Wilfried Rickels

Explaining European Emission Allowance Price Dynamics: Evidence from Phase II

Abstract We empirically investigate potential determinants of the allowance price dynamics in the European Union Emission Trading Scheme during Phase II. In contrast to previous studies, we place particular emphasis on the fuel price selection. We show that results are extremely sensitive to choosing different price series of potential determinants, such as coal and gas prices. In general, only the influence of economic activity in Europe and hydropower provision in Norway is robustly explaining allowance price dynamics. The influence of fuel switching on allowance prices and, therefore, equalization of marginal abatement costs - in particular in the long run - is still rather small.

Price and Market Behavior in Phase II of the EU ETS: A Review of the Literature

Since 2005, the EU ETS has provided a market-based price signal for European carbon emissions. This article reviews the literature on the formation of carbon allowance prices during phase II of the EU ETS. A consensus has emerged in the literature that allowance prices are driven by fuel prices and other variables that affect the expected amount of abatement required to meet the EU ETS emissions cap. However, this relationship is not robust, most likely because the relevant abatement technologies change with the economic conditions in which they operate. There is evidence that models that explicitly account for uncertainty about the future demand and supply of allowances are better at explaining allowance price variation during certain periods. However, our understanding of the level of the allowance price remains poor. We cannot say with any degree of confidence whether the allowance price is “right,” in the sense that it reflects marginal abatement costs, or whether there is a price wedge caused by uncertainty, transaction costs, or price manipulation. Nevertheless, we find that the EU ETS market has matured in phase II compared with phase I and that banking of allowances has induced the market to incorporate the future scarcity of allowances and, as intended, to smooth the effect of temporary shocks. We argue that further research is needed in several key areas to increase our understanding of the emissions allowance market provided by the EU ETS. ( JEL: Q56, Q58)

The Real Economics of Climate Engineering

In 2008 Scott Barrett wrote a paper on “The incredible economics of geoengineering” in which he argued that the potentially low cost of climate engineering (CE) measures together with the quick response of the earth’s temperature to such interventions will change the whole debate about the mitigation of climate change. Whereas Barrett was mostly focusing on the cost of running CE measures, we point out that several determinants of overall economic cost like price or external effects are not yet sufficiently accounted for and that the question of dynamic efficiency is still unresolved. Combining the existing theoretical investigations about the topic from the literature, we show that even though these new measures provide new options to deal with climate change, several of them might also reduce our scope of action. Consequently, we suggest that economic research should shift its focus to portfolios of CE measures and put more emphasis on those measures which control atmospheric carbon concentration and therefore allow extending our scope of action. Additionally, economic research should address the question of phase-in and phase-out scenarios for measures which directly influence the radiation balance.

Climate Engineering: Economic Considerations and Research Challenges

Climate engineering measures are designed to either reduce atmospheric carbon concentration (by growing trees or spreading iron in the ocean, for example) or directly influence the radiation reaching or leaving the earth (by injecting sulfur into the stratosphere or modifying cloud formations, for example) to compensate for greenhouse gas–induced warming. The former measures are termed carbon dioxide removal (CDR), which we characterize as a low-leverage causative approach, and the latter are termed radiation management (RM), which we characterize as a high-leverage symptomatic approach. There are similarities between CDR and emission control. Accordingly, benefit-cost analysis can be used to assess certain CDR measures. By contrast, high-leverage RM represents a genuinely new option in the climate change response portfolio, at first glance promising insurance against fat-tail climate change risks. However, the persistent intrinsic uncertainties of RM suggest that any cautious climate risk management approach should consider RM as a complement to (rather than a substitute for) emission control at best. Moreover, the complexity of the earth system imposes major limitations on the ability of research to reduce these uncertainties. Thus we argue that a research strategy is needed that focuses on increasing our basic understanding of the earth system and conducting comprehensive assessments of the risk(s) associated with both climate change and the deployment of climate engineering. (JEL: Q52, Q54, Q55)

Indicators and metrics for the assessment of climate engineering

Selecting appropriate indicators is essential to aggregate the information provided by climate model outputs into a manageable set of relevant metrics on which assessments of climate engineering (CE) can be based. From all the variables potentially available from climate models, indicators need to be selected that are able to inform scientists and society on the development of the Earth system under CE, as well as on possible impacts and side effects of various ways of deploying CE or not. However, the indicators used so far have been largely identical to those used in climate change assessments and do not visibly reflect the fact that indicators for assessing CE (and thus the metrics composed of these indicators) may be different from those used to assess global warming. Until now, there has been little dedicated effort to identifying specific indicators and metrics for assessing CE. We here propose that such an effort should be facilitated by a more decision-oriented approach and an iterative procedure in close interaction between academia, decision makers, and stakeholders. Specifically, synergies and trade-offs between social objectives reflected by individual indicators, as well as decision-relevant uncertainties should be considered in the development of metrics, so that society can take informed decisions about climate policy measures under the impression of the options available, their likely effects and side effects, and the quality of the underlying knowledge base.

How healthy is the human-ocean system?

Halpern et al (2012 An index to assess the health and benefits of the global ocean Nature 488 11397)propose a detailed measure of the state of the human-ocean system against ten societal goals. They devote less attention to the normative foundation of the index, which is crucial for assessing the overall health of the human-ocean system, notably when it comes to aggregation of potentially conflicting goals. Social choice theory provides several possible functional forms for assessing the compound change in various goals. The one chosen by Halpern et al, the arithmetical mean, is not only a specific but also an extreme case. It implicitly allows for unlimited substitution. A one-unit reduction in one goal can be fully offset by a one-unit increase in another with the same weighting factor. For that reason, the current index satisfies an extremely weak sustainability concept. We show that the results in Halpern et al are not robust when one adopts a strong sustainability concept. The overall health score of the ocean decreases, the ranking of the various coastal states changes substantially, and the assessment of sustainable development needs to be partially reversed.

Regional climate engineering by radiation management: Prerequisites and prospects

Radiation management (RM), as an option to engineer the climate, is highly controversial and suffers from a number of ethical and regulatory concerns, usually studied in the context of the objective to mitigate the global mean temperature. In this article, we discuss the idea that RM can be differentiated and scaled in several dimensions with potential objectives being to influence a certain climate parameter in a specific region. Some short-lived climate forcers (e.g., tropospheric aerosols) exhibit strong geographical and temporal variability, potentially leading to limited-area climate responses. Marine cloud brightening and thinning or dissolution of cirrus clouds could be operated at a rather local scale. It is therefore conceivable that such schemes could be applied with the objective to influence the climate at a regional scale. From a governance perspective, it is desirable to avoid any substantial climate effects of regional RM outside the target region. This, however, could prove impossible for a sustained, long-term RM. In turn, regional RM during limited time periods could prove more feasible without effects beyond the target area. It may be attractive as it potentially provides the opportunity to target the suppression of some extreme events such as heat waves. Research is needed on the traceability of regional RM, for example, using detection and attribution methods. Incentives and implications of regional RM need to be examined, and new governance options have to be conceived.

Integrated Assessment of Carbon Dioxide Removal

To maintain the chance of keeping the average global temperature increase below 2 degrees C and to limit long-term climate change, removing carbon dioxide from the atmosphere (carbon dioxide removal, CDR) is becoming increasingly necessary. We analyze optimal and cost-effective climate policies in the dynamic integrated assessment model (IAM) of climate and the economy (DICE2016R) and investigate (1) the utilization of (ocean) CDR under different climate objectives, (2) the sensitivity of policies with respect to carbon cycle feedbacks, and (3) how well carbon cycle feedbacks are captured in the carbon cycle models used in state-of-the-art IAMs. Overall, the carbon cycle model in DICE2016R shows clear improvements compared to its predecessor, DICE2013R, capturing much better long-term dynamics and also oceanic carbon outgassing due to excess oceanic storage of carbon from CDR. However, this comes at the cost of a (too) tight short-term remaining emission budget, limiting the model suitability to analyze low-emission scenarios accurately. With DICE2016R, the compliance with the 2 degrees C goal is no longer feasible without negative emissions via CDR. Overall, the optimal amount of CDR has to take into account (1) the emission substitution effect and (2) compensation for carbon cycle feedbacks.

Indicators for monitoring sustainable development goals: An application to oceanic development in the European Union: OCEAN SDG

The 2030 Agenda for Sustainable Development that includes a set of 17 Sustainable Development Goals (SDG) with 169 specific targets could be a step forward in achieving efficient governance and policies for global sustainable development. An essential element will be the global indicator framework for monitoring and assessing progress over and against both the overall goals and the specific targets and to guide policy towards sustainable solutions. In the debate over the current indicator framework, little attention is devoted to conceptual issues. Here, we argue that the inclusion of composite indicators, which can be used to aggregate individual indicators, as complements to the single indicators could support the overall assessment process without necessitating any significant changes to the currently proposed indicator base. While the individual indicators remain the backbone of the indicator framework, serving the purpose for detailed assessment of specific policy measures, the composite indicators allow for an explicit assessment of trade-offs between policies. Our illustrative investigation of the sustainable oceanic development of EU coastal states highlights how much a comprehensive assessment can benefit from the additional inclusion of composite indicators.