The impacts of data deviations between MRIO models on material footprints: A comparison of EXIOBASE, Eora, and ICIO. (30th January 2019)

• Record Type: Journal Article
• Authors: Giljum, Stefan; Wieland, Hanspeter; Lutter, Stephan; Eisenmenger, Nina; Schandl, Heinz; Owen, Anne
• Is Part Of: Journal of industrial ecology. Volume 23:Number 4(2019:Aug.)
• Page Start: 946
• Page End: 958
• Publication Date: 2019-01-30
• Subjects: material footprint -- multiregional input–output databases -- raw material equivalents -- resource policy -- structural decomposition analysis -- structural production layer decomposition; Industrial ecology -- Periodicals; Product life cycle -- Environmental aspects -- Periodicals; Industrial management -- Environmental aspects -- Periodicals; Écologie industrielle -- Périodiques; 658.56
• DOI: 10.1111/jiec.12833
• Languages: English
• ISSNs: 1088-1980

Abstract

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.