A classification framework for carbon tax revenue use

ABSTRACT

Carbon pricing could assist in the dual pursuit of mitigating global climate change and contributing to government coffers. The way in which a government allocates carbon tax revenues is a key factor in the public’s acceptance of carbon pricing policy and ultimately in its enduring success. To that end, this article presents an innovative, simple classification framework of carbon tax revenue usage which has four modalities to cater for various policy design features. These are: a constrained approach as opposed to an unconstrained one; a revenue-neutral recycling approach as opposed to a revenue-raising one; an approach according to public preference; and a thematic approach. Thereafter, various attributes are examined to assist policymakers in selecting an appropriate modality. The classification framework will be useful for policymakers as a quick point of reference before embarking on more complex and in-depth policy deliberations.

Key policy insights

• Carbon pricing is the most cost-effective regulatory approach for reducing greenhouse gas emissions and is recognized as a significant contributor to government revenue.

• Carbon tax revenue use can be classified into four overarching modalities to cater for various policy design attributes.

• There is no dominating revenue use option from an economic or political viewpoint, owing to trade-offs across various fiscal policy objectives.

• Carbon taxes are elements of broader tax reform and therefore revenue use options should be aligned with a jurisdiction’s broader fiscal policy charter.

KEYWORDS:

• carbon tax
• revenue use
• revenue recycling
• carbon pricing
• earmarking
• willingness-to-pay

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Consequently, the purpose of this article is neither to evaluate the success of carbon taxes, nor to propose optimal tax rates. In this regard, see Haites et al. (2018), where the authors assess the performance of carbon taxes and emissions trading systems for environmental effectiveness (by assessing the reduction of actual emissions), cost effectiveness (through marginal abatement cost), economic efficiency, public finance, and administrative issues.

2 Also, in order to establish a baseline from which to conduct comparative analyses in the pre- and post-COVID-19 pandemic periods, the scope of this article is restricted to carbon taxes which were in effect as of the end of 2019. Similarly, the literature review is limited to studies conducted in the pre-COVID-19 era.

3 It is apposite at this stage to point out a seeming contradiction in the use of the term ‘hypothecation’. The OECD equates earmarking with hypothecation, therefore considering this action as an interchangeable form of legal prescription (Marten & Van Dender, 2019). Conversely, the World Bank views hypothecation in the same light as political commitments, and not as earmarking. This is due to their definition of ‘hypothecation’ as meaning ‘[w]here revenue is linked to expenditure through communication rather than enforcing legal structure such as legislation’ (PMR, 2019, p. 2). A cursory literature review reveals that other studies appear to follow the OECD interpretation. For example, Bowen (2015) describes hypothecation as strict earmarking, without explicitly stating whether this refers to legal or policy commitments. In the same vein, Carattini et al. (2018) regard earmarking and hypothecation as being one and the same. Bachus et al. (2019) also view earmarking and hypothecation in the same light. Consequently, for the purposes of this article, hypothecation and earmarking will be used interchangeably.

4 As pointed out earlier, an examination of the pros and cons and subsequent analysis of the trade-offs for different types of carbon tax revenue use is considered beyond the scope of this synthesis article. A thorough evaluation of the effectiveness of each revenue use option is undoubtedly required and could be the subject matter of future research.