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BIOCLIMAPATHS is an AXIS-ERANET 2019 granted project, that aims to better understand the impacts of climate change in future societies that have adopted bioeconomy as a substantial pillar of their economies. The project’s main aim – and output – is to provide insights and recommendations for climate resilient and just bioeconomy transition paths for society and economy. The BIOCLIMAPATHS (BCP) consortium leverages on complementary expertise of research teams from Austria, Germany and Spain, developing an innovative, spatially explicit, modelling framework for risk assessments of bioeconomy transitions subject to climate extremes. The project’s main aim – and output – is to provide insights on climate resilient and just bioeconomy transition paths in society. A key tool to achieve this aim is the elaboration of a detailed multisectoral database with high disaggregation on bio-based sectors. For the elaboration of this database, called Bio-MRSUT (Bio-economic Multi-regional Supply-Use Tables) framework, we started from EXIOBASE (Stadler et al. 2018). From the EXIOBASE data to obtaining the series of multi-regional SUT monetary marks, some estimation is required. First, by adapting the initial tables from EXIOBASE to the sectoral structure proposed in BIOCLIMAPATHS. Subsequently, to complete the database with additional information on certain bioeconomy sectors (agriculture, livestock, and biofuels), the 2010 and 2015 BioSAMs (Mainar et al., 2021) carried out by the Joint Research Centre (JRC) of the European Commission have been used, building the pertinent extrapolations to complete the proposed time period. The result of these processes has given rise to multi-regional monetary SUT frameworks for the EU and its Member States with a very broad disaggregation of the bioeconomy sectors. These multiregional frameworks comprise, with reference to the year 2015, a total of 78 activities (44 of Bioeconomy) and 78 goods and services (44 of them bio-economics), for the 28 EU countries (including the United Kingdom) and the Rest of the World, (as well as the interrelationships and bilateral exchanges between all these territories). In addition, they contain the breakdown of final demand and added value, as well as taxes on activities and products and imports by origin (the resulting data matrix contains 4,529 rows and 4,669 columns).

The Supply-Use Tables (SUTs) form a central part of the national accounts, providing a framework to bring together a range of data and, through balancing, to ensure the coherency and consistency of various parts of the national accounts. The SUTs thus serve many purposes, in particular, statistical and analytical, not just for producers but also for a range of different users, and their analytical dimension is especially enhanced when the SUTs are transformed into Input-Output Tables (IOTs). For analytical purposes, the assumptions about the relationships between inputs and outputs are required irrespective of whether the products have been produced by the primary industry or by other industries as their secondary output., {"references":["UN Handbook on Supply and Use Tables and Input-Output Tables with Extensions and Applications (2018)","Eurostat Manual of Supply, Use and Input-Output Tables (2008)"]}

The statistical challenges of globalization are profound. We cannot rely solely on national statistics to understand how economies work and how to create industrial policies focusing on competitiveness. It is necessary to see the whole. National statistics build pictures based on relationships between producers and consumers and the rest of the world. But these relationships, especially those with the rest of the world, have become increasingly more complex. There is an increasing need to consider global production within a global accounting framework. This implies a departure from the traditional role of international organizations as compilers of internationally comparable national statistics to bring together the national tables to create a global table.

This paper develops a method to consolidate national supply-use tables (SUTs) into a single supra-regional SUT. The method deals with mirror trade statistics problems, such as the different valuation of imports and exports, and it corrects for the double-counting of re-exports. To test the contribution of the various construction steps, the paper decomposes the EU value added that is embodied in the EU exports to third countries into seven components. When the national SUTs for the period 2000-2007 are used, neglecting intra-EU spillover and feedback effects between the 27 EU-members results in an underestimation of the embodied value added of 12-15%. Not consolidating the national tables leads to a further under-estimation of 11-16%. Both types of errors are substantial. With these underestimations removed, the exports to third countries still only explain around 11% of the EU27 GDP.

This paper develops a method to consolidate national supply-use tables (SUTs) into a single supra-regional SUT. The method deals with mirror trade statistics problems, such as the different valuation of imports and exports, and it corrects for the double-counting of re-exports. To test the contribution of the various construction steps, the paper decomposes the EU value added that is embodied in the EU exports to third countries into seven components. When the national SUTs for the period 2000-2007 are used, neglecting intra-EU spillover and feedback effects between the 27 EU-members results in an underestimation of the embodied value added of 12-15%. Not consolidating the national tables leads to a further under-estimation of 11-16%. Both types of errors are substantial. With these underestimations removed, the exports to third countries still only explain around 11% of the EU27 GDP.

This paper develops a method to consolidate national supply-use tables (SUTs) into a single supra-regional SUT. The method deals with mirror trade statistics problems, such as the different valuation of imports and exports, and it corrects for the double-counting of re-exports. To test the contribution of the various construction steps, the paper decomposes the EU value added that is embodied in the EU exports to third countries into seven components. When the national SUTs for the period 2000-2007 are used, neglecting intra-EU spillover and feedback effects between the 27 EU-members results in an underestimation of the embodied value added of 12-15%. Not consolidating the national tables leads to a further under-estimation of 11-16%. Both types of errors are substantial. With these underestimations removed, the exports to third countries still only explain around 11% of the EU27 GDP.