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
If you use the database, please cite
Mancini M., Montalbano P., Nenci S., Vurchio D., 2022, Positioning in Global Value Chains: World Map and Indicators. A new dataset available for GVC analyses, DiSSE Working Paper.
Global production complexity, across different sources
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
- Readme and countries’ and sectors’ labels
- Full dataset (all sources): Stata version (dta), CSV version.
- Background paper
Download data for a specific ICIO source
1.1 2022 Mar.
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.
- November 2022: first release