174
3.3 Addressing Uncertainty in MRIO Modelling
Currently the only tool to unravel the intricacies of international supply chains is
MRIO modelling. The remarkable development in MRIO databases (Tukker and
Dietzenbacher 2013 ; Wiedmann et al. 2011 ) has been accompanied by an equally
impressive number of publications studying the impacts of globalisation and trade.
Some studies have begun comparing the results obtained from different models,
fi nding reasonable agreement as well as signifi cant discrepancies for certain indictors (e.g. Peters et al. 2012 for CO 2 emissions and Wiedmann et al. 2015 and Schoer
et al. 2013 for raw materials).
An important observation was made by Peters et al. ( 2012 ) in a pioneering comparative study: differences in consumption-based, embodied CO 2 emissions from
different models were mostly due to the use of different territorial emission data and
different defi nitions for allocating emissions to international trade. When adjusting
for these issues, results were robust and in reasonable agreement. Larger discrepancies occur when different approaches are used for the calculations. Kastner et al.
( 2014b ) fi nd contradictory results for China ’s trade in embodied cropland when
using physical instead of monetary input-output data. And Schoer et al. ( 2013 )
explore the differences of employing life cycle inventory data versus MRIO modelling for raw material equivalents embodied in EU27 imports.
A special issue of Economic Systems Research 2014 (26/3) was devoted to the
question of uncertainty in MRIO analysis (Inomata and Owen 2014 ). Insights
gained included the fi nding that the trade matrix structure (Leontief Inverse) is one
major determinant of differences (Owen et al. 2014 ), likely due to assumptions
made during its construction.
Further work remains to be done to improve the accuracy of MRIO models and
to increase confi dence in their results. This should include an increase in resolution,
the use of specifi c process data in mixed units and hybrid LCA models and regular
inter-comparison studies.
4 Is Trade Good or Bad? Some Final Thoughts
Is trade good or bad for sustainability? To answer this question conclusively would
require comparing the status quo with the counterfactual of a world without trade.
Alas, no one knows what this world would look like. It is easy enough to ‘switch
off’ trade in models and to assume that the fi nal demand is met by domestic production alone. But would fi nal demand be the same? Would countries without trade
consume the same amount of the same products? Most likely not. Many countries
would certainly not be able to produce the products they import. What is clear, from
the facts presented in the introduction, is that trade has been a strong driver of economic growth around the world. Had trade not happened, the GDP of all countries
would very likely be much lower than it is today. Trade has also undoubtedly
T. Wiedmann
3.3 Addressing Uncertainty in MRIO Modelling
Currently the only tool to unravel the intricacies of international supply chains is
MRIO modelling. The remarkable development in MRIO databases (Tukker and
Dietzenbacher 2013 ; Wiedmann et al. 2011 ) has been accompanied by an equally
impressive number of publications studying the impacts of globalisation and trade.
Some studies have begun comparing the results obtained from different models,
fi nding reasonable agreement as well as signifi cant discrepancies for certain indictors (e.g. Peters et al. 2012 for CO 2 emissions and Wiedmann et al. 2015 and Schoer
et al. 2013 for raw materials).
An important observation was made by Peters et al. ( 2012 ) in a pioneering comparative study: differences in consumption-based, embodied CO 2 emissions from
different models were mostly due to the use of different territorial emission data and
different defi nitions for allocating emissions to international trade. When adjusting
for these issues, results were robust and in reasonable agreement. Larger discrepancies occur when different approaches are used for the calculations. Kastner et al.
( 2014b ) fi nd contradictory results for China ’s trade in embodied cropland when
using physical instead of monetary input-output data. And Schoer et al. ( 2013 )
explore the differences of employing life cycle inventory data versus MRIO modelling for raw material equivalents embodied in EU27 imports.
A special issue of Economic Systems Research 2014 (26/3) was devoted to the
question of uncertainty in MRIO analysis (Inomata and Owen 2014 ). Insights
gained included the fi nding that the trade matrix structure (Leontief Inverse) is one
major determinant of differences (Owen et al. 2014 ), likely due to assumptions
made during its construction.
Further work remains to be done to improve the accuracy of MRIO models and
to increase confi dence in their results. This should include an increase in resolution,
the use of specifi c process data in mixed units and hybrid LCA models and regular
inter-comparison studies.
4 Is Trade Good or Bad? Some Final Thoughts
Is trade good or bad for sustainability? To answer this question conclusively would
require comparing the status quo with the counterfactual of a world without trade.
Alas, no one knows what this world would look like. It is easy enough to ‘switch
off’ trade in models and to assume that the fi nal demand is met by domestic production alone. But would fi nal demand be the same? Would countries without trade
consume the same amount of the same products? Most likely not. Many countries
would certainly not be able to produce the products they import. What is clear, from
the facts presented in the introduction, is that trade has been a strong driver of economic growth around the world. Had trade not happened, the GDP of all countries
would very likely be much lower than it is today. Trade has also undoubtedly
T. Wiedmann