Policy effectiveness and acceptance in the taxation of environmentally damaging chemical compounds

Autor: Patrik Söderholm, Anna Christiernsson
Rok vydání: 2008
Předmět:
Zdroj: Environmental Science & Policy. 11:240-252
ISSN: 1462-9011
Popis: Taxes on chemical compounds still constitute a fairly small share of the total environmental tax base in Europe, but proposals for new chemical tax schemes have become common. The overall purposes of this paper are to analyze: (a) the economics and politics of taxing chemical compounds; and (b) the future potential for increased implementation of such taxation policies in Europe. While much of the discussion is general in scope, the empirical part focuses on the case of fertilizer taxation in Austria, Denmark, the Netherlands, Norway and Sweden. There exists an inevitable trade-off between costly monitoring on the one hand and the achievement of a cost-effective allocation of nitrate leaching abatement measures on the other. This is true for many types of chemicals and our analysis of the fertilizer case provides a number of general lessons for future implementation of environmental taxes in the chemicals field. The choice of tax scheme design matters not only for the cost effectiveness of the policy, but can also be an important mean of reducing any political opposition towards environmental taxes. The European experience in fertilizer taxation indicates that some kind of earmarking of tax revenues can be effective in increasing the legitimacy of the tax policy, and taxes which achieve a close proportionality to damage done will often be perceived as fair. The latter implies that taxation close to environmental damages and the reduction of the associated transaction costs should be policy priorities. Finally, an important feature of many legal provisions – including the EC Nitrate Directive – is the weight given to goal fulfilment, and although taxes are in no way prohibited they may be abandoned since their impacts on environmental quality (and ultimately on goal fulfilment) can be hard to predict.
Databáze: OpenAIRE