Biodiversity impacts and nested trade models

Usually MRIO models are either global or subnational, with global models containing international trade relations between nations and subnational models containing trade between regions within a country. However neither of these models detail the relationships between local centers of production and global consumption. Specifying these relations requires a “nested” model, where the subnational models is nested with a global model.

Recently we constructed a nested MRIO model, featuring extensive subnational and global trade detail, and information on imports and exports between subnational Australian regions and global regions. Our aim was to show how a nested MRIO model offers a more accurate quantification of localized impacts than use of global-only models. To this end, we traced Australian beef along international trade routes, destined for consumption in the USA.

We linked the nested MRIO model with data on biodiversity threats from the International Union for Conservation of Nature (IUCN) Red List of Threatened Species, specifically “Animalia” kingdom that are listed as “Critically Endangered”, “Endangered”, and “Vulnerable”, and that are threatened by livestock farming (by both smallholders and agro-industry) in all Australian regions. We highlight the distribution of threats obtained from the nested MRIO model to show the power of this nesting technique in capturing localized impacts, specifically in the Northern regions of Australia, which export beef to the USA.

For more detail see: https://pubs.acs.org/doi/10.1021/acs.est.1c08804

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Distribution of biodiversity threats in Australia, driven by beef consumption in the USA: based on the global model.

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Distribution of biodiversity threats in Australia, driven by beef consumption in the USA: based on a nested model

UN Comtrade and MRIO integration

I recently worked on a pipeline to pre-process the UN Comtrade dataset before it is incorporated into the GLORIA MRIO. GLORIA (Global Resource Input-Output Assessment) is a multi-regional input-output (MRIO) database that was built by the University of Sydney using the IELab infrastructure for the UN International Resource Panel (UN IRP). GLORIA has 164 regions, 120 sectors per region, forms a continuous time series for 1990-2020 and is one of the largest and most up-to-date published MRIO databases (at the time of writing).

While the Comtrade¹ is an excellent source of bilateral trade data, there are issues with this dataset that must be resolved before the data can be incorporated into a MRIO framework. These issues include:

• Comtrade contains 2 perspectives on the same trade, representing both the importer and exporter’s reports. However the values of these data points do not always agree, and in some cases one is zero and the other is not.
• UN SNA MA trade data provides an additional trade dataset, and is taken to be the point-of-truth. SNA MA details total imports and exports by country, however these totals do not agree with the combined totals from the Comtrade and Services trade databases. UN SN MA sets total import and exports by country but not bilateral trading pairs.
• Trade in certain commodities contains gaps (zero entries) in the timeseries, where such a gap is unlikely to occur in reality.

The raw UN Comtrade and Services trade data are unpacked into a sparse tensor H, with elements h_iv^rst, and where r and s are the origin and destination countries respectively. t indexes the year dimension. Commodities and services categories are indexed by i, using the custom classification HSCPC (containing > 6,357 distinct categories). HSCPC is the union of the HS (commodities) and CPC (services) classification systems. The index v denotes valuation, where imports (v = 1) are valued as CIF (purchaser’s prices) and exports (v = 2) are valued as FOB (producer or basic prices).

A reconciliation algorithm is then implemented to resolve the errors and inconsistencies in the Comtrade database. A RAS procedure involving a series of scaling operations is used; the sparse tensor data structure makes this scaling relatively easy to implement. Smoothing is also implemented to fill zero entries.

¹ The term ‘Comtrade’ is used lazily here to refer to both the UN’s Comtrade and Services trade databases.

Australian multi-regional input-output tables by IELab

IELab is a cloud pipeline for constructing multi-regional IO models. Recently a collection of these MRIO tables for Australia were made available for the community to use. The model resolution is 8 sub-regions (Australian states and territories) at 25 sectors, and cover the timeseries 2009-2018. For each year, the model contains margin layers: Basic prices, Trade margin, Transport margin, Taxes margin, Subsidies. The model is available from the IELab site: https://ielab.info/resources/117, and is also mirrored here: https://github.com/spottedquoll/aus_ielab_mrio. Use of this model is governed by a creative commons attribution non-commercial license.