Abstract
This chapter explains how the new-fangled configurations of global production, investment, and trade being orchestrated by the new nexus of multinational enterprises (MNEs), foreign direct investment (FDI), and global value chains (GVCs) have been transforming global patterns of employment and specialization in the twenty-first century. The chapter provides conceptual underpinnings and empirical findings on the linkages between trade, investment, and value chains, and identifies the underlying forces and dynamics that are propelling the new trends and patterns of employment and specialization across the world under the new nexus.
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Notes
- 1.
For further details on the Heckscher-Ohlin theory see an excellent recent collection of contributions in Findlay et al. (2006).
- 2.
Several influential economists, such as Anne Krueger, Dani Rodrik, and Joseph Stiglitz subscribe to this school of thought. For further details see a good collection of contributions in Lin (2012).
- 3.
- 4.
- 5.
The ICITE consists of scores of organizations, including the ADB, the AfDB, the ECLAC, the IADB, the ILO, the OAS, the OECD, the UNCTAD, the World Bank, and the WTO.
- 6.
A report on the economic impact of 14 trade agreements that the US has signed with 20 countries concluded that these trade agreements increased US aggregate trade by about 3 percent and US employment by 1.59mn full-time equivalent employees (USITC 2016).
- 7.
These studies also found that open economies significantly outperformed closed economies in improving overall working conditions, such as injuries on the job, child labor, informality, effects on female labor, fatal accidents, life expectancy, and labor rights (Friedman et al. 2012).
- 8.
Based on www.data.worldbank.org, accessed on October 10, 2017.
- 9.
- 10.
The study points out that much of the skepticism of earlier studies resulted from the econometric models and methods used, exogeneity/endogeneity assumptions made, and the choices of data transformations. They maintain that foreign aid can spur growth and investment by changing the equilibrium level of investment, raising private investment through improvements in infrastructure, and when used wisely for growth-enhancing activities, such as the health and education sectors.
- 11.
Majority-owned foreign affiliates (MOFAs) are more than 50 percent owned by their US parents. Most foreign affiliates of the US-based MNEs are majority-owned.
- 12.
A US parent is a fully consolidated US domestic enterprise consisting of a US business enterprise whose voting securities are not owned more than 50 percent by another US corporation. A US parent comprises the domestic (US) operations of a multinational enterprise.
- 13.
During the 1992–2007 period, US foreign affiliates created on average about 100,000 jobs per year in low-cost developing countries (Jackson 2013).
- 14.
For example, during the 2005–2010 period, the General Electric cut 1000 employees overseas and 28,000 in the US; Cisco added 10,900 employees in the US and 21,250 overseas; and Honeywell cut 5000 employees in the US and added 19,000 overseas (Beatty and Liao 2012). Despite such huge cuts in domestic workforce during the last recession, the US-MNEs in the banking, computer, logistics, and retail industries added nearly 700,000 jobs through intra-firm exports (Alejandro et al. 2011).
- 15.
For example, Caterpillar cut 2800 jobs in the US since 2008 when it hired over 8000 workers in the Asia Pacific region, where its sales grew by nearly 40 percent. Additionally, two-thirds of the company’s revenues come from outside the US. IBM has reduced its US workforce from 105,000 to 83,000 between 2009 and 2012, while its workforce in India increased to 112,000 in 2012 from 6000 in 2002. The Cisco Systems kept its US workforce steady since 2009 while adding 8000 jobs abroad, but about half of the company’s sales revenues comes from abroad (USA Today, September 28, 2014).
- 16.
Such higher returns of affiliates in developing countries were however associated with rapid increase in overseas investment by the US-MNEs in the 1990s due to privatization of electric utilities and telephone companies as well as liberalization of direct investment policies in many developing countries.
- 17.
Some of the studies that considered the impact of acquisition in the context of developed countries, on the other hand, found that firm-level employment levels remained unchanged or increased only slightly following foreign acquisition. See, for example, Girma (2005) for the UK; Bandick and Karpaty (2007) and Heyman et al. (2007) for Sweden; Balsvik and Haller (2010) for Norway; Malchow-Moller et al. (2013) for Denmark; Andrews et al. (2015) for Germany; and Huttunen (2007) for Finland.
- 18.
Such gaps in worker productivity and wages in domestic firms and foreign-owned firms are however also partly explained by the differences in training opportunities for workers in such firms (Rizvi and Nishat 2009).
- 19.
The countries covered by the study were Burkina Faso, Burundi, Cameroon, Cabo Verde, Ethiopia, Ghana, Kenya, Lesotho, Madagascar, Malawi, Mali, Mozambique, Niger, Nigeria, Rwanda, Senegal, Tanzania, Uganda, and Zambia.
- 20.
These studies are cited in Mucuk and Demirsel (2013), which also provides a review of other studies, along with their methodologies and findings, on the relationship between employment and FDI in the context of host developing countries.
- 21.
In the context of host developed countries, Ireland provides an excellent example of FDI and employment relationship. In 2011, foreign-owned MNEs accounted for €48.9bn or 57.4 percent of the country’s gross value-added (GVA), and about 22 percent of the country’s total employment in business economy—2.5mn out of 11.51mn jobs. Economic Impact of the Foreign-Owned Sector in Ireland (2015), a publication of the Department of Finance, Ireland.
- 22.
Kiyota (2014) showed that Japanese employment increased its export dependence during the 1975–2006 period—directly through own exports of industries as well as indirectly through exports of other industries via intra-industry linkages—and the magnitude of the indirect effects exceeded those of the direct effects throughout the period. Similar high employment-export dependencies were also found in China, Japan, and Korea for 1995–2008 period (OECD 2013).
- 23.
The New York Times on September 20, 2013, reported that the American manufacturing sector lost 32 percent of its jobs—numbering 5.8mn—between 1990 and 2012, and the hardest hit was the textile and apparel subsectors, which alone lost 1.2mn jobs or 76.5 percent. In 1991, American-made apparel accounted for 56.2 percent of all the clothing bought domestically, but by 2012, the share dropped to 2.5 percent.
- 24.
At the same time, automobile production increased by 158.8 percent in Czech Republic, 148.8 percent in Turkey, 28.3 percent in Poland, 395.1 percent in Slovakia, 332.1 percent in Romania, and 58.5 percent in Hungary (Frigant and Miollan 2014).
- 25.
The author, Kaushik Basu, is currently the chief economist at the World Bank.
- 26.
International Federation of Robotics. http://www.ifr.org/news/ifr-press-release/world-robotics-report-2016-832/, accessed on June 22, 2017.
- 27.
In 2016, global sales from industrial robots exports amounted to US$4.5bn. Top-10 exporters were Japan, $1.6bn (36 percent of total industrial robots exports); Germany, $639.7mn (14.2 percent); Italy, $293.4mn (6.5 percent); France, $250.7mn (5.5 percent); the US, $193.5mn (4.3 percent); South Korea, $179.5mn (4 percent); Austria, $156.6mn (3.5 percent); China, $155.3mn (3.4 percent); Sweden, $143.6mn (3.2 percent); and Taiwan, $107.3mn (2.4 percent). (Based on http://www.worldstopexports.com/top-industrial-robots-exporters/, accessed on June 25, 2017.)
- 28.
The study by Acemoglu and Restrepo (2017) estimates that one more robot per thousand workers reduces the employment-to-population ratio by about 0.18–0.34 percentage points and wages by 0.25–0.5 percent in the US economy. The study however cautions that the impact of robots is distinct from the impact of imports from China and Mexico, the decline of routine jobs, offshoring, other types of information technology (IT) capital, and the total capital stock, and these variables are only weakly related to exposure to robots.
- 29.
Economist, May 27, 2017.
- 30.
Based on http://www.ifr.org/news/ifr-press-release/world-robotics-report-2016-832/ accessed on June 21, 2017.
- 31.
The O-ring model holds that failure of any one step in the chain of production may lead to the failure of entire production process. On the other hand, improvements in the reliability of any given link increase the value of improvements in all the others. The name came from Space Shuttle Challenger accident of 1986. The Challenger exploded and crashed back to earth less than two minutes after its takeoff, killing all seven crew members. The proximate cause of the crash was traced to a seemingly inconsequential rubber O-ring seal in one of its booster rockets that failed after hardening and cracking during the icy Florida weather on the night before the Challenger takeoff (Autor 2015).
- 32.
Economic Policy Institute. 2016. The Productivity Gap, updated August 2016. Accessed on April 2017, (http://www.epi.org/productivity-pay-gap/).
- 33.
- 34.
Service occupations involve jobs in helping, caring for, or assisting others. Most of the workers in service occupations have no postsecondary education, and average hourly wages in service occupations are in most cases below the other occupation groups.
- 35.
Such remarkable changes in the labor markets of these two periods—1940–1980 and 1980–2010—can be attributed to many factors, including changes in the relative supply of college and noncollege labor, rising trade penetration, offshoring, global value chains, declines in labor union penetration, changes brought forth by information and communication technology (ICT), and changes in the minimum wage and tax policies (Katz and Margo 2014).
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Dowlah, C. (2018). The New Nexus and the Emerging Trends in Global Employment and Specialization. In: Transformations of Global Prosperity. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-71105-8_8
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