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Fabrication vs Knowledge Activities in Global Value Chains: Contributions to Asian Development

Co-author: Elisabetta Gentile

This post draws on a paper presented at the Allied Social Science Association Annual Meeting in a session sponsored by the American Committee on Asian Economic Studies on "Economics of Innovation in Asia", 3 January 2021, 3:45-5:45pm US EST (GMT-5).  

Integration into global value chains (GVCs) is widely viewed as a powerful driver of growth, productivity, and job creation. The ‘East Asian miracle’—which saw the region grow faster than any other during the second half of the 20th century—is presented as evidence of this link (Gereffi 1999). However, with the 21st century came the concern that while developing Asia has been successful in increasing employment in labor-intensive fabrication activities and emulating production techniques, the switch from imitation to innovation is more difficult yet necessary to avoid a middle-income trap (Bulman, Eden, and Nguyen 2017).

We use a global value chain (GVC) approach to study how the types of activities carried out drive growth and income convergence in an economy. Our findings aim to shed light on why, as of 2018, GDP per capita in developing Asian economies is about one third the level in Organisation for Economic Co-operation and Development (OECD) member countries.

The focus of our study is not manufacturing industries in developing Asia, but rather the set of activities carried out in the region for final manufactured products produced anywhere in the world (Timmer et al. 2013). For example, an Asian firm might be involved in business processing, such as data entry, accounting, or call centers, for a final manufacturing product from a firm in France. Indeed, activities in GVCs of manufactured products can be performed by firms classified in any sector of the economy. That is why the use of input-output linkages is required to explicitly account for interdependence among firms.

In a value chain, pre-fabrication activities are carried out by workers with occupations relating to R&D and design; fabrication activities are the tasks carried out by workers with occupations involved in the physical transformation process; and post-fabrication activities are carried out by workers with occupations relating to branding, marketing, and logistics. To keep the analysis manageable, we merge pre- and post-fabrication activities into one category that we call knowledge-intensive activities. That is because both pre- and post-fabrication activities have higher value added than fabrication activities and require higher-skilled workers.

Based on the framework introduced by Buckley et al. (2020), income convergence may originate in three ways. First, through increasing the scale of either fabrication or knowledge activities, i.e., the number of workers involved in activities carried out for final manufactured products relative to the OECD. Second, through the reallocation of workers from low- to high-value added activities within GVCs, which would increase the overall skill content of the activities. This shift towards higher value-added activities within GVCs is referred to as ‘functional upgrading.’ A stylized functional upgrading pattern would involve the shift from assembly, to own-equipment manufacturing, to ultimately own-brand manufacturing (Gereffi, 1999). In our framework, functional upgrading is defined as an increase in the share of workers in knowledge relative to fabrication activities. Finally, productivity convergence in one (or both) activities will lead to income convergence and implies process upgrading, for example through better organization of the production process or the use of improved technology, or product upgrading, for example by improving quality or design, or adding new features.

In Figure 1, we examine the role of scale and productivity effects in driving income convergence. Panel A shows GVC employment in each of 14 developing Asian economies in 2000 and 2018. A value above one indicates that a larger share of the workforce is employed in GVCs relative to the OECD average. In 2000, nine out of 14 economies had a scale ratio above one. This increased to 12 out of 14 by 2018. In fact, in China, India, Indonesia, Taiwan, and Thailand the ratio was above 2, which highlights the active involvement of Asian workers in manufactures GVCs. The average employment ratio for the developing Asian economies was 1.19 in 2000 rising to 1.62 by 2018. This suggests the GVC income gap between developing Asia and the OECD is not due to the overall scale of their involvement in GVCs.

Panel B shows the income gap is due to differences in productivity. On average, the productivity ratio was about 12% of the OECD mean in 2000. While productivity increased rapidly, it started from low levels such that it was still at only 19% of the OECD mean by 2018.

Figure 1: GVC Employment & Productivity  

Panel A: GVC workers/population vs OECD mean

Panel B: GVC income/worker vs OECD mean

Data Source: ADB MRIOTs and occupations databases.



     Figure 2: Decomposition by Activity

     Panel A: GVC workers/population vs OECD mean

   Panel B: GVC income/worker vs OECD mean

   Data source: ADB MRIOTs and occupations datasets. 

Figure 2 presents a decomposition between fabrication and knowledge-intensive activities. Panel A depicts the employment ratio whereas Panel B shows the productivity ratio for each of fabrication and knowledge activities. Both panels convey a great deal of diversity among the 14 developing Asian economies. However, the scale of fabrication activities is generally close to or greater than one, and as high as 5.3 for Vietnam in 2018. The employment ratio for knowledge activities was mostly less than one, but as high as 2.5 for Taiwan and over one for many economies by 2018. The productivity ratio was in all cases below one, and mostly far below one. But the increases over time are widely disparate, both across economies and between fabrication and knowledge activities.

Perhaps the most encouraging finding from our study is that many of the 14 developing Asian economies under consideration saw big productivity increases in knowledge activities, albeit from a low base and at low employment levels, suggesting that true income convergence may be underway.




Co-author Elisabetta Gentile is Economist at the Economic Research and Regional Cooperation Department of the Asian Development Bank and a Fellow of the Global Labor Organization. The statements in this publication are the views of the author and do not necessarily reflect the policies or the views of ADB.

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