EXIOBASE 3: Developing a Time Series of Detailed Environmentally Extended Multi‐Regional Input‐Output Tables

Environmentally extended multiregional input-output (EE MRIO) tables have emerged as a key framework to provide a comprehensive description of the global economy and analyze its effects on the environment. Of the available EE MRIO databases, EXIOBASE stands out as a database compatible with the System of Environmental-Economic Accounting (SEEA) with a high sectorial detail matched with multiple social and environmental satellite accounts. In this paper, we present the latest developments realized with EXIOBASE 3-a time series of EE MRIO tables ranging from 1995 to 2011 for 44 countries (28 EU member plus 16 major economies) and five rest of the world regions. EXIOBASE 3 builds upon the previous versions of EXIOBASE by using rectangular supply-use tables (SUTs) in a 163 industry by 200 products classification as the main building locks. In order to capture structural changes, economic developments, as reported by national statistical agencies, were imposed on the available, disaggregated SUTs from EXIOBASE 2. These initial estimates were further refined by incorporating detailed data on energy, agricultural production, resource extraction, and bilateral trade. EXIOBASE 3 inherits the high level of environmental stressor detail from its precursor, with further improvement in the level of detail for resource xtraction. To account for the expansion of the European Union (EU), EXIOBASE 3 was developed with the full EU28 country set (including the new member state Croatia). EXIOBASE 3 provides a unique tool for analyzing the dynamics of environmental pressures of economic activities over time.

[1]  Arnold Tukker,et al.  Identifying priority areas for European resource policies: a MRIO-based material footprint assessment , 2016 .

[2]  Richard Wood,et al.  Labor Embodied in Trade , 2015 .

[3]  Arnold Tukker,et al.  Global Sustainability Accounting—Developing EXIOBASE for Multi-Regional Footprint Analysis , 2014 .

[4]  S. Pfister,et al.  Monthly water stress: spatially and temporally explicit consumptive water footprint of global crop production , 2014 .

[5]  Richard Wood,et al.  CONSTRUCTION, STABILITY AND PREDICTABILITY OF AN INPUT–OUTPUT TIME-SERIES FOR AUSTRALIA , 2011 .

[6]  G. Gaulier,et al.  BACI: International Trade Database at the Product-Level (the 1994-2007 Version) , 2009 .

[7]  Maria Paola Mariani,et al.  OECD (Organization for economic co-operation and development) , 2006 .

[8]  Harry C. Wilting,et al.  A METHOD TO CREATE CARBON FOOTPRINT ESTIMATES CONSISTENT WITH NATIONAL ACCOUNTS† , 2015 .

[9]  Anne Owen,et al.  COMPARATIVE EVALUATION OF MRIO DATABASES , 2014 .

[10]  Helmut Haberl,et al.  Global human appropriation of net primary production doubled in the 20th century , 2013, Proceedings of the National Academy of Sciences.

[11]  Richard Wood,et al.  Effect of aggregation and disaggregation on embodied material use of products in input–output analysis , 2015 .

[12]  Steven J Davis,et al.  The supply chain of CO2 emissions , 2011, Proceedings of the National Academy of Sciences.

[13]  Bart Los,et al.  THE CONSTRUCTION OF WORLD INPUT–OUTPUT TABLES IN THE WIOD PROJECT , 2013 .

[14]  Richard Wood,et al.  The Environmental Footprints Explorer - a database for global sustainable accounting , 2015, EnviroInfo/ICT4S.

[15]  Arnold Tukker,et al.  EXIOPOL – DEVELOPMENT AND ILLUSTRATIVE ANALYSES OF A DETAILED GLOBAL MR EE SUT/IOT , 2013 .

[16]  Marc Mueller,et al.  Construction of Social Accounting Matrices for the EU-27 with a Disaggregated Agricultural Sector (AgroSAM) , 2009 .

[17]  Stephan Moll,et al.  Towards a global multi-regional environmentally extended input-output database , 2009 .

[18]  Sherman Robinson,et al.  Updating and Estimating a Social Accounting Matrix Using Cross Entropy Methods , 2001 .

[19]  Martina Flörke,et al.  Domestic and industrial water uses of the past 60 years as a mirror of socio-economic development: A global simulation study , 2013 .

[20]  Laan van Westenenk,et al.  ASSESSMENT OF GLOBAL EMISSIONS FROM FUEL COMBUSTION IN THE FINAL DECADES OF THE 20 TH CENTURY , 2007 .

[21]  Richard Wood,et al.  Towards Robust, Authoritative Assessments of Environmental Impacts Embodied in Trade: Current State and Recommendations , 2018 .

[22]  Kirsten S. Wiebe,et al.  Estimating CO2 Emissions Embodied in Final Demand and Trade Using the OECD ICIO 2015: Methodology and Results , 2016 .

[23]  T. Nemecek,et al.  Overview and methodology: Data quality guideline for the ecoinvent database version 3 , 2013 .

[24]  N. Ramankutty,et al.  Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000 , 2008 .

[25]  Richard Wood,et al.  THE ‘REST OF THE WORLD’ – ESTIMATING THE ECONOMIC STRUCTURE OF MISSING REGIONS IN GLOBAL MULTI-REGIONAL INPUT–OUTPUT TABLES , 2014 .

[26]  M. Hansen,et al.  The last frontiers of wilderness: Tracking loss of intact forest landscapes from 2000 to 2013 , 2017, Science Advances.

[27]  A. Barbosa‐Póvoa Supply chain , 2015, 2015 International Conference on Industrial Engineering and Systems Management (IESM).

[28]  Konstantin Stadler,et al.  Pymrio - a Python module for automating input output calculations and generating reports , 2015, EnviroInfo/ICT4S.

[29]  C. Kroeze N2O from animal waste. Methodology according to IPCC Guidelines for National Greenhouse Gas Inventories. , 1997 .

[30]  P. Canning,et al.  A Flexible Mathematical Programming Model to Estimate Interregional Input-Output Accounts , 2005 .

[31]  G. Psacharopoulos Overview and methodology , 1991 .

[32]  Zhang Yaxiong,et al.  Compilation, application and challenge of IDE-JETRO's International Input-Output tables , 2012 .

[33]  Glen P. Peters,et al.  CONSTRUCTING AN ENVIRONMENTALLY-EXTENDED MULTI-REGIONAL INPUT–OUTPUT TABLE USING THE GTAP DATABASE , 2011 .

[34]  Kirsten S. Wiebe,et al.  CALCULATING ENERGY-RELATED CO2 EMISSIONS EMBODIED IN INTERNATIONAL TRADE USING A GLOBAL INPUT–OUTPUT MODEL , 2012 .

[35]  Helmut Schütz,et al.  CREEA Report and data Task 4.2: P-SUT , 2014 .

[36]  S. Pfister,et al.  Environmental impacts of water use in global crop production: hotspots and trade-offs with land use. , 2011, Environmental science & technology.

[37]  J. Olsen,et al.  The European Commission , 2020, The European Union.

[38]  W. I. Morrison,et al.  A LAGRANGIAN MULTIPLIER APPROACH TO THE SOLUTION OF A SPECIAL CONSTRAINED MATRIX PROBLEM , 1980 .

[39]  Edgar G. Hertwich,et al.  Mapping the carbon footprint of EU regions , 2017 .

[40]  Helmut Haberl,et al.  A comprehensive global 5 min resolution land-use data set for the year 2000 consistent with national census data , 2007 .

[41]  ISCO-88 International Standard Classification of Occupations , 2005 .

[42]  Arnold Tukker,et al.  Environmental and resource footprints in a global context: Europe’s structural deficit in resource endowments , 2016 .

[43]  Richard Wood,et al.  Prioritizing Consumption‐Based Carbon Policy Based on the Evaluation of Mitigation Potential Using Input‐Output Methods , 2018 .

[44]  Manfred Lenzen,et al.  EFFECTS OF SECTOR AGGREGATION ON CO2 MULTIPLIERS IN MULTIREGIONAL INPUT–OUTPUT ANALYSES , 2014 .

[45]  Arjen Ysbert Hoekstra,et al.  National water footprint accounts: the green, blue and grey water footprint of production and consumption , 2011 .

[46]  Robert McDougall,et al.  Global trade, assistance, and production : The GTAP 5 Data Base , 2002 .

[47]  Richard Wood,et al.  Resource footprints and their ecosystem consequences , 2017, Scientific Reports.

[48]  Arnold Tukker,et al.  A network approach for assembling and linking input–output models , 2016 .

[49]  Markus Amann,et al.  Integrated assessment tools. The Greenhouse and Air Pollution Interactions and Synergies (GAINS) model , 2009 .

[50]  Employment Sector,et al.  Guide to the new Millennium Development Goals Employment indicators : including the full decent work indicator set , 2009 .

[51]  Edgar G. Hertwich,et al.  The “Bad Labor” Footprint: Quantifying the Social Impacts of Globalization , 2014 .

[52]  E. Hertwich,et al.  Environmental Impact Assessment of Household Consumption , 2016 .

[53]  G. Etiope EMEP/EEA air pollutant emission inventory guidebook 2009 , 2009 .

[54]  Steffen Fritz,et al.  Development of a global hybrid forest mask through the synergy of remote sensing, crowdsourcing and FAO statistics , 2015 .

[55]  Edgar G. Hertwich,et al.  HARMONISING NATIONAL INPUT—OUTPUT TABLES FOR CONSUMPTION-BASED ACCOUNTING — EXPERIENCES FROM EXIOPOL , 2014 .

[56]  Manfred Lenzen,et al.  The Global MRIO Lab – charting the world economy , 2017 .

[57]  Arkaitz Usubiaga,et al.  CARBON EMISSION ACCOUNTING IN MRIO MODELS: THE TERRITORY VS. THE RESIDENCE PRINCIPLE , 2015 .

[58]  Kendall R. Jones,et al.  Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation , 2016, Nature Communications.

[59]  Arnold Tukker,et al.  GLOBAL MULTIREGIONAL INPUT–OUTPUT FRAMEWORKS: AN INTRODUCTION AND OUTLOOK , 2013 .

[60]  T. Hertel,et al.  Matrix balancing with unknown total costs: preserving economic relationships in the electric power sector , 2016 .

[61]  Jing Meng,et al.  Global overview for energy use of the world economy: Household-consumption-based accounting based on the world input-output database (WIOD) , 2019, Energy Economics.

[62]  R. Goldbohm,et al.  Environmental impacts of changes to healthier diets in Europe , 2011 .

[63]  Arnold Tukker,et al.  Growth in Environmental Footprints and Environmental Impacts Embodied in Trade: Resource Efficiency Indicators from EXIOBASE3 , 2018 .

[64]  Reinout Heijungs,et al.  Recommendation of terminology, classification, framework of waste accounts and MFA, and data collection guideline , 2014 .

[65]  Manfred Lenzen,et al.  Mapping the structure of the world economy. , 2012, Environmental science & technology.

[66]  J. Townshend,et al.  Annual Global Automated MODIS Vegetation Continuous Fields (MOD44B) at 250 m Spatial Resolution for Data Years Beginning Day 65, 2000 - 2010 , 2017 .