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The impacts of data deviations between MRIO models on material footprints: A comparison of EXIOBASE, Eora, and ICIO

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  • Stefan Giljum
  • Hanspeter Wieland
  • Stephan Lutter
  • Nina Eisenmenger
  • Heinz Schandl
  • Anne Owen

Abstract

In various international policy processes such as the UN Sustainable Development Goals, an urgent demand for robust consumption‐based indicators of material flows, or material footprints (MFs), has emerged over the past years. Yet, MFs for national economies diverge when calculated with different Global Multiregional Input–Output (GMRIO) databases, constituting a significant barrier to a broad policy uptake of these indicators. The objective of this paper is to quantify the impact of data deviations between GMRIO databases on the resulting MF. We use two methods, structural decomposition analysis and structural production layer decomposition, and apply them for a pairwise assessment of three GMRIO databases, EXIOBASE, Eora, and the OECD Inter‐Country Input–Output (ICIO) database, using an identical set of material extensions. Although all three GMRIO databases accord for the directionality of footprint results, that is, whether a countries’ final demand depends on net imports of raw materials from abroad or is a net exporter, they sometimes show significant differences in level and composition of material flows. Decomposing the effects from the Leontief matrices (economic structures), we observe that a few sectors at the very first stages of the supply chain, that is, raw material extraction and basic processing, explain 60% of the total deviations stemming from the technology matrices. We conclude that further development of methods to align results from GMRIOs, in particular for material‐intensive sectors and supply chains, should be an important research priority. This will be vital to strengthen the uptake of demand‐based material flow indicators in the resource policy context.

Suggested Citation

  • Stefan Giljum & Hanspeter Wieland & Stephan Lutter & Nina Eisenmenger & Heinz Schandl & Anne Owen, 2019. "The impacts of data deviations between MRIO models on material footprints: A comparison of EXIOBASE, Eora, and ICIO," Journal of Industrial Ecology, Yale University, vol. 23(4), pages 946-958, August.
    • Handle: RePEc:bla:inecol:v:23:y:2019:i:4:p:946-958
    DOI: 10.1111/jiec.12833
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    1. Joseph S Shapiro, 2021. "The Environmental Bias of Trade Policy," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(2), pages 831-886.
    2. Bruckner, Martin & Wood, Richard & Moran, Daniel & Kuschnig, Nikolas & Wieland, Hanspeter & Maus, Victor & Börner, Jan, 2019. "FABIO - The Construction of the Food and Agriculture Biomass Input-Output Model," Ecological Economic Papers 27, WU Vienna University of Economics and Business.
    3. Gino Sturla & Lorenzo Ciulla & Benedetto Rocchi, 2022. "Italy's Volumetric, Scarce and Social-scarce water footprint: a Hydro Economic Input-Output Analysis," Working Papers - Economics wp2022_17.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    4. abid, Nabila & Ceci, Federica & Razzaq, Asif, 2023. "Inclusivity of information and communication technology in ecological governance for sustainable resources management in G10 countries," Resources Policy, Elsevier, vol. 81(C).
    5. Dorninger, Christian & Hornborg, Alf & Abson, David J. & von Wehrden, Henrik & Schaffartzik, Anke & Giljum, Stefan & Engler, John-Oliver & Feller, Robert L. & Hubacek, Klaus & Wieland, Hanspeter, 2021. "Global patterns of ecologically unequal exchange: Implications for sustainability in the 21st century," Ecological Economics, Elsevier, vol. 179(C).
    6. Piñero, Pablo & Pérez-Neira, David & Infante-Amate, Juan & Chas-Amil, María L. & Doldán-García, Xoán R., 2020. "Unequal raw material exchange between and within countries: Galicia (NW Spain) as a core-periphery economy," Ecological Economics, Elsevier, vol. 172(C).
    7. Albert Kwame Osei-Owusu & Michael Danquah & Edgar Towa, 2022. "Unravelling Africa's raw material footprints and their drivers," WIDER Working Paper Series wp-2022-115, World Institute for Development Economic Research (UNU-WIDER).
    8. Xiaobo Xue Romeiko & Zhijian Guo & Yulei Pang & Eun Kyung Lee & Xuesong Zhang, 2020. "Comparing Machine Learning Approaches for Predicting Spatially Explicit Life Cycle Global Warming and Eutrophication Impacts from Corn Production," Sustainability, MDPI, vol. 12(4), pages 1-19, February.
    9. Popescu, Ioana-Stefania & Gibon, Thomas & Hitaj, Claudia & Rubin, Mirco & Benetto, Enrico, 2023. "Are SRI funds financing carbon emissions? An input-output life cycle assessment of investment funds," Ecological Economics, Elsevier, vol. 212(C).
    10. Matthias Pfaff & Rainer Walz, 2021. "Analysis of the development and structural drivers of raw‐material use in Germany," Journal of Industrial Ecology, Yale University, vol. 25(4), pages 1063-1075, August.
    11. Onat, Nuri Cihat & Kucukvar, Murat & Aboushaqrah, Nour N.M. & Jabbar, Rateb, 2019. "How sustainable is electric mobility? A comprehensive sustainability assessment approach for the case of Qatar," Applied Energy, Elsevier, vol. 250(C), pages 461-477.
    12. Wang, Xin & Yang, Jianxun & Zhou, Qi & Liu, Miaomiao & Bi, Jun, 2022. "Mapping the exchange between embodied economic benefits and CO2 emissions among Belt and Road Initiative countries," Applied Energy, Elsevier, vol. 307(C).
    13. Bilgili, Faik & Soykan, Erkan & Dumrul, Cüneyt & Awan, Ashar & Önderol, Seyit & Khan, Kamran, 2023. "Disaggregating the impact of natural resource rents on environmental sustainability in the MENA region: A quantile regression analysis," Resources Policy, Elsevier, vol. 85(PA).

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