Global Value Chains

Understanding Production and Trade Patterns Using an Input-Output Lens With the increasing demand for GVC research, there is a pressing need for quantitative approaches that characterize and describe production linkages across sectors and economies. The ADB undertakes statistical initiatives to facilitate research on this topic by constructing input-output tables for its 19 developing member economies. The initiative builds on the latest World Input-Output database (Timmer et al., 2015) by augmenting the tables with 19 developing member economies and extending the coverage up to the latest year.

Multiregional input-output tables (MRIOTs) make explicit the supply-use relations among the producers and consumers in the global economy. For GVC analysis, the tables permit the measurement of linkages between economies and the interactions between them. Moreover, the utilization of MRIOTs in economic analyses enables researchers to 1) capture the evolution of economies as actors in global value chains, 2) quantify the relative importance of GVC-related activities for each economy, and 3) uncover the potential policy implications of emerging trade patterns.

Timmer, M. P., Dietzenbacher, E., Los, B., Stehrer, R. and de Vries, G. J. (2015). An illustrated user guide to the world input–output database: the case of global automotive production. Review of International Economics, 23, 575–605.

Traditional trade (i.e., goods and services trade for final consumption) statistics can no longer capture important elements of current trade relationships across economy-sectors. Due to the increasing fragmentation of production processes across economies worldwide, calculating the relative importance of economies in global value chains need to account for back-and-forth trade in intermediates. This consequently leads to the measurement of trade in value-added terms.

The GVC index system developed by Wang, Wei and Zhu (2018) decomposes gross exports into several value-added terms. This decomposition can be undertaken at the global, country, bilateral and country-sector levels. Running the exports decomposition using the ADB MRIOT dataset produces a panel dataset covering 63 economies (including rest-of-the-world) for the years 2007 to 2017.

Wang, Z., Wei, S., and Zhu, K. (2018). Quantifying International Production Sharing at the Bilateral and Sector Levels (NBER Working Paper 19677). Cambridge, MA: National Bureau of Economic Research. Retrieved from the National Bureau of Economic Research: http://www.nber.org/papers/w19677.

The traditional method of computing for revealed comparative advantage was introduced in Balassa (1965). In this method, an economy is defined to have an RCA in a product if it exports more than its "fair share," or a share that is equal to or greater than the share of the product to total world trade.

The traditional RCA may not be the most appropriate measure of comparative advantage in a GVC world characterized by intensive and extensive networks of trade in intermediates. There are at least two reasons for this. First, TRCA ignores the fact that a country-sector’s value-added may be exported indirectly via the country’s exports in other sectors. Hence, a more conceptually correct measure should be able to account for value-added exported indirectly across economy-sectors. Second, TRCA neglects the fact that an economy-sector’s gross exports may partly carry foreign value-added content. Therefore, a conceptually correct measure should exclude foreign value-added content embedded in exports.

To address the abovementioned issues, a redefinition of TRCA is accomplished in Wang, Wei, and Zhu (2018). The new RCA indicator makes use of value-added contributions to exports (i.e., forward linkage-based measure of domestic value-added in exports) in lieu of gross exports.

Balassa, B. (1965). Trade Liberalisation and “Revealed” Comparative Advantage. The Manchester School 33(2), 99-123.

Wang, Z., Wei, S., and Zhu, K. (2018). Quantifying International Production Sharing at the Bilateral and Sector Levels (NBER Working Paper 19677). Cambridge, MA: National Bureau of Economic Research. Retrieved from the National Bureau of Economic Research: http://www.nber.org/papers/w19677.