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UIBE GVC Index System

UIBE GVC Index System

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Please click on UIBE GVC Index (or Baidu cloud, Amazon cloud)to access the database. Alternatives are: using the Aliyun service (URL: or the Baidu cloud service (URL: For your convenience, you can also click on UIBE GVC Index(or Baidu cloud, Amazon cloud) anywhere mentioned in the following context to access the database. For users in China, the Aliyun service and Baidu cloud service are recommended; for foreign users, the Amazon cloud service is recommended.

Please read this instruction carefully before you download and use the data. The instruction includes the following sections: background of setting up the database, data structure, update records, copyright and download methods.

  • Background

With the rapid growth of international trade in intermediate goods and the deepening of vertical specialization, the global economy enters into the era of global value chains (GVCs), which is characterized by international fragmentation of production and trade in intermediate inputs. In recent years, studies on global value chains at industry and country levels have been developing extremely fast. This is an important development to the GVC studies at firm levels. Specifically, the measurement of global value chains (also known as accounting of trade in value added) emerges as a hot research topic. Driven by investigation on this topic, researches on global value chains evolve from micro-level case-based management studies to macro-level economic and statistical studies.

For GVC accounting studies, important work includes Timmer et al. (2013, 2014), Koopman et al. (2014, AER), WWZ (2013, NBER Working Paper) and WWYZ (2017a, 2017b, NBER Working Paper). They have proposed the GVC accounting methods at the industry and country levels and have successfully applied them to international economics related studies. On one hand, these cutting-edge works provide important quantitative analyses for GVC studies and scientific decision-supports for policy makers. On the other hand, the basic GVC accounting framework will also promote other GVC related studies, such as employment and environmental issues. In addition, the GVC accounting method overcomes the double counting issue suffered by the transitional trade statistics and can provide answers to questions that cannot be fully answered by traditional supply chains and logistics management disciplines as well as GVC governance studies. The literature review shows that the accounting method for trade in value added and the indicators for industry competitiveness as well as participation in global value chains have been well developed and successfully applied and will be widely used in the future.

The development of GVC accounting studies benefits from the recent public release of Inter-country input-output tables. Ever since the 1970s, the issue of trade in intermediate goods has attracted much attention, but no significant progress due to limited data on trade in intermediate products and final products (Baldwin et al., 2013). Economists try to deal with this data limitation in many ways, which is crucial to studies on trade in intermediate good. Before 2011, some economists classify trade in intermediate goods and trade in final products by using HS codes and the characteristics and end-use of products, but it was difficult to identify all of the trade in intermediate goods. Hummels et al. (2001) employs the input-output table to track the use of imported products, and then proposes the VS index. Some recent studies, such as Koopman et al. (2014), processed the GTAP database into the ICIO database (Inter-Country Input-Output Tables) based on some assumptions and additional data, which allowed them to make a further and more comprehensive exploration on the basis of Hummels et al. (2001). The first version of WIOD (World Input-Output Database, Timmer et al., 2012) was released in 2013. The world input-output tables in this database (also known as WIOTs in WIOD, World Input-Output Tables) provide data on trade in both intermediate goods and final goods for 35 industries, covering 27 countries in EU and 13 major economies in the world for the period 1995-2011. This database has strongly contributed to GVC studies in the field of international trade (Los et al., 2012; Stehrer, 2012; Stehrer et al., 2012; Timmer and Erumban, 2012; Timmer and Los, 2012; Baldwin, 2013; etc.). Furthermore, WIOD has also facilitated studies on employment, energy and carbon embodied in international trade, since it includes social-economic account and environmental account. The latest version of WIOD was released in 2016 (WIOD 2016). In the new version, the WIOTs have 56 industries, covering 43 countries, for the period 2000-2014. Other representative global ICIO tables include OECD ICIO, EORA and ICIO tables developed by Asian Development Bank (See Appendix G in Taglioni and Winkler (2016) for more details). The databases above have different features, in terms of countries or regions, industry classifications, time spans and the distinguishing of processing trade.

  • Underlying Data and Accounting Methods

GVC accounting is the fundamental method for GVC studies at industry and country levels. To provide researchers the required GVC indicators (such as value added export) for GVC studies and to avoid unnecessary duplicated workload of calculations, the research team for global value chains at University of International Business and Economics (UIBE) complied a set of accounting indicators, i.e. the UIBE GVC Index. The team leader is Professor Zhi Wang at UIBE. The construction of the index system is based on the representative studies on GVC accounting, which bridges the gap between international trade statistics and the system of national accounts (SNA), and uniforms all previous measures of vertical specialization in the literature (such as VS, VS1, RCA and VAX). Our aim is to promote studies on global value chains, to facilitate the use of accounting results in other areas, and to provide convenience for researchers in the fields of trade theory, empirical studies, as well as economic and policy analyses.

The construction of UIBE GVC index system is mainly based on the GVC indicators calculated by using the widely accepted methods of GVC accounting. Therefore, it is a secondary (derived) database, which is processed based on the public released ICIO tables. Considering that the accounting methods developed by KWW (2014), WWZ (2013) and WWYZ (2017a, 2017b) are relatively comprehensive inclusive, UIBE team primarily use these methods to construct the index system. The detailed methods can be found in the following literatures (all the indicated working papers are the latest versions):

Robert Koopman, Zhi Wang and Shang-Jin Wei, “Tracing Value-added and Double Counting in Gross Exports”, American Economic Review, 104(2): 459-494, 2014.

Zhi Wang, Shang-Jin Wei, and Kunfu Zhu, “Quantifying International Production Sharing at the Bilateral and Sector Levels”. NBER Working Paper 19677, 2013.

Zhi Wang, Shang-Jin Wei, Xinding Yu and Kunfu Zhu, “Characterizing Global Value Chains: Production Length and Upstreamness, NBER Working Paper 23261, 2017a.

Zhi Wang, Shang-Jin Wei, Xinding Yu and Kunfu Zhu, Measures of Participation in Global Value Chains and Global Business Cycles, NBER Working Paper 23222, 2017b.

The data used for constructing the UIBE GVC Index (or Baidu cloud, Amazon cloud) are from the world-renowned global ICIO tables. These ICIO tables have different features, in terms of countries or regions, industry classifications, time spans and the distinguishing of processing trade. For more information on the original worlds ICIO tables, please refer to their websites (WIODOECDICIOGTAPEora). The features of different ICIO tables are summarized in the following table (please see the next section for more detailed information on region and industry classifications):

ICIO tables

Number of Countries or Regions

Number of Sectors

Time span
















20042007, 2011









Eroa(suspension of opening)




Notes: a. China and Mexico distinguish between processing trade and non-processing trade at sector level (or global manufacturing and non-global manufacturing).

b. This database is developed by RIGVC at UIBE on the basis of GTAP database in the same way as Koopman et al. (2014), characterized by the more detailed agricultural sectors (six agricultural sectors).

c. This database is developed by ADB (Asian Development Bank), and it includes five more Asian countries (Bangladesh, Malaysia, Philippines, Thailand and Vietnam) in the WIOTs. In the new version (ADB-MRIO2017), the table has been updated to 2016 and the number of countries and regions has increased to 61.

  • Index Structure and Instructions

UIBE GVC Index (or Baidu cloud, Amazon cloud) is developed by Research Institute for Global Value Chains (RIGVC) at University of International Business and Economics (UIBE). It is free to download and use for researchers around the world. Please do not use it for commercial purposes. In the research outputs (including but not limited to papers, reports, books, etc.), please indicate the data source.

Download Link: UIBE GVC Index (or Baidu cloud, Amazon cloud) © 2016, Research Institute for Global Value Chains, University of International Business and Economics.

Reference: RIGVC UIBE, 2016, UIBE GVC Index,

Any questions and suggestions about UIBE GVC Index, please contact RIGVC at UIBE.

Contact: Fei Wang


At present, UIBE GVC Index includes five categories of indexes. In the future, we will add new indicators as needed and continue to improve the existing ones. Welcome to use UIBE GVC Index. We really appreciate your valuable advice. In addition, please contact us if any requirements about data processing and further analysis related to UIBE GVC Index.

UIBE GVC Index is stored in Aliyun (and Baidu cloud, Amazon cloud). When you click on the download link of the index system, you will see a guide page, as shown below. First, users should decide which ICIO database they would like to use to calculate GVC indicators. Second, choose your GVC Indicators calculated based on the selected ICIO database. For example, if users would like to use the GVC Index based on WIOD, they should first click the WIOD folder in the guide page. Furthermore, in the papers folder, you can find UIBE GVC Index related papers. The three documents at the bottom of the guide page introduce the detailed indicators under UIBE GVC Index System. You can also click on the language icon at the top right corner of the guide page to switch the language to your native language.

After clicking the WIOD2016 folder on the guide page, you will go to the next page shown below. For other folders, the page structure is the same.

As shown in the figure above, all of the indicators in UIBE GVC Index are stored in three files (index1_PROD, index2_Trade, index3_Length). For the convenience of different software users, all the indicators are in csv format. The units of the indicators are the same as those in the ICIO database you have selected, unless otherwise specified. For instance, the indicators based on WIOD are in million dollars, which is exactly the unit used in the WIOD database.

  • Three Categories of Indicators in the UIBE GVC Index System

    • index1_PROD: Production based GVC decomposition. It includes two types of decompositions: the decomposition of final products by using backward production linkage and the decomposition of industrial value added by using forward production linkage.

    • index2_Trade: The decomposition of bilateral gross trade. The bilateral gross trade can be decomposed into domestic value added, returned domestic value added, foreign value added and the double counting component.

    • index3_Length: The length of GVC, including production length, the position in the global production chain and the number of cross border times.

See the technical notes of UIBE GVC Index System (the three documents at the bottom of the guide page) for more details, including detailed indicators and their explanation. In the doc folder (see the figure above), you can find the introductions to the country and industry classifications used in the ICIO databases.

  • Notes on the Decomposition of Bilateral Gross Trade (index2_Trade)

The WWZ formula (see NBER working paper 19677) can decompose the bilateral gross trade Esr into 16 components by using backward production linkage. In some studies, we also need to decompose the bilateral gross trade by using forward production linkage. Therefore, by extending the WWZ method, we also include the forward linkage based decomposition in index2_Trade. For the decomposed 16 components, each component is expressed by a matrix of three dimensions.

The bilateral gross trade Esr is a matrix of two dimensions (GN*G). G is the number of countries (or regions) and N is the number of industries. The first dimension GN represents the exporting country and the industry (each country has N industries). The second dimension G represents the importing country in the bilateral trade. By using the extended WWZ method, the bilateral gross trade matrix of two dimensions (GN*G) can be decomposed into 16 components. Each component is expressed by a matrix of three dimensions (GN*GN*G). We call these matrices component matrices. The third dimension G is the importing country in the bilateral trade; the second dimension GN is the exporting country and industry (the same as the GN in Esr); the first dimension GN is the country and industry where the value added is created. For the domestic value added component, its first dimension GN is the same as the first dimension GN in the Esr, i.e. the exporting countries and industries are exactly the same countries and industries that create value added in the production of these exports (so we call it domestic value added). For the foreign value added component, its first dimension GN is not the same as the first dimension GN in the Esr, i.e. the exporting countries and industries is not the same countries and industries that create value added in the production of these exports (so we call it foreign value added).

If you would like to analyze the decomposition results by using backward production linkage, you should sum across the first dimension of each component matrix. After this summation, the component matrices add up to the Esr matrix. If you would like to analyze the decomposition results by using forward production linkage, you should sum across the second dimension of each component matrix. After this summation, however, the component matrices do not add up to the Esr matrix. You can also analyze the decomposition results by using backward production linkage and forward production linkage at the same time. For example, when analyzing the bilateral export of electronic products, you can obtain the domestic value added embodied in the exported electronic products and can also know in which industries is these domestic value added created. Meanwhile, you can also know the foreign value added embodied in the exported electronic products and in which industries is these foreign value added created.

In the UIBE GVC Index Database, the 16 components are further aggregated to 8 components (see the technical documents for details). This requires breaking down each component matrix of three dimensions to G component matrices of two dimensions (GN*GN). G represents the countries where the exports go to. For example, AUS in the csv file name 2000.WIOD2016.L3_1_DVA_FIN.AUS.csv” tell us that the destination country of the export is Australia. L3_1_DVA_FIN represents the first component in the 8 components. “WIOD2016” represents the ICIO database used for the decomposition. 2000 represents the year.

  • R codes

We also provide the R codes for calculating the indicators. They are written based a case of three countries and four industries. They can be simply generalized to other cases by adapting 01.0.ReadingData.r. The R codes can be found on the guide page of the UIBE GVC Index is stored in Aliyun (and Baidu cloud, Amazon cloud). They are stored in the compressed file” (or in Baidu cloud, Amazon cloud).

Where you run the program, please first run 01.0.ReadingData.r. This will yield some intermediate outcomes (such as A, B, L, Esr, see the file inc) which are required to calculate the GVC indicators.

The RIGVC of UIBE will provide service for copying the UIBE GVC index, R codes, and original data in the near future. This can solve the downloading problems encountered by some users. Data in R and csv formats can be provided. Data in csv format can be read by most data processing software. The R format data can be used by the R users and can be directly analyzed by using our R codes. The intermediate outcomes (A, B, L, Esr) can significantly reduce the calculation costs for researchers who attempt to analyze the GVCs by using ICIO database. Before analyzing the GVCs based on ICIO database, the procedure of data preparation and processing are rather time consuming. It is wise to work with data processing software (such as R and Python). Our R codes can be used as a starting point.

For the copy service, please contact with

  • Download Methods

The download methods depend on the size of the data file. When the data is in small size, you can directly click on the “download” icons as shown in the next two figures, following the first and the second steps. However, for the big size data, its better to use some software with functions of pausing and resuming downloads, such as Flashget, to avoid the waste of time in case the downloads are interrupted.

You can download Flashget at The English version of Flashget can be downloaded at:

When you use Flashget to download the GVC indexes, you can follow the next four steps. The figures are examples of downloading FVA_FIN index in 2011 under Index 4 which is calculated based on OECDICIO. Besides, note that the names of GVC indexes do not change with time and the original database. Please be careful, in case of incorrect time or original database selection.

Step 1:

Step 2:

Step 3:

Step 4:

  • Update Records

3.0 April 29, 2018: Improved the structure of the UIBE GVC index system. The five categories of indicators in the previous version have been aggregated to 3 categories. The big files have been broken down to small files to solve the downloading problems. Cooperating with WTO, the Amazon cloud service has been used to solve the downloading problem encountered by the foreign users. The Baidu cloud is used as an alternative choice for domestic users.

2.1 Mar 24, 2017: Adding two NBER Working Papers and their download links, which introduce the implications and computation equations of Index 1, Index 2 and Index 5 in the UIBE GVC Index System in detail.

2.0 Jan 15, 2017: Recalculating all the indicators based on WIOD2016, in line with the replacement of 2007 data in the original database (WIOD2016).

1.1 Dec 26, 2016: The UIBE GVC Index is officially open to the public.

1.0 Sep 20, 2016: The UIBE GVC Index is open to a small group of researchers.

  • Applications of Some Indicators

(in progress)


  1. Baldwin, Richard & Javier Lopez-Gonzalez, 2013. "Supply-Chain Trade: A Portrait of Global Patterns and Several Testable Hypotheses," NBER Working Papers 18957, National Bureau of Economic Research, Inc.

  2. Daria Taglioni and Deborah Winkler(ed)(2016), Making Global Value Chains work for Development, World Bank, Washington DC.

  3. Hummels, D., Ishii, J., and Yi, K-M. (2001). “The Nature and Growth of Vertical Specialization in World Trade.” Journal of International Economics, 54(1), 75-96.

  4. Johnson, Robert, and Guillermo Noguera. 2012. “Accounting for Intermediates: Production Sharing and Trade in Value-added,” Journal of International Economics, 86: 224–236.

  5. Koopman, R., Z. Wang, and S.J. Wei (2014) “Tracing Value-added and Double Counting in Gross Exports,” American Economic Review, 104(2): 1–37. or NBER wp18579(2012).

  6. Los B., Timmer M.P. De Vries, G.J. 2014, How Global are Global Value Chains? A New Approach to Measure International Fragmentation. Journal of Regional Science.

  7. Los, B., M. P. Timmer, and G. J. de Vries (2016): “Tracing Value-Added and Double Counting in Gross Exports: Comment,” The American Economic Review, 106, 1958–1966.

  8. Los Bart, Erik Dietzenbacher, Robert Stehrer, Marcel Timmer and Gaaitzen de Vries (2012), Trade Performance in Internationally Fragmented Production Networks: Concepts and Measures, WIOD Working Paper No.11, May 2012

  9. Mattoo, Aaditya, Zhi Wang and Shangjin Wei,Trade in Value-Added — Developing New Measures of Cross Border Trade, co-edited with CEPR/World Bank, April 2013.

  10. Robert Stehrer (2012), Trade in Value Added and the Value Added in Trade, WIOD Working Paper No. 8, April 2012.

  11. Robert Stehrer, Neil Foster, Gaaitzen de Vries (2012), Value Added and Factors in Trade: A Comprehensive Approach, WIOD Working Paper No.7, April 2012

  12. Timmer, M.P. , B. Los, R. Stehrer and G.J. de Vries, 2013, "Fragmentation, Incomes and Jobs: An Analysis of European Competitiveness" Economic Policy, 28, 613-661.

  13. Timmer, M.P., Erumban, A.A., Los, B., Stehrer, R., De Vries, G.J. 2014. Slicing Up Global Value Chains. Journal of Economic Perspectives, 28(2): 99-118.

  14. Timmer, Marcel P.(ed), 2012, "The World Input-Output Database (WIOD): Contents, Sources and Methods", WIOD Working Paper Number 10, downloadable at

  15. Timmer, Marcel P., A. A. Erumban, J. Francois, A. Genty, R. Gouma, B. Los, F. Neuwahl, O. Pindyuk, J. Pöeschl, J. M. Rueda-Cantuche, R. Stehrer, G. Streicher, U. Temurshoev, A. Villanueva, and G. J. d. Vries (2012). The World Input-Output Database (WIOD): Contents, sources and methods. WIOD Background document available at

  16. Timmer, Marcel P., Bart Los, Robert Stehrer, Gaaitzen de Vries (2012), Fragmentation, Incomes and Jobs. An analysis of European competitiveness, WIOD Working Paper No.9, November 2012.

  17. Zhi Wang, Shang-Jin Wei, Kunfu Zhu, 2013. Quantifying International Production Sharing At The Bilateral And Sector Level. NBER Working Paper 19677,

  18. Zhi Wang, Shang-Jin Wei, Xinding Yu and Kunfu Zhu. (2017a). Characterizing Global Value Chains: Production Length and Upstreamness. NBER Working Paper 23261.

  1. Zhi Wang, Shang-Jin Wei, Xinding Yu and Kunfu Zhu. (2017b). Measures of Participation in Global Value Chains and Global Business Cycles. NBER Working Paper 23222.