This is further illustrated in Appendix I on the globalization of car markets. ..... There are four types of trades: (i) commodities trade that comprises fuels, minerals and ...... trains with the petrol crisis of 1973. ... by the White Pass and Yukon Route.
GLOBALIZATION AND ECONOMIC CONVERGENCE, THE SECOND WAVE: A REINTERPRETATION
Abel M Mateus EBRD and UCL
Abstract: The second wave of globalization, usually dated from 1985 to the Present, is characterized by an increase of the goods and services ratio to World GDP of 9 pp, integration of capital markets with an expansion of 23 pp in FDI over GDP, more intense communication and information relationships with significant transfers of human capital and build-up of business and technological networks. The integration of the Communist countries, including Russia, China, Eastern European and East Asian countries led to a massive expansion, about one third, of the world production possibility set as well as the world market. It redesigned the polyhedron of international trade with the large transfer of manufacturing (5.5 trillion USD from 1985 to 2010) from the developed world to China and East Asian countries. The transfer of technology with the intensification of trade and investment led to an unprecedented convergence in East Asian countries and a reduction of 400 million persons under the poverty line, predominantly in China and India. Another major contribution of our paper is to give an integrated index of trade costs at national and international level that reflects technological progress and trade integration. Coupled with the increasing differentiation and geographical reallocation in factor endowments across the world, they fully explain globalization. The analysis calls for further integration of growth and trade theories. Our reinterpretation is fully consistent with the first wave of globalization and also gives a better framework to estimate the limits of the present globalization wave. Key Words: Globalization, Economic Growth, Economic History, Trade and Industrial Organization
This draft: London, January 31st, 2014
1. Introduction 2. Intensification of trade and FDI flows 3. Structural changes in international trade and FDI 4. Review of literature on causes of globalization and relationship between globalization and economic convergence 5. Expansion of the world Production Possibility Set and World Market 6. Technological progress and technology transfer 7. Reducing trade barriers and trade integration (regional and global) 8. Organization of the production at world level: multinational enterprises, offshoring and production networks 9. Human capital transfer 10. Trade costs 11. Factors behind globalization: explaining globalization 12. Convergence at world scale 13. Similarities with 19th century 14. Conclusions
1. Introduction Globalization is the process of integration of economies across borders, regions and world, through a more intense and enlarged exchange of goods and services, financial flows and investment, transfer of technology and human capital. The process could be extended also to the exchange of institutions and cultural integration. The second wave of globalization that took place since the mid-1980s to the present, and that has its roots in the post-II World War, reached unprecedented levels when compared historically. In fact, the rates of exchange of goods, capital, technology and human capital have never in history reached such intensity and broadness after the mid to late 1990s. It is important to consider an economic and financial world system of trade and factor flows, based on market economies, that is at the core of globalization. It would be difficult to conceive the extent and deepness of the present wave of globalization without the fall of the socialist economies and their transition to market economies. When compared with the first wave of globalization in the second half of the 19th century we witness the deliberate construction of political entities like the European Union or NAFTA, the rise of multinationals and the appearance of production networks with vertical and horizontal integration, and most notably the integration of developing economies (without the same cultural and institutional background) into the globalization process. In fact, as we emphasize in a companion paper, Mateus (2013), the first wave of globalization was mainly the transplant of Western European economies to the so-called Western offshoots (North America, Australia and New Zealand). The process of globalization fed into the growth of several regional/national economies that accelerated its convergence. As we will see below, the convergence was evident only in three cases: East Asian export model, European Union and countries rich in natural resources. For the first time in history countries adopting a coherent set of economic policies were able to fully or get close to converge to the income levels of the most advanced countries in just three to four decades. But growth is always uneven and agglomeration economies prevent the spread of industry across a large number of regions or countries: leading nations have high growth rates and also lead in the globalization process, but overall developing countries have achieved record levels of income per capita and although poverty continues to affect a large share of human population, also never in history so many hundreds of millions have escaped poverty. In order for economy theory to be able to explain the recent economic history there is a need to marry development (growth) theories with theories of international trade: development spurts in some poles and then spreads/pulls other regions at national and international level through a process of technological diffusion; but the diffusion cannot be explained unless we reach out to the models built to explain international trade in differentiated goods and monopolistic/oligopolistic markets, and in regional terms using paradigms of economic geography.
International trade plays a major role in the international process of specialization and division of labor by the interchange of goods, factors and ideas, facilitated by the reduction in trade costs plus setting-up production and knowledge networks. We can identify three phases of globalization in the post-II World War. The first phase starts with the spread of US multinationals to Europe, taking advantage of reconstruction and integration in European Communities. It ended with the oil shocks. The second wave appeared simultaneously in East Asia, North America and Europe until the end of the 1980s, and is marked by the appearance of value chains and further rise of multinationals. The third phase started with the fall of the socialist systems and the integration of these economies into the core world trade and economic system, and accelerated with the intensification of the ITC technological revolution. In this phase China rose to be the manufacturing center of the world. Literature on globalization has most of the ingredients but lacks a coherent picture (what are the most important factors and what are the relevant channels of causation) and we also need to establish a link with modern growth (development) theories. There are three main components of growth theories: (A) Process of accumulation of human capital (stock of knowledge – ideas – embodied in a given population at a given time and place), and in particular the level of technological knowledge (engineering and managerial/organizational). How new technological knowledge is generated? How does it spread? Note that only part of this knowledge is generated by R&D in laboratories or universities, most of it is generated by “mass flourishing” by independent individuals, in the shop floor, by learning-by-doing, etc.. It is also transmitted (diffused) through a multitude of channels (from face-to-face conversations, learning in schools to consulting the internet). (B) The design of institutions and their transformation and evolution. These institutions, from the political system, economic power structure and distribution, rule of law, property rights, etc. frame basic economic decisions: to get education, to save, to invest, to work, to emigrate, etc. which influence the process of accumulation of knowledge and the growth engine. (C) The process of accumulation of physical capital (factories, infrastructures, cities) that the neoclassical school has recognized as the growth engine, the process of savings/investment. It should also include externalities and agglomeration process, as recognized by the modern theories of geography and growth. How to marry these growth theories with trade theories to explain globalization? A technological innovation sprung up somewhere in a given country (usually a developed country) and subsequently it spreads from one firm to others in the proximity and later it is diffused to other economies. When that diffusion crosses borders there is technology transfer. Technology transfer takes place through trade, use of a patent or foreign direct investment. Usually trade of a given good from the center of innovation takes precedent to the spread of production either by investment abroad of the innovator, or any other form of technology transfer. Nowadays, underlying this process there are production chains and networks at international level with vertical and horizontal integration that produce the good or spread the
new technique or innovation. Thus, speed and quality of networking is fundamental, in terms of trade costs, communication costs (that have been neglected thus far) and interaction of individuals (transaction of ideas). The theoretical models in the literature are not yet able to fully explain the main trends have not been fully integrated and be able to is framework tell a very different story of the relevant facts to explain the present as well as first wave of globalization. A valid model should encompass both episodes of globalization. The present wave is characterized by: (A) Incorporation of whole new nations in the World Economic System with the fall of communism: the system expands by more than a third, which led to a reallocation of economic activity at world level (labor scarce North to technology scarce Asia). The process of technological innovation continued to operate (some economists argue, namely R. Gordon, at a lower level since the 1970s, using an analysis of total productivity indexes) but technological and human capital transfer intensified throughout the last two decades , (i) massive flow of international students to developed countries universities, (ii) diffusion of R&D and other forms of innovation through value-chains and production networks, and (iii) diffusion of knowledge through internet, (iv) facility of contacts through internet and international transport. (B) Opening-up of those economies to the World Economic System was in itself the major institutional change; Recognition of the role of markets in development of economies; transfer of institutions from North to South and in particular of the Asian export-led growth model; Trade liberalization through GAT/WTO. (C) High-gear growth engines in Asian tigers and China plus continuation of steady growth in North. There are important similarities with the first wave: (A) The World Production Possibility Set also expanded due to the incorporation of the territories of the Western Offshoots in the world economic system: mass migrations of relatively skilled persons from Europe to the Western Offshoots plus the opening-up and incorporation in the world economic system of massive natural resources expanded allowed increase in productivity and expansion of productions at world level with the reallocation of activities at international level (from land scarce Europe to labor scarce New World). The process of creation and diffusion of technological knowledge reached unprecedented levels. In fact, the process of technological innovation and transfer of the liberal era – spread of the first and rise of the second industrial revolutions - led to rapid technological progress: US become the center of technological leadership, relatively to Britain, just in 40 to 60 years – this transfer of a center of technological progress is unique so far in the last 200 years history. (B) Institutional change also occurred in massive way, and was much more rapid than in the present wave: building of institutions in the New World was immediate because of the transfer of European institutions: democracy, legal systems, culture. A completely different investigation is the comparing institutional building in nations of quite different cultures like Asian or African.
(C) By all accounts, engines of growth worked in high gear in the Western Offshoots.
Technological progress plays a major role in globalization and growth. In terms of growth it is essential to push forward the world production frontier that is the benchmark for convergence of any economy. Second, technological transfer by diffusion from the centers originating the innovation is crucial for both growth and globalization. Over the long term (Schumpeterian long waves) technology is the dominant factor. New (higher productivity or new products) technologies are central to the growth/trade process. However, as Comin and Hobijn (2004) recognizes, there was a lack of empirical models and studies of the process of technological change. It is interesting that their research not only confirms that the lags in the diffusion and adoption of new major technologies have shortened through time and especially after the II World War – more evidence that the process of globalization is associated with technological diffusion, but also that most important determinants of the speed at which a country adopts technologies are the country’s human capital endowment, type of government, degree of openness to trade, and adoption of predecessor technologies. General Purpose Technologies have played a major role in the globalization/convergence process. However, it is difficult to identify the date of the technology – usually is a succession of innovations that allow first the technology to start and after to be fully effective) and subsequently its adoption date. A proxy can be defined using the production levels of the product or industry, but is only an input and not provide the output impact that is our object of research. Also important is the date of maturity, defined when it reaches a plateau (e.g. in infrastructures when it has reached most of its full potential capacity – railways, telephone wires) An important conclusion from our research is the confirmation of two basic factors to explain convergence: (i) openness/integration in the world economic system and (ii) institutional development. No economy has converged significantly in the last half century without participating in the world economic system: this is the strongest evidence we have seen so far that trade promotes growth. The evidence does not specify what type of trade policy is put in place but without success in exports over the long-term there is no convergence, even for large economies. The East Asia model proves it. Second, adoption of institutions to support market efficiency, accumulation and “open” trade there is no convergence.1 The case of the European Union proves it. Third, abundance of valuable natural resources can be an enhancer of growth and especially support high income levels – it naturally depends on endowments per capita – but is subject to the “curse of natural resources” when monopolization by an elite and waste of the rents generated takes place. Section 2 studies the main indicators of globalization commonly used and the phases discerned so far: trade flows and FDI over GDP as well as market shares of different regions and countries. Despite their limitations they show clearly the intensification of the globalization process, the rise of developing countries and in particular China as manufacturing activity 1
Our analysis complements the research of Acemoglu and Robinson (2012).
spreads from the traditional centers to these new countries, where the most regions have not participated in the past in the world economic system. Section 3 exploits the structural changes that have been taking place in trade and investment like the rise of intra-industry trade, inter-firm trade and vertical trade, the terciarization of developed countries and the transfer of manufacturing to emerging economies, and in particular China. Section 4 exploits the theoretical literature that tries to explain globalization and the recent movements for horizontal and vertical specialization across regions/countries. It shows that new and new/new trade theories based on monopolistic competition and microeconomics of trade have made fundamental contributions and that geography through agglomeration economies is also essential to understand globalization. New theories of multinationals are also important. We also study the relation between trade theories and growth theories that still need further integration. Section 5 characterizes the expansion of the world production and consumption sets that are the basis of globalization. This is one aspect frequently referred to but never quantified and put at the center of the second wave of globalization: the integration of the old socialist economies in the world economic system. Section 6 identifies the major technological changes and their impact on globalization/growth: very few industries and areas of economic activity have been left untouched, even if there was not such a revolutionary change as in the second industrial revolution. Section 7 documents how the lowering of trade barriers and political movements of world/regional integration have reduced the costs of transactions across regions/nations. Reduction in trade barriers is hard to quantify due to a myriad of regulations and institutional aspects that affect trade nowadays. Section 8 studies one of the most important structural changes in the organization of production across the world, allowed by the reductions in trade and communication costs as well as new management techniques and the rise of the internet which are the value or supply chains. The introduction of value chains in trade statistics by international organizations are changing the way we read trade data and their impact on domestic economies. This is further illustrated in Appendix I on the globalization of car markets. Section 9 studies one of the phenomena that has been completely neglected in the study of globalization and international trade which is the transfer of human capital. One particular aspect that this transfer assumes is the millions of students that are now crossing borders to study in the more developed countries at secondary and mainly university level. However, also important is the movement of PhDs and the setting-up of laboratories and R&D centers across the world to exploit the pools of highly level scientific knowledge. Section 10 quantifies the dramatic reduction in transport, communication and information costs. All the above factors are then brought in context using econometric analysis in section 11. Section 12 studies the relation of globalization and convergence, which is exploited econometrically in Appendix II. Section 13 compares the first and second waves of globalization and section 14 concludes.
2. Intensification in trade and FDI flows
Globalization is always characterized by rapid growth of trade across regions and continents and factor movements in terms of human and physical capital, technological transfer and may be labor. Figure 1 show that total exports increased at an average rate of 6.2% in the 19502005 period, 1.6 times the GDP world growth rate of 3.8%. But trade of manufactures increased even at a higher rate: 7.5%. The second wave of globalization surpassed in intensity of trade the first wave by at least a factor of 3 taking the 2010 data and comparing it with 1913. In fact, by the early 1970s the ratio of world exports over GDP had reached the 1913 level, it hovered around 15% in the 1970s and took off in the mid-1990s. From 1985 to 2012 there was an increase in the ratio of world exports of goods to GDP of 9 pp.. In 2012 UNCTAD records total world exports of goods and services of 18.2 trillion USD, while the WEO IMF records 22.5 trillion, corresponding to 25.5 and 31.2 percent of GDP, respectively. There has been a gradual intensification in the level of exports of goods and services over GDP in the world since 1960, as Figure 1 documents. The data shows three phases: (i) 1961-1974 with an increase of 5.7 pp in the ratio, which can still be considered part of the catching-up process after the II WW ending with the oil shocks, (ii) 1975-1992 when part of the world suffered from the oil shocks and the financial crisis of the developing countries, as well as a phase of low technological progress. In this period the ratio only increased by 2.6 pp with substantial fluctuations – only in 1992 the ratio was higher than the 1982 level, (iii) 1993Present with an almost steady increase, when the ratio jumped by 10 pp, interrupted suddenly by the global financial crisis of 2007-2009 of devastating consequences. By 2013 the ratio had yet to recover to the peak of 2007.
Figure 1: World globalization index 31.00
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Source: UNCTAD and Author´s Estimates The second part of Figure 1 gives the globalization indices (Exports of Goods and Services over GDP) by major groups of countries. Decomposing the exports ratio between developed and developing countries we get a different periodization for the developing world, while the developed countries ratio evolved parallel to the world ratio, due to the dominance of those countries in the world trade. The oil shocks pushed the export ratio of developing countries by 5 pp, but after 1986 there was a steady increase in the ratio up to 2006. In fact, the data gives clearly an inflection point at around 1986. In the 1961-1986 period the ratio of exports increased at an annual rate of 0.18 pp, while for the 1987-2006 period the average increase was 0.91 pp. This acceleration is particularly due to the explosion in East Asia, that jumps from an increase in the ratio of 9 pp in the 1961-1986 period to 31.7 pp in the 1987-2006 period. While in East Asia there was acceleration above 3 times, in Latin America the expansion was more regular: the ratio of exports increased from 4.8 pp in the first to 9.7 pp in the second period, an acceleration of 2. What factors explain the turning point in terms of globalization around the mid-1980s? Table 1 shows the impact in the structure of international trade. The share of developing countries of about 30% in 1980 starts to decline up to 1995 (21.7%) and then it recovers, to reach a share of 35.9% at the close of the 2010 decade. A group of countries that is behind that decrease are the transition economies associated with the collapse of the Soviet Union, where the share of exports decreased from 13.7% in 1970 to 1.2% in 2000, starting then a long comeback.
Table 1
Share of World Exports of Goods and Services Developed economies Developing economies of which: Transition econ
1970 69.4 30.6 13.7
1975 69.4 30.6 11.2
1980 69.9 30.1 8.5
1985 72.8 27.2 7.4
1990 78.7 21.3 3.8
1995 78.3 21.7 1.9
2000 77.0 23.0 1.2
2005 73.9 26.1 2.4
2010 64.1 35.9 3.4
Source: UNCTAD The composition of world trade by major country shows important changes throughout the post-II WW period. Figure 2 shows exports in current USD for the countries that had exports of goods and services above 500 Billion USD in 2012. China, including Hong-Kong and Macau, has the world largest volume of exports of goods and services (2.8 trillion), having surpassed Germany in 2006 and the US in 2008. The second largest is the US with 2.2 trillion, followed by Germany with 1.7 trillion. Figure 2 Exports of goods and services 3,000,000
2,500,000
2,000,000 USA
Millions USD
China Germany
Japan
1,500,000
France Korea Italy Canada United Kingdom
1,000,000
500,000
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
0
Source: UNCTAD This set of nine countries (Figure 3) represents roughly half of world trade.2 An analysis by countries and by periods shows that 1950-1973 was the cycle of Germany and Japan with both countries increasing appreciably their world market shares (Germany 9.1 pp to 12.9% and Japan 5 pp to 6.3). With European recovery from the II WW all EC countries did quite well. This evolution came to an abrupt end with the first and second oil shocks and the loss in 2
The calculations are at constant prices of 1982-84.
competitiveness of these oil importing economies. The period up to 1990 shows the stability of the structure of the world trade shares but with the awaking up of East Asian countries (Asian Tigers) and later China. The period up to 2002 marks the rise of China as a world power in manufacturing with its trade share doubling 4.2 to 8.1%, largely at the cost of developed countries. The period of 2002 to the Present is marked by the establishment of China as the first world power in trade with its market share reaching 13% in 2012. Panel B of Figure 3 gives the market shares but aggregating the EU countries and reporting only extra community trade. The market share in international trade of goods of the EU was still the largest in the world with 16% in 2012, but it was slightly above 20% in the late 1990s. The 1950s up to the first oil shock was a period of steady expansion of the EU in world trade.3 In the later period it lost about 5 pp, similarly to the US who lost even more. Once again it is clear the success of Japan up to late 1980s and then the rise of China, with Korea steady increase although at a lower level. A trend analysis of the 3 largest developing countries shows that Korea had the following periods: (1) strong growth from 1960 to 1977, (2) deceleration but still strong growth in the 1977 to Present. In India there were three periods: (1) almost stagnation in 1950 to 1973, (2) acceleration in 1973 to 1999, (3) further acceleration in 1999 to Present. And in China: (1) strong growth in the 1950 to 1985, (2) acceleration in the 1985 to Present. Figure 3 World market shares 60.0
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France 20.0
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We extrapolate the share before 2000 with data for EU-15 and then EU-12 and EU-6.
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Source: UNCTAD and Author´s calculations An analysis of the evolution of the degree of openness of these countries puts three countries in a special league: China, Korea and Germany. In China4 the ratio of Exports of Goods over GDP increased from about 5% in 1970 to a peak of 43% in 2006 (before the financial crisis). Korea had an equally successful performance by increasing its openness ratio from 9.4% in 1970 to 33% in 1987. It experienced a long slump until the Asian crisis and then the country resumed expansion, with its weight of exports rising to 49.7% of GDP in 2011. In the case of Germany there was a steady increase up to 1974 and then a stagnation in the opening up to around 1998-99, followed by a very successful wave of improved competitiveness and opening leading to an increase in the ratio to 41.5% of GDP in 2012. Another important measure of globalization is the cross-border flows of FDI. The flows of FDI were less than 0.5% of world GDP before 1985; they grew to about 1.14% in 1995 and reached a peak in 2000 with 4.34% of GDP. Thus, the year 1985 is a clear inflection point in the rise of FDI world flows. But it was only in the first decade of the 21st century that the flows to developing countries reached a significant part of the total flows, representing about half of investments. FDI flows also show a more pronounced cyclical behavior than trade. By the end of the 1990s, annual flows as a proportion of developing-country GDP were three times higher than in the 1970s. Nonetheless, measured against the apparent opportunities for productive investment in the developing countries, as well as against the flows a century earlier, they were still small. At the end of 2001, the worldwide stock of cross-border bank loans and deposits was $9 trillion. Of that, only around $700 billion was attributable to developing-country borrowers. The stock of global cross-border investment in securities was some $12 trillion, of which developing-country borrowers accounted for just $600 billion. As in 4
Defined as above.
the 19th century, moreover, most of the capital exported by rich countries to poor countries still travels to just a handful of recipients. Figure 4 FDI over GDP 80.00
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In 2010 of a total world FDI stock of 19.1 trillion USD current, 9.6 was in developed economies (US, UK, France, Germany, Belgium, Netherlands, Canada, Singapore and Australia). Only two developing countries had a stock of at least half a trillion: China and Hong Kong (1.6 trillion) and Brazil (.5 trillion).5 An indication of how closely trade is linked with investment is the fact that about one third of the $6.1 trillion total for world trade in goods and services in 1995 was trade within companies — between subsidiaries in different countries or between a subsidiary and its headquarters. Table 2 shows the stock of FDI by investing country in the 1980-2010 period, for the 12 countries with highest share in the total. In aggregate they represent 75.6% of the total. They are all developed countries. Hong-Kong is the country that has had the largest expansion in the last thirty years, as a platform for investment in continental China. The second strongest increase has been Spain which has been investing mainly in Latin America. Table 2
5
Taking the criteria of (i) GDP above 100 billion USD, (ii) ratio of FDI stock over GDP above 50%, and (iii) country not classified as an offshore financial center, there are only four countries: Sweden, Hungary, Chile and Czech Republic.
Foreign Direct Investment by Investing Country, stocks In billions USD current
United States United Kingdom Germany France China, Hong Kong SAR Switzerland Japan Belgium Netherlands Canada Spain Italy
World Total
1980
1990
2000
2010 Percent
215 80 43 25 0 0 20 6 42 24 2 7
732 229 152 112 12 66 201 41 105 85 16 60
2,694 898 542 926 388 232 278 180 305 238 129 170
4,767 1,627 1,436 1,580 936 934 831 917 962 639 651 488
22.8 7.8 6.9 7.6 4.5 4.5 4.0 4.4 4.6 3.1 3.1 2.3
549
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Source: UNCTAD
Table 3 reports the eighteen countries with the highest share in the stock of FDI, in 2010. As an aggregate they represent 72% of the total. Both outward and inward FDI are thus highly concentrated. After the US which is both the largest investor and the largest recipient of FDI, UK, France and Germany are also at the top of the list. The only exception is China that when considered jointly with Hong-Kong is the second recipient country in the world with 8.7% of the total in 2010. Table 3
Foreign Direct Investment by Recipient Countries In billions current USD
United States China, Hong Kong SAR United Kingdom France Germany Belgium Spain Netherlands China Canada Switzerland Australia Brazil Singapore
1980
1990
2000
2010 Percent
83 178 63 32 37 7 5 19 1 54 0 25 17 5
540 202 204 98 111 58 66 69 21 113 34 80 37 30
3 9
13 60 22
2,783 455 439 391 272 195 156 244 193 213 87 119 122 111 32 94 121 97
3,451 1,098 1,086 1,008 674 670 614 590 579 561 539 508 473 470 423 349 337 327
18.0 5.7 5.7 5.3 3.5 3.5 3.2 3.1 3.0 2.9 2.8 2.7 2.5 2.5 2.2 1.8 1.8 1.7
699
2,081
7,446
19,141
100.0
Russian Federation Sweden Italy Mexico
Total Source: UNCTAD
Figure 5 shows the weight of FDI in terms of stocks, as shares of GDP, by recipient region. Today all the three groups are rather aligned at about 30% of GDP. The region that has shown the largest increase has been the Transition countries, with an explosion after the late 1990s, although they represent only 3.3% of the total. Cross-Border Mergers and Acquisitions make up a large fraction of FDI and are a particularly important mode of entry into developed countries.6 After the mid-1980s FDI accelerated substantially in developing countries. In our view this is one of the main reasons we consider the start of the second wave of globalization in the mid1980s. As we saw above, it was marked by the delocalization of manufacturing from Japan to Asia, from the USA to Mexico and Western Europe to the South. The process intensified resolutely with the delocalization from the three origins above to China after the 1990s. Multinational activity is primarily concentrated in developed countries where it is mostly twoway. Developing countries are more likely to be the destination of multinational activity than the source.
Figure 5
6
See UNCTAD (2012).
FDI in stocks 40.0
35.0
30.0
Percent of GDP
25.0
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20.0
Transition economies Developed countries 15.0
10.0
5.0
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
0.0
Less studied have been the population flows in the period under analysis. There were substantial emigration flows from Southern Europe to the Central and Northern parts, as well as to Western Europe offshoots, totaling about 55 million persons in the 1950-1998 period7, corresponding to 8 and 10%, respectively, of the 2010 population of those areas: reaching the same intensity as in the late 1800s. However, and contrary to the experience of the Western Offshoots in the 19th century, the incorporation of the new countries in the world economic system did not entail major migrations.
3. Structural changes in International Trade and Investment We are going to analyze the evolution of the structure of trade by type and by regions/countries. The majority of international trade in the century before the 1960s has been in terms of exports of fuels and minerals for imports of manufacturing countries or countries with lack of those natural resources for final consumption, tropical agricultural products and grains for food deficit countries, and manufactured products. The expansion of multinational enterprises after the II WW and in particular after the 1960s, first from the USA to Europe and later to Latin America, as well as the regional integration movement in Europe, with dominant relevance of the European Communities, and Japanese outsourcing in East Asia, led to the rise of intra-firm trade. The outsourcing and offshoring intensified to extraordinary levels with the integration of China in the world economic system after the 1980s, with intensification after the turn of the century. There are four types of trades: (i) commodities trade that comprises fuels, minerals and agricultural products, (ii) intra-industrial trade that refers to flows of goods within the same industry, it includes horizontal outsourcing and offshoring, (iii) intra-firm trade that refers to trade within the same multinational firm, it includes vertical offshoring, (iv) inter-sectoral trade 7
Maddison (2000)
that refers to trade between differs sectors across nations that usually is identified with traditional comparative advantages that rise from different factor prices/factor endowments or Ricardian trade associated with different productivities, and (v) more recently, the concept of value-added trade that excludes double accounting in imports of intermediate goods. Table 4 reports the estimates for major types of trade.8 They show the following important trends: (a) Intra-industry trade rose intensively in the 1960s by more than doubling its share from 10.5 to 23.5% of total trade. It rose again by 10 points in the next two decades and again by 5 points in the 1990-2010 period. Moreover: most of trade among developed countries is intra-industry trade. These movements are related with two factors, as we will see below: the integration of the European communities, and the expansion of multinationals in Europe and North America; (b) Intra-firm trade increased from 9.6% of total trade in the 1960s to 41.2% in the 2010s. The expansion of intra-firm (multinationals) trade was intense in the 1960s (see FDI expansion) across the North-Atlantic, reaching 22.1% of total trade in 1970. There was a slow expansion in the next two decades (5 points in 1970 to 1990). It accelerated again in 1990-2000 with an expansion of 12 points, with a strong expansion in Asia, and particularly with China. It increased very slightly in the first decade of the 21st century; (c) Commodities trade fluctuated around 21.6 and 28.8% of total trade, except for the price boom of oil and other commodities in the 1974-1985 period; (d) Value-added trade has been in a downward trend since the 1970s, and in particular in the 1990-2000 decade that also registered the largest increase in intra-firm trade, with a particular movement of offshoring and outsourcing to East Asia and China, in particular. Combined with the increase in overall trade ratio over GDP it shows that production is more roundabout or that trade in intermediate goods has increased significantly (more importance of value chains); (e) Inter-sector trade is computed as a residual and it has shown a downward trend, in particular in the 1980s and in the 2000-2010. However, this component is roughly estimated because it reflects errors in other categories. Recent analysis of intra-firm trade by Alfaro (2009) using a large world firm database shows that about 54% of this trade is horizontal and 46% is vertical.
Table 4
8
It is important to remark that they are not mutually exclusive.
Structure of International Trade by Type 1960 10.5 (27) 9.6 25.7 -
1970 23.5 22.1 23.6 52.9 87.0
1980 24.4 28.9 40.6 35.0 83.0
1990 33.6 27.2 26.4 40.0 84.0
2000 37.0 39.1 21.6 41.4 77.0
2010 38.8 (54) 41.2 28.8 32.4 78.0 60.0 55.0
Intra-industry trade Intra-firm trade Commodities trade Inter-sector trade Value-added trade Intra-regional trade (EU) Intra-regional trade (East Asia) Source: Author´s estimations based on World Bank, UNCTAD and OECD estimates.
Most of the trade among industrialized countries is intra-industry: the Grubel-Lloyd index for OECD-OECD trade in 1990 is 68.4, while the Grubel-Lloyd index for OECD-RW trade in 1990 is 38.1. The structure of international trade by region also shows profound structural changes among developing countries (Figure 6). All developing regions show a substantial drop in market shares in the 1950-70 period, with especially large drops in Latin America (6 pp), East Asia excluding Japan and Asian Tigers (6 pp) and Africa (2 pp). This was the era when inward import-substitution industrial policies prevailed.
Figure 6
World market shares: rise of developing world 70.0
60.0
50.0
East Asia excl. China and Japan 40.0 Percentage
Transition economies Africa Korea Oil and gas exporters
30.0
China Latin America 20.0
10.0
1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
0.0
Source: UNCTAD data base.
The 1974-1985 period was characterized by the two oil shocks with serious consequences on developing countries external financial situation that led to the debt crisis of the early 1980s. Most of the East Asian economies had already switched to a more outward industrial policy, which was reflected in a gain of 4 pp in their market share. The three decades after 1985 marked the ascension of developing countries into a major player of international trade, by increasing their market share from 38.7 to 62.4%, although with different success: East Asia, including China, was the extraordinary winner (market share increased to 35%, with an increase of 19 pp). In the 1985-2000 period we witness the collapse of transition economies in the early 1990s and its long revival: by 2000 they were still 2 pp below the market share of 1985. Africa continued to lose share (2 pp) and East Asia deepened its share by 4 pp again. From 2000 to 2012 all developing regions gained share, the largest being the oil exporting countries due to the commodities price boom (5.7 pp), East Asia (5.2 pp) and transition economies (2.2 pp). In fact, the defining structural change of the last half a century has been the rise of developing countries, and in particular China, in world manufacturing. In the 1985-2010 period the most advanced developed countries have lost about 5.5 trillion USD, annually, in manufacturing value added (MVA), when comparing their shares of that sector in GDP at the beginning and end of the period. Notwithstanding factors like increase in productivity and consumption patterns, a significant part of that loss was due to delocalization of production to developing countries.
In 1990 developed countries accounted for 79.3% of world manufacturing value added.9 From 1990 to 2000 their share fell 0.4% annually. In the first half of the first decade of the 21th century was decreasing at 1.2% per year and in the following half accelerated to 2.1%. By 2010 their share had dropped by 12 pp to 64.4%. China increased its share from 6.7% in 2000 to 15.4% in 2010, becoming the second largest manufacturer after the United States. East Asia and the Pacific remains the largest manufacturing region by far, with manufacturing value added of 1.5 trillion USD in 2010, more than half of developing countries production. The shares of employment and value added by manufacturing for the most developed economies have been halved in the last 3 to 4 decades.
Figure 6
Manufacturing Value Added 35 30 25 Perc GDP
Germany 20
Italy United Kingdom
15
United States
10
Japan
5
9
UNIDO (2011).
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
0
Employment in Industry (BLS) 60.0
Percent Total
50.0 United States
40.0
France 30.0
Germany Italy
20.0
United Kingdom Japan
10.0
2009
2006
2003
2000
1997
1994
1991
1988
1985
1982
1979
1976
1973
1970
0.0
Source: USA, Bureau Labor Statistics, 2012 Our statistical analysis shows three important facts that we will further exploit: (i) the rise of multinationals and inter-industry trade and horizontal outsourcing/offshoring across Europe and North America after the 1960s, (ii) the rise of intra-firm trade and vertical outsourcing/offshoring in the 1990s decade, and (iii) the success of the East Asian Tigers, first with Japan then with Korea, Taiwan, Singapore and Hong-Kong, and after the 1980s China, with strong ramifications in all the rest of East Asia, and spreading lately to India.10 The last wave of globalization led to a massive transfer of manufacturing from developed economies to China, in particular. 4. Review of literature on causes of globalization and relationship between
globalization and economic convergence Trade theories that could explain globalization are quite diverse. First, what causes trade among nations, and even more important, what speeds up trade among nations? Second, what increases cross-border investment? There are the several schools of trade theory that have different explanations for those phenomena. Third, and more recently, what explains Outsourcing and Offshoring? The new theories integrating industrial organization and trade theories have a lot to explain. Also another avenue is the geography and trade theories that could explain location of economic activity across the globe. Fourth, explanations provided by the feedback between trade and growth theories with a dynamic factor endowment genesis or a technological progress affiliation. Let us review selectively some of these theories.
10
Almost all these countries followed an outward industrial policy, with some important nuances: HongKong and Taiwan more private oriented, Japan and Korea where conglomerates played a major role, and China with still heavy state intervention, despite the introduction of market economy in the economic zones.
In the Ricardian theory of comparative advantage if we put side-by-side two countries each country produces the string of goods where it has higher productivity up to a cross-over point determine by relative costs and trades the rest. Thus larger trade would result from higher disparities in productivity across sectors and larger the demand gap for those goods. In a smooth Heckscher-Ohlin world trade would be higher the higher the differential in factor endowments and the higher the demand gap. It is obvious that the demand gap will increase with income of both countries and logically its size. Another important consideration is the differential between tradable and non-tradable goods. A reduction in trade costs, defined in a comprehensive manner and including tariffs and quantitative restrictions will increase international trade by even making some goods move from the non-tradable to the tradable categories. A relatively obvious proposition is that if a new country is added to the set of existing countries, what we designate as being incorporated into the “world economic system”,11 it will expand international trade by expanding world set of potential trade. The other consideration is that if a country is split into 2 or more countries it will obviously increase international trade, since part of the domestic trade will then be reclassified as cross-border trade. Assume the same preferences across countries and consumers spend the same amount across all goods. If a large country produces two thirds of the goods and a small country one third, then the large country imports one third of the goods and the small country two thirds. If the smaller country was only one tenth of the large one, only one tenth of the large country goods would be exported. Thus, trade tends to increase as countries became more equal in size and will decrease if the countries are lower in number. Product cycle models suggest that trade would increase as products become more mature and firms will transfer the stages of production which are more labor intensive to countries with lower labor costs (vertical specialization), and also implicitly that international trade will increase when firms become more “internationalized”, i.e., are able to decompose its production process into different stages and try to reduce its costs by “adopting a new frame of mind” by looking at a world geography to locate each stage of production and not just its region or national territory. However, a majority of the trade among developed countries is in the same sector: intraindustry trade. From the new trade theories of Krugman and Helpman international trade will increase when economies of scale increase and when goods become more differentiated (horizontal specialization). These are important observations since those factors are clearly influenced by technological factors and its dynamics. The newest trade theories (Melitz, Eaton and Kortum, Bernard et al., Costinot) with firm heterogeneity provide the foundation for the gravity equation and incorporate the idea that only the most productive firms (they are larger and more skill intensive) in a given country export, they are a small fraction of the total and mostly export for a small number of countries. These models are generally considered an extension of the Ricardian models with a continuum of goods and multiple countries. However, the same factors contributing to international trade 11
See the companion paper Mateus (2014).
considered above by the new trade theory are also relevant here. An increase in the productivity of the firms of a particular country could increase its exports as well as the demand for that country exports. These may entail an increase in international trade. In fact, it has been widely recognized that productivity increase in tradable sector has empirically surpasses the non-tradable sector, which naturally pushes the ratio of trade over GDP up.12 Part of the productivity increase is reflected in prices which show a very substantial drop of around 40% in the last 30 years for the developed economies.
There are new factors that may contribute to an expansion in trade for a given country and international trade that have to do with firm dynamics. An environment conducive to a higher rate of firm creation and expansion as well as more flexibility and mobility for reallocation of factors will lead to the expansion of the export sector and an increase in its productivity. All previous models consider a single product-firm by industry. However, empirical analysis (Pavcnik (2002) on Latin America and others) shows that a reduction in trade costs has very significant intra-industry effects: less productive firms exit and there is a reallocation of assets even within the same firm. These results show that we need a model of trade with heterogeneous firms by industry/sector. Bernard et al. (2007) build a model of comparative advantage by embedding heterogeneous firms in a Krugman-Helpman model with increasing returns to scale and differentiated goods. In addition, the model is in line with Hecksher-Ohlin by considering at least two sectors and two countries with different factor endowments/factor prices. They show that a reduction in trade costs, in contrast to the neoclassical model, entails simultaneous within- and across-industry reallocations of economic activity that generate job turnover in all sectors. The end result is net job creation in comparative advantage industries
12
Dean and Sebastia-Barriel (2004)
and net job destruction in comparative disadvantage industries in the H-O sense. There are three surprising results. First, the creative destruction of firms is highest in the comparative advantage industry. This occurs because the expected value of entering the industry rises more in comparative advantage industries than in others, which induces relatively more entry and so lead to a larger increase in the zero-profit productivity cut-off and average industry productivity in comparative advantage industries. This leads to a larger exit in these industries and also to an increase in the size. These are all magnification effects. Second it raises the possibility that the productivity gains associated with self-selecting heterogeneous firms be strong enough to raise the real wage of both the scarce and abundant factor, contradicting the Stolper-Samuelson theorem. Third, although a reduction in trade costs boosts the welfare gains from trade, the value of intra-industry and total trade may not increase as much as in the homogeneous goods case because the increase in average productivity raise firm output at the expense of the number of varieties. This also explains the “missing trade” phenomena arising from non-negligible trade costs, the selection of firms that occurs into export markets, and the non-neutral technology differences driven by the differential selection of high-productivity firms across countries and industries with comparative advantages. All these factors generate the violation of the factor equality theorem. Gravity equation models of international trade, which have experienced a renaissance after the new Ricardian models gave it a theoretical foundation, predicts an increase in international trade with an increase in income of countries and a decrease in “distance” which is defined by trade costs, as above. Since trade integration leads to a decrease in trade costs it should lead to an increase in international trade. In general, even just regional integration leads to an increase in international trade. The EU is a case in point, where the extra-community trade has grown considerably, despite the strong increase in intra-community trade. This shows that in this case trade diversion was largely supplanted by other factors in the long-run. Endogenous growth models with innovation generated by R&D are of two types: one where the economy climbs a quality ladder and the other where innovation increases the number of varieties available. Innovation is generated at national level and then spreads throughout the world. In a new trade theory model generating new varieties or new qualities not only generates growth of GDP and welfare, but also leads to new trade opportunities which should mean a higher intensity of world trade. In a Schumpeterian environment (e.g. Aghion and Howitt) the new products replace the old ones through the process of “destructive creation”. However, the new products are of better quality or higher productivity. If they replace old products in another country there is one more reason for trade to grow. In these models growth and trade could be accelerated by government interventions like subsidizing R&D. However, Jones (1995) has shown that if we assume that R&D has also decreasing returns the endogeneity and the political impact ends.
Learning by doing models usually also have associated country size effects. They show (Young (1991)) in a world with domestic but not international spillovers in technology, a large country more technological advanced can capture comparative advantage from a small less advanced country, and trade can be welfare reducing if this country gets stuck in sectors that have lower productivity. As Graham (1923) and Ethier (1982) show, there have to be within country externalities for this case that calls for protection, to occur. In this case, there is import substitution of domestic production in the less advanced country, so international trade will increase. But the conditions for that to occur may not be realistic. First, there are important international spillovers in technology through transfers and imitation. Second, it is surprising that in a dynamic context the loosing country would not acquire skills in other sectors as in a Ricardian world would happen. Young (1991) also shows that if two countries of a similar size are in a technological race and if one starts to industrialize it would capture production from the other and in this case international trade may also increase. This is a similar effect of economies of scale above. Technology catch-up models have been hard to come by, and especially difficult to test empirically. Comin and Habijn (2204) have advanced substantially the subject by building a model of international diffusion of technologies and testing it for about 20 technologies. They show that technological lags have been decreasing in the last century and half with a particular acceleration after the II WW. New technologies are invented in the advanced countries and its spread to the other countries depends on human capital endowments, type of government, degree of openness to trade, and adoption of prior technologies. An acceleration of technological diffusion would increase the growth rate of world GDP. Acceleration in technological diffusion would accelerate convergence and most likely would increase the intensity of trade. Empirical analysis has shown that dispersion of production across the globe and consequently, trade, is not only determined by comparative advantage and productivity, but also by agglomeration economics. What determines location of production across the globe is the object of another field of research known as economic geography or spatial economics. Agglomeration economies result in increasing returns that are external to the enterprise or external to the industry and may be generated by network effects of market access or suppliers’ access (forward or backward linkages), access to a pool of human capital or knowledge. Geography matters for factor prices and for the structure of production in each country. Geography impacts the economy through the trade costs, which vary systematically with distance and other geographical forces, and also vary across industries. Trade costs are composed of a package of transport costs, time costs, and information costs. The empirical success of the gravity equation continues to show that trade decreases with distance. Trade costs prevent goods price equalisation from occurring, and hence also prevent factor price equalisation. But geography also influences the economy through spatial differences in institutions (social infrastructure) and in technology. It is obvious that (international) trade would be minimized if the spatial distribution of economic activity was in continuum and if the home-bias was large. As we diverge from that model trade would tend to grow. The model of Krugman and Venables (1995) has distinct conclusions from the factor endowment model by generating an inverted U-curve between agglomeration and trade costs. Assume a monopolistic competitive model with differentiated goods with two countries/regions and 2-sectors (agriculture and manufacturing) with similar sizes, different factor endowments (labour and capital) with trade costs and immobile labor
across countries. Manufacturing is characterized by increasing returns to scale and uses intermediate goods. The iteration between transport costs and trade in intermediate goods creates country-specific external economies, which may lead to agglomeration of industrial activity. The mechanism creating externalities is input-output linkages between firms. The same effect can be created using labour mobility. Starting with high trade costs there is no specialization and industrial activity is spread among the two regions. Suppose that one region has a larger capital stock and manufacturing is capital intensive, so one region has a larger manufacturing sector. This region has a larger market for intermediate goods so it offers a lower cost to locate manufacturing (backward linkage), but at the same time, with lower input costs the final goods would also have a lower price (forward linkage). This agglomeration effect will create a circular effect that leads to a world economy with an industrialized core and a deindustrialized periphery. If the manufacturing sector is large enough it will create a divergence between real wages in the two regions. Labour costs will go up in the core and fall in the periphery. At still lower transportation costs the wage advantage of the periphery will take over versus trade costs and the periphery will industrialize as manufacturing will either move from the core or outsource activities. The process will lead to a convergence of wages. This is the inverted U-curve effect. In the traditional H-O or Krugman-Helpman model the reduction in trade costs will continue to lead to increased specialization. The greater are firms' price cost markups, and the greater is the share of intermediates in production, the more powerful are the forces for agglomeration. Puga and Venables (1998) extend the model to several countries. As wages in the core increase, manufacturing migrates to countries/regions with lower labour costs. But, they observe that the logic of agglomeration determines that manufacturing will migrate to only a small subset of the countries/regions of the periphery (leading to a convergence process) and then to other countries/regions of lower wages and so on in different waves of globalization. It should be emphasized that linkages do not play any role in a perfect competition model, but they are crucial in a non-competitive world. However, since agglomeration play a major role in real world economies, new geography models are extremely relevant for explaining the lumpiness in the world distribution of economic activity and population and the process of globalization. There has been very few work dedicated to answer this question: assuming there is a core and there are multiple countries/regions in the periphery, how economic activity and FDI will discriminate among them in the third phase of the Krugman-Venables model corresponding to the spread of manufacturing cum wage-convergence, which we identify with globalization? Although is not explicitly dealt with, the model can be used to answer this question. First, the higher is the level of labour endowment, so larger countries have an advantage over smaller countries. Second, the higher is the difference in the wage rates vis-a-vis-à-vis the other region. However, this derives from the limited specification of the model. If other factors of production would be considered, the relevant ratio would be in total real production costs (which would include quality of the labour force, cost of capital, and trade costs in general, including institutional costs – costs of doing business). Third, the intensity of the forward and backward linkages which are the driving forces of agglomeration. Thus, if we had two countries with similar size and relative production costs vis-à-vis the core, the country were there were already more easily available raw-materials and other intermediate goods, as well as a larger country-specific consumer market would have a clear advantage. The forth will be the time it would take to equalize wages. Ceteris paribus, the country with a larger pool of surplus and more easily “employable or trainable” labour for manufacturing would have an advantage relative to other periphery countries. This aspect ties up with Arthur Lewis model of laboursurplus economies that has been quite relevant for China, were the labour elasticity of supply
has been an important parameter in explaining the rise of that country as the “factory of the world”. They also look at what policies will attract manufacturing activity by contrasting unilateral trade liberalization with import substitution. They show that the first policy which lowers trade costs is superior to the second, especially for small countries, as countries specialize in labor intensive industries. Forsid et al. (2002) simulates the core-periphery model for the European Union using the effects of integration in the distribution of economy activity by region. He uses a full-scale CGE-model — the EURORA model with 14-industries and 10-regions (Forslid et al., 1999b) — which is calibrated on actual 1992 data. This model captures comparative advantage due to differences in endowments and technology, imperfect competition and scale economies, as well as backward and forward linkages through a complete input–output structure. Their results show that the locational effects of economic integration are highly region- and sector-specific with some sectors being driven primarily by comparative advantage and others by agglomeration forces associated with scale economies and input–output linkages (manufacturing sectors with strong backward and forward linkages given by inverse Leontief matrices). However, the results for the overall increasing returns to scale manufacturing sector reveal an (inverted) U-shaped relationship between trade liberalisation and concentration of the manufacturing sector. Dual to this they report movements in factor prices and welfare effects. They show that welfare is positively associated with the location of the increasing-returns-to-scale (IRS) manufacturing. Finally, factor price movements tend to co-vary and are positively related to the pattern of industrial location. Relative factor price changes, on the other hand, show clear traces of Stolper–Samuelson effects.
Why China became the factory of the world? Why not Mexico or South America? Why not Thailand, Malaysia and Indonesia? It is a large country of low wages and with large pools of manpower with a tradition of manual dexterity and work ethics. According to the model of Krugman and Venables China had the largest pool of labour and potential consumer market. Although transportation costs were higher than South America, it is not clear that overall trade costs were higher in view of the high costs of doing business in South America. Although Mexico is certainly a country that benefited from outsourcing and expansion of multinationals right from the beginning of the process in the 1980s, with substantial relocation of activity from Mexico city to the US border, it does not have the potential labour force of China (is just about 1 tenth of the size). The other Southern Asian countries were part of the same region of China, with different scales of industrialization and entering in the convergence process at different levels. China just offered the last continuous geographic unity. There is a common factor in all trade theories: a fall in trade costs always leads to an increase in trade, ceteris paribus. The fall in trade costs may be a decrease in transportation, insurance and freight handling, communication costs as well as generally the costs of doing business across different regions and states, which includes obviously tariffs and other barriers to international trade as well as transaction costs, e.g., in terms of contract enforcement. Capital market integration will reduce transaction costs among nations and thus increase trade. The same would happen with a more stable exchange rate system and with an improved international payment system.
The other aspect that is sometimes overlooked is the complementarity between trade, investment, technology and financial flows as well as transfers of human capital and institutional transfer. There are four key mechanisms at work in models of trade and growth: (i) trade increases potential market size (via exports). Increasing the market size leads to more profits and, possibly through ‘scale effects’ generates increasing growth of GDP; (ii) trade increases domestic competition (via imports). Increasing competition entails less profits which decreases growth, but the incentive effect for further innovation and productivity increase leads to increased growth; (iii) trade and factor price equalisation (if it holds) equates the marginal product of capital across countries (diminishing returns reflect world averages, growth rates convergence) and allows the country to escape domestic diminishing returns and may even lead to miracle growth like in the Asian Tigers as Ventura (1997) has shown. More relevant to our analysis are dynamic models, in particular models that generate dynamic comparative advantage. This may derive from a simple accumulation model where the increase in physical and/or human capital intensity ratio leads the country to move into higher value chain comparative advantages. Models of endogenous growth also generate comparative advantage, like in Grossman and Helpman (1990) where R&D play the creative role. If knowledge spillovers occur with a time lag and diffusion is faster within the borders of the innovating country than across the world, comparative advantage becomes endogenous and could be “created” by moving up the technology scale. Countries have multiple sectors (e.g. low tech and high tech), international trade creates specialisation (e.g. by the static theory of comparative advantage), which means some countries increase size of high (low) tech sectors. This affects growth if inherent differences in sectoral growth rates, or scale effects, vary between sectors. Thus, countries’ growth rates may diverge (e.g. richer countries, and countries with a fast technology, transfer may grow faster), hence trade (comparative advantage) may influence the convergence rate. Let us turn now to some microeconomics of globalization and the role of multinationals. One of the most salient features of the second wave of globalization is the rise and extent of multinational enterprises. Theoretical studies of the multinational firm in general-equilibrium models of international trade literature has developed models rationalizing the emergence of multinational firms in the presence of international factor-price differentials (e.g., Helpman [1984]), whenever trans port costs are high, and whenever firm-specific economies of scale are high relative to plant-specific economies of scale (e.g., Markusen [1984] and Brainard [1997]). But in the current second wave of globalization, as we will see below, transport and communication costs have decreased so much and its quality has improved to such an extent that the feasibility and cost of running business networks led to the international fragmentation of the production process, known as outsourcing and offshoring. Outsourcing refers to an organization contracting work out to a third party, while offshoring refers to getting work done in a different country, usually to leverage cost advantages. Outsourcing may be done within the same country or in a foreign country. It is possible to outsource work but not offshore it; for example, hiring an outside law firm to review contracts instead of maintaining an in-house staff of lawyers. It is also possible to offshore work but not outsource
it; for example, a Dell customer service center in India to serve American clients. Offshore outsourcing is the practice of hiring a vendor to do the work offshore, usually to lower costs and take advantage of the vendor's expertise, economies of scale, and large and scalable labor pool. The first type of theoretical models to address the problem of fragmentation of production still used a neoclassical model of trade, as e.g. Feenstra and Hanson (1996) and Grossman and Rossi-Hansberg (2008), and showed that fragmentation generates nontrivial effects of reduction in trade costs on patterns of specialization and factor prices. But in neoclassical models there is no room for incomplete contracts and intermediate inputs are usually differentiated goods. In fact, there are additional costs in offshoring: (i) the country may be low-wage but suppliers are usually unreliable and courts rarely enforce contracts, (ii) it may be possible to deploy advanced technologies but the contractual environment may not provide enough security to firms. Antras (2003) notes that about one-third of world trade is intra-firm trade. Moreover, the share of intra-firm imports in total U. S. imports is significantly higher, the higher the capital intensity of the exporting industry. The author explains these facts by combining a GrossmanHart-Moore view of the firm with a Helpman-Krugman view of international trade. In particular, he incorporates an incomplete-contracting, property-rights model of the boundaries of the firm into a standard trade model with imperfect competition and product differentiation. Capital intensive goods are transacted within firm boundaries, while labour intensive goods are traded at arm´s length. The interaction of transaction-cost minimization and comparative advantage is shown to naturally give rise to the relationship between intrafirm trade and relative factor endowments. This is because vertical integration (relationshipspecific investments in capital) increases with the capital intensiveness of intermediate goods. Contrary, investments related to the labor input are harder to share than investments in physical capital. This may be the result of suppliers having superior local knowledge in hiring workers, or it may be explained by the fact that managing workers requires a physical presence in the production plant. Why some firms spread production by several countries and others not? What are the determinants of the location of the production units in a given country? Why some firms own foreign facilities while others simply contract out with local producers or distributers (arm´s length relationship)? In 1990-2010 the center of analysis of international trade has shifted from countries and industries to firms: a handful of large firms that dominate trade and investment in a global scale. In 2000, 85% of the total US exports was made by the top 1% of exporting enterprises, which represents only 25% of their total production.13 A multinational enterprise is a firm that controls (at least 10% of capital share) and manages production facilities located in at least two countries. Building on the Krugman and Melitz contributions, Antras (2013) sets-up a benchmark model for multinationals by using a differentiated goods model under monopolistic competition, with 13
Brainard et al. (2009).
two countries with different costs due to price or technology differences and production with increasing returns to scale. This is a horizontal FDI model where the firm confronts the decision of exporting the good from the home to the foreign country or alternatively to produce it in the foreign country. Rooted on Dunning´s OLI paradigm where a firm can replicate its production facilities abroad by facing a trade-off of reducing the benefits from increasing returns against the increased benefit of reducing trade costs (transportation, tariffs or other trade costs): the proximity-concentration hypothesis. Increasing returns may result from fixed costs in R&D, marketing and others in order to start production or overhead costs for operating the facilities. One of the results from the model is that the higher the firm-specific economies of scale relative to plant-specific economies of scale the higher the incentive to invest in FDI in the foreign country in order to serve consumers in that market. Another result is that the choice between exporting or setting-up an affiliate depends on the balance between low fixed costs but higher marginal costs (exporting) and high fixed costs but low marginal costs (affiliate). Brainard (1997) finds evidence in favor of the proximityconcentration model using US multinationals data: FDI increases with tariffs and transportation costs and with higher corporate economies of scale (overheads of the whole firm) and lower plant economies of scale. The results also show that US multinationals are more likely to export to smaller countries and to invest in affiliates in larger countries. These results were confirmed again by Antras (2013). In the case the two countries are different, the equilibria with exporting is more likely the larger is the home country relative to the other, because it allows the firm to reap more economies of scale. Or, in another way, the larger the endowment of the home country in the factor used intensively in the production of the differentiated good sector. Thus, FDI is more likely to arise for countries with similar sizes or endowments. This is consistent with the empirical observation that smaller countries have in general a lower level of FDI, and that the larger volume of FDI occurs among developed countries. Adding heterogeneity to firms in the tradition of Melitz shows that only the most productive firms engage in exports and only a subset of the this and more productive engage in FDI. In particular, a more productive firm will set-up affiliates serving a larger number of countries. And a greenfield operation will be preferred to a merger or acquisition of a local firm when the multinational owns superior abilities that domestic firms do not have even when decreasing competition is not a superior strategy. Vertical FDI can be modelled by introducing two stages of production: headquarter services and manufacturing, where the first requires a higher intensity of capital associated with R&D, marketing and other costs. These services area assumed firm specific and non-rival and thus can be spread by a number of plants. The manufacturing sector uses capital and labor to turn headquarter services into final goods using a technology with increasing returns to scale. It is immediately evident that if countries have similar endowments there is no incentive for FDI. In this model firms would offshore unskilled labor tasks while pursuing at home skilled labor tasks. However, as in an unskilled-labor intensive technological progress wages in the foreign country will rise and may lead later to an increase in unskilled labor in the home country. Empirical analysis shows that exports back to the US of affiliates is concentrated in only a few countries, which derives from the fact that vertical FDI is motivated by exploration of lower production manufacturing costs. Antras (2013) finds that US firms export more to a human
capital scarce country in skill intensive industries and would prefer affiliates in industries with low skill intensive industries. Using a large world data set for 2005, Alfaro (2009) has shown that about half of the intra-firm trade is horizontal and half is vertical. Most of the intra-firm trade among developed countries was traditionally considered in the literature to be horizontal. How can we reconcile this new finding with the fact that this vertical trade takes place among highly skilled countries?14 The reasons go back to the Krugman model that explain trade in terms of heterogeneous goods with different qualities located in different countries because economies of scale and hysteresis. In the end some special pools of highly skilled labor and capital may have evolved in particular locations. However, none of the models above is able to discriminate between a strategy of a firm setting-up an affiliate or establishing a contract with a local supplier at arm´s length. In order to clarify this option we have to use a theory establishing the boundaries of the firm. There are two basic theories using the Coase-Grossman-Hart framework: (a) transaction-cost approach that says that firms will internalize when transaction costs through the market mechanism is higher – this may derive, in particular, to rent dissipation (e.g. valuable patents or technological knowledge that may be easily appropriated by the licensee) or hold-up inefficiencies. One implication in horizontal FDI is that the larger are wage differentials the lower FDI will take place because higher internalization costs (incentive compatible effects are at play here); (b) property-rights approach says that internalization is important because ownership pf assets concedes the power (residual rights control) in the presence of incomplete contracts. The central idea is with incomplete contracts ownership rights of assets should be allocated to parties contributing with noncontractible investments that generate the highest value to the firm. Empirical evidence tends to favor the property-rights approach (Antras (2013)). This approach delivers the result (using US data) that the share of intra-firm trade increases with barriers to trade and with firm productivity dispersion and decrease with the wage gap.
5. Expansion of the World Production Possibility Set and World Market There were two sub-waves of globalization in the post II WW. First, there was the expansion of trade, investment and the rise of multinationals mostly across the Atlantic and the rise of the Asian Tigers up to the end of the 1980s. The second sub-wave started with the integration of the old Communist countries and their integration in the world economic system, with the massive reallocation of manufacturing from developed to developing countries, with a particular role of China. Although most of time overlooked, this second wave which is generally associated with the present wave of globalization represented a large expansion of the world Production Possibility Set. The integration of the Communist countries, including Russia, China, Eastern European and East Asian countries expanded roughly the Production Possibility Set and the 14
Alfaro (2009) gives the example of GM that imports parts and engines from some European and Japanese affiliates to assemble in US factories. E.g. some affiliates/foreign factories may have developed special technologies like diesel engines, which the mother firm has not yet dominate or do not intend to incorporate due to the benefits of specialization.
world consumer market by about a third. Figure 7 shows the expansion of those sets in terms of world population and using the impact on GDP. The impact in terms of population is calculated based on the incorporation of the special economic zones of China into the world economic system and later the other Communist countries that have opened up to that system. Similarly, for Eastern Europe it computes the integration in European trade and especially the European Union. Finally, it considers the integration of the Soviet economies into the world economic system. Our calculations show an addition of about 20% in terms of population and a contribution of more than 10% of GDP.15 Figure 7 Impact of Entry FNME 0.25
Perc. World Population
0.2
0.15 China and ComA Former URSS+EE
0.1
0.05
0
Market Expansion FNME 0.12
0.1
Perc. World GDP
0.08
0.06
China ComA Former URSS EE
0.04
0.02
0
Source: Author´s estimates based on World Bank data 15
The impact on GDP is computed by the difference between actual numbers and the extrapolation of trends without any change of the status in the country.
Figure 8 Former Non-Market Economies: GDP 0.95
Perc. Of Lower and Middle Income Countries GDP
0.9
0.85
0.8
0.75
0.7
0.65
Former Non-market Economies: GDP 0.18 0.16 0.14
Perc. World GDP
0.12 0.1 0.08 0.06
0.04 0.02
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6. Technological progress and technology transfer
The shape of the world production possibility frontier changed significantly after the II World War. The following table summarizes the most important innovations that were behind the second wave of globalization and had a major economic impact. As we see in the table most of the times there was a string of innovations sometimes over several
decades, so it is difficult to pinpoint the time of the innovation. The main countries of diffusion re simply countries where there were some accumulation points in the process of diffusion. Type of innovation
Date and country innovation
Main countries of diffusion
Television becomes a major media system in 1950s.
Invented in the 1930s and 1940s, it becomes a media system in the 1950s (UK, USA) 1971-1990s USA, Japan
France, Czechoslovakia, Italy, Soviet Union, Germany
1979-1996 USA, Finland, UK
Japan, Taiwan
1948- 1981 USA
UK, Germany, France
1981-1985 USA
UK, France, Nordic countries
1952-1958 UK, USA
URSS, France, Belgium,
Video recorders and music players: VCR or videocassette invented in 1971. Walkman invented in 1979. Compact disk (CD-ROM) invented in 1984. Ipod invented in 2001. Cell phone invented in 1979. Digital cellular phones invented in 1988. In the 1990s, the 'second generation' mobile phone systems emerged. Two systems competed for supremacy in the global market: the European developed GSM standard and the U.S. developed CDMA standard. In 1991 the first GSM network (Radiolinja) launched in Finland. In 1993, IBM Simon was introduced: the world's first smartphone. 1996: Nokia introduces the first commercial "smartphone". SMS introduced in 1992-93 in UK. In 1998 the first downloadable content sold to mobile phones was the ring tone, launched by Finland's Radiolinja. Computers-hardware: John Presper Eckert & John W. Mauchly build the ENIAC 1 (1948); Computer transistor radio invented by Bardeen (1948). John Presper Eckert & John W. Mauchly build the first commercial computer (UNIVAC) in 1951. Fortran is invented by Backus (IBM) in 1954. The integrated circuit invented by Jack Kilby and Robert Noyce in 1958. Faggin, Hoff & Mazor build the Intel 4004 Computer Microprocessor in 1971. 1976/77 the first personal computers (Apple I and II). 1981 IBM PC home computer. Computers-software: Thomas Kurtz and John Kemeny created BASIC in 1964. In 1981 Microsoft MS-DOS and 1985 Windows. Spreadsheet (Kapor developed Lotus 12-3 in 1982), word processor (Wordperfect) and presentations from 1981-1985. Databases. Object oriented programming. CAD-CAM. Netscape’s Navigator written by Marc Andreessen and Eric Bina in 1993. Commercial airplanes and jet age: The first commercial jet airliner to fly was the British de Havilland Comet,
Netherlands
introduced by BOAC in 1952. 1958: Boeing introduces the long-distance jet. 1969: The Concorde, a supersonic passenger airplane by Airbus and Boeing 747 by Boeing. Automobiles: Throughout the 1950s, engine power and vehicle speeds rose, designs became more integrated and artful, and automobiles were marketed internationally. The market changed in the 1960s, as the U.S. "Big Three" automakers began facing competition from imported cars, the European makers adopted advanced technologies, and Japan emerged as a car-producing nation. Electronic Fuel injection for cars invented in 1966, Railways: 1964: Japan inaugurates the first "bullet train", the Shinkansen. In Europe, the TGV was developed during the 1970s by GEC-Alsthom (now Alstom) and SNCF. Originally designed to be powered by gas turbines, the prototypes evolved into electric trains with the petrol crisis of 1973. Inaugural service was between Paris and Lyon in 1981. Logistics: In 1955, former trucking company owner Malcom McLean worked with engineer Keith Tantlinger to develop the modern intermodal container. The world's first purpose-built container ship was the Clifford J. Rodgers, built in Montreal in 1955 and owned by the White Pass and Yukon Route. Four ISO rules standardized containers (1968-1970). Space exploration: 1957: the Soviet Union launches the first artificial satellite, the Sputnik, mostly designed by Sergei Korolev. 1961: Yuri Gagarin becomes the first astronaut. 1962: Telstar, the first telecommunication satellite. 1969: Neil Armstrong is the first human to walk on the Moon. 1990: The Hubble space telescope is launched. Chemicals: In the 1960s and 1970s, control of the electronic structure of semiconductor materials was made precise by the creation of large ingots of extremely pure single crystals of silicon and germanium. Accurate control of their chemical composition by doping with other elements made the production of the solid state transistor in 1951 and made possible the production of tiny integrated circuits for use in electronic devices, especially computers. A high-temperature super-conductor invented by J. Georg Bednorz and Karl A. Muller. in 1984. In 1991, Sumio Iijima used electron microscopy to discover a type of cylindrical fullerene known as a carbon nanotube, though earlier work had been done in the field as early as 1951. This material is an important component in the field of nanotechnology. Materials: After 1950 continuous casting contributed to productivity of converting steel to structural shapes.
1950-60 USA, Germany, UK, France, Japan
Canada, Germany, and many countries Italy, Sweden, URSS, Czechoslovakia
1964-1981 Japan, France
Germany, Spain
1955-1970 USA, Canada
Western Europe and other developed countries
1957-1969 Soviet Union and USA
1951-1970 USA, Japan, UK, Germany
Korea, Taiwan
1950-1970 USA
UK, Germany, France, Sweden,
Optic fiber invented in 1955. The liquid-crystal display (LCD) invented by James Fergason in 1971. Optical fiber began to replace copper wire in the telephone network during the 1980s. Medical research: In 1960 Peter Medawar discovers the acquired immune tolerance. In 1967 Barnard makes first heart transplant, but only in the 1980s became prevalent. Medicines: Oral contraceptives invented - the pill, in 1954. Tetracycline invented in 1955. 1955: Jonas Salk develops the first polio vaccine. 1957: Albert Sabin develops the oral polio vaccine. Valium invented in 1961. Prozac invented at the Eli Lilly Company by inventor Ray Fuller in 1988. Medical instruments and machinery: The artificial heart invented in 1969. 1972: Raymond Damadian builds the world's first magnetic resonance imaging (MRI) machine. Godfrey Hounsfield and Allan Cormack invent computed tomography scanning or CAT-scanning. Biotechnology: 1973: Stanley Cohen and Herbert Boyer create the first recombinant DNA organism (the birth of "biotechnology"). Gene splicing invented in 1973. 1977: Frederick Sanger invents a method for rapid DNA sequencing and publishes the first full DNA genome of a living being. Human growth hormone genetically engineered in 1982. The first patent for a genetically engineered animal is issued to Harvard University researchers Philip Leder and Timothy Stewart in 1988. 1990: William French Anderson performs the first procedure of gene therapy Consumer electronics and payment services: 1968: Barclays Bank installs networked "automated teller machines" or ATMs. 1998: The first handheld devices to read ebooks.
and other developed countries 1960-1980 USA
UK, Germany, France, all EU
1954-1961 USA, UK
Germany, all EU
1969-1972 USA, UK
Germany, all EU
1973-1988 USA, UK
All EU
1968-1998 USA, UK
All developed countries
Hardly any sector of economic activity has not been touched by technological changes. However we identify communication and information and transportation and logistics as the general purpose technologies with the most profound impact on productivity and the structure of production. The invention of computers not only revolutionized the scientific process itself and the instruments of research and innovation, but it changed radically the workplace and home activities. Combined with advancements in telecommunications and the invention of internet it reduced telecommunication and information costs. Telecommunications also became mobile and mass-media become accessible to the majority of populations. But there was also a transformational change: the way firms can operate and coordinate across the globe. Improvements in air, land and sea transport with intermodal connections and the use of containers contributed to the reduction in transportation costs internationally and domestically.
Technological improvements in chemicals and materials (silicone, fiber optics or carbon nanotube), industrial machinery and instruments (laser, robotics and computerized assisted design) and improved management systems (time-to-market, electronic commerce) spurred productivity growth in manufacturing and accelerated the “tertiarization” of economies. The home-place was also substantially changed with advances in consumer electronics, medicine and media. No simple methodology to measure the impact of these technological changes on the world production frontier is available, so we can only use some impressionistic evidence. One of the research areas that showed some results was the investigation of IT on productivity in the US and other economies, that failed to show some tangible results until the mid-1990s. Although this should be an analysis of long-term impacts, the simple measure of increase in productivity and performance of the IT-producing sector shows an extraordinary decrease in computer memory and storage costs at the same time that performance levels improved dramatically.
Figure 7
Source: http://www.jcmit.com/index.htm
Figure 8
Source: http://www.jcmit.com/index.htm In fact, the drop in computer prices was one of the more dramatic in the history of technology. Figure 7 shows the evolution of several components of computer prices, from memory to drives. It shows a drop in memory prices from 100 in 1987 to .01 in 2008. The largest drop took place in the 1990s, but it did not stop there. A hedonic price index computed by the Bureau of Labor Statistics dropped from 100 in 1998 to .117 in 2008. The rate of diffusion of technical innovations was also significantly faster in the second wave when compared with the first wave of globalization. While the average number of years of lags in adoption of new technologies was above 34 and up to 120 for new transportation and communication technologies in the 19th century and early 20th century, it dropped to 14-15 in the case of personal computers and cellphones and even 8 for internet users, according to Comin and others (??) calculations. Figure 9 shows the intensive margins of the indicated technologies and how they differ between Western and non-Western countries, given evidence of their convergence in the second wave compared with data of the last two centuries.
Figure 9
Table 18 compares the importance of each channel of technology diffusion in the first and second age of globalization (in a scale of 1 to 5). In the first wave immigration to the Western Offshoots and trade in capital and intermediate goods were the dominant form of technology transfer. In the second wave all types of technology transfer were relevant with a lower role for immigration and still an undeveloped process of exchange of researchers and training/internships abroad as well as exchange of managers. Table 18
Local R&D or network R&D
First Global Wave 0
Second Global Authors Wave Eaton and Kortum 5 (1999), Griffith, Redding and Van Reneen (2000) Rivera-Batiz and Romer (1991) Xu and Wang (1999)
Lease and other utilization of patents
1
5
Trade in capital goods incorporating superior technologies Trade in intermediate goods incorporating superior technologies Foreign Direct Investment
5
5
3
5
Eaton and Kortum (2002)
2
5
Multinational corporation
0
5
Griffith, Redding, and Simpson (2003) Keller and Yaple (2003)
Technical advice and assistance Students in foreign universities Exchange of researchers Training and internships abroad Trade fairs and trade associations Emigration/immigration of professionals and managers
0 0 0 0 2 5
5 5 3 3 4 2
The aggregate variable mostly used to measure the intensity of innovation is the number of patents granted. The USA jumped ahead after the civil war with acceleration after 1880s. France, Britain and Germany follow, with Britain taking second place after 1885, largely due to the reform in patent registration. Another important fact is the closing of the gap by Germany in the first decade of the 20th century. Figure 10 shows the number of patents granted in North America, EU and Japan in aggregate and disaggregated data. It shows acceleration in the early 1990s and some deceleration in the early 2000s. Figure 10 1200000
1000000
800000
600000
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0
Patents Granted 300000
250000
200000
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50000
Source: WIPO
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USA 150000
Among the above technologies, the ones of particular relevance for the study of the second wave should (i) be strategic important in terms of technological relations (input-out matrix) or as an infrastructure, (ii) cover the pre-globalization as well as the globalization phase. The IT technology satisfies both criteria. Figure 11 shows the rate of use of internet across the globe, compared with phone subscribers. The data show exponential curves for phone and internet users. The acceleration for phones, with the explosion of mobile phones, took place in the mid1990s while most of the diffusion of internet took place in the first decade of the 21st century. In fact, there seems to be a saturation level for the number of internet hosts in the second decade of the 21st century.
Figure 11 Internet and phone subscriptions 6000
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Phone subscribers-millions
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7. Reducing trade barriers and trade integration (regional and global) The average tariff level for industrial countries was around 40 per cent before the first GATT negotiation in 1947. Woytinski and Woytinski (1955) reports estimates for (applied) tariff averages in 1950 for 13 West European countries, covering agricultural and industrial products (Table 19). The results confirm the existence of a low tariff country group (comprising Denmark, Norway, Sweden, and the Benelux countries) with tariffs somewhat below 10 per cent and a high tariff group with tariffs averaging close to 20 per cent (comprising France, Italy, Portugal and the UK). The average applied tariff rate among developed European countries thus ranged somewhere between 10 and 20 per cent. Note that these rates include the rather limited tariff cuts negotiated during the second round of tariff negotiations in 1950 (e.g a supplementary tariff cut of 3 per cent in the case of the United States). The GATT report “International Trade 1952” confirmed the general view of the existence of a low tariff country group (rates varying between 5 and 9 per cent, comprising the Benelux countries, Denmark and Sweden) and another group with distinctively higher tariff rates,
ranging from 16 to 24 per cent (including the United States, Germany, the United Kingdom, France and Italy in ascending order). The industrial countries’ arithmetic average of applied tariff rates was still between 10 and 20 per cent (Table 20). These estimates also include in principal the cuts made in the third round (Torquay). Table 19
Table 20
Under the GATT/WTO16 umbrella there were eight rounds of trade negotiations from the Geneva round in 1947 to the Uruguay round of 1995-99. Table 21 reports the weighted average of tariff reductions, under the Most Favored Nation (MFN) procedure. According to Table 20 the (arithmetic) average tariff had decreased from 14% in 1952 to 3.9% in 2005. However, this is not an exact picture of trade policy in developed countries. Extensive protection, e.g. in the form of subsidies, remain in the agricultural sector.
Table 21
Figure 12 gives a longer term view of the levels of protection in developed countries. It shows that from 1950 to 1970 the level of protection remained at about 15%, a level comparable to the Continental Western European levels in the last part of the 19th century (Table 1). In 197276 there was a reduction to about 8.7% and again in 1988-91 and in 1999-2003. By 2011 the average among developed countries was about 73% below the 1952 level. The 2011 average is only 4.1%.
Figure 12 Average Protection Levels 80.00
70.00
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0.00
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16
st
WTO was born in Jan 1 , 1995.
Developing
World
The extent of free trade taking place under free trade zones is estimated in Figure 16 which shows that about one third17 of world merchandise trade takes place within this two major free trade zones. Compared with decades earlier these numbers represent a substantial liberalization of trade flows. Figure 16: Intra-trade in percent of world merchandise trade 0.45 0.4 0.35 0.3 0.25 NAFTA 0.2
EU-27
0.15 0.1 0.05 0 1990
1993
2000
2005
2006
2007
2012
Source: WTO, Trade Statistics
Developing countries were always given a special status in the GATT/WTO negotiations largely due to the recognition of the infant industry argument. Thus, they took a longer term to reduce trade barriers. The levels of protection averaged about 65% from 1952 to 1966 (Figure 9). Largely due to the trade liberalization of the Asian countries, the average level of protection dropped to about 40% until 1978. After that date, there was a progressive lowering that extended around the world. As Figure 13 shows, while Asian tariffs were already low after 1980 (about 8%) Latin America only dropped their levels after 1990, converging to a tariff rate of about 10%. Figure 13 Tariff rates in Latin America and Asia (1980-2006)
17
The decrease in intra-EU trade after 2007 may be associated with the euro crisis.
90
Applied MFN tariffs (%) BR
80
PE
70 EC CO
50 AR 40 30
VE UY PY
20 18
Philippine Thailand Korea
16
Malaysia
14
China
12
Indonesia
10
Singapore
20
8 6
4
CH 10
Applied MFN tariffs (%)
MX
2
BO
0
0 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
60
AR BO BR CH CO EC MX PE PY UY VE
Source: Baldwin According to our estimates the average protection rate decreased 83% from 1952 to 2011. Taking a world average (Figure 12) the levels of protection decreased 80% in the last six decades, with the average rate of 6.5% in 2011, an historical low record. By the mid-1980s the average world level had dropped below 15%. However, there are two important facts that are not captured with aggregate protection levels: first, the extent of regional free trade zones, second is the fact that nontrade restrictions are quite high and they have been on the rise since the financial crisis (Figure 14). The problem with nontrade restrictions is that they are hard to quantify and there are no studies evaluating their impact on prices on a time consistent way.
Figure 14
Source: GTA, 14th report.
8. Organization of the production at world level: multinational enterprises, offshoring and production networks
The globalization of the last part of the 20th century is very different from the globalization of the 19th century. The technological revolution in transport, information technologies and communications after the 1980s reduced dramatically coordination costs and led to the unbundling of the production process that is now scattered around the world according to the comparative advantage of each stage of production. This branch-out of the firm led to the multiplication of the multinational or transnational corporation, leading to the formation of firms that dwarfed quite a number of states in terms of production capacity. This contrasts with the first globalization that was characterized by specialization in natural resources and raw materials as well based on the new frontiers of the Western off-shoots and the colonial system. According to UNCTAD sales of home and foreign affiliates of transnational corporations reached 75 trillion USD in 2010, value added 16 trillion USD, about one-quarter of world GDP, and world exports 6 trillion USD, equivalent to one-third of global exports. Figure 15
Recently, Johnson and Noguera (2012) have computed a global input-output table from which it is possible to estimate the value added and intermediate input contents of gross trade flows. The VAX ratio, the value added to gross value ratio to exports is an inverse measure of the vertical specialization in world production. Figure 15 shows that the VAX ratio declined significantly since 1970 with about two thirds of the decline occurring after 1990. Their calculations also show that the decline is concentrated in manufacturing. Thus, the great international unbundling has been taking place since the beginning of the 1990s. To appreciate how the production and marketing process is dispersed throughout the world, let us take the example of a high-end mobile phone from Nokia. The direct and indirect costs
imputable to Nokia are 47% of the total (R&D, marketing, sales, managing, sourcing as well as profits). The rest is outsourced: processors take up 6%, memories 3%, other integrated circuits 12%, display 6%, camera 3%, other parts 11%, assembly 2%, distribution and retailing 10%. Breaking down by regions, EU-27 (including Finland where headquarters are located) takes up 55%, US 17%, Asia 18% and other non-allocated parts 11%. This example (as a number of other examples also confirm, like Apple products) shows that although quite a number of parts are manufactured in Asia, the value added of those parts is a relatively small percentage of the total value of the product. Figure 16 shows the same fragmentation of production for a Volvo car. The Figure makes clear how far today´s production process is from Henry Ford factories requiring spatial concentration. Not only the production process of a given firm is dispersed throughout the world but quite a number of parts are contracted-out to other firms making car components, sometimes for different car models and even car companies. Figure 16 Origin of parts composing a Volvo car
In fact, volumes of trade are not a good indicator of the value chain and the value of each chain appropriated by a given country. An interesting case study by Linden and associates for the Apple IPod shows the decomposition of the price by country (Table 18). It shows that the US based Apple is able to appropriate 53 to 47% of the final price, despite the fact that does not manufacture any of the parts or do the assembly. China, that assembles the product in Taiwanese affiliates, merely appropriates 3% for this process, plus about 20% for the hard drive fabricated by Toshiba in Japan.
Technological innovation in the form of modularization has brought drastic changes to the pattern of division of labor among companies, as well as among nations. Taking advantage of differentials in resource and labor costs and endowments multinationals have been relocating their low-skill labor intensive part of the production process to developing countries. As a result of this process they are able to reduce their labor and consequently overall labor costs. The lower costs of transport, communication and superior capacities of network management supplant distances between clusters of production. But not totally since there is still substantial regional clustering, showing the continuous importance of externalities and agglomeration economies. The distribution of activities within the multinational led to the formulation of the so-called “smile curve” (Figure 17) where stages (modules) of production are represented in the horizontal axis and level of value-added of the respective stage in the vertical axis. It is the relative independence of the different modules of production which allows the fragmentation of production and the working of the value or supply-chain. The convex curve appears because high value added is higher at the extremes of the supply-chain: at the R&D, innovation and design stage, and also at the marketing, retail and after-sales services (like maintenance). In the computer industry the upstream corresponds to the development of operating systems and central processing units (chips), and the right-hand side of downstream the services close to consumers like computer maintenance, fitting to consumer needs and consulting services for use of IT. Value added (and profit margins) are lowest in the middle corresponding to mass manufacturing of parts, assembly, transport and wholesale distribution. Value Figure 17 THE SMILE CURVE
Figure 17 illustrates the drastic difference that resulted from the reduction in transportation and communication costs as well as the technological revolution in coordination of networks, which resulted in the increase in the convexity of the curve, with the intermediate part reduction in value-added. Another crucial factor for this increase in steepness was the integration of the former socialist economies into the global economic system, and in particular China, East Asia and Eastern Europe. These economies added to competition in the middle-range of the curve and the reallocation of labor resulted in overall lower unit costs for the different goods. And now also for services with the offshoring of service activities.18 The large research carried out on multinationals (Antras (2007)) shows that within multinational enterprises, parents are relatively specialized in R&D while affiliates are primarily engaged in selling goods in foreign markets, particularly in their host market, within horizontal specialization. However, the intensification of the vertical specialization also shows up in other reults. The relative importance of multinationals in economic activity is higher in capital intensive and R&D intensive goods, and a significant share of two-way FDI is intraindustry in nature. And the impact on world productivity is clear. Both the parents and the affiliates of multinational tend to be larger, more productive, more R&D intensive and more export oriented than non-multinational. Globalization has been accompanied by the emergence of regional clusters. E.g. major car component firms will reallocate or open factories/branches in other countries or continents to be close to major assembly plants owned and operated by major car companies. See Appendix I for an analysis of the globalization of the automobile markets. Unbundling of production and regional clusters
18
Reduction in ITC and coordination costs leads to competition between tasks and jobs when in the past there was competition between firms and sectors. Flexibility and unpredictability are the norm: e.g. policies in EU may favor ITC but those jobs are now offshorable.
The post II World War witnessed a rise in multinationals when American firms started to expand to Europe. One of the most important sectors was automobiles when Ford and General Motors started manufacturing operations in several Western European countries. The expansion of American multinationals and the hegemony of American R&D combined with its military power led to some European concerns of the “challenge” they posed to the geopolitical position of Europe.19 Up to the mid-1980s Figure 18 shows that FDI flows were mainly directed to Southern Europe, East Asia and Mexico. After the mid-1980s China rose steadily to the detriment of the rest of East Asia and Mexico. After 1992 China becomes the dominant destination and South Europe loses to Central and Eastern Europe with the fall of the Berlin wall. One of the main contributors for the appearance of value chains was the introduction of the “lean production” model by Japanese firms in the 1960s and 1970s. As Annex II describes in detail, one of the pillars of the lean system was the Toyota Production System based on “justin-time”, total quality control and sub-contracting parts and components to suppliers and maintain minimum stocks, at the same time that they would require total quality control to its supplies, and improve continuously tasks. Based on this system Japanese automakers increased their market share from a negligible amount in the early 1960s to 20% in late 1970s. It was only in the 1980s that US automakers would start to adopt the system. The first large scale production unbundling started in the mid-1980s and took place over very short distances that led to regional clusters. The Maquiladora process took place in both sides of the US-Mexican border. Although the process had started at around 1965, it only boomed in the 1980s with employment growing at 20% annually from 1982-89 (Dallas Fed 2002, Feenstra and Hanson 1996). It took advantage of the proximity of Mexico to the largest consumer market in the world, the United States of America, and of the lower labor costs in the Mexican side. The cluster arose from the easy access from both sides of the border and the possibility of breaking the production chain in a way that took advantage of the relative comparative advantage in both states.
19
See the book Servin-Schreiber, Le Defie American. The European Communities project and several of the Gaullist policies were undertaken with this concern in mind.
Figure 18
FDI inflows: shares 100.0 90.0 80.0
Perc. Aggregate
70.0 60.0
Eastern Europe Spain, PT, Irl,Gr
50.0
Mexico 40.0
China East Asia excl. Ch
30.0 20.0 10.0 0.0
Source: UNCTAD data base.
Another second unbundling started in East Asia at about the same time and taking advantage of the same disparity in factor costs. Distances are short: Tokyo and Beijing are about 90 minutes by plane, while wages in Japan were 40 times the Chinese wages. Rising Japanese unit labor costs in labor intensive processes led Japanese businesses to seek lower cost manufacturing sites for labor intensive stages of production and the obvious solution was to off-shore these stages of manufacturing to nearby East Asian nations. This tendency, which has been called the ‘hollowing out’ of the Japanese economy, started the development of what can be called “Factory Asia” or the “Asian Manufacturing Matrix”. Instead of Japanese goods being made in Japan and sold in the US or Europe, a new pattern of so-called ‘triangle trade’ emerged. Firms that were headquartered in Japan would produce certain hi-tech parts in Japan, ship them to factories in ASEAN nations for labor intensive stages of production (including assembly) and then ship the final products to Western markets or back to Japan. This division of East Asia into headquarters (HQ) economies and factory economies strengthened as Taiwan, Korea, Singapore and Hong Kong experienced their own ‘hollowing out’ and followed the lead of Japanese manufacturing companies in off-shoring the most labor intensive production stages to East Asian nations who had a comparative advantage in such task (i.e. nations whose low wages more than compensated for their low labor productivity).
Figure 19
Figure 20
Information technology advances and the falling costs of transportation, especially air freight, facilitated and accelerated the development of the Asian Manufacturing Matrix by making
complex production structures easier and cheaper to manage while at the same time making them more flexible and more reliable. China’s opening up and domestic pro-market reforms brought something like a half billion low-wage/low-productivity workers to the gates of “Factory Asia”. This accelerated the erosion of the HQ nations’ comparative advantage in labor intensive production processes while simultaneously expanding the attractiveness of the offshoring solution. In short, China added a pull-factor to push-factors and this quickened the hollowing out of the HQ economies (Japan, Korea, Taiwan, Singapore and Hong Kong).
In Europe the second unbundling started in the late 1970s, well before the EU accession of Spain in 1986 with the relocation of some automobile factories to Spain by Fiat and GM. The same happened to Portugal in late 1980s, with the relocation of car factories and associated car component industries. However, after the fall of the Berlin Wall the unbundling of mostly European and some Japanese and Korean firms moved to Central and Eastern Europe, with Czech Republic, Poland, Slovakia and Hungary playing a major role. In the automotive industry, in the US, clustering centered in Detroit with 50% within a radius of 250 miles. However, Appendix II shows that that clustering is now split with another cluster developing in the South with closer links to the maquiladoras of North Mexico. In Central Europe it clustered, since the 1990s, around South Germany, Czech Rep, Slovakia, south Poland and North Hungary. Figure 21 gives evidence about the dominant trade flows among nations, in 2005, based on OECD Input-output tables and trade data for intermediate goods. It clearly shows three clusters, one based on Europe, the other in North America and the other in Japan. Besides flows among both regions, intermediate goods, that are particularly important in value chains and globalization of production, flows are also intense between those regions and Asia, and in particular China. Using national data, OECD, UNIDO and academic research are now mapping the world using the concept of value-chain and clusters, as Figure 21 illustrates. Figure 21
Source: De Backer and Yamano (2012).
In fact, we are now giving statistical content to old concepts of development economics like the forward and backward linkages of Rosenstein-Rodan and Hirschman, among others or the concept of leading industry of Rostow. Projected on the space, the same concept appeared in the 1960s among French regional economists like François Prerroux and the concept of industrial pole.
9. Human capital transfer One of the major channels of technology (and knowledge) transfer since the 1970s has been the international mobility of students at the tertiary level of education. Table 44 reports the largest host and origin countries. With 1.7 million students in 2008 these 6 host countries absorbed 57% of the world total. Six Asian developing countries supply about 29% of the world total. The numbers for China have expanded by 5 in only a decade reaching now more than half a million. The main countries of destination are China (134 thousand), Australia (83 thousand), United Kingdom (65 thousand), France (25 thousand) and Germany (21 thousand).
Table 44 Students studying abroad
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
By Host Country USA United Kingdom France Germany Australia Japan Total
451,909 475,169 475,168 582,909 586,283 569,984 590,119 584,719 595,768 624,443 660,495 684,520 231,482 222,203 225,268 226,628 254,348 298,855 310,879 322,595 343,090 333,942 361,504 391,311 130,038 136,171 146,392 164,315 206,877 212,575 211,694 224,377 226,631 226,545 233,785 242,948 176,457 185,099 197,386 217,271 238,852 258,601 257,814 191,740 190,111 175,115 181,946 185,620 96,286 103,453 93,458 129,919 166,379 176,374 157,827 167,265 173,326 198,752 214,779 237,562 55,040 55,829 58,951 62,869 74,074 85,666 116,984 124,966 129,126 124,878 125,531 130,447 1,141,212 1,177,924 1,196,623 1,383,911 1,526,813 1,602,055 1,645,317 1,615,662 1,658,052 1,683,675 1,778,040 1,872,408 1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Japan China India Korea Malaysia Thailand Indonesia
57,086 119,275 50,133 61,931 54,112 19,612 25,620
58,388 122,488 51,185 66,660 49,421 20,026 27,272
59,300 140,639 58,091 71,011 40,467 19,066 32,101
57,130 165,060 70,014 73,632 39,420 20,070 33,450
63,933 223,910 96,035 85,769 41,625 23,826 36,982
64,973 312,190 114,670 91,465 44,043 23,846 37,033
61,489 365,367 129,595 96,982 43,460 23,974 31,397
64,286 402,938 141,777 100,911 42,561 23,677 30,084
59,152 406,727 141,301 104,807 44,166 23,855 28,371
55,343 429,713 157,270 109,923 47,693 24,803 31,042
50,839 459,158 179,438 117,986 51,197 24,433 32,278
45,395 516,318 198,887 127,058 54,670 25,238 33,711
40,600 564,175 203,481 126,859 53,949 26,286 34,477
Brasil Argentina Chile Mexico
16,203 5,734 4,454 13,317
16,475 5,879 4,568 13,654
17,481 6,904 4,942 14,398
17,671 6,892 5,234 15,443
19,741 7,975 5,755 20,048
20,294 9,512 6,679 21,892
19,492 8,333 5,503 21,690
19,631 8,293 7,545 23,215
20,087 8,343 6,185 24,142
21,741 8,362 6,048 25,212
23,212 9,321 6,991 25,778
26,448 9,047 8,084 26,994
27,913 9,754 8,926 26,287
By Country Origin
Source: Unesco, Institute of Statistics, Database
These six Asian countries have the highest rates of mobility in the world, as Table 45 documents. Singapore is the country with the highest rate, followed by Malaysia and Korea. Their mobility rates are almost 10 times higher than in Latin America, with Africa still trailing much behind. Table 45 1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
14.4 19.6 6.1 23.5 122.3 12.9 10.1 135.0 7.4 6.6 11.0 7.7
14.8 19.2 6.1 23.5 104.4 11.0 10.2 141.8 6.7 6.1 10.1 7.4
14.9 19.1 6.2 23.6 73.7 10.0 10.3 153.0 6.3 6.6 10.9 7.3
14.4 17.6 7.1 23.5 70.8 9.6 11.1 107.0 5.7 6.5 10.9 7.5
16.1 18.4 9.1 26.7 65.8 11.1 11.6 123.4 5.5 6.6 11.0 9.3
16.3 20.6 10.2 28.4 60.7 10.8 10.8 142.4 5.1 7.1 11.8 9.8
15.3 20.2 10.9 30.1 59.4 10.6 8.8 135.0 4.9 5.7 9.5 9.3
15.9 19.6 12.0 31.4 61.1 10.0 8.2 110.1 4.9 6.8 11.4 9.7
14.5 17.4 11.0 32.7 59.9 10.2 7.8 102.6 5.0 5.6 9.4 9.9
13.7 17.0 10.6 34.3 59.2 9.9 8.2 97.5 5.4 4.8 8.0 10.0
12.9 17.2 10.4 36.8 55.5 10.1 7.3 96.0 5.8 5.2 8.7 9.8
11.7 17.6 10.7 39.5 54.6 10.4 6.9 98.9 6.6 5.5 9.2 10.0
10.6 18.2 9.8 38.8 50.8 10.8 6.9 94.9 7.0 5.4 9.0 9.2
Mobility ratios (%o) Japan China India Korea Malaysia Thailand Indonesia Singapore Brasil Argentina Chile Mexico
Source: Unesco, Institute of Statistics, Database
An analysis of the PhDs awarded to foreigners in the US shows a very high growth rate in the 1960-2005 period (4.1%), from 2.8 to 16.5 thousand per year. Of this total about half return to their countries of origin in the next five years.20
20
A study conducted by NFS showed that about 36% of PhDs in engineering and science returned to their country of origin within five years of graduation, data collected for 2009. Study conducted by the Oak Ridge Institute for Science and Education (ORISE), Stay Rates of Foreign Doctorate Recipients from U.S. Universities, 2009, 2012.
18000 16000 14000 12000
10000 8000 6000 4000 2000
2004
2002
2000
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
1968
1966
1964
1962
1960
0
Source: NFS
An analysis of the country of origin of those graduates in science and engineering shows again that the largest share is from China (12.7%) and India (5.4%) followed by Korea (3.1%) and Taiwan (2.5%). These numbers confirm again the importance of Asian countries in the technology transfer from US universities, with a substantial presence among the top universities of the world.
PhD Awarded by US Universities by Country and Field in Science and Technology 1994-1996
Brazil Canada China Egypt France Germany India Iran Israel Italy Japan Korea Taiwan Mexico Russia/USSR Spain UK USA Total
Life Physical Engineering Sciences Sciences Total 163 193 106 462 144 314 228 686 2,259 2,752 2,882 7,893 154 47 30 231 85 58 83 226 80 155 246 481 1,718 720 912 3,350 229 82 85 396 59 58 82 199 31 36 97 164 117 92 79 288 676 597 647 1,920 512 478 586 1,576 97 187 107 391 61 42 219 322 26 73 40 139 47 114 102 263 6,620 13,787 9,880 30,287 18,278 23,881 20,213 62,372
Source: NSF, Survey of Earned Doctorates in: Bound et al., Internationalization of US Doctorate Education
Share 0.74 1.10 12.65 0.37 0.36 0.77 5.37 0.63 0.32 0.26 0.46 3.08 2.53 0.63 0.52 0.22 0.42 48.56 100.00
10. Reduction in Trade costs: transportation, communication and information costs, tariffs and quantitative restrictions Figure 5 illustrates the decrease in transportation costs due to the spread of jet aviation and the decrease in aviation costs, reducing about 60 times the goods and persons travel time. According to Figure 5 average air transport revenues per mile and passenger in the 1980s were cut from 100 in the 1930s to 16 in the 1980s. A similar revolution happened in transportation of goods by sea. The average charge for ship freight fell from 100 in the 1920s to around 26 in the 1950s. Another transport revolution is associated with containerization. The standardization of containers led to a reduction in packaging costs and the dramatic improvement in logistics as all kinds of goods can be now handled by a single type of carrier. Moreover, this type of packaging has allowed the construction of ever large ships, capable today of transporting more than 15 thousand “twenty foot equivalent units”. While about a century ago transportation costs represented on average about 125% of the final price of goods, today they represent about 1%. Another important revolution occurred in the 1980s and 1990s in the information and communication sectors. The rise of the computer age was accompanied by the rise of digital communications and the internet that is the one of the most important technological advancements of the last century. In fact, communication not only improved dramatically in quality and range but costs decreased even faster than in transportation. The cost of a 3minute telephone call from New York to London fell from 100 in the 1940s to 28 in the 1950s and then steadily to about 3-4 in the 1980s. Satellites that are today an essential means of world global communication were only available in the 1970s and the prices dropped from 100 to about 8 in the late 1990s. The internet explosion occurred also in the 1990s as Figure 6 shows.
Figure 5
30.0
25.0
20.0
Communication costs
15.0
Transport costs
10.0
5.0
0.0 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
Trade Costs 80.00
70.00
60.00
Axis Title
50.00
40.00
Transp+Com Costs Tariff Costs
30.00
20.00
10.00
2012
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
1968
1966
1964
1962
1960
1958
1956
1954
Figure 11
1952
0.00
Trade Costs with transport and communication costs adjusted for quality 75.0 70.0 65.0 60.0 55.0
Perc. Total cost
50.0 45.0 40.0
Trade Barriers
35.0
Communication costs
30.0
Transportation costs
25.0 20.0 15.0 10.0 5.0
1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
0.0
11. Factors behind the globalization: econometric evidence The ratio of exports of goods and services over GDP for the developing countries accelerated substantially throughout the 1970-2012 period, increasing from 10 to 30%. However, the increase of that ratio jumped from 1.9 pp in the 1970s to 3.4 in the 1980s, 5.6 in the 1990s and 7.8 pp in the 2000 to 2008, just before the global recession. There are several factors behind such expansion: in particular, the increase in market size, infrastructure and opening of economies in the form of institutional and political aspects, adding to the trade costs analyzed above.
35
18.00
16.00 30
14.00
25
Financial Crisis 12.00
20 10.00
World Globalization Index
Second Oil Shock
Trade Facilitation Index 8.00
15
6.00 10
Reversal Oil Prices
4.00
5 2.00
0
0.00 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Source: UNCTAD and Author´s Estimates In Figure 12 we represent three factors that show the same trend as the exports GDP ratio. The expansion of infrastructure in developing countries is captured by the number of phone lines per persons (TELPHONE), weighted by the population of each country. From 1970 to the peak of network construction the number of lines was multiplied by 18 times. Construction of communication infrastructures accelerated in the 1993-2001 period when the 5-year average of growth rates jumped from 5 to above 13%. This expansion largely coincides with the expansion of the internet and the decrease in communication costs around the world. In fact, the decrease in a 5-year average of annual growth rates of a composite index of international transportation and communication costs (TRACOMM, an inverse of the unit cost index) increases from below 2% a year up to 1986 to above 7% in late 1990s and early 2000s. The market expansion variable (MARKET) is based on the integration into the world market economy of the countries under the influence of the URSS, from Central and Eastern Europe to Asia; as well as the gradual opening of China through the designation of “special economic zones” by the Chinese government. As we know, this process started in 1982 and was carried
Figure 12 Trade globalization and its factors (I)
40
0.95
35 0.9
30
0.85
25
EXPGDPNG 20
0.8
TELEPHONE TRACOMM MARKET-RHS
15
0.75
10
0.7 5
0
0.65 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011
out throughout most of the 1980s and early 1990s. The fall of the Berlin Wall of 1989 culminated in the accession of Central and Eastern European countries into the EU in 2004. Consequently, the graph shows the most intense growth in the 1980s and 1990s. Figure 14 shows the institutional and regulatory factors: (i) the number of countries considered with a free political system by the Heritage Foundation as measure of a democratic regime (INDPOLITIC), which is a proxy for a politically open society and consequently a country with a system integrated in the world market economies, and (ii) an index of institutional development compiled by the Fraeser Institute that includes an array of indicators from the size of government, rule of law, to restrictions on foreign ownership and capital account controls (INSTDEV). For completeness we also add the index computed above that represents the inverse of the tariffs and trade restrictions of developing countries (TFNG). The first indicator shows a large progress in the 1980s, but prolonged to the last decade, and the second shows a large jump in the end of the 1970s and beginning of the 1980s and then a steady improvement in the rest of the period.
Figure 14 Trade globalization and its factors (II)
35
7
30
6
25
5
20
4 EXPGDPNG INDPOLITIC TFNG
15
3
10
2
5
1
0
INSTDEV-RHS
0 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011
The following table (Table 12) shows that there is substantial co-linearity among the factors of globalization and consequently how difficult would be to estimate the relative contribution of
Table 12 Correlation between globalization factors EXPGDP EXPGDP TF MARKET
TF MARKET INSTDEV INDPOLITICTELPHONETRACOMM 1 0.952968 0.89565 0.908562 0.865863 0.948474 -0.94248
0.952968 1 0.962259 0.904534 0.944505 0.960916 -0.98954 0.89565 0.962259 1 0.915792 0.968083 0.890381 -0.98058
INSTDEV 0.908562 0.904534 0.915792 1 0.909502 0.84071 -0.92918 INDPOLITIC0.865863 0.944505 0.968083 0.909502 1 0.864576 -0.95946 TELPHONE 0.948474 0.960916 0.890381 0.84071 0.864576 1 -0.93259 TRACOMM -0.94248 -0.98954 -0.98058 -0.92918 -0.95946 -0.93259 1
each factor. The market expansion indicator is highly correlated with the trade facilitation (TF) index, the inverse of the tariffs and trade restrictions indicator, as well as the political index. These correlations are even higher than the correlation with the export ratio. The institutional development indicator is also highly correlated with the market expansion. The build-up of infrastructure is also highly associated with the trade facilitation and the reduction in trade costs with the trade facilitation and market expansion.
Table 13
Regressions explaining Global Exports to GDP Global Exports over GDP Eq 1
Eq 2
Constant
22.185 (4.603)
11.434 (1.002)
Tariffs
.489 (.0286)
.131 (.220)
International Transp&Comm
-.403 (.149)
Eq 3 1.279 (6.354)
Trade Costs (inverse)
2.268 (1.65)
Infrastructure
.538 (.141)
Institutional
1.251 (.343)
.707 (.101)
.179 (.316)
19.215 (8.113)
Market
.998 (.298)
Inst and Political
R-squared F-statistic DW
Eq 4
0.936 352.49 0.568
0.942 206.83 0.985
0.912 202.67 0.686
0.926 159.25 0.815
LR
LR
LR
LR
Regression analysis of these factors (Table 13) shows that trade costs explain jointly 93.6% of the variance of the export ratio of developing countries (Eq. 1). Because of co-linearity, adding other factors requires that we have to drop one of those factors. Eq 2 adds infrastructure and the institutional indicator. Eq 3 includes market and infrastructure variables and Eq 4 considers a composite of trade costs (inverse) and a composite of institutional and political variables. All equations have the correct signs. However, the standard errors are affected by the serial correlation in the residuals. Is there any difference in the reaction to the globalization factors among country groups? Table 14 shows a substantial difference in the elasticities of export ratio by factor among different groups of countries. Developed countries have a much lower elasticity of export ratio to trade liberalization when compared with developing countries, which may be related with Table 14
Increase in Export Ratio by factor Developed Developing East Asia Latin America 0.250 1.389 1.806 0.584 -0.531 -0.259 -0.693 -0.335
Trade Liberalization Trade Costs
Table 15
Exports of Developing Countries over GDP
Constant
Tariffs International Transp&Comm
Eq 1 11.615 (5.720)
Eq 2 Eq 3 -13.312 21.240 (10.605) (9.005)
1.389 (.340)
.949 (.358)
.559 (.425)
-.260 (.177)
-.248 (.166)
-.645 (.277)
Eq 4 2.587 (1.242) .864 (.273)
Eq5 Eq 6 15.031 -1.465 (9.199) (22.979) .764 (.232) -.378 (.290)
.465 (.175)
Infrastructure .770 (.506)
Institutional
1.008 (.184)
1.697 (.458)
34.245 (12.562)
Market
-.217 (.335)
15.930 (20.244)
Inst and Political
R-squared F-statistic DW
0.958 557.92 0.650 LR
0.964 424.25 0.768 LR
0.966 359.78 0.934 LR
0.967 374.02 0.926 LR
0.971
0.979
0.980
1.579
Coint Coint Trend-.136Trend.47 Trend2-.002 Trend2-.007
the fact that tariffs and trade restrictions are already quite low among developed countries and they have not changed significantly, and/or the fact that most of the trade among these countries are intra-industry and not very sensitive to changes in these variables. Developed countries seem also to be more sensitive to transport and communication costs. Among developing countries Latin America is less sensitive to trade liberalization as well as transport and communication costs (trade costs) than East Asia. We next exploit the factors that determine the export ratio for developing countries. The more consistent factors in our estimations (Table 15) are the reduction in tariffs and trade
restrictions, with an elasticity of about .8, according to our preferred equations (5, 6,7),21 and .2 to -.4 for transport and communication costs. Infrastructure has an elasticity of about .3, institutional development .4 and market expansion .7.
12. Has globalization accelerated convergence at world scale? We know that unconditional convergence does not hold with the data. However, some forms of conditional convergence have been shown to hold for some periods. Has globalization accelerated convergence at world scale? We have shown elsewhere that the first wave of globalization led to convergence restricted to Europe and the western offshoots. In the present wave of globalization, FDI and integration of economies first spread from Japan to Eastern Asia, from North America to Mexico and as the European Union spread first southwards and then eastwards it also led to the integration of these areas. However, it was the Eastern Asian miracle (Korea, Taiwan, Singapore and Hong Kong), now with China at the center stage, which originated the most important process of convergence. We have seen above that only combining economic growth and trade theories we are able to explain these phenomena. China become the “factory of the world” and intra-firm and vertical off-shoring and outsourcing trade exploded. But, only a relatively small number of regions/countries benefited from the spread of technology and world production capacity due to agglomeration economies. These economies limit the spread of these phenomena to a larger number of regions/countries. Barro (1991) shows that holding constant education levels and government policies, rates of return to investment (and GDP growth rates) are negatively related to the level of income of a country. However, large differences persist in the rates of return to investment among countries, as Figure y1 shows.
Figure 1y Marginal Efficiency of Capital
21
Equations 5 and 6 use the method of cointegration in view of the serial correlation observed in the residuals.
0.7
0.6
0.5
0.4
0.3
0.2
0.1
Czech Republic
Central African Republic
Cuba
Slovenia
Croatia
Bulgaria
Belgium
Spain
Austria
Guyana
Sweden
New Zeland
United Kingdom
Estonia
Paraguay
United States
Latvia
Morocco
Slovakia
Korea
Bhutan
Kenya
Colombia
Saudi Arabia
Turkey
Philippines
Nepal
Papua New Guinea
Togo
Argentina
Belarus
Chile
Sri Lanka
Nigeria
Swaziland
Costa Rica
Ghana
Ireland
China
Benin
Sudan
Panama
Lebanon
Dominican Republic
Cambodia
Bosnia
Macao (China)
Liberia
0
Source: Author estimates based on World Bank data. But the negative relationship between the Marginal Efficiency of Capital for 1990-201022 and the GDP per capita persists with more recent data and with a large data sample.23 This relationship holds even without a conditional hypothesis. Figure 2y Relation between Marginal Efficiency of Capital and GDP per capita
22
Excluding several countries 1990-1995 with large negative rates, due either to war or the transition from a state controlled to a market economy. 23 Measured in USD, Atlas method of the World Bank.
Source: Author estimates and World Bank data. The persistence of the differentials in the rates of return to investment means a low degree of integration among countries. The higher rates of return in countries with lower GDP per capita may be the result of scarcer capital or because in these countries imitation or incorporation of new technologies via transfer of incorporated technological progress has a higher return than innovation in developed countries. We define convergence on a sustainable and substantive way if the country or region shows a decrease in the gap of its GDP per capita, in PPP,24 vis-à-vis the United States of at least 7 pp in one decade.25
Fact 1: There is no unconditional convergence across all the countries in the last half a century – here the benchmark country is the USA. Figure 3y illustrates convergence/divergence across different continents and regions and takes a representative country of each one. In 1960-1990 there were success cases like East Asian countries (Asian Tigers) as Singapore, Japan and Korea. Western European countries had convergence in the 1960s up to the early 1980s. Eastern Europe and the old socialist countries converged up to the early 1980s and then had a
24
We use for the world sample data from Maddison, updated by the Groningen database and the World Bank database. For the European Union we use the Ameco data base. 25 We define calendar decades.
strong debacle that culminated with the fall of the Berlin Wall and the dissolution of the Soviet Union. Latin America also experienced convergence until the developing countries debt crisis that erupted in 1982-83. Africa experienced divergence throughout the all period. China started its astounding ascent since the mid-1990s, and Eastern Europe, Russia and other countries of the URSS recovered and converged after the mid-1990s and in particular after 2000. India also started to converge after the mid-1990s. Among the Asian Tigers Japan diverged and Taiwan stagnated, while Korea and Singapore continued their ascent.
Figure 3y Convergence of GDP to the US level in PPP 120.0 115.0 110.0 105.0 100.0
95.0 90.0 85.0 80.0
Germany
75.0
Hungary Korea
70.0
Singapore
65.0
Japan China
60.0
India
55.0
Turkey
50.0
Russia Brazil
45.0
Poland Senegal
40.0
Zambia
35.0 30.0 25.0 20.0
15.0 10.0 5.0
1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
0.0
Figure 4y shows a quite different picture for the rest of developing countries. Latin America had a small improvement in the last six decades and Africa registered a large fall in 1950-1990 and quasi stagnation afterwards. West Asia had a large spike with the oil shocks of 1974-1980 and then fell in 1985-1990 with the fall in oil prices with quasi stagnation afterwards. The countries of state controlled economies had a large fall in convergence with the disaggregation of the URSS, and then started a long recovery. Russia and Eastern Europe have now reached a
higher level than the pre-crisis, but Central Asia and the other countries of the URSS have yet to recover fully.26
Figure 4y
Convergence GDP per capita US=100 -40.0
-45.0
-50.0
-55.0
-60.0
Gap in Percent
-65.0
Eastern Europe Ex-URSS excl. Russia
-70.0
Russia Latin America West Asia
-75.0
Sub-Saharian Africa
-80.0
-85.0
-90.0
-95.0
-100.0
Source: Author estimates based on World Bank data.
Fact 2: Three types of countries had periods of sustained and strong convergence in the last half milenium: (A) countries that followed the East Asian model, (B) countries that followed the European Union integration, and (C) countries that exploited natural resources.27 Group A comprises Hong Kong (1960-2010, except for 1990-2000); Japan (1960-1990); Korea (1970-2010); Singapore (1960-2010); Taiwan (1970-1990) and China (2000-2010). Group B comprises Bulgaria, Cyprus, Estonia, Lithuania, Latvia, Romenia and Slovakia (all in 2000-2010); Poland (1990-2010); Italy (1960-1980); Ireland (1990-2000) and three South European countries in pre-accession: Spain, Greece (1960-1980) and Portugal (1960-1970).
26
Mainly Ukraine and Belarus. We excluded from our analysis the periods of state controlled economies previous to the fall of the Berlin wall because of the profound change in the economic system and also for lack of comparability of data. We also excluded countries that had a decade of a large increase in the convergence ratio but just followed a 27
Group C comprises Azerbaijan (2000-2010); Kazakhstan (1990-2010); Botswana (1970-1990); Chile (1990-2010); Equatorial Guinea (1990-2010); and Norway (1990-2010). There are two countries that do not follow strictly the above categories but can be considered to be impacted by the European Union and have also benefited from its integration in Central Asia: Armenia and Turkey (both in 2000-2010).
In all of them trade played a major and determinant role. The East Asian model (or Asian Tigers model) is based on export promotion. At the core of the EU is a free trade area, and moreover there is institutional transplant of the institutions embodied in the EU Treaties, the so-called Acquis Communutaire. Countries endowed with rich natural resources, like oil and gas, cannot develop those resources without exporting to the consumer countries.
Fact 3: The East Asian model is based on export promotion. All usual indicators: export world market shares of total or manufactured goods and export of goods or goods and services over GDP show a major increase with globalization. And export growth sustains the convergence process: revenues from exports lead to income growth by employing labor force and increasing productivity by incorporating more developed imported technologies. Households and state use higher revenues to expand human capital. The state uses increased revenues to build better infrastructure. And nontradables demand and supply increase by multiplier effect. Looking at the different regions/countries for convergence, Figure 5y clearly shows a strong convergence to the USA level of income per capita after the II World War in a process of reconstruction from 1950 to 1970 for Japan, followed by Korea and other Asian Tigers in the 1960s. The convergence process continued for Japan until the crisis of early 1990s. Only the Asian Tigers continued to converge, with Singapore, Taiwan and Hong Kong now close to the USA levels. China is also experiencing a steady process of convergence since the 1980s, but started from a very low level. Other South Asian countries, with relatively higher level of income per capita (Thailand, Malaysia and Indonesia), are also catching-up, after a downward adjustment in the Asian crisis of the late 1990s. India is also converging since the mid-1980s, but from a lower level than China. Considering the 1985-2010 period, the countries with the largest convergence were the Asian Tigers (Singapore, Taiwan and Hong Kong with a gain of 46 pp, and Korea with 39 pp), China with 11 pp, followed by South Europe (9 pp) and East Asian countries with a higher level of GDP (Malaysia, Thailand and Indonesia) (8 pp).
Figure 5y East and South Asia: Convergence GDP per capita USA=100 0.0
-10.0
-20.0
-30.0
Gap in percent
-40.0
Japan Korea
-50.0
Other Asian Tigers China India
-60.0
Asia East high
-70.0
-80.0
-90.0
-100.0
Source: Author estimates based on World Bank data.
Fact 4: There are some exceptions to Fact 2, but no other country satisfies two other conditions (no major fluctuations in convergence, so the high convergence is simply a recovery from a high divergence in the previous decade) or having two decades of sustainable and substantive convergence. Even so, the best performer was Turkey after the mid-1990s. It benefited from the drive in Eastern Europe and Central Asia and indirectly from the European Union. Fact 5: The least developed regions of the EU were South Europe up to the early 1990s and then Eastern Europe as they prepared for accession in the mid-1990. South Europe (Greece, Portugal and Spain) had a strong convergence process in the 1960s and 1970s and then convergence tapered off in the 1980s. From the stagnated until the early 2000s, but with the Euro crisis they lost all the gains made afterwards. The data shows that it is not the date of accession that is important but when countries enter in some form of association as an antecamera for entry in the EU.
In the European Union there are two parallel processes in operation that lead to convergence: trade integration in the Single Market and institution transplant/adoption in the accession phase and deepened with EU entry. These two processes complement each other and have constituted a powerful engine of convergence in Europe. Figure 6y shows three groups of countries: countries close to the EU average that shift around the average through time. Some experienced divergence up to the mid-1980s like Netherlands and UK and then converged again, and countries that showed the reverse movement like Italy. The second group is the South European countries that have converged overall, and the third group is the Eastern European countries that experienced strong convergence after the mid-1990s.
Figure 6y Convergence of GDP to the EU average in PPP 140 BEL BUL CZE
120
DEN GER EST IRE
100
GRE SPA FRA CRO
80
ITA CYP LAT LIT
60
HUN MAL NET AUS
40
POL POR ROM SLO
20
SLK FIN SWE UK
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
1982
1981
1980
1979
1978
1977
1976
1975
1974
1973
1972
1971
1970
1969
1968
1967
1966
1965
1964
1963
1962
1961
1960
0
Source: Ameco database, April 2014. According to our hypothesis above, there are two processes that impacted convergence. The first was trade driven and the second was institutional driven. Does the data give some evidence about these processes? We could seek evidence on the first by looking at trade data, while some kind of institutional variables like rule of law or business environment could measure the second. The next Table orders the countries with the highest convergence ratios in 1970-2014 side-by-side with the increase in the ratio of Exports over GDP, a measure of openness of the economy, although imperfect. The Table shows that South and Eastern European countries, including Ireland, are among the countries with the highest rates of
convergence with high increases in the degree of openness. Among the more developed countries also in this group are Luxembourg, Austria and Finland. Table 1y Exports and Convergence in the EU Ratio of Exports G&S to GDP Increase 1970-2014 1990-2014 Luxembourg Estonia Ireland Slovenia Lithuania Romania Portugal Croatia Poland Slovakia Austria Finland Latvia Spain Germany Bulgaria Belgium Denmark United Kingdom Netherlands France Hungary Italy Sweden Greece Czech Republic
83.86 14.85 74.93 13.00 22.00 19.00 23.77 8.00 16.00 59.00 29.91 16.09 23.41 37.63 14.00 39.07 26.82 8.36 44.03 11.72 42.00 15.38 21.44 20.63 21.00
73.63 24.85 52.46 -5.90 35.26 27.25 13.42 13.33 22.41 70.93 21.28 17.94 17.10 19.62 63.41 28.29 20.20 17.70 6.45 32.34 6.21 66.75 12.00 15.56 12.19 44.46
Conv Increase 1970-2014 1991-2014 41.31 29.19 27.24 24.64 21.34 20.39 14.41 14.06 13.89 13.83 12.14 11.59 11.18 9.39 4.53 3.52 -0.05 -1.35 -1.56 -1.79 -2.26 -5.42 -6.35 -11.21 -19.28 -24.17
-7.66 32.19 25.54 -1.31 27.54 14.33 1.49 -7.66 26.17 22.57 3.10 0.02 18.68 7.39 3.12 13.46 -2.30 11.07 3.66 11.27 -3.02 6.25 -13.53 4.87 -10.91 -9.50
Source: Author´s estimates based on Ameco with backward extension of the data based on Maddison, op.cit.
Data on convergence for Eastern European countries for 1970-2014 has to be considered with some reservation because there was a regime change from central planned to market economy in the early 1990s. This clearly affects comparisons like Hungary and Czech Republic. Among the worst cases are Italy and Greece with some increase in the openness ratio but bad experience in convergence. Sweden had also a bad experience but recovered in 1991-2014. Both of these cases clearly point out to institutional factors and mismanagement of the economy. Figure 7y confirms that there is a positive correlation between the degree of openness and convergence. Figure 7y
Exports and Convergence in the EU 50.00
40.00
Convergence 1970-2014
30.00
20.00
10.00
0.00 0.00
10.00
20.00
30.00
40.00
50.00
60.00
70.00
80.00
90.00
-10.00
-20.00
-30.00
Exports over GDP 1970-2014
Source: Same as Table 1y.
There is a positive correlation between trade expansion and convergence in 1970-2014. Because of the large number of Eastern European countries in the sample, and its positive impact after 1990, we estimated a multiple regression for 1990-2014. It shows a strong negative impact of the level of convergence at the beginning of the period and a positive impact of the rule of law level at the same date. The impact of the increase in the export ratio over GDP is also positive. Countries with the highest negative residuals are Greece and Portugal which experienced a serious financial crisis at the end of the period.
Dependent Variable: CONV90 Method: Least Squares Date: 04/14/14 Time: 14:10 Sample: 1 25 Included observations: 25 Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
36.50688
9.291615
3.929014
0.0008
EXPIN90
0.177695
0.099391
1.787833
0.0882
CONVLEVEL90
-0.482388
0.125402
-3.846740
0.0009
RLLEVEL90
7.023438
2.972666
2.362673
0.0279
R-squared
0.533329
Mean dependent var
7.378667
Adjusted R-squared
0.466662
S.D. dependent var
12.72275
S.E. of regression
9.291430
Akaike info criterion
7.441709
Sum squared resid
1812.944
Schwarz criterion
7.636729
Hannan-Quinn criter.
7.495799
Durbin-Watson stat
1.580537
Log likelihood
-89.02136
F-statistic
7.999858
Prob(F-statistic)
0.000959
The largest positive residuals are for Denmark, Estonia, Latvia, Lithuania, Netherlands and Poland.
40 30 20 10 20
0 -10
10
-20 0 -10
Austria Belgium Bulgaria Croatia Czech Republic Denmark Estonia Finland France Germany Greece Hungary Ireland Italy Latvia Lithuania Netherlands Poland Portugal Romania Slovakia Slovenia Spain Sweden United Kingdom
-20
Residual
Actual
Fitted
Adding a macro-desequilibria variable (public debt plus net foreign assets) increases strongly the R2 but takes away part of the explanatory power of exports.
Dependent Variable: CONV90 Method: Least Squares Date: 04/15/14 Time: 09:51 Sample: 1 25 Included observations: 25 Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
51.71579
8.293099
6.236003
0.0000
CONVLEVEL90
-0.605070
0.103181
-5.864183
0.0000
EXPIN90
0.087418
0.081223
1.076268
0.2946
RLLEVEL90
7.369989
2.324512
3.170553
0.0048
DEBTIN014
-0.086996
0.022928
-3.794321
0.0011
R-squared
0.728655
Mean dependent var
7.378667
Adjusted R-squared
0.674386
S.D. dependent var
12.72275
S.E. of regression
7.259935
Akaike info criterion
6.979475
1054.133
Schwarz criterion
7.223250
Hannan-Quinn criter.
7.047088
Durbin-Watson stat
2.165616
Sum squared resid Log likelihood
-82.24344
F-statistic
13.42672
Prob(F-statistic)
0.000018 40 30 20 10 0 -10
10
-20
5 0 -5 -10
Austria Belgium Bulgaria Croatia Czech Republic Denmark Estonia Finland France Germany Greece Hungary Ireland Italy Latvia Lithuania Netherlands Poland Portugal Romania Slovakia Slovenia Spain Sweden United Kingdom
-15
Residual
Actual
Fitted
Appendix II explores statistically and econometrically the relationship between globalization (trade) and convergence. Does opening up the economy to the international trade, i.e. participating in the globalization, contributes to bring the GDP closer to the most developed countries in the world? There is substantial statistical and econometric evidence for a yes answer. Can a country by simply increasing its export market share expect to converge? The Appendix shows that they may not be enough. Countries like Nigeria, Kazakhstan and Iran28 have been able to increase substantially their market share without converging in 40 years! We can point out a number of reasons from geopolitical problems to institutional aspects. But what is quite obvious is that increasing the share of exports over the GDP has no power in driving convergence. This may purely be the result of GDP declining despite the fact that exports are still being maintained (e.g. due to a largely autonomous oil sector). Among the factors that may complement or reinforce the increase in export market share (globalization) to accelerate convergence improving institutions play a major role. The 28
The other countries are previous state controlled economies, but the regime change and the statistical changes put them in a separate category.
evidence of the countries that have entered or are in the process of accession to the European Union is clear. But can other type of institutions than the Acquis Communutaire play a similar role? The East Asian model proves it. This is a more complex issue that would require an analysis of unbundling institutions which is rather complex. However, on aggregate, our econometric evidence helps prove that improving institutions can contribute to convergence, but even more important, that maintaining “backward” institutions holds down convergence. Does wealth in natural resources contribute to convergence? Being rich in natural resources leads to a higher level of GDP per capita, especially if the country has a very large per capita endowment? It does not ensue that convergence will take place, because the country may have backward institutions and/or bad business environment or squander the revenues accruing from the exploitation of its natural resources in uses with low returns. Ventura (1997) uses a combination of a neoclassical growth model with factor equalization across countries, using a technology with global diminishing returns but not a local level, to explain the above facts.
13. Similarities with 19th century globalization The second wave of globalization of the 1985-Present period compared with the first wave of 1870-1914 takes place at much higher levels of income and technological capability. The second wave is no doubt of a stronger intensity and reached levels of trade and investment without precedent, but in relative terms neither wave seems to dominate. Let us compare the main indicators.
Table 20A Summary of globalization indicators: first wave
End-point
Trade flows FDI stocks
Labor migrations
7.9% GDP
Variation (1870-
Restricted (1880-
1913)
1913)1
3.3 pp 110.6% GDP
106% GDP
(140.7% GDP) 13.9% Western Europe
Notes
population (1870) Decrease in trade
33%
costs Convergence goods
-76%
prices
Reduction land-
Convergence factor prices Convergence in income per capita
No convergence
-24%
No convergence
21 pp
wage ratio
1/ Western Europe and Western offshoots only.
Data for the first wave show not only an intense level of trade, investment and labor migration among Western Europe and their offshoots, but also a large drop in trade costs and significant convergence between the groups of countries directly involved (Western Europe and offshoots). But these integration indicators do not generalize to other parts of the globe. Table 10 summarizes the main indicators of the globalization at world level and for a restricted set of countries that experienced integration (Western Europe and offshoots).
Table 20B Summary of globalization indicators: second wave
End-point
Variation (1985-
Restricted1
Notes
2010) Trade flows FDI stocks Labor migrations (integration in world system) Decrease in trade costs Convergence factor
24.2% GDP
9 pp
30.4% GDP
22.8 pp
8 pp
20% world population
83% No convergence
-85% (US-China)
Reduction in differential
prices
-56% (GER-BUL)
Convergence in
China: 12 pp v. US
income per capita
No convergence
average wage
Bulgaria:18 pp v. EU
1/ European Union and East Asia. Wages and income data are for 1995 to 2011.
The intensity of the trade flows, relative to GDP was about three times larger in the second wave, but the intensity of FDI for the countries of destination was much larger in the first wave. While in the first wave there were massive migrations that led to the transplant of economies in the second there was a similar massive integration of labor/population in the world economic system. The decrease in trade costs was about three times larger in the second wave. While in the first wave there was a significant convergence in commodity prices, in the second wave markets were already significantly integrated so no such movement occurred. However, we could say that there was also a significant impact in world producer prices since by transferring a large part of manufacturing to countries with lower labor costs prices of manufactured goods were reduced in relative terms. According to calculations of Amiti and Chai of the FRBNY China29 is the largest single supplier of imports to the United States, accounting for more than 20 percent of nonoil imports and more than 30 percent of consumer goods. They show that consumer goods prices remained almost stable from 1997 to 2011.
Now what would be the counterfactual? Suppose they increased at the same rate as the US 29
See http://libertystreeteconomics.newyorkfed.org/2013/01/chinas-impact-on-usinflation.html#.U4tDBigzS5I.
CPI, then they would have increased by 43%. This is a very rough calculation but it gives an idea of the importance of the phenomena. The convergence process in both waves is not comparable. In the first wave was an integration “of equals” so we could say, despite the fact that there was a reduction in measure income per capita numbers, in PPP, of about 27 pp, these countries had similar income opportunities from the beginning. The only differences were the different endowments of natural resources. In the second wave there it is an “integration of unequals” in view of the large difference in incomes and wages between e.g. US or Germany and China or Bulgaria. In the case of the US versus China, the multiple of wages has been reduced from about 60 to 10 in the 1995 to 2011 period, with a reduction of 12 pp in the income levels: a truly astounding achievement. In the case of Germany versus Bulgaria the multiple of average wage rate in manufacturing was reduced from 26 to 11 in the same period. When compared with the first wave of globalization in the second half of the 19th century we witness the deliberate construction of political entities like the European Union or NAFTA, the rise of multinationals and the appearance of production networks with vertical and horizontal integration, and most notably the integration of developing economies (without the same cultural and institutional background) into the globalization process. In fact, as we emphasize in a companion paper, Mateus (2013), the first wave of globalization was mainly the transplant of Western European economies to the so-called Western offshoots (North America, Australia and New Zealand). What is the potential for further globalization? If we take as measure of potential openness the symmetric of the share of GDP of a country in the world economy there is still a large potential. E.g. the US trade over GDP ratio would have to rise another six-fold, from its current 12 per cent to more than 70 per cent, before it fully reflected the share of non-US producers and consumers in the world economy.
Source: Frankel, J. (2006).
14. Conclusions and further research
There is a simple common model to the first and second globalization: in both there was a large expansion of the production possibility frontier. In the first wave due to the transplant of the European economies to the Western offshoots and in the second due to the integration in the world economic system of the previous socialist economies. In both cases the expansion was equivalent to 20 to 30% of the previous scale. Both had as major causes the technological revolutions that decreased transport and communication costs. But the second had a more profound change in terms of management techniques, the affirmation of multinationals and the creation of value chains across the world although clustered around certain regions. While in the first most of the international trade was inter-sectoral, exploiting OH differential ratios of endowments, the second wave is characterized by the growth and large share of intraindustry and intra-firm trade with both horizontal and vertical specialization. In the first wave there was an almost immediate convergence process since the large migrations of people from Europe to the Western offshoots carried with them the human capital, institutions and culture of the technologically most advanced countries in the world. In the second wave we witness the unprecedented phenomena of developing countries catchingup significantly, with some of them closing the gap with developed countries, and even surpassing them, like Singapore, Hong-Kong or the oil-rich states of the Middle East – although all being still relatively small.30 The present wave is characterized by a new division of labor at world level that (i) integrates China and other East Asian economies in the world economic system, with their vast human resources and low wages compared with the developed countries, (ii) India with a large segment of relatively educated labor force and also low wages, and (iii) Russia, Brazil, Mongolia and some African states, with their large natural resources also in the world endowment set. The present wave of globalization started a large process of political and economic integration among developed economies, of which the European Union is the paradigm. But it also reached vast populations and areas of the developing world: (i) reallocation of low and middle-skilled manufacturing from developed countries to China and other Asian economies, at the same time that Korea, Japan, Taiwan, Singapore and Hong-Kong assert themselves as mature or emerging technological centers. At same time vertical disaggregation of stages of production and localization according to comparative advantages of multinational corporations deepened; (ii) outsourcing of services to India especially in the IT sector, and (iii) intensification of trade in natural resources with the entry of new regions like the old Soviet Union and the accession of China as a major industrial power. How long this phase of globalization will last and what will be the next stage? The present stage will last, if no major natural cataclysm or war occurs, until the following trends last: (i) the surplus-labor model of China runs out (wages start to increase significantly and transfer of low and medium-level technology manufacturing runs out), and the other Asian countries substitute for the low-wage levels of China (Indonesia, Vietnam and Myanmar), (ii) the 30
Korea is possibly the relatively large country which will be able to close the gap in the next two decades.
resurgence of North America and Europe using advanced high-skill and capital intensive manufacturing, (iii) technological change and resource bounds lead to less natural resource intensive economies and more environment friendly technologies. What are the implications of the passage of the present globalization phase to the next? China is fast becoming the largest economy of the world in GDP terms. But the industrialization process and GDP growth will progressively decelerate, as in all convergence processes: its growth rate will decelerate from the present 8% to converge to 3-4% when entering the next phase. The threshold for the new phase depends on a number of technological and institutional factors.31 Presently, China has an income per capita of 4,270 USD per capita (WB, Atlas method, 2010) equivalent to 9% of US income per capita. Assuming growth decelerates to a 4% growth rate of GDP in the decades of 2030-2050, in 2050 the income per capita of China would be already 25% of the US level.32 The process of outsourcing in the services sector is more limited than in manufacturing: in developed countries the share of manufacturing has decreased by 10-20 pp of GDP. We estimate that outsourced services can hardly go above 5% of GDP of developed countries, about 1 fifth of the manufacturing level. Thus, India cannot count on the same level of impact of globalization than China, unless it also turns to manufacturing for trade. Transfer of manufacturing industry from developed countries has always been quite limited in India due to regulatory problems and government policies, but also due to the domination of industry by a small number of conglomerates. The main policy conclusion we reach are that the significant convergence achieved by the countries that followed the East Asian export model, integration in the EU and that exploited rich natural resources would not be possible without globalization. Trade and openness to the world economy is the essence of their success. However, there have been different modalities of trade and industrial policies: from the dirigisme and protectionist of East Asian countries to the more liberal approaches of the European Union or NAFTA. Thus, countries should maintain an open system with continuous policies for encouraging exports. Infant industry arguments may apply to certain isolated cases (like automobile manufacturing in large countries) but it should be restricted and temporary. The second conclusion is that institutions matter, as so many other researchers have shown. Having a market economy with a favorable business environment and rule of law is crucial as our own results above show. The transference of institutions in the case of the European Union is a case in point. The other is the efficient use of the proceeds from exploiting natural resources to avoid the curse of the riches. Much research still needs to be done on the nexus of globalization and development. Theoretical models have not yet fully integrated growth theory with technological change and
31
A number of economists consider that the present institutional system would have to be adapted to maintain the momentum of economic growth. How Chinese government will adapt is quite uncertain. But even with substantial improvement of institutions, there is the technological process of catching-up that will put a brake on growth. 32 And in 2070 about 30% assuming a g.r. of 3%.
the dynamics of globalization.33 Although we can identify some of the causes of globalization there is still too little research on the relevance of each of the factors. And the same in terms of the impact of globalization: there is a large body of research on its impact on labor markets of developed countries and inequality, but not much in terms of impact on world consumers and the broader impact on global growth. Quantification and integration of technological factors in models of growth and globalization is also a major area of further research, after the recent contributions of Comin and its associates. Finally, the structure of the world economy is changing rapidly, but we do not know what is the new steady state for each the present transitions will carry us. E.g., what would be the new steady state for China, with the present policies? These are questions that require simulation models of dynamic general equilibrium but with more precise specification of technology and instituions.
33
See our companion paper Mateus, Causes and Impact of Globalizations a Reinterpretation in Light of New Trade Theories, forthcoming 2014.
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