Carbon tariffs for financing clean development

Abstract

In order to address carbon leakage and preserve the competitiveness of domestic industries, some industrialized Annex I countries have proposed to implement carbon tariffs. These tariffs would be levied on energy-intensive imports from developing non-Annex I countries that have not agreed to binding emissions reductions. This action could have detrimental welfare impacts, especially on those developing countries, and may not lead to significant reductions in leakage. A recent proposal is to use the revenues generated from carbon tariffs to finance clean development in the relevant exporting non-Annex I countries. This proposal is evaluated using an energy-economic model of the global economy. The model is supplemented by marginal abatement cost curves and bottom-up information on abatement potentials in order to represent how clean development financing affects emissions reductions. The results indicate that carbon tariffs could raise US$3.5–24.5 billion (with a central value of $9.8 billion) for clean development financing. This could reduce the emissions of non-Annex I countries by 5–15% and still leave funds available for other purposes, such as adaptation. Furthermore, recycling the revenues generated from carbon tariffs back to the exporting country itself could alleviate some of the negative welfare impacts associated with them. However, a net negative impact especially on the welfare and gross domestic product of developing countries would remain.

Afin de lutter contre les fuites de carbone et de préserver la compétitivité des industries nationales, certains pays industrialisés de l'Annexe I ont proposé des tarifs sur le carbone. Ces tarifs seraient prélevées sur les importations à forte intensité énergétique provenant de ces pays en développement non-inscrits à l'Annexe I n'ayant pas pris d'engagement de réductions contraignantes des émissions. Pourtant, ceci pourrait avoir des impacts néfastes au bien-être social sans pour autant mener à des réductions significatives des fuites. Une proposition récente serait d'utiliser les revenus générés par les tarifs carbone pour financer le développement propre dans les pays exportateurs concernés. Cette proposition est évaluée par un modèle énergie-économie de l’économie mondiale, supplémenté de courbes de CMA et une information de base sur les potentiels d'abattement de manière à représenter l'effet du financement du développement propre sur la réduction des émissions. Les résultats indiquent que les tarifs carbone pourraient rapporter US$3.5–24.5 milliards (avec une valeur centrale de $9.8 milliards) au financement du développement propre. Cela pourrait réduire les émissions des pays non inscrits à l'annexe I de 5 à 15% tout en laissant des fonds disponibles à d'autres fins, telles que l'adaptation. De plus, le fait de recycler les revenus générés par les tarifs carbone de nouveau dans les pays exportateurs eux-mêmes adoucirait certains des impacts négatifs sociaux associés. Il resterait cependant un net impact négatif surtout sur le bien-être et le PIB des pays en développement.

Keywords:

• border adjustments
• carbon leakage
• climate and trade
• climate finance
• development and climate
• global economic model

Mots clés:

• ajustements aux frontières
• fuites de carbone
• climat et commerce
• finance climatique
• développement et climat
• modèle économique mondial

Acknowledgements

I greatly thank Niven Winchester for his advice on modelling, as well as Philippe Quirion and Jan Abrell for their detailed comments on an earlier draft. I also thank Justin Caron, Christoph Bertram, Carolyn Fischer, and Mun Ho for helpful discussions, and Christian von Hirschhausen for his general support. Lastly, I want to acknowledge the constructive comments from four anonymous referees which helped to improve the manuscript considerably. This research project was supported by a doctoral grant from the AXA Research Fund. All remaining errors and opinions are my own.

Notes

For example, Grubb (2011) contains indicative revenue estimates for the major carbon-intensive sectors and a comprehensive discussion. Böhringer et al. (2011) presents aggregate welfare results of revenue recycling and welfare compensation schemes connected to carbon tariffs (they do not, however, consider climate finance). The UN Secretary General's High-Level Advisory Group on Climate Change Financing (UN, 2010) also estimates total potential revenues from a carbon tariff-related ‘carbon exports optimization tax’, which could be levied by non-Annex I countries.

The model is formulated in GAMS/MPSGE code, which can be obtained from the author upon request. A detailed description of the basic framework and its energy extension can be found in Appendix 1, Rutherford (2010a), Rutherford and Paltsev (2000), and Böhringer et al. (2011).

The GTAP consortium states that in order to construct a consistent global data set for a given base year, significant adjustments were made to ensure that national input–output tables matched external macroeconomic, trade, protection, and energy data (Narayanan and Walmsley, 2008, Chapters 7–8). Note that although this ensures overall consistency, it also imposes limits on the accuracy of the data, in particular on the sectoral national details.

Energy-intensive goods include iron and steel, chemicals (including plastics and petrochemical products), non-ferrous metals (including copper and aluminium), and non-metallic minerals (including cement).

Responses to carbon prices include the substitution from coal to gas in electricity production, improving energy efficiency, the use of non-fossil energy, and reducing energy demand. Clean development investments can promote some but not all of these activities (unless the policy is highly prescriptive).

Previous studies, which have aimed at estimating the availability of emissions reductions in developing countries, have scaled back the emissions reduction potential derived from MAC curves in various ways, e.g. by assuming practical abatement costs that are one-tenth of the economy-wide MAC estimate (Jotzo and Michaelowa, 2002; Michaelowa and Jotzo, 2005) or by limiting the implementation of abatement measures via a participation rate of less than one (Kallbekken, 2007).

Adopting constant abatement costs is tantamount to assuming that all CDM credits (CERs) can be supplied at current prices. This assumption is justified for the volume of CERs associated with the magnitude of emissions abatement considered in this study (see e.g. World Bank, 2011).

‘Indirect emissions’ included the carbon contents of all imported and domestic intermediate inputs. The carbon content of goods was computed using a recursive diagonalization algorithm (as described in Rutherford, 2010b).

Possible tariff exemptions for least-developed countries, as included in several US proposals (von Asselt and Brewer, 2010), were not considered in the main scenarios, because such exemptions would also preclude these countries from receiving moneys for clean development investment in the carbon tariff/clean development scenario considered.

Monetary values are given in US$₂₀₀₄. The model was calibrated to match current carbon prices and short-term emissions reductions, so the monetary values can be seen as indicative of the possible short-term (e.g. annual) effects of the climate policies modelled.

This practice might create ‘wrong’ incentives, which are discussed in Section 5.

Note, in comparison to Table A3, the aggregation was reduced for ease of presentation: KOR and SIT were summarized as TIG; THA and MYS were included in XAS; XNF was included in XAF; and XAM was included in ROW.

Table 2 lists emissions reductions in non-Annex I countries that are higher than the 11% emissions reductions prescribed for Annex I countries. This was calculated with respect to the CAT scenario and therefore included the compensation of leakage-related emissions increases from that scenario.

Introducing a price of carbon in the CAT scenario reduced the welfare of the affected Annex I countries. Non-Annex I countries were also affected, primarily due to reductions in fossil fuel exports to Annex I countries. Thus, the reference against which the carbon-tariff scenarios were evaluated included aggregate welfare losses for both regional blocks.

The poorest region in the aggregation used was the Rest of Africa (XAF). In Table 3, XAF is further aggregated to AFR. Relative to regional aggregates, it was still the poorest region listed.

Additional information

Notes on contributors

Marco Springmann

Present address: Department of Economics, University of Oldenburg, 26111 Oldenburg, Germany