Potential Headwinds for Shifting Wealth

The sustained growth that large emerging countries have experienced over the last two decades has conferred on them a considerable growth delta over the OECD average. Combined with very large populations, these growth differences are translating into a new world economy.  For the first time in history, the countries with the largest economic mass are not also the richest countries. The shorthand for this complex event is what we call “Shifting Wealth” – the recalibration of the world economy toward the East and the South –, well documented since 2010 in the OECD Perspectives on Global Development. The last post on this blog had discussed potential tailwinds for Shifting Wealth that may arise from the twin-turbo China cum India. Today, I want to reflect on four potential headwinds going forward:

·         Slower speed of GDP convergence as the distance to the advanced countries is shrinking;

·         The middle-income trap in emerging countries;

·         Technological innovations that might reduce labor demand in emerging countries;

·         Global trade, notably normalisation and protectionism.

To be sure, there is no mechanical necessity about these risks. But policymakers, notably in middle-income emerging countries must be aware of them. Whether economists´ almost Pavlovian responses to these trends - better education, redistribution, activist industrial policy - can deal with these trands in a welfare improving way is beyond the scope of this paper, which is busy looking at trends.

Convergence Speed

China´s growth has been the engine of Shifting Wealth since the 2000s. After almost four decades of sustained growth, the Chinese economy has grown from an average GDP_PPP/capita of 313 US dollar in 1980 to 15,417 US dollar in 2016. Its GDP per capita is currently equivalent to 55 percent of the world's average. China, initially capital poor, has saved and invested a large part of its annual GDP over the past 40 years. The neoclassical Solow-Swan growth model postulates diminishing returns to capital. This has led Krugman (1994)[1] to make one of the most blatant errors in the history of economic prognosis:

”If growth in East Asia runs into diminishing returns, however,  the conventional wisdom about an Asian-centered world economy needs some rethinking”…”From the perspective of the year 2010 (sic!), current projections of Asian supremacy  … may well look as silly as 1960s-vintage forecasts of Soviet industrial supremacy did from the perspective of the Brezhnev years”.

The hypothesis that poor economies tend to grow faster per capita than rich ones— without conditioning on any other characteristics of economies—is referred to as absolute convergence. However, it has held in the past only for a fairly homogenous group of countries, such as the OECD, or for incomes across US states (Barro and Sala-i-Martin, 2004)[2]. The key proposition of endogenous-growth models is the absence of diminishing returns to capital. The simplest version of a production function without diminishing returns is the AK function Y = AK, where A is a positive constant that reflects the level of the technology. The global absence of diminishing returns may seem unrealistic, but the idea becomes more plausible if we think of K in a broad sense to include human capital.

Acemoglu, Aghion and Zilibotti (2006)[3] produced a stochastic growth model in which a country‟s “distance to the frontier” matters for the selection of appropriate growth strategies. Countries at early stages of development (optimally) pursue an investment-based strategy, which relies on existing firms and managers to maximize investment under the guidance of the government; at this stage, local entrepreneurship and home-made innovation matter relatively less, a condition that carries implications in shaping appropriate institutions. The three authors show that relatively backward economies risk shifting out of the investment-based strategy too soon. Policies that encourage the investment-based strategy, such as limits on product market competition or investment subsidies, may be beneficial for a lengthy period in terms of facilitating economic convergence and poverty reduction.

Table 1: BRIICS Innovation Ranking

Country	China	Russia	S Africa	India	Brazil	Indon´ia	Total
2017	22	45	57	60	69	87	127
2007	29	54	38	23	40	48	107

Source: World Intellectual Property Organization, Global Innovation Index 2017 and 2007.

Investment-based development strategies may also have significant long-run costs, if the country holds on too long, failing to reach the world technology frontier and finding itself devoid of domestic entrepreneurs and innovation capacity. Reassuringly, China has managed to reach the world technology frontier and is blessed with millions of highly innovative entrepreneurs. The Global Innovation Index 2017 (published annually since 2007 at the World Intellectual Property Organization) provides detailed metrics about the innovation performance of 127 countries and economies around the world, with 81 indicators. China ranked at 22, the only middle-income country among the top 25 innovative countries. Note that, China and Russia aside, no other BRIICS country was able to move up the WIPO innovation ranking over the past decade (Table 1).

The Middle Income Trap

Closely related is the concern that middle-income countries can be ´trapped´ in growth slowdowns.  Gill and Kharas (2015)[4] had coined the term ´middle-income trap´ in 2005, because they had found growth theory wanting for the group of middle-income countries (which the World Bank in 2018 classifies as the large group of countries with GNI per capita between $1,005 and $12,235): endogenous growth theories addressed the problem in high-income economies, and the Solow growth model was still the work-horse for understanding the growth problem in low-income countries, but neither were satisfactory for understanding what to do in countries where 5 billion (out of 7billion) people in the world live.

The middle-income trap, whereby GDP per capita growth slows down once a country approaches an intermediate level of development, is particularly persistent in Latin America[5]. Although average per capita income in the region was relatively high in the mid-20th century, most Latin American countries have been unable to reduce significantly the income gap with advanced economies and reach high-income status. The few regional exceptions are Chile, Uruguay and some Caribbean countries. These trends contrast with European and Asian countries, much more effective in joining the high-income group during the last half of the 20th century. Even though ´Emerging Asia´ has made remarkable progress over the past four decades in raising income levels, it will take from several years (Malaysia, China) to decades (Indonesia, India) to join in the ranks of the advanced high-income countries, according to OECD (2014)[6] estimates (Fig. 1). The jury is still out as to whether middle-income ASEAN countries like Indonesia, Malaysia, the Philippines, Thailand or Vietnam can expect to replicate the growth experience of the Asian Tigers, or whether they will follow the trajectories of Latin America.

Figure 1: Estimated years required to become high-income country, 2014

Source: SEAO 2014, http://dx.doi.org/10.1787/888932937111

To be sure, there is nothing mechanical about the development transition from middle-income to high-income country, not even in Asia. Since 2000 (tiny island economies aside), six European and two Latin American countries have joined the ranks of high-income economies as classified by the World Bank, but no Asian country.

Technological Innovations and Labor Demand

Especially the 1990s opening phase of Shifting Wealth had been rooted in the abundance of labor with basic skills in poor countries that got connected to demand in advanced countries via trade and investment, resulting initially in manufacturing job creation in China above all. The world entered a new phase of globalisation: Information and communication technology, trade liberalisation and lower transport costs have enabled firms and countries to fragment the production process into global value chains (GVCs). However, the current proliferation of artificial intelligence, such as industrial robots, and other forms of worker-replacing technological progress have the potential to disrupt global labor markets (Korinek and Stiglitz, 2017)[7]. Technology innovation, such as 3D printing, may facilitate reshoring and would deepen the domestic (rather than global) division of labor for major economies, including China. Policymakers in middle-income countries have started to worry about the “end of global value chains” (Arbache, 2016)[8].

Robots could alter the global pattern of comparative advantage, for example in shoe production, which would shift from skill-scarce to skill-abundant countries if skilled workers with robots could make shoes more efficiently than unskilled workers[9]. The familiar benefits of industrialization as a development strategy might be eroded if robot-based automation makes industrialization more difficult or causes it to yield substantially less manufacturing employment than in the past (Mayer, 2017[10]). To be sure, technical feasibility of workplace automation does not imply economic profitability, especially in developing countries with low wage levels. And Central European countries, it has been argued recently by Professor Dalia Marin (LMU Munich) at a globalisation conference run by the Hans-Boeckler Foundation (https://www.boeckler.de/veranstaltung_107484.htm), have been able to advance to high-income status despite sharply rising wage cost thanks to relatively massive robotisation. Robotisation as a way to beat the middle-income trap?

Figure 2: Vulnerability to robot-based automation in manufacturing

Source: UNCTAD (2017), "Robots, industrialization and inclusive growth", chapter 3 in Trade and Development Report 2017

Figure 2 suggests “that on current technological and economic indicators, developed countries and developing countries other than least-developed countries (LDCs) are exposed to robot-based automation in manufacturing to a larger extent than LDCs. It should be noted that this evidence only refers to exposure to robot-based automation and does not take account of the risks to employment from other forms of automation. But it suggests that robot-based automation per se does not invalidate the traditional role of industrialisation as a development strategy for lower income countries. Yet, the dominance of robot use in sectors higher up on the skill ladder implies greater difficulty for latecomers in attaining sectoral upgrading and may limit their scope for industrialisation to low-wage and less dynamic (in terms of productivity growth) manufacturing sectors. This could seriously stifle these countries’ economic catch-up and leave them with stagnant productivity and per capita income growth” (Wood, 2017).

For the past decade, 3D printing has become popular due to availability of low-cost 3D printers such Fab@Home and better software. The brand name Fab@Home is suggestive of the technological possibilities to move production closer to the consumer, which may impact on trade, global value chains and shifting Wealth. Ishengoma and Mtaho (2014)[11] discuss 3D printing from a developing-country perspective, both challenges and opportunities. In developing countries, 3D printers are increasingly used in fabrication laboratories and engineering faculties, for example to produce 3D-printed prosthetic limbs. Major (economic) challenges are the lack of 3D experts and losses in manufacturing employment substituted for home platforms. Opportunities are lie in moving developing countries close to world supply chains For example, developing countries can use 3DP technology to manufacture local equipment such as farming tools and goods such as clothing.

Slowdown of Global Trade

Policymakers in low- and middle-income countries worry about the slowdown of the most important vehicle of Shifting Wealth, global trade. World trade growth was rapid in the two decades prior to the global financial crisis but has halved subsequently. There are both structural and cyclical reasons for the slowdown. A deceleration in the rate of trade liberalisation post 2000 was initially obscured by the ongoing expansion of global value chains and associated rapid emergence of China in the world economy. Post the financial crisis global value chains started to unwind and Chinese weakened markedly (Haugh et al., 2016)[12].

Figure 3: Drop in China’s export openness since 2007

Source: Banque de France (2017)“The role of China in the trade slowdown”, Rue de la Banque #30, September.

In recent years, global trade and global production have grown at similar rates, whereas before 2008, global trade grew at twice the rate. Apart from increasing protectionism (see Evenett and Fritz, 2016^[13]), this slowdown in global trade was initially (2008-2010) largely due to China’s rebalancing towards its domestic demand and its services sector (Banque de France, 2016^[14]). In the 2010s, however, the near-parallel growth for global trade and production seems to have been caused by changes in the supply chain (Los and Timmer, 2016^[15]).

Degain, Meng, and Wang (2017) find that there has been a reduction in cross-country production sharing in complex global value chains (GVC) during the current economic recovery, contrary to the rapid production globalization driven by the growth of complex GVC activities in previous periods^[16]. Decomposing four types of value-added creation activities (pure domestic production, traditional trade production, simple GVC, and complex GVC) unveils the structure of value-added creation during the economic recovery since 2011. That structure is found quite different from that during the three previous economic growth periods in the last 20 years. Unlike the rapid production globalization driven by the growth of complex GVC activities in previous periods, during the current economic recovery the pattern was reversed, with less cross-border production-sharing activities in complex GVCs. This may also mean that the China centric growth of middle- and low-income countries observed during the 2000s has been lower since 2011.

Protectionism is clearly another concern for the future of Shifting Wealth. The Economist (2016)[17] asked YouGov, a polling outfit, to survey 19 countries to gauge people's attitudes towards immigration, trade and globalisation. The data revealed a split between emerging markets and the West. Unsurprisingly, the countries that are the biggest enthusiasts of globalisation are the ones that have benefitted most from it – the poorer nations of East and South East Asia. In Asia, belief that globalisation is a force for good reaches at least 70% in all countries surveyed, and as high as 91% in Vietnam. In France, the US, the UK, Australia and Norway, less than 50 per cent thought that globalization had been a “force for good”. From disillusionment with globalisation to populist protectionism is a short distance.

Figure 4: Global Trade Liberalisation Index

 Source: Haugh et al (2016), OECD Economic Policy Papers No.18

Research has confirmed that the slowdown of trade liberalisation and rising protectionism is taking its toll on trade flows (Evenett and Fritz, 2015, op.cit.). Less international fragmentation of production processes than in recent decades cannot be excluded with labour saving innovations, increasing domestic capabilities to substitute for imported intermediate goods, and subsequent reshoring. And while support for globalization has dropped in some advanced countries below the 50 percent threshold, resort to protectionism and retreat from multilateralism, notably in advanced countries, are a potential threat for Shifting Wealth present and future.

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[1] Paul Krugman (1994), “The Myth of Asia´s Miracle”, Foreign Affairs 73.6, pp. 62-78.

[2] Robert Barro and Xavier Sala-i-Martin (2004), Economic Growth, 2nd edition, MIT Press: Cambridge, Mass.

[3] Daron Acemoglu, Philippe Aghion and Fabrizio Zilibotti (2006), “Distance to Frontier, Selection and Economic

Growth.” Journal of the European Economic Association 4.3, pp. 37–74.

[4] Indermit Gill and Homi Kharas (2015), “The Middle-Income Trap Turns Ten”, World Bank Policy Research Working Paper No. 7403, August.

[5] Angel Melguizo, Sebastián Nieto-Parra, José Perea and Jaime Perez (2017), “No sympathy for the devil!

Policy priorities to overcome the middle-income trap in Latin America”, OECD Development Centre Working Paper No. 340, September.

[6] OECD (2014), Economic Outlook for Southeast Asia, China and India 2014: Beyond the Middle-Income Trap

[7] Anton Korinek and Joseph Stiglitz (2017), “Artificial Intelligence and Its Implications for Income Distribution and Unemployment”, NBER Working Paper No. 24174, December.

[8] Jorge Arbache (2016), “The end of the global value chains”, Valor Econômico, June.

[9] Adrian Wood (2017), “Variation in structural change around the world, 1985–2015: Patterns, causes, and implications”, UNU-WIDER: WIDER Working Paper 2017/34, February.

[10] Jörg Mayer (2017), “Industrial robots and inclusive growth”, Vox, October.

[11] Fredrick Ishengoma and Adam Mtaho (2014), “3D Printing: Developing Countries Perspectives”, International Journal of Computer Applications, 104 .11, pp. 30-34.

[12] David Haugh, Alexandre Kopoin, Elena Rusticelli, David Turner, Richard Dutu (2016), “Cardiac Arrest or Dizzy Spell: Why is World Trade So Weak and What can Policy Do About It?”, OECD Economic Policy Papers No.18, September.

[13] Simon Evenett and Johannes Fritz (2016), “Global Trade Plateaus”, Vox, July.

[14] Guillaume Gaulier, Walter Steingress & Soledad Zignago (2016), “The role of China in the trade slowdown”, Rue de la Banque #30, Banque de France, September.

[15] Bart Los and Marcel Timmer (2016), “Peak trade? An Anatomy of the Recent Global Trade Slowdown”, University of Groningen, May.

[16] Christophe Degain, Bo Meng, and Zhi Wang (2017), Global Value Chain Development Report 2017, Chapter 2.

[17] The Economist (2016), What the world thinks about globalisation, 18^th November.