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Ecological Economics
Article . 2017 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
SSRN Electronic Journal
Article . 2015 . Peer-reviewed
Data sources: Crossref
EconStor
Research . 2015
Data sources: EconStor
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A structural decomposition of global Raw Material Consumption

Authors: Pothen, Frank;

A structural decomposition of global Raw Material Consumption

Abstract

Between 1995 and 2008, the global extraction of biomass, fossil fuels, and minerals grew from 48 to 69 billion metric tons. This study investigates how changing consumption and investment patterns affected the aforementioned increase. A series of Structural Decomposition Analyses at a global level as well as for 38 major economies is conducted. The analyses disentangle the drivers of Raw Material Consumption, which measures the extraction of materials necessary to produce a country’s final demand. Data is taken from the World Input-Output Database. The results suggest that rising final demand is the predominant driver of growing Raw Material Consumption. Furthermore, final demand shifted into countries that consume material intensive goods. This shift was particularly pronounced for construction minerals and investment, indicating that infrastructure investment in industrialising nations was a key driver. The mix of goods in final demand slightly dematerialised. Falling material intensities in extractive industries as well as changes in production and trade patterns decelerated the growth of Raw Material Consumption. The country-level Structural Decomposition Analyses obtained qualitatively similar results.

Country
Germany
Keywords

330, ddc:330, Raw Material Consumption, Input-Output Models, Q3, Q2, Structural Decomposition Analysis, Raw Material Consumption,Structural Decomposition Analysis,Input-Output Models, C67, jel: jel:C67, jel: jel:Q2, jel: jel:Q3

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    29
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
29
Top 10%
Top 10%
Top 10%
Green
bronze