Alexander Golub

Uncertainty in Integrated Assessment Models of Climate Change: Alternative Analytical Approaches

Uncertainty plays a key role in the economics of climate change, and the discussions surrounding its implications for climate policy are far from settled. We give an overview of the literature on uncertainty in integrated assessment models of climate change and identify some future research needs. In the paper, we pay particular attention to three different and complementary approaches that model uncertainty in association with integrated assessment models: the discrete uncertainty modeling, the most common way to incorporate uncertainty in complex climate-economy models: the real options analysis, a simplified way to identify and value flexibility: the continuous-time stochastic dynamic programming, which is computationally most challenging but necessary if persistent stochasticity is considered.

Using the social cost of carbon to value earth observing systems

The goal of this study is to show how to quantify the benefits of accelerated learning about key parameters of the climatic system and use this knowledge to improve decision-making on climate policy. The US social cost of carbon (SCC) methodology is used in innovative ways to value new Earth observing systems (EOSs). The study departs from the strict US SCC methodology, and from previous work, in that net benefits are used instead of only damages to calculate the value of information of the enhanced systems. In other respects the US SCC methodology is followed closely. We compute the surfeit expected net benefits of learning the actionable information earlier, with the enhanced system, versus learning later with existing systems. The enhanced systems are designed to give reliable information about climate sensitivity on accelerated timescales relative to existing systems; therefore, the decision context stipulates that a global reduced emissions path would be deployed upon receiving suitable information on the rate of temperature rise with a suitable level of confidence. By placing the enhanced observing system in a decision context, the SCC enables valuing this system as a real option. Policy relevance Uncertainty in key parameters of the climatic system is often cited as a barrier for near-term reductions of carbon emissions. It is a truism among risk managers that uncertainty costs money, and its reduction has economic value. Advancing policy making under uncertainty requires valuing the reduction in uncertainty. Using CLARREO, a new proposed EOS,as an example, this article applies value of information/real option theory to value the reduction of uncertainty in the decadal rate of temperature rise. The US interagency social cost of carbon directive provides the decision context for the valuations. It is shown that the real option value of the uncertainty reduction, relative to existing observing systems, is a very large multiple of the new systems cost.

Uncertainty, climate change, and irreversible environmental effects: application of real options to environmental benefit-cost analysis

Benefit-cost analysis (BCA) is the foundation of environmental policy analysis in the USA. This has worked reasonably well as a resource allocation tool for conventional environmental problems, although not for climate change. Conventional economic analyses of the 2° C stabilization target usually report modest benefits while costs are significant. Time lags and the discount rate “eat up” distant future benefits while present costs remain high. Modest estimates of benefits, based on expected value, do not reflect possible irreversible outcomes of climate change, and so the policy system tends to ignore these plausible conditions which are often statistical tail risks. BCA on tail risks would show benefits from acting, but typically, the costs might be shown to be much too high. When decisions made under high uncertainty have irreversible consequences, these consequences should be taken into account and properly priced. In this paper, we are proposing that the use of real options analysis can help us better understand values and costs of irreversible decisions and to value the costs of delay or early actions. Real options analysis is the most suitable instrument for estimating economic value of risk to be used in the BCA policy framework.