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Relaxing the import proportionality assumption in multi-regional input-output modelling.

Simon Schulte1, Arthur Jakobs1, Stefan Pauliuk1

  • 1Industrial Ecology, University of Freiburg, Tennenbacher Str. 4, 79110 Freiburg, Germany.

Journal of Economic Structures
|November 1, 2021
PubMed
Summary

The import proportionality assumption in multi-regional input-output (MRIO) tables introduces uncertainty in environmental footprint calculations. This study quantifies this uncertainty, finding it generally low nationally but significant at the industry level for carbon, land, material, and water footprints.

Keywords:
Carbon footprintEnvironmentally-extended multi-regional input–outputFootprint analysisImport proportionality assumptionLand footprintMaterial footprintUncertaintyWater footprint

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Area of Science:

  • Environmental science
  • Economics
  • Sustainable development

Background:

  • Most multi-regional input-output (MRIO) tables rely on the import proportionality assumption due to a lack of destination industry data for international trade.
  • This assumption distributes imported commodities proportionally across all sectors within an importing region.

Purpose of the Study:

  • To quantify the uncertainty introduced by the import proportionality assumption in environmental footprint assessments using the EXIOBASE MRIO database.
  • To evaluate the impact of this assumption on national and industry-level environmental footprints (carbon, material, water, land).

Main Methods:

  • Randomization of global import flows using a block-wise assignment algorithm to target sectors.
  • Maintenance of trade balance throughout the randomization process.
  • Calculation of variability using coefficient of variation (CV) for environmental footprints.

Main Results:

  • National environmental footprints exhibit low variability (CV < 4%) under the assumption, except for material, water, and land footprints in small, trade-dependent economies.
  • Industry-level footprints show higher variability: 25% exceed CVs of 10% (carbon) and 30% (land, material, water).
  • Maximum CVs reached up to 394% at the industry level, highlighting significant uncertainty.

Conclusions:

  • The import proportionality assumption can lead to substantial uncertainty in industry-specific environmental footprint calculations.
  • Researchers using MRIO data should assess this uncertainty for critical industries/regions and consider improving bilateral trade data.
  • Findings guide database improvements and inform uncertainty reporting in environmental footprint analyses.