Positioning in Global Value Chains: a comprehensive database

We make a comprehensive database of positioning measures – upstreamness and downstreamness -available to researchers. The measures are based on the most popular Inter-Country Input-Output tables – ADB MRIO, EORA , OECD TiVA, WIOD, WIOD Long-Run – and are available at the global, country, and country-sector level.
The database will be updated regularly with new data releases.

by Michele Mancini, Pierluigi Montalbano, Silvia Nenci, Davide Vurchio

Go to the Download section

Please cite Mancini M., Montalbano P., Nenci S., Vurchio D., 2024, Positioning in Global Value Chains: World Map and Indicators. A new dataset available for GVC analyses, World Bank Economic Review, forthcoming. [old WP version]

Global production complexity, across different sources

Source: Mancini, Montalbano, Nenci, Vurchio, Positioning in Global Value Chains: World Map and Indicators. A new dataset available for GVC analyses.

If you are interested in GVC participation and Value-Added measures take a look at the Stata command icio and the World Bank WITS GVC Database.

What are these measures?

Upstreamness and downstreamness are measures of positioning in Global Value Chains, computed with data from Inter-Country Input Output tables.

  • Upstreamness of a country/sector measures the distance of its productions from the final demand. Far from final use? High Upstreamness. See Antràs et al. (2012), Measuring the Upstreamness of Production and Trade Flows, American Economic Review Papers & Proceedings 102(3): 412-416.
  • Downstreamess of a country/sector measures the distance from the factors of production (sources of value-added). Far from the source of value-added? High Downstreamness. See Antràs, P., and Chor, D. (2013), Organizing the Global Value Chain, Econometrica 81(6): 2127-2204.

At what level of aggregation are they available?

These measures were originally used to know where single industries are located along global value chains. Nevertheless, they can be aggregated at the country, global industry and global aggregate level. As a matter of fact, at the global aggregate level, upstreamness and downstreamness coincide and are a proxy for global production complexity. See Antràs, P. and Chor, D. (2019). On the Measurement of Upstreamness and Downstreamness in Global Value Chains. In L. Y. Ing and M. Yu (Eds.), World Trade Evolution: Growth, Productivity and Employment, Chapter 5, pp. 126–194. Routledge.

Download the full dataset

Download data for a specific ICIO source

Version
2022 Jun.
199.82
2022 Nov.
2016
1.1 2022 Mar.

Time coverage
2000; 2007-2021
1990-2015
1995-2020
2000-2014
1965-2000

Please, remember also to cite the original Inter-Country Input-Output database you are using:
ADB MRIO: Asian Development Bank MRIOT Database, mrio.adbx.online
EORA: Lenzen, M., Moran, D., Kanemoto, K., Geschke, A. 2013. ‘Building Eora: A Global Multi-regional Input-Output Database at High Country and Sector Resolution.’ Economic Systems Research, 25:1, 20-49.
Please remember that the Eora MRIO is free for academic (university or grant-funded) work at degree-granting institutions. All other uses require a data license before the results are shared.
OECD-TiVA: OECD, Trade in Value Added database, 2018, oe.cd/tiva.
WIOD: Timmer, M. P., E. Dietzenbacher, B. Los, R. Stehrer and G.J. de Vries, 2015. ‘An Illustrated User Guide to the World Input-Output Database: the Case of Global Automotive Production.’ Review of International Economics. 23: 575–605.
WIOD Long Run: Woltjer, P., Gouma, R. and Timmer, M. P. (2021), “Long-run World Input-Output Database: Version 1.1 Sources and Methods”, GGDC Research Memorandum 190.

Last updates

  • November 2022: first release