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The authors are grateful to Diego Cerdeiro, Wenjie Chen, Marcello Estevao, Hamid Faruquee, Sergi Lanau, Andre Meier, Petia Topalova, for useful discussions and Steve Brito, Ava Yeabin Hong, and Hong Yang for excellent research assistance. All remaining errors are our own.
The global Eora MRIO tables with a harmonized 26-sector classification across countries (also known as Eora26) can be accessed from http://worldmrio.com/simplified/. Please see the supporting documentation on the website for additional details.
The 2016 release of the World Input-Output Tables covers 43 countries and 56 sectors.
Currently, the GTAP 9 database provides data for three reference years (2004, 2007, and 2011) for 140 regions and 57 sectors.
There is also a mapping of these sectors to revision 3 of the standard industrial trade classification (SITC Rev.3). For more details, please contact authors.
At the country level, to calculate value added in exports at the aggregate (i.e. not bilateral) level, we would recommend applying the methodology of Los et al. (2016) to more detailed national input-output tables (provided they are available).
In this example, final demand comprises only household consumption. In the full Eora data, there are 6 components of final demand: (1) household final consumption; (2) non-profit institutions serving households; (3) Government final consumption; (4) gross fixed capital formation; (5) changes in inventories, and (6) acquisitions less disposals of valuables.
There are two files of accompanying Matlab code. The first Matlab code was written using with the toy example (3 countries, 4 sectors each; see Eora_example_calc_userguide.m), and may be helpful for step-by-step calcualtions using block matrices, via loops, but this approach comes at the cost of efficiency. The second Matlab code (see code_eora_c_final.m) assumes the use of full Eora data and, when used with full Eora data it will run faster. Essentially most of the same concepts are coded in two different ways, to assist the reader.
Note that notation Tv does not imply matrix multiplication.
Borin and Mancini (2015) refine the framework in Koopman et al. (2014), by distinguishing further between the DVA in intermediate exports absorbed by direct importers and that going for final use in a third country in terms 2, 3, and 4 of the decomposition.
It is important to note that it was recent work by Johnson and Noguera (2012) and Koopman et al. (2014) that generalized Hummels et al. (2001) vertical specialization measures to complex production chains. Koopman et al. (2014) demonstrate that the VS and VS1 measures do not accurately decompose exports into their foreign and domestic value-added components when the production chain spans several countries, i.e., when one country imports intermediate inputs, adds value, and then exports semi-finished goods to another country that produces the final goods. In these cases, it is not accurate to assume that imports from a source country embody only domestic value added from that country, as they may also include value added from third countries. These more complicated production chains may include the increasingly important phenomenon of round-tripping, in which intermediate goods may cross the same borders several times, with some of a country’s intermediate goods imports embodying some of its own value added.