Adidas announced in late 2019 that its Speedfactoriesin Ansbach in Germany and Atlanta in the U.S.which use computerized knitting, robotic cutting, and 3D printing to produce athletic footwear will close next year. Having been heralded as evidence of how robots will lead to wide-scale reshoring of manufacturing to Europe and the U.S., does this reversal mean that these worries were all overblown? Tellingly, the other headline in the announcement was that these automated production lines will instead be moved to China and Vietnam where 90 percent of Adidas suppliers are currently located. This is not an isolated example. China has installed more industrial robots than any other country and is rapidly automating to address declining wage competitiveness. This is important given that China produces a quarter of all manufacturing globally, and the production of labor-intensive goods and tasks has typically shifted to countries with lower labor costs in a pattern that then reproduces itself among countries in the lower tiers.
Akamatsus flying geese paradigm describes this shifting international division of labor based on dynamic comparative advantage. American, European, and Japanese firms moved a lot of their production to developing Asia and Latin America, first helping countries like Malaysia and Chile, then others like China and Mexico, and then others like Vietnam and Bangladesh. Lower-wage countries in Asia and Africa are hoping to be next in line. Will robotization slow down the offshoring of production to lower-cost locations and ground the flying geese? In a new paper, we move beyond anecdotes to analyze the impact of robotization in high-income countries on greenfield FDI flows from high-income countries (HICs) to low- and middle-income countries (LMICs). Unlike trade flows and other investments, which can be sticky and slow to change in response to other factors, greenfield FDI data represent announcements and are therefore forward-looking.
The intensity of robot use varies widely across manufacturing industries and high-income countries. In 2015, the number of robots per 1,000 employees was the highest in the Republic of Korea, Germany, Sweden, the United States, and Denmark. Among these, the intensity of robot use increased discernibly between 2004 and 2015 in Korea and the United States but remained largely unchanged in several European countries. Robotization remains more limited in China (Figure 1). Among industries, robotization is most pronounced and has advanced most rapidly between 2004 and 2015 in electronics, automotive products, rubber and plastics, and metal products. In contrast, the intensity of robot use in textiles, apparel, and leather products remains the most limited (Figure 2).
Exploiting these differences in how the intensity of robot use has increased across countries and industries between 2004 and 2015, and accounting for any other changes at the country-sector and country-year level, we find a 10 percent increase in the number of robots per 1,000 employees in HICs is associated with a 5.5 percent increase in the growth of FDI from HICs to LMICs. The results are robust. The positive impact of robotization in HICs on FDI growth from HICs to LMICs is (a) not driven by any single industry, (b) accounts for the stock of related ICT capital and the market size of destination countries, and importantly (c) is robust to the inclusion and exclusion, respectively, of China as a source and destination country. This positive relationship is consistent with the income effect of automation outweighing the substitution effect. On the one hand, robotization makes it economically profitable to reshore some labor-intensive tasks to advanced economies. On the other hand, it leads to an expansion in the scale of production, which results in greater offshoring to low- and middle-income countries.
However, the relationship between robotization in HICs and FDI from HICs to LMICs is not a linear one. While the linear effect remains positive, continued robotization past a threshold level of robots per 1,000 workers has a negative impact on this FDI growth. This reflects initial signs that scale economies in the use of robots may concentrate production in fewer places. However, only 3 percent of the sample exceeds the threshold level beyond which further automation results in negative FDI growth and is consistent with reshoring. For another 25 percent of the sample, the impact of robotization on FDI growth is positive, but at a rate that is declining. So, although these are early warning signs, automation in HICs has still resulted in growing FDI from HICs to LMICs for more than two-thirds of the sample under consideration.
Robots have therefore not grounded the flying geese, at least not yet. However, for the geese to fly unabated, lower-cost locations will likely need to walk the extra mile to remain attractive investment destinations. This means relying less on low wages only to be globally competitive but doing more to meet demanding ecosystem requirements in terms of infrastructure, logistics and other backbone services, regulatory requirements, and so on. Robotization has not yet changed the larger development agenda.
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