Local air pollution and global climate change taxes: a distributional analysis for the case of Spain

Global climate change measures are difficult to implement. In this context, local air pollution measures may play an important role in the political agenda since their effects are felt more immediately by citizens. Distributional implications are one of the main barriers for implementing environment...

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Bibliographic Details
Published in:Journal of environmental planning and management 2017-03, Vol.60 (3), p.419-436
Main Authors: García-Muros, Xaquin, Burguillo, Mercedes, González-Eguino, Mikel, Romero-Jordán, Desiderio
Format: Article
Language:English
Subjects:
Air pollution
Air pollution measurements
Baskets
Carbon dioxide
Citizens
Climate change
cocal air pollution taxes
Constraints
distributional impact
Economic models
Efficiency
Environmental policy
environmental tax reform
global climate change taxes
Low income groups
Neutrality
Pollutants
Pollution
Pollution taxes
Recycling
Regression analysis
Revenue
Revenues
Support groups
Taxation
Taxes
taxes regressivity
Weight
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Summary:Global climate change measures are difficult to implement. In this context, local air pollution measures may play an important role in the political agenda since their effects are felt more immediately by citizens. Distributional implications are one of the main barriers for implementing environmental policies. This paper explores the distributional implications of air pollution taxes and compares them to climate change taxes. For the comparison, both tax schemes were set to yield the same revenue. Methodologically, the study uses a top-down approach linking a macro model to a micro model. We find that taxes on local air pollutants are more regressive than those levied on CO 2 . This is because the goods implicitly taxed have a greater weight in the consumer basket of low-income groups, even if the tax revenues are recycled. Furthermore, the revenue-neutral recycle scheme increases both taxes efficiency, but, at the same time, can increase regressivity.
ISSN:0964-0568
1360-0559
DOI:10.1080/09640568.2016.1159951