Operationalizing climate targets under learning: An application of cost-risk analysis

Abstract

Cost-Effectiveness Analysis (CEA) determines climate policies that reach a given climate target at minimum welfare losses. However, when applied to temperature targets under climate sensitivity uncertainty, decision-makers might be confronted with normatively unappealing negative expected values of future climate information or even infeasible solutions. To tackle these issues, Cost-Risk Analysis (CRA), that trades-off the costs for mitigating climate change against the risk of exceeding climate targets, has been proposed as an extension of CEA under uncertainty. Here we build on this proposition and develop an axiomatically sound CRA for the context of uncertainty and future learning. The main contributions of this paper are: (i) we show, that a risk-penalty function has to be non-concave to avoid counter-intuitive preferences, (ii) we introduce a universally applicable calibration of the cost-risk trade-off, and (iii) we implement the first application of CRA to a numerical integrated assessment model. We find that for a 2°-target in combination with a 66 % compliance level, the expected value of information in 2015 vs. 2075 is between 0.15 % and 0.66 % of consumption every year, and can reduce expected mitigation costs by about one third. (iv) Finally, we find that the relative importance of the economic over the risk-related contribution increases with the target probability of compliance. Electronic supplementary material The online version of this article

The Role of Bioenergy and Carbon Capture and Storage (BECCS) in the Case of Delayed Climate Policy – Insights from Cost-Risk Analysis

“…From a political point of view, therefore, an alternative called Cost-Risk Analysis (CRA) was suggested that circumvents the inconsistencies of CEA (Schmidt et al, 2011 andNeubersch et al, 2014). Instead of including climate damage functions, CRA weighs the risks of transgressing a predefined temperature target against the costs of mitigation, representing a hybrid of 20 CBA and CEA.…”

“…Instead of including climate damage functions, CRA weighs the risks of transgressing a predefined temperature target against the costs of mitigation, representing a hybrid of 20 CBA and CEA. Thereby, an evaluation of the 2°C target remains possible, even in cases that would be infeasible under CEA (Neubersch et al, 2014). The value system of the 2°C target can be extrapolated into any future scenario.…”

Climate Change and Decision-Making Under Uncertainty

“…Therefore, we may conclude that the overall uncertainty about forest management under climate change may be reduced in the future depending on international cooperation and commitments along with technological advancements. This conclusion highlights the value of learning and obtaining novel knowledge about climate change [32] by monitoring forest responses to a combined effect of climate and management, and the necessity to consider robust decisions and avoid high economic loss (see an example in the BDealing with Deep Uncertainty of Climate Change^section). It is worth highlighting that the difficulty in modeling extreme climate events and the imposed high impacts on forests health and productivity remains a challenging issue as there is no historical parallel to build the climate model predictions upon [33].…”

Climate targets and cost-effective climate stabilization pathways

“…The properties and consequences of this new decision analytic tool are at present subject to academic investigation( 8 ). Neubersch et al [30] utilize a version of CRA that linearly penalizes a transgression of a temperature target. They argue it was the most conservative way to formulate a risk function that would still avoid any counterintuitive "tipping" towards a high-emission path, once a target has been missed.…”

“…could be up to hundreds of billions of Euro per year [30] which could be seen as an incentive to invest faster in improved climate observation and modelling systems. Finally, does the above development of a new decision-analytic tool like CRA imply in part a "rehabilitation" of CBA from the perspective of the "CEA community"?…”