Brief: Environmental Footprinting With Multiregional Input-output Models

This brief outlines how Swedish national statistics will be linked with a global model of material flows and related environmental pressures to create the core of PRINCE’s comprehensive consumption-based national accounting system.

To monitor the extra-territorial environmental pressures linked to a country’s consumption of goods and services requires three types of information: 1) how much of different imported goods and services are consumed in the national economy; 2) where they came from; and 3) the environmental pressures associated with their production.

While many countries attempt to do this for at least some environmental pressures (typically greenhouse gas emissions) the systems they use rarely produce accounts that are reliable and detailed enough to base policy on. For example, the systems typically do not account for the different production methods and regulations, or the sensitivity of local ecosystems, in the producer countries. Or they cover only one or two environmental pressures. Or they ignore the reality of complex global supply chains, which means that the varied environmental pressures associated with producing parts, materials, chemicals and other inputs used in final production, often in different countries, are not included in the accounts.

As described in this brief, the accounting framework being developed in PRINCE combines the accuracy and detail of Sweden’s national environmental and economic accounts with the complex supply chain modeling of a “multi-regional input-output” model. The project will also produce a wide range of “environmental extensions” to the model – helping to quantify and locate the diverse environmental pressures associated with Swedish consumption, and so produce indicators.

This brief is an output of PRINCE Work Package 1. It is written by work package leader Elena Dawkins of Stockholm Environment Institute, with PRINCE communications lead Caspar Trimmer.

Brief: Environmental Footprinting With Multiregional Input-output Models



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