The Global Resource Accounting Model (GRAM) is a multi-regional input-output model (MRIO), which currently distinguishes between 62 countries and one ‘rest of the world’ region and 48 industrial sectors per country or region. The heart of the model is made up of OECD data on bilateral trade flows and input-output tables for 1995 to 2010. Combined with additional data sets, such as CO2 emissions and material extraction, the model enables production-related variables to be attributed to end consumption.
GRAM is a ‘real’ MRIO model containing a global input-output matrix. Matrix P (consumption-based emissions) is derived from matrix E (emissions intensity), matrix A (inverted input-output) and matrix Y (final demand). The matrix is very large (63x63), requiring correspondingly large amounts of computing time. As an example, the diagram below depicts the calculations for Austria.
Unlike other GWS models, GRAM is not a dynamic simulation and forecasting model, but instead allows statistical calculation of consumption-based emissions, material rucksacks, value added and employment attributable to a product. Official emissions and material consumption statistics are production-based/territorial. This means that emissions arising during production of goods or services are attributed to the country in which the goods or services are produced.
The production-based/territorial emissions concept is the basis for international climate change reporting referenced in international agreements such as the Kyoto Protocol. With the assistance of global MRIO models, this production-related data can be used to calculate the quantities of emissions and material rucksacks along the length of the production chain for goods consumed in a country (the ecological footprint).
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Our figure of the month 05/2022: Strong increase in timber prices due to rising global demand, supply bottlenecks and trade embargoes
Forestry and sawmills benefit
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