Ecological footprints and sustainable development policy assessment
What and why - ecological footprints?
Ecological footprint (EF) is a measure of sustainability of the patterns of consumption and production. EF quantifies the impact of human activities in terms of the area of biologically productive land and water required to produce the goods consumed and to assimilate the wastes generated.
Biological capacity (BC) is a measure of ecosystems' capacity to produce biological materials used by people and to absorb waste material generated by humans, under current management schemes and extraction technologies.
Both EF and BC are expressed in terms of “global hectare (gha)” which is defined as a biologically productive hectare with world average biological productivity for a given year. This makes it easy to judge whether a certain country (or the world) is on a sustainable path or not. EF > BC means unsustainable.
Contribute to SDG12 on sustainable consumption and production, in particular Target 12.2.
Develop policy impact assessment tool in terms of impacts on ecological footprints as well as economic and welfare impacts.
Ensure sustainable consumption and production patterns
By 2030 achieve sustainable management and efficient use of natural resources
What policy measures will enable us to achieve “one planet living”?
What are the economic and welfare outcomes of such policy measures?
How will one country’s policies towards one planet living affect others?
Policy shocks will be given to a recursive dynamic global computable equilibrium model and policy impacts in terms of economic activities (production patterns, consumption patterns, etc.) will be simulated.
We assume ecological footprints (EF) are associated with factor input (land for agriculture and cattle sectors, natural resources for forestry and fishery), and we estimate EF coefficients per one unit of factor input.
Production-based EF (EFp) will be estimated by multiplying these coefficients by policy simulation results in terms of factor inputs (physical quantity). Finally, consumption-based EF (EFc) will be derived by input-output model.
Measuring policy impacts in terms of planetary boundaries
A prototype of global recursive dynamic CGE model was developed and GTAP version 8 database (base year: 2007) was aggregated to 18-region focusing on ASEAN+6 (the remaining countries are aggregated as US, EU and Rest of the World) and 30-sector focusing on sectors associated with EF (agriculture, cattle, forestry, fishery and carbon intensive sectors).
Policy shock: Fossil fuel tax (in terms of additional ad valorem tax, 60%) on intermediate uses of fossil fuels (coal, crude oil, and natural gas) was introduced for Japan from 2008. In case of crude oil, this tax rate was approximately equivalent to USD 100-150/t-CO2.
Test run was carried out from the base year (2007) to 2010. Policy impacts were estimated by comparing simulation results with policy shock (PLC) and without policy shock (BAU: business-as-usual).
EF in Japan:
Fossil fuel tax (additional 60%) will effectively reduce production-based EF (EFp), but only marginally affect consumption-based EF (EFc).
Policy impact on real GDP:
As expected, fossil fuel tax negatively affects Japan’s real GDP (-1.3%). Some ASEAN countries exporting fossil fuels to Japan (Malaysia, Brunei Darussalam included in other ASEAN, and Vietnam) are also negatively affected.
Policy impacts on EFc in 2010:
Japan’s fossil fuel tax will have significant impacts on consumption-based EF (EFc) outside Japan.