The Global Resource Accounting Model (GRAM) is a multi-regional input-output (MRIO) model, covering 53 countries and 2 regions and 48 sectors per country/region. It covers the years between 1995 and 2005. In contrast to other models of GWS mbH, it is not used for forecasting, it rather calculates historic data that does not yet exist in such a form: CO₂ emissions and resource use by consuming country and not by producing or extracting country. Furthermore, the results are detailed in such a way that the countries of origin are determined within the model.

Purpose

The GRAM model allows the calculation of aggregated indicators of production/extraction versus consumption of raw materials and emissions of countries and world regions, taking into account resource requirements along international production chains. Thereby, comprehensive physical trade balances for individual countries or regions can be calculated and the main net-importers and net-exporters of different categories of natural resources and emissions in the world economy can be identified. GRAM results thus show the extent to which an economy is dependent on natural resource/emission imports from abroad. These types of calculations are the empirical basis for the discussion as to whether producer or consumer countries are responsible for related environmental impacts.

Structure of the model

It is a "true" MRIO model including one global inter-industry requirements matrix (A). It therefore differs from the common form of MRIO models: linked single-region IO models. These are models that include one IO model per country, which is solved separately from the others, and then linked to the other country models via international trade. The GRAM model implicitly includes international trade in the inter-industry requirements matrix, which is calculated from monetary input-output and bilateral trade data. The central equation of the model is:

The pollution matrix P (the main result of this model) and the final demand matrix y are composed of 55x55 vectors pij and yij, respectively. Each of these vectors has 48 entries corresponding to the sectoral classification of the OECD input-output data. yij is the final demand in each sector of country j directed at the production of country i. pij is the pollution in each sector associated with production in country i to satisfy demand in country j. The matrices P and y are of size 2640x55. The matrix A includes inter-industry requirements between all sectors in all countries. It consists of 55x55 48x48 matrices Aij. Hence, the total dimension of this matrix is 2640x2640. The matrices Aii correspond to inter-industry requirements within a country, and the matrices Aij, for j≠i, correspond to inter-industry requirements of exporting country i and importing country j. The matrix E (2640x2640) is a matrix including emission intensities on the diagonal (t CO₂E/USD). The emission intensity matrix E can also be replaced by a matrix containing raw material input requirements. The pollution matrix P, with its subvectors pij, would then be interpreted as the material extracted in country i to produce the products consumed in country j. The final outcomes of the model are diverse: trade balances for all countries including embodied emissions or raw materials, embodied emissions in domestic production and consumption, direct and indirect emission/raw material intensities.

Data

The main data-sources are the Organisation for Economic Co-operation and Development (OECD) Input-Output Database (2009 edition), the OECD Bilateral Trade Database (2008 edition), and CO₂ emission data and energy balances of the International Energy Agency (IEA). The raw material data is provided by Sustainable Europe Research Institute (SERI).

Applications

The first version of this model (detailed model description), which was solved by an iterative procedure with single-country IO models linked via a trade model, was developed by GWS and SERI in 2007 during the course of the petrE project (Resource Productivity, Environmental Tax Reform, and Sustainable Growth in Europe). In this application raw material rucksacks of 8 raw material extraction categories (Agriculture, grazing, fish and fibre crops, Forestry, Coal and oil, Natural gas, Iron ores, Other metal ores, Industrial minerals, Construction minerals) were calculated for the year 2000.
The model was updated to the second (current) version in 2009 during the KLIEN project (Die Klimabilanz des Österreichischen Außenhandels). Updates concerned the model structure on the one hand and the application area on the other hand. Due to increased computational capacities and enhanced programs, it is no longer necessary to use the iterative solution procedure. Rather, it is now possible to directly calculate the Leontief inverse of the 2640x2640 inter-industry requirement matrix, and solve the model at once. Further, the 2009 edition of the OECD IO data include not only tables for 2000, but also IOTs for 1995 and 2005 for each country. It was therefore possible to extend the model period from a single year (2000) to also include all years between 1995 and 2005.
As the first version only contained material and no emission data, the database of GRAM had to be extended to include emission data and energy balances for the KLIEN project, which was primarily interested in embodied emissions in Austrian trade.

Publications

• Bruckner, M., Giljum, S., Lutz, C. & Wiebe, K.S. (2012): Materials embodied in international trade - Global material extraction and global material consumption between 1995 and 2005. Global Environmental Change (forthcoming).
• Wiebe, K.S., Lutz, C., Bruckner, M. & Giljum, S. (2012): Calculating energy-related CO2 emissions embodied in international trade using a global input-output model. Economic Systems Research, Vol. 24, doi:10.1080/09535314.2011.643293
• Wiebe, K.S., Bruckner, M., Giljum, S., Lutz, C. & Polzin, C. (2012): Carbon and Materials Embodied in the International Trade of Emerging Economies: A Multiregional Input-Output Assessment of Trends Between 1995 and 2005. Journal of Industrial Ecology (forthcoming).
• Wiebe, K.S. (2012): Methodische Aspekte des Global Ressource Accounting Modells (GRAM). In: IWH [Hrsg.]: Neuere Anwendungsfelder der Input-Output-Analyse, Tagungsband. Beiträge zum Halleschen Input-Output-Workshop 2010, Halle, S. 181-193.
• Bruckner, M., Giljum, S., Khoroshun, O., Lutz, C. & Wiebe, K. S. (2009): Die Klimabilanz des österreichischen Außenhandels (Endbericht). Sustainable Europe Research Institute (SERI), Vienna.