Using Input-Output Analysis to Identify the Effects of Globalised Trade on the Environment

Using Input-Output Analysis to Identify the Effects of Globalised Trade on the Environment

Fri, 26/10/2012 - 09:00

About the Presenter

Dr Arne Geschke

Arne Geschke is a post-doctoral researcher at the Integrated Sustainability Analysis (ISA) group at the University of Sydney.

Born in Hamburg, Germany, in 1980, he grew up in Hamburg and studied Industrial Mathematics at the University of Hamburg, the University of Technology in Hamburg and he also studied at the University of Bath in the UK.

Following his degree, he worked for General Motors in the research department developing models for mathematical engine simulations. He moved to Australia and joined the ISA group in 2008. From July 2009 until July 2012 he was a PhD student supervised by Professor Manfred Lenzen and was part of the team that developed the Eora model.

He was appointed a post-doctoral researcher at ISA in August 2012.


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Input-Output (IO) models track cash flows on a macroeconomic scale. Extending IO models by physical indicators (so-called satellite accounts) such as mega litres of water, tonnes of CO2 or hectares of land allows for a quantitative analysis (or footprint-calculation) of the environmental resources that are required to produce certain goods.

While previously IO-models were produced for individual countries only, larger models that include several countries or regions (so-called Multi-Regional Input-Output (MRIO) models) are now in high demand. These MRIO models are – for example - used to analyse supply-chains and to identify the resource needs that may be driven by a demand on the other side of the world. The construction of large-scale, highly-detailed MRIOs is not straight-forward and requires the handling of large amounts of data, the application of sophisticated mathematical optimisation routines, and the use of high-performance computing facilities. We have developed the largest and most detailed global MRIO available up to date (the "Eora model").

The Eora model was used to identify how international trade drives biodiversity threats in developing nations. We integrated the IUCN Red List of Threatened Species and data from Bird Life International into the satellite accounts structure of the Eora database. Following the analysis of over 5 billion supply chains we concluded that about 30% of species threats are driven by international trade. The majority of these species threats occur in developing nations and are caused by the demand of developed nations for commodities such as coffee, tea, sugar and textiles. The results of this study were published in Nature.

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