To achieve the 2030 and 2050 climate goals, EU household Green House Gas (GHG) footprints will have to be substantially reduced. The Green EUROMOD project, kicked off in 2020, was developed to feed the Indirect Tax Tool of EUROMOD with information on household GHG footprints.
We combined information on pollution intensities from EXIOBASE with consumption information from Household Budget Surveys (HBS) and income and other socioeconomic characteristics from the European Statistics on Income and Living Conditions (EU-SILC). This extremely rich and harmonized micro datasets are combined with the Indirect Tax Tool, and this places us in an advantageous position to conduct carbon tax microsimulations considering the current tax-benefit systems (direct and indirect) in the EU 27 countries.
The pollution intensities from EXIOBASE differentiate:
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direct emissions (e.g., emissions associated with the combustion of fuels by households for heating/driving);
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Indirect emissions (e.g., emissions embedded in the production of goods and services consumed by households, through all the value chain). These distinguishes in turn where they were emitted (locally, in the rest of the EU or in the rest of the world, through international trade for the case of imported goods).
Therefore, we can simulate hypothetical reforms with different rates across products, direct/indirect emissions and place of origin within indirect GHG depending on the policy question.
The first phase of the project concluded in Summer of 2023, and has mainly focused on Green House Gas emissions. We plan to extend the coverage to several other pollutants.
There are two ongoing research lines that will summarize the main lessons from the first phase:
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Carbon taxes in the EU: Challenging the green and fair trade-offs of consumption taxation in the EU27.
Contributors: Antonio F. Amores, Gabriele Bertuzzi, Silvia De Poli, Sofia Maier.
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Data dissemination report: Imputing pollution intensities from EXIOBASE to HBS-SILC matched data.
Contributors: Antonio F. Amores, Gabriele Bertuzzi, Silvia De Poli, Ilda Dreoni, Sofia Maier, Richard Wood.
Links:
Team:
Gabriele Bertuzzi
Silvia de Poli
