/ReportFolders/reportFolders.aspx (accessed on  April 2018).

[51] UNCTAD (2013), UNCTAD Handbook of Statistics 2013, United Nations Publications.

[18] US Bureau of Labor Statistics (2018), Employment, Hours, and Earnings from the Current Employment Statistics survey (National) (database), https://data.bls.gov/timeseries/CES3000000001 (accessed on 01 May 2018).

[91] White, J. (2011), “Fostering innovation in developing economies through SEZs”, in Farole, T. and G. Akinci (eds.), Special Economic Zones: Progress, Emerging Challenges, and Future Directions, World Bank Publications, https://openknowledge.worldbank.org/bitstream/handle/10986/2341/638440PUB0Exto00Box0361527B0PUBLIC0.pdf.

[57] Wignaraja, G. and D. Lazaro (2010), North-South vs. South-South Asian FTAs: Trends, compatibilities, and ways forward.

[7] Wolf, M. (2006), Answer to Asia's rise is not to retreat, https://www.ft.com/content/6a5a0f68-b389-11da-89c7-0000779e2340 (accessed on 14 March 2018).

[10] Wood, A. (2018), “The 1990s trade and wages debate in retrospect”, The World Economy, Vol. 41/4, https://doi.org/10.1111/twec.12619.

[3] Wood, A. and J. Mayer (2011), “Has China de-industrialised other developing countries?”, Review of World Economics, Vol. 147/2, pp. 325-350, https://doi.org/10.1007/s10290-011-0088-8.

[41] World Bank (2018), IDA Graduates, World Bank, http://ida.worldbank.org/about/ida-graduates (accessed on 01 April 2018).

[75] World Bank (2018), International Debt Statistics (database), World Bank, http://databank.worldbank.org/data/reports.aspx?source=International%20Debt%20Statistics (accessed on 01 March 2018).

[79] World Bank (2018), Trade effects of the new silk road, World Bank, https://www.gtap.agecon.purdue.edu/resources/download/9023.pdf.

[39] World Bank (2018), World Bank Country and Lending Groups, World Bank, https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups (accessed on 01 August 2018).

[27] World Bank (2018), World Development Indicators (database), http://databank.worldbank.org/data/source/world-development-indicators (accessed on 01 February 2018).

[6] World Bank (2018), World Integrated Trade Solution (database), https://wits.worldbank.org/ (accessed on 01 April 2018).

[21] World Bank (2017), Commodity Markets Outlook, http://pubdocs.worldbank.org/en/817261508960786112/CMO-October-2017-Data-Supplement.xlsx (accessed on 01 February 2018).

[64] World Bank (2017), Migration and Remittances Data, World Bank, http://www.worldbank.org/en/topic/migrationremittancesdiasporaissues/brief/migration-remittances-data (accessed on 01 July 2018).

[66] World Bank (2016), Migration and Remittances Factbook 2016, Third Edition, World Bank, https://openknowledge.worldbank.org/bitstream/handle/10986/23743/9781464803192.pdf.

[29] World Inequality Lab (2018), World Inequality Database, https://wid.world/data/ (accessed on 01 February 2018).

[59] WTO (2017), Global Value Chain Development Report, World Bank Publications, https://www.worldbank.org/en/topic/trade/publication/global-value-chain-development-report-measuring-and-analyzing-the-impact-of-gvcs-on-economic-development.

[62] Xu, J. and R. Carey (2015), China's international development finance - Past, present, and future, https://www.wider.unu.edu/publication/china%E2%80%99s-international-development-finance.

Notes

← 1. Since 2010, the Credit Suisse Research Institute’s Global Wealth Report has been the leading reference on global household wealth (for more details, consult Davies, Lluberas and Shorrocks (2018[90]), (2017[89])).

← 2. Due to lack of data on standard deviation underlying the various data on household wealth, Table 2.2 neither provides evidence on skewness nor on the Asia-Pacific region excluding Japan.

← 3. The UN uses a further indicator to determine which countries are eligible to enter or leave the LDC category: the Human Assets Index, a measure of the level of human capital. The idea behind it: low levels of human assets indicate major structural impediments to sustainable development.

← 4. Net FDI flows do not necessarily constitute net capital flows as they are often financed in the host country’s domestic financial markets; multinational companies try to keep currency and expropriation risk down.

← 5. For instance, over two decades, labour-intensive industries fell from about 50% of the turnover in zones in Korea and Chinese Taipei to about 10% in the mid-1990s; by then, technology-intensive industries contributed over 80% (White, 2011[91]).

← 6. The Belt and Road Initiative aims to connect Asia, Europe and Africa along five major routes. The Silk Road Economic Belt focuses on: (1) linking China to Europe through Central Asia and Russia; (2) connecting China with the Middle East through Central Asia; and (3) bringing together China and Southeast Asia, South Asia and the Indian Ocean. The 21st Century Maritime Silk Road, meanwhile, focuses on using Chinese coastal ports to: (4) link China with Europe through the South China Sea and Indian Ocean; and (5) connect China with the South Pacific Ocean through the South China Sea.

← 7. The highest estimate to be found in the media according to Hurley, Morris and Portelance (2018[81]).

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