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Globalization Note Series Pankaj Ghemawat

Copyright © 2014 Pankaj Ghemawat. This material was developed for students in the GLOBE course at IESE Business School and should not be cited or circulated without the authors’ written permission.

Economic Distance: The Big Shift to Emerging Economies

In the first few decades after World War II, country market sizes and per capita income levels were highly correlated, implying that large multinational corporations (nearly all from advanced economies at the time) faced relatively little economic distance.1 Their most important foreign markets were in other advanced economies. The rapid growth of emerging economies, particularly since the beginning of the 21st century, has dramatically altered that pattern, with emerging economies becoming the world’s largest markets across many industries. The shift of economic activity to emerging economies requires multinationals to bridge greater economic distance: selling to customers across income levels, competing with firms from both advanced and emerging economies, and assembling value chains that tap into distinct resources and cost levels across advanced and emerging economies. And there is some evidence that multinationals from advanced economies are struggling with these challenges.

This note will focus primarily on the most prominent type of economic distance that separates advanced and emerging economies: income distance, i.e. differences in per capita income levels. Other types of economic distance that will not be emphasized here include differences in capital costs, factor endowments, business systems, and economic size. The first section of this note presents an analysis of how differences in levels of economic development relate to international interactions. It shows that per capita income differences inhibit most types of international interactions but do boost those that are motivated by arbitrage (e.g. exports of labor-intensive manufactures from low wage countries). The second section tracks the “big shift” of a rising proportion of economic activity to emerging economies, comparing the extent and speed of that shift across a variety of macroeconomic, corporate, and other indicators. The third section systematically examines differences between advanced and emerging economies that firms must account for when doing business between them. The fourth section raises the question of whether the big shift will lead to a big shakeup of the corporate pecking order, with firms from emerging economies displacing incumbents from advanced economies as global industry leaders.

I. Economic Distance and International Interactions

Economic distance inhibits most—but not all—types of international interactions. Exhibit 1 compares the impacts of halving per capita income disparities across ten types of international interactions, as estimated using a gravity model.2 Per capita income disparities, for this analysis, were measured based on the ratios of country pairs’ per capita incomes (higher divided by lower). If countries have the same per capita income, the ratio is one, and it rises as their per capita incomes become more different. Halving per capita income disparities implies, for example, shifting from a country pair such as France (GDP per capita ~$40,000) and Mexico (~$10,000) (ratio = 4) to a pair such as France and Portugal (~$20,000) (ratio = 2).

Merchandise exports was the only interaction, among the ten covered on Exhibit 1, where the impact of halving per capita income disparities was not statistically significant. This does not mean that merchandise exports are unrelated to per capita income disparities. Rather, it reflects how trade can be both motivated and inhibited by economic distance. Trade that is motivated by per capita income disparities seeks, for example, to arbitrage across wage levels by exporting labor-intensive products and services from poorer countries to richer countries. Along similar lines, trade can also be motivated by other aspects of economic distance such as differences in countries’ natural resource endowments. Traditional Ricardian and Heckscher–Ohlin trade theories focus on trade that is motivated by differences.

Trade can also be motivated by economic similarities (and inhibited by differences). Across countries with similar per capita incomes, buyers are more likely to be able to afford and interested in

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purchasing similar products. Firms, thus, can often sell products they develop for their home markets in other countries with similar levels of economic development without investing as much in adapting to meet foreign market requirements as would be necessary to sell in more different economies. Large observed bi-directional trade flows of similar products between countries with similar levels of economic development motivated the development of New Trade Theory by Paul Krugman and others. Data on total merchandise exports mix together trade that is motivated by economic differences and trade that is inhibited by them, resulting in a non-significant overall effect estimate.

Looking beyond trade, income distance has statistically significant effects on all of the other nine types of international interactions shown in Exhibit 1. In seven of the nine cases, the effects are positive, indicating that halving per capita income ratios increases interactions—in other words, that per capita income differences inhibit interactions. This is consistent with the broad pattern seen also for cultural, administrative, and geographic distance: interactions are more intense among countries that are more similar and decline as countries become more different.

The two interactions for which per capita income differences have the largest inhibiting effect are the two types of portfolio investment covered in the analysis: portfolio long term debt (where halving per capita income ratios boosts interactions by 48%) and portfolio equity assets (36%). Portfolio investment still takes place primarily between advanced economies, with upwards of three-quarters of these interactions involving one advanced economy investing in another advanced economy (and an even higher proportion if tax havens are excluded from the calculations).3

Per capita income differences inhibit people flows less than capital flows, presumably because there are also important arbitrage-style motivators of people flows. According to a World Bank estimate, the workers who move from developing to developed countries, on average, triple their real incomes.4 More emigrants from emerging economies, however, move to other emerging economies rather than to advanced economies, in part due to restrictions on people flows associated with visa and work permit requirements.5 Also, nearly 80% of international students from emerging economies go to study in advanced economies, where nearly all of the world’s top ranked universities are located.6

Services exports and outbound telephone calls are the two interactions for which statistically significant negative rather than positive effects are found for halving per capita income ratios, implying that these interactions are more intense between countries that are more different rather than more similar in this respect. For services exports, one possible explanation is that many services exports are motivated by arbitrage. India’s IT services exports, of which roughly three-quarters by value are destined for the United States and United Kingdom, present an obvious example.7 Advanced economies also export services to emerging economies arbitraging across differences in the availability of specialized skills. For example, the five tallest buildings in China were all designed by architects based in the United States and United Kingdom. And finally, the pattern of more intense outbound telephone calls between countries with more different levels of per capita income likely reflects how phone calls between advanced and emerging economies tend more often to be placed by the party in the advanced economy. A rough analysis indicates more than 3 times as many minutes of calls were placed from advanced economies to emerging economies than vice versa in 2012.8

In summary, economic differences can both motivate and inhibit international interactions, but the inhibiting effect tends to be stronger across the majority of the types of interactions studied here. These effects are becoming increasingly important to firms as the rising share of economic activity taking place in emerging economies—the focus of the next section—prompts them to do business across increasingly large economic differences.

II. The Big Shift to Emerging Economies

In 2012, emerging economies (defined throughout this note as those designated by the IMF to be emerging or developing9) generated 38% of the world’s economic output in U.S. dollar terms, nearly double their 20% share in 2000. (In purchasing power parity or PPP terms, emerging economies’ share of world GDP rose from 37% in 2000 to 50% in 2012.) Between 2008 and 2012, as most advanced economies were hit hard by the economic crisis, 77% of the world’s economic growth took place in emerging economies (74% at PPP). Between 2012 and 2018, 53% of global growth is projected to take place in emerging economies (65% at PPP).10 As shown in Exhibit 2, the big shift of economic activity to emerging

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economies predates the crisis, with the emerging economies’ share of world GDP having started a strong upward trend in the early 2000s (with a pronounced uptick after 2003).

The rising share of output generated in emerging economies is causing a geographic shift eastward of the planet’s economic center of gravity. It had already moved from the mid-Atlantic in 1980 to the rough longitude of Turkey by the late 2000s, and forecasts suggest that it could be on the Chinese- Indian border by 2050.11 One of the advantages of visualizing the big shift in terms of a moving center of gravity is that it helps to avoid mistaking the declining relative share of activity in advanced economies with absolute decline. Output per person (in constant currency) in the advanced economies, in spite of the crisis centered in those economies, was 13% greater in 2012 than in 2000 (as compared to 76% greater in the emerging economies).12

More granular analysis of the big shift is important because its extent and velocity vary widely across different types of activity. Exhibit 3 compares emerging economies’ shares of world totals across 75 metrics in 2000 versus 2013 or the most recent year with data available. Starting at the top of the exhibit, in light of emerging economies’ lower per capita incomes, it is unsurprising that population is the variable with the highest emerging share, and that seven of the top ten are demographic or other people- related variables. Nonetheless, it is still striking to note that 86% of the world’s population resided in emerging economies in 2012 (up only one percentage point from 2000). Those 86% enjoyed only 31% of the world’s final consumption expenditure in 2011—although this did reflect a very large improvement versus 19% in 2000.13

The five metrics with the largest shifts from advanced to emerging economies since 2000 were fixed broadband Internet subscribers (emerging share up from 1% in 2000 to 52% in 2012), mobile cellular subscriptions (up from 32% to 82%), FDI inflows (up from 12% to 47%), new registrations of passenger cars (up from 20% to 54%), and apparent steel use (up from 45% to 75%).14 These metrics exemplify the fast shifts taking place across a broad range of economic activities.

Merchandise exports ranks 35th out of the 75 categories, with 42% of merchandise exports coming from emerging economies (up from 26% in 2000). Exhibit 4 provides additional perspective by tracking the changing composition of global merchandise trade since 2005. It reveals that all of the growth of merchandise trade since 2008 has involved emerging economies either as exporters or as importers: trade between advanced economies had yet to regain its pre-crisis level as of 2012. Furthermore, “south-south” trade between emerging economies was the fastest growing component of merchandise trade flows, growing 18% (CAGR) from 2005-2012, versus 10% for exports from advanced economies to emerging economies and vice versa and 4% between advanced economies. The rise of emerging economies has also contributed to deepening trade integration by spreading the world’s economic activity more broadly across countries. According to one estimate, roughly one-third of the increase in trade intensity since the early 1990s was caused by economic output becoming less concentrated among a small number of large economies.15

Turning to the bottom of the list, five of the bottom ten metrics involve capital flows and stocks, particularly portfolio equity. Emerging economies accounted for only 5% and 9%, respectively, of outward and inward portfolio equity stocks in 2012 and only 7% and 14%, respectively, of outward and inward portfolio equity flows. This reflects the limited development of stock markets across many emerging economies as well as the use of capital controls in some. The emerging economies’ share of outward FDI stock, 10%, also places this metric among the bottom ten.

Corporate metrics are also concentrated near the bottom of Exhibit 3, with three placed in the bottom ten. While the emerging economies’ share of the world’s 500 largest firms by revenue (the Fortune Global 500) rose from 4% to 25% from 2000 to 201316 (with an accelerated shift since 2010 when the emerging share stood at 15%), that rise was driven by Chinese state-owned firms, many of which focus primarily on the Chinese domestic market. Excluding state-owned firms, the emerging economies’ share of the Fortune Global 500 rose only from 2% in 2000 to 9% in 2012 (ranking 70th on the chart). And on corporate measures that focus more on strength than on size, emerging economies are even more thinly represented. Only 6% of the world’s top 600 firms ranked by their R&D expenditures in 2012 and only 1% of the top 100 based on their brand values in 2013 were from emerging economies. The final section of this note—on the possibility of a “big shakeup” in the corporate pecking order—will return to the topic of the growth of firms based in emerging economies.

In between the macroeconomic and corporate levels, Exhibit 5 traces the shift of production and consumption to emerging economies across nine industries. The automotive industry exhibited the

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largest shift, moving from having roughly 85% of its production and consumption in advanced economies in 1998 to roughly 50% in 2012. The pharmaceutical industry, in contrast, barely shifted at all, still retaining approximately 90% of production and 80% of sales (in value terms) in advanced economies. Nonetheless, analysts predict that upwards of 75% of pharmaceutical industry growth through 2020 could come from non-traditional markets.17 Also note that mobile phones and footwear, located well above the diagonal line, are industries with large net exports from emerging to advanced economies.18

Looking at the big shift at the industry or product level also reveals that the world’s largest emerging economy, China, has also become the world’s largest market for a wide range of products. China ranked first in sales volume or value in 2012 across nearly all types of commodities and industrial products for which data were available (e. g. chemicals, steel, gold, soybeans, tobacco) and first or second for most consumer durables (e.g. first on consumer appliances and mobile phones, second on computers and peripherals and consumer electronics). China’s ranks are more varied on services (e.g. second on car rentals and fourth on insurance) and soft goods (e.g. first on apparel and twenty-fifth on pet care products).19 The broad variation in how the big shift has played out across industries and products suggests granular industry-level (and firm-level) analysis to spot business implications.

III. What is Different about Emerging Economies?

The rise of emerging economies described in the previous section has prompted many to probe for a deeper understanding of what distinguishes emerging economies from advanced economies, beyond the obvious pattern that emerging economies have lower per capita incomes ($6,933 on average in 2012 as compared to $42,225 across advanced economies) and faster real growth rates (4.4% as compared to 0.3%).20 This note provides a data-driven approach to answering that question, covering economic metrics as well as cultural, administrative, and geographic ones. Due to space limitations, it does not segment economies more finely than the broad categories of advanced versus emerging. However, it should be noted up front that there is substantial diversity within both categories and especially among emerging economies.21

The economic differences between advanced and emerging economies extend beyond the obvious ones cited above, as shown in Exhibit 6. Emerging economies also average larger shares of value added coming from agriculture and smaller shares from services, more volatile GDP growth, and higher levels of inequality. And despite their faster growth rates, with very few exceptions, there is little evidence of convergence of income levels between advanced and emerging economies.22

Emerging economies also differ from advanced economies on the cultural, administrative, and geographic dimensions of the CAGE framework. Culturally, people in emerging economies report that they accord work a higher priority in their lives, presumably an advantage for employers. However, generalized levels of trust are lower in emerging economies, which complicates all sorts of business dealings, and societies are typically more hierarchical, implying differences in the styles of leadership that will be most effective.23 Emerging countries are also, on average, more internally diverse ethnically and culturally, providing a reminder of the importance of not treating large emerging economies as monolithic entities: China and India are, in some ways, as diverse as Europe.24

Administratively, emerging economies rank significantly worse than advanced economies on standard indicators of rule of law, political stability and corruption. The latter is of particular importance with respect to international interactions. According to one estimate, an increase in corruption levels from that of Singapore to that of Mexico has the same negative effect on inward foreign investment as raising the tax rate by over 50 percentage points.25 Overall government final consumption expenditure as a percentage of GDP is also about one-third lower in emerging as compared to advanced economies. Military expenditure as a percentage of GDP is roughly equivalent between advanced and emerging economies but public health expenditure averages only half as large a share of GDP in emerging economies as it does in advanced economies.

Emerging economies also tend to pose more challenging geographic conditions. They are more likely to be landlocked, and poor built infrastructure can exacerbate natural geographic barriers. Emerging economies are also less urbanized and have lower population densities, adding to the challenges associated with extending a firm’s reach throughout a country.

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Some types of cross-country differences, such as the presence or absence of a common language, can only be measured relationally (i.e. with respect to bilateral country pairs), and so could not be included in Exhibit 6. Exhibit 7 provides a set of bilateral comparisons on the cultural, administrative, and geographic dimensions of the CAGE framework. It compares the likelihood that a randomly selected pair of two advanced economies, one advanced economy and one emerging economy, and two emerging economies share a set of commonalities.

It is useful to consider the analysis behind Exhibit 7 separately from the perspectives of firms based in advanced and emerging economies. From the perspective of a firm based in an advanced economy, emerging economies are more different or distant—to a statistically significant extent—than other advanced economies on every variable except language. Physically, emerging economies are more than one-third more distant, and administratively, advanced economies are more than three times more likely to have a trade agreement with another advanced economy than with an emerging economy (and advanced economies almost never share common currencies with emerging economies). These factors underscore the greater challenges firms from advanced economies face pursuing growth in emerging economies.

Firms expanding abroad from emerging economies have fewer commonalities both with other emerging and with advanced economies. Particularly notable is the relative paucity of trade agreements involving emerging economies. A randomly selected pair of emerging economies is only 10% as likely as a randomly selected pair of advanced economies to share a trade agreement. Emerging economies are also, on average, more distant physically from each other and less likely to share common land borders. Interestingly, many of the commonalities that can help ease international expansion from emerging economies reflect the colonial histories shared by many emerging economies. Emerging economies are more likely to share common languages and common legal origins with each other and with advanced economies than advanced economies share among themselves.

Emerging economies also differ from advanced economies in terms of the intensity with which they are integrated into international trade, capital, information, and people flows, i.e. how deeply globalized they are, as shown in Exhibit 8. Advanced and emerging economies are roughly at parity with respect to trade intensity—exports and imports of goods and services as a share of GDP. However, with respect to capital and people flows, advanced economies are 4-5 times as deeply globalized and advanced economies are 9 times as deeply globalized with respect to international information flows. Consider examples for each of these categories: While emerging economies attracted a record 47% of FDI inflows in 2012, advanced economies still provided 79% of FDI outflows. Emerging economies still have only 15% as much international internet bandwidth per internet user as advanced economies. And in emerging economies, people travel outside of their own countries’ borders on average once every 14 years (as compared to every 1.7 years in advanced economies).26

IV. Will the Big Shift Lead to a Big Shakeup?

Given the big shift, the firms that prove themselves most adept at bridging the differences between advanced and emerging economies covered in the previous section will gain a large edge over their rivals as they compete for global leadership of their respective industries. And some have even ventured to predict where the winners will be from. Thus, a McKinsey report released in October 2013 projected that more than 45% of the Fortune Global 500 are likely to be based in emerging economies by 2025 (up from 25% in 2013).27 This section considers whether—as that projection suggests might take place—firms from emerging economies will shake up the global pecking order in their respective industries and displace many incumbents from advanced economies as global leaders. This section begins by reviewing evidence in favor of such a scenario and then turns to evidence against it.

First, it is important to recognize that multinationals from advanced economies do not currently hold dominant positions broadly across sectors in emerging economies. 100 of the world’s largest companies headquartered in advanced economies derived just 17 percent of their total revenue in 2010 from emerging economies—even though those markets accounted for 36 percent of global GDP and were projected to contribute more than 70 percent of global GDP growth through 2025.28 This alone suggests that without any changes in their market shares in emerging economies, the rising proportion of economic activity taking place in emerging economies will shrink the global market shares of these firms.

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Recent growth trends also point toward further market share erosion for multinationals from advanced economies. Analysis over time frames from 1999 to 2008 indicates that emerging economy companies not only grew 10 percentage points faster annually at home than companies from advanced economies (18% vs. 8%) but also enjoyed a similar edge (22% vs. 12%) in advanced economies and an even bigger one in other (foreign) emerging economies (31% vs. 13%)!29

Surveys also indicate a growing recognition among executives in multinational firms from advanced economies of the problems their firms face dealing with the big shift. A recent survey by the Boston Consulting Group (BCG) indicated that while 78% of multinationals expect to gain market share in emerging economies, only 13% say they have an advantage over local competitors. BCG also reported that more respondents cited local competitors as a major threat in emerging economies than multinationals from either advanced or emerging economies.30

Limited globalization in their senior ranks is probably a significant reason why 56% of the executives attending a global leadership summit in May 2013 in London felt that “Western leaders are missing key opportunities in BRICS (S. Africa included) because they do not understand local business practices in these nations.”31 Of the 375 companies from advanced economies in the Fortune Global 500, only 4% have CEOs from emerging economies.32 And below the CEO level, a recent McKinsey survey of leading Western companies found that just 2% of their top 200 employees hailed from key Asian emerging economies.33

Although this talent gap could in principle be addressed by moving executives to emerging economies, according to the same BCG survey of large multinationals, only 9% of the companies’ top 20 leaders were located in these markets, vs. an average of 28% of their revenues. BCG also found that companies with some of their top executives located in emerging economies were more likely to outperform in those markets.34 Hiring local talent is also getting harder for Western multinationals in emerging economies. According to a Corporate Executive Board survey, highly skilled Chinese professionals’ preference for working in multinational over domestic companies in 2010 was only half as strong as it was in 2007.35

Multinationals from emerging economies are also developing significant capabilities of their own. A number of Chinese and Indian companies, for example, have developed low-cost capabilities that are the envy of competitors from advanced countries. And while governments have a poor track record at picking winners to become “national champions,” the high priority the Chinese government places on fostering the growth of Chinese multinationals—including via channeling cheap credit to them—is also a factor that must be recognized. Mauro Guillén and Esteban García-Canal also argue that multinationals from emerging economies tend to be less focused on short-term results (better able to pursue long-term strategies due to state or business group backing), are less encumbered by tradition, and are more willing to pursue growth in difficult and potentially dangerous locations.36

Yet another apparent trend that might help firms from emerging economies is the possibility that Western (especially U.S.) firms may be starting to “re-shore” production operations—i.e. to bring back manufacturing that had previously been offshored to emerging economies, as 87% of supply chain executives reported their firms intend to do, according to one survey.37 BCG estimates that across seven industry groups, “production of 10-30% of the goods that the U.S. now imports from China…could shift back to the U.S. before the end of the decade.”38 While this trend had not shown up in aggregate U.S. manufacturing and imports data as of 2011, should it indeed take place as some predict, it would reduce another avenue through which Western firms engage with emerging economies.

Established multinationals, on the other hand, do enjoy significant advantages that could help them defend against new rivals from emerging economies. As Exhibit 3 showed, firms from advanced economies still have a very large lead with respect to R&D expenditure and own almost all of the world’s most valuable brands. As the entrenched incumbents, they also have a disproportionate ability to dictate the terms of engagement.

The growth of multinationals from emerging economies may also be held back by their even less globalized leadership teams than multinationals from advanced economies. Only 2% of the firms from emerging economies on the Fortune Global 500 are led by a non-native CEO (as compared to 16% among firms from advanced economies). And below the CEO level, the same pattern also holds with only 3% of top management team members (direct reports to the CEO) being non-native at firms based in emerging economies on average (as compared to 18% in firms from advanced economies).

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Finally, the possibility of a big shakeup at the global level is also reduced by the fact that large firms based in emerging economies tend to be more domestically oriented than their advanced economy counterparts. Among the Fortune Global 500, advanced economy based firms generated 24% of their revenue outside their home regions, as compared to only 14% for emerging economy based firms.39 And if the world’s largest corporations are ranked based on their foreign assets (instead of their revenues), only 7 of the top 100 are from emerging economies.40 This pattern underscores the important point that climbing the ranks of the world’s largest corporations is not equivalent to taking over global leadership.

Conclusion

The rising share of economic activity taking place in emerging economies implies that it is along the economic dimension of the CAGE Framework that firms are likely to face their largest new challenges over the medium term. The economic dimension also differs from the others in the greater importance of arbitrage strategies along this dimension. Firms can and do arbitrage across cultural differences (e.g. selling the history of French winemaking to boost exports), geographic differences (e.g. importing fruits from other regions when they are out of season locally), and administrative differences (e.g. taking advantage of differences in tax policies). However, it is only on the economic dimension of the CAGE Framework where arbitrage strategies—particularly those focused on labor costs—are so central to the operations of many firms. Strategies for bridging economic distance will therefore remain a key focus, and must pay careful attention to both its attractions and its challenges.

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Exhibit 1: The General Effects of Halving Per Capita Income Ratios (Higher/Lower) (Gravity Model Estimates)41

‐12%

21%

10%

12%

9%

18%

36%

48%

‐25%

1%

‐40% ‐30% ‐20% ‐10% 0% 10% 20% 30% 40% 50% 60%

Outgoing Phone Calls

Printed Publications Exports

Tertiary Students' Arrivals

Emigration

Tourists' Arrivals

FDI Outward Stocks

Portfolio Equity Assets

Portfolio Long Term Debt

Services Exports

Merchandise Exports

In fo

P e o p le

C a p it a l

T ra d e

Note: All effects statistically significant except merchandise exports. Source: Generated based on gravity model analysis elaborated in Pankaj Ghemawat and Tamara de la Mata, “Globalization, Gravity, and Distance,” Working Paper, September 2013.

Exhibit 2: Emerging Economies’ Share of World GDP, 1980-2018 (IMF Projections)

Source: Generated based on data from IMF World Economic Outlook, October 2013.

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Exhibit 3: Emerging Economies’ Share of World Totals, 2000 vs. 2013 (or most recent available)

Notes: Unless otherwise noted, 2013 (or most recent) values are based on 2012 or 2013 data. Items marked with † are based on 2010 or 2011 data. For items marked with * 2000 data were unavailable: top 500 companies by market capitalization substitute 2001 data; portfolio equity and media expenditures substitute 2005 data.

Source: Generated based on data from International Monetary Fund, European Commission, Financial Times, Forbes magazine, Fortune magazine, GroupM This Year Next Year report (various editions), Interbrand, International Copper Study Group, Euromonitor Passport, Shanghai Academic Ranking of World Universities, UNESCO Institute for Statistics, ITU, Telegeography International Traffic Database, World Bank World Development Indicators 2013, UNCTAD World Investment Report, United Nations Commodity Trade Statistics Database, United Nations Population Division, World Steel Association, World Trade Organization.

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Exhibit 4: Merchandise Trade, Advanced vs. Emerging: Share (Left), Total (Right), 2005-2012

Source: Generated based on data from IMF Direction of Trade Statistics (DOTS) Exhibit 5: Industry Level Shift of Production and Consumption to Emerging Economies

Source: Generated based on data from World Health Organization (WHO), OECD, IMS Health, UN Comtrade, Anderson, K., & Nelgen, S. (2011). Global Wine Markets, 1961 to 2009: a statistical compendium. Adelaide: University of Adelaide press, Euromonitor Passport, United States Department of Agriculture. (2012). Sugar: World Markets and Trade., Koo, W. W., & Taylor, R. (2000). 2000 Outlook of the U.S. and World Sugar Markets, Northern Plains Trade Research Center - Department of Agribusiness and Applied Economics - North Dakota State University, iSuppli, and ResearchInChina.

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Exhibit 6: Unilateral Comparisons between Advanced and Emerging Economies

Notes: Variables marked with asterisk (*) were transformed using min-max normalization prior to calculating comparisons.42 The vertical lines between zero and one correspond to the vertical lines between 1 and 3. For example, 1.5 represents an equivalent excess of emerging over advanced as 0.67 represents of advanced over emerging.

Source: Generated based on data from World Value Survey (last wave 2005-2008); Fearon, James D. "Ethnic and cultural diversity by country." Journal of Economic Growth 8.2 (2003): 195-222; The Hofstede Centre; World Bank World Development Indicators; GMI Ratings Women on Boards Survey (2012); World Bank Worldwide Governance Indicators; Heritage Foundation Economic Index of Freedom (2013); World Economic Forum Global Enabling Trade Report (2012); World Bank Ease of Doing Business; HumanFreedom.org (2006); Centre d'Etudes Prospectives et d'Informations Internationales (CEPII) Geography Database; IMF World Economic Outlook Database (April 2013), United Nations Development Program HDI (2012); Hausmann, Ricardo, et al. "The atlas of economic complexity." Boston. USA (2011).

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Exhibit 7: Bilateral Comparisons between Advanced and Emerging Economies

Source: Generated based on data from Centre d'Etudes Prospectives et d'Informations Internationales (CEPII) and WTO.

Exhibit 8: Ratios of Advanced / Emerging Economies’ Globalization Depth Scores by Pillar (Trade, Capital, Information, People) on the Depth Index of Globalization

Source: Pankaj Ghemawat and Steven A. Altman, “Depth Index of Globalization 2013.”

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1 In 1950, countries in the top 20% on GDP per Capita generated a record 69% of global economic output (on purchasing power parity basis), a ratio that would average 60% throughout the second half of the 20th century but fall rapidly in the early 21st, reaching 48% in 2008, a level last seen in 1939.

2 For a brief explanation of the gravity model, refer to the note on Geographic Distance within this series. 3 Based on data from the IMF Coordinated Portfolio Investment Survey (CPIS). 4 World Bank, “Global Economic Prospects 2006: Economic Implications of Remittances and Migration,”

2006. 5 United Nations Development Programme, Human Development Report 2009, 29. 6 Pankaj Ghemawat and Steven A. Altman, “Depth Index of Globalization 2013,” Chapter 5. 7 Geographic distribution of India’s IT Services exports based on data reported by Nasscom. 8 Based on data from Telegeography Traffic Database. 9 The IMF classifies as emerging or developing both countries with low per capita incomes as well as

countries that achieve high per capita incomes but lack advanced market infrastructures, typically because they achieve high income levels primarily based on the extraction and export of natural resources. Thus, Qatar is classified as an emerging economy even though it ranked second worldwide on GDP per capita in 2012, behind Luxembourg. For additional material on country classification, refer to Appendix B of Pankaj Ghemawat and Steven A. Altman, “Depth Index of Globalization 2013.”

10 IMF World Economic Outlook Database, October 2013 revision. 11 Danny Quah, “The Global Economy’s Shifting Centre of Gravity,” Global Policy, Volume 2, Issue 1,

January, 2011; McKinsey Global Institute, “Urban world: Cities and the rise of the consuming class,” June 2012.

12 Calculated based on data from World Development Indicators and IMF World Economic Outlook Database, October 2013 revision.

13 Based on data from World Bank World Development Indicators covering countries accounting for 99% of the world’s GDP in 2000 and 98% in 2011.

14 See sources listed for Exhibit 3. 15 Arvind Subramanian and Martin Kessler, “The Hyperglobalization of Trade and Its Future,” Peterson

Institute for International Economics Working Paper WP13-6, July 2013. 16 Note that the 2013 Fortune Global 500 reflects data on firms’ revenues during 2012. 17 Gbola Abusa, et. al., “UBS World Pharma Model,” September 21, 2010. 18 Calculations cited here paragraph were generated based on data from Euromonitor Passport, World

Health Organization, OECD, IMS Health, and UN Comtrade. The estimates for pharmaceuticals include finished pharmaceuticals only (not bulk).

19 Based primarily on data from Euromonitor Passport database, supplemented with industry-specific sources to fill gaps.

20 Simple average across countries based on data from IMF World Economic Outlook Database, October 2013.

21 Economist Ricardo Hausmann quotes Tolstoy to make this point with respect to diagnosing country- specific obstacles to economic growth: “Anna Karenina starts with the famous line: ‘Happy families are all alike; every unhappy family is unhappy in its own way.’ Paraphrasing Tolstoy: each developing country may be held back by very different things.” Quoted from Ricardo Hausmann, “In search of the chains that hold Brazil back,” Center for International Development at Harvard University, 2008.

22 An analysis of real GDP per capita in PPP terms since the 1960s highlights only the “Asian Tigers” (Hong Kong, Singapore, South Korea, and Taiwan) as having converged to the levels of the

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industrialized economies. A similar analysis focused on real GDP per worker is provided in Exhibit 7 of the Note on The Globalization of Markets.

23 Data on importance of work and on levels of trust are drawn from World Values Survey (last wave 2005-2008). Data on hierarchy based on Hofstede’s Power Distance.

24 Data on ethnic and cultural diversity drawn from James D. Fearon, “Ethnic and cultural diversity by country,” Journal of Economic Growth 8.2, 2003.

25 Shang-Jin Wei, “How Taxing is Corruption on International Investors?” Review of Economics and Statistics, 82, 1-11, February 2000.

26 These comparisons are all drawn from Pankaj Ghemawat and Steven A. Altman, “Depth Index of Globalization 2013.”

27 McKinsey & Company, “Urban world: The shifting global business landscape,” October 2013. 28 McKinsey & Company, “Winning the $30 trillion decathlon,” 2012. 29 Ibid. 30 The Boston Consulting Group, “Playing to Win in Emerging Markets,” September 2013. 31 “Lack of local knowledge prevents expansion into BRICS,” London Business School Leadership Summit Poll, 2013. For more details, see http://www.london.edu/newsandevents/news/2013/05/ Lack_of_local_knowledge_prevents_expansion_into_BRICS_1663.html. 32 Based on a custom dataset assembled by Pankaj Ghemawat and Herman Vantrappen. 33 McKinsey & Company, “Winning the $30 trillion decathlon,” 2012. 34 The Boston Consulting Group, “Playing to Win in Emerging Markets,” September 2013. 35 McKinsey & Company, “Winning the $30 trillion decathlon,” 2012. 36 Mauro Guillén and Esteban García-Canal, Emerging Markets Rule: Growth Strategies of the New Global

Giants, McGraw Hill Professional, 2012. 37 BDP International and Temple University Supply Chain Survey, 2012. 38 The Boston Consulting Group, “Made in America, Again: U.S. Manufacturing Nears the Tipping Point,” March 2012. 39 McKinsey & Company, “Urban world: The shifting global business landscape,” October 2013. 40 Based on 2012 data reported in UNCTAD World Investment Report, 2013, Annex Table 28. 41 As described in the text, halving per capita income ratios implies, for example, shifting from a country

pair such as France (GDP per capita ~$40,000) and Mexico (~$10,000) (ratio = 4) to a pair such as France and Portugal (~$20,000) (ratio = 2). The calibration shown on the chart for Portfolio Long Term Debt, thus, means that this example (shifting from a ratio of 4 to a ratio of 2) would imply a 48% increase in portfolio long term debt between a country pair. Shifting from a ratio of 8 to 2 (halving twice, from 8 to 4 and then from 4 to 2) would imply an increase of 1.48 * 1.48 = 2.19 (or 119%).

42 Min-max normalization rescaled values to lie between 0 and 1 without changing the shapes of the relevant distributions. Variables from World Governance Indicators and Economic Complexity Index were normalized to avoid incorporating negative values into the ratio calculations; variables from World Values Survey were coded based on answers to individual survey questions and made comparable via normalization; World Bank’s Ease of Doing Business ranks were normalized in order to reverse order and improve comparability with other data components.