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Public Preferences for Carbon Tax Attributes

Author

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  • Z. Eylem Gevrek

    (Department of Economics, University of Konstanz, Germany)

  • Ayse Uyduranoglu

    (Istanbul Bilgi University, Turkey)

Abstract

The impacts of climate change are already visible throughout the world. Recognizing the threats posed by climate change, the Durban Platform, the 17th Session of the Conference of Parties (COP 17), underscores that the global nature of climate change calls for the widest possible cooperation and ambitious action by all countries. A crucial starting point for the design of effective and publicly acceptable policies is to explore public preferences for climate policy instruments. Using a choice experiment, this study investigates public preferences for carbon tax attributes in a developing country context. The results account for heterogeneity in preferences and show that Turkish people prefer a carbon tax with a progressive cost distribution rather than one with a regressive cost distribution. The private cost has a negative effect on the probability of choosing the tax. Earmarking carbon tax revenues increases the public acceptability of the tax. Moreover, there is a preference for a carbon tax that promotes public awareness of climate change.

Suggested Citation

  • Z. Eylem Gevrek & Ayse Uyduranoglu, 2015. "Public Preferences for Carbon Tax Attributes," Working Paper Series of the Department of Economics, University of Konstanz 2015-15, Department of Economics, University of Konstanz.
  • Handle: RePEc:knz:dpteco:1515
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    File URL: http://www.uni-konstanz.de/FuF/wiwi/workingpaperseries/WP_15_Gevrek_2015.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    Carbon taxes; Choice experiment; Latent class model; Mixed logit model; Preferences; Turkey;
    All these keywords.

    JEL classification:

    • H - Public Economics
    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics

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    This paper has been announced in the following NEP Reports:

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