Wiedmann, T., H. C. Wilting, M. Lenzen, S. Lutter, and V. Palm (2011) Quo Vadis MRIO? Methodological, data and institutional requirements for multi-region input-output analysis. Ecological Economics, 70, 1937-1945. Wiedmann, T. O., H. Schandl, M. Lenzen, D. Moran, S. Suh, J. West, and K. Kanemoto (2013) The material footprint of nations. Proceedings of the National Academy of Sciences, 112, Tables with captions Table 1. Characteristics of the assessed databases. Eora () Source data National IO tables 74 IO tables from national statistical offices Bilateral trade data Trade in goods from UN Comtrade database Trade in services from UN Service trade database Value added data National IO tables UN National Accounts Main Aggregates Database UN National Accounts Official Data System structure Region detail 186 countries Sector detail Varies by country; ranges from 26 to 511 sectors Structure of IO tables Heterogeneous table structure. Mix of SUT and SIOTs. SIOTs can be industry-by-industry or product-by-product System construction Harmonization of sectors Uses original classification from national accounts Harmonization of prices and currency Converts national currencies into current US$ using exchanges rates from IMF Assumption for countries with no IO data For each of the 113 countries with no IO table, sector data is taken from the UN National Accounts Main Aggregates Database then applied to a general template averaged from the IO tables of Australia, Japan and the US Off-diagonal trade data calculations, balancing and constraints Large-scale KRAS optimisation of an intial MRIO estimate with various constraints Eora26 () Source data National IO tables As Eora Bilateral trade data As Eora Value added data As Eora Region detail As Eora
Sector detail 26 homogeneous sectors Structure of IO tables As Eora System construction Harmonization of sectors Uses concordance matrices to aggregate Eora to 26 sectors Harmonization of prices and currency As Eora Assumption for countries with no IO data As Eora Off-diagonal trade data calculations, balancing and constraints As Eora GTAP () Source data National IO tables Tables submitted by GTAP consortium members Bilateral trade data Trade in goods from UN Comtrade database. Trade in services from UN Servicetrade Value added data Tables submitted by GTAP consortium members System Region detail 129 regions Sector detail 57 homogeneous product-by-product sector tables Structure of IO tables Homogenous SIOT table structure System construction Harmonization of sectors To disaggregate a country’s non-agricultural sectors, the structure from other IO tables within regional groupings is used. For agricultural sectors data from the FAO is employed Harmonization of prices and currency IO tables scaled to US$ using GDP data from the World Bank Assumption for countries with no IO data GTAP contains 20 composite regions such as ‘Rest of South East Asia’ which are calculated as a linear combination of the known IO tables for that region and matching the required income level for the area Off-diagonal trade data calculations, balancing and constraints Uses ‘entropy-theoretic methods’ to harmonize dataset. Constraints include consumption data from the World Bank, energy data from IEA), Bilateral trade data from UN’s COMTRADE database. WIOD () Source data National IO tables SUTs from National Accounts. Bilateral trade data Trade in goods from UN Comtrade database. Trade in services from UN, Eurostat and OECD Value added data SUTs from National Accounts. System Region detail 40 countries and a rest of the world region Sector detail 35 homogeneous industry-by-industry sector tables Structure of IO tables Homogenous SIOT table structure
System construction Harmonization of sectors Developed concordance tables between national classifications and the 35 sectors used in WIOD. Harmonization of prices and currency Supply table (from SUT) in basic prices. Use table in purchases prices. Transform the Use table to basic prices. Convert all data to current US$ using exchange rate from IMF Assumption for countries with no IO data A single RoW region. To determine the RoW data, global totals are found and the sum of the 40 WIOD countries is subtracted from this total Off diagonal trade data calculations, balancing and constraints International SUTs merged to a ‘World SUT’ then transformed to a WIOT using the fixed product sales structure assumption. Missing data – use additional info and reallocate negative entries