Climate change adaptation

The investment needed to adapt to climate change will be largely irreversible and its future benefits will be risky due to uncertainty about the scale and scope of climate change and economic growth. These conditions make real-options analysis a natural tool for deciding how, when, and where to react to climate change. However, factors such as “deep” uncertainty about climate outcomes make standard techniques unsuitable. My current research involves modifying real-options analysis so that it can cope with these climate-specific factors.

Current activity


Climate change adaptation: Evaluating simple alternatives to real options analysis

This paper introduces a new framework for evaluating climate-change adaptation projects. This framework incorporates uncertainty surrounding future climatic and economic conditions and allows for Bayesian learning about the magnitude of climate change. The paper uses real options analysis to construct an optimal policy for determining the scale and timing of investment and then evaluates simpler alternative approaches to project evaluation against this benchmark. The performance of standard cost-benefit analysis improves if projects are evaluated less frequently. Rules of thumb involving arbitrary thresholds for the benefit-cost ratio or increments to the social discount rate can capture most of the value of investment flexibility. Approximating the option value of waiting by assuming delayed investment occurs after a fixed delay performs even better, with little increase in difficulty. Basing decisions on a single source of volatility (climatic or economic) leads to even better performance, but the rules are harder to implement. 

This project is funded by the Deep South Challenge as part of its “Impacts and implications” research programme.

Recent activity


Optimal adaptation to uncertain climate change

Enormous public investment will occur as communities adapt to climate change. Much of this investment will be irreversible and the future benefits are currently uncertain. The real options embedded in adaptation projects are therefore potentially important and their existence needs to be incorporated into investment decision-making. Standard real options analysis is  inadequate for this purpose because the future arrival of information about climate change is unlikely to conform to the stochastic processes typically used in real options analysis. This paper presents a new framework that reflects current uncertainty about climate change and how that uncertainty might change over time. Optimal investment depends on current beliefs regarding the severity of future climate change, how quickly these beliefs are likely to change in the future, and current economic conditions. Most of the net benefits of optimal investment can be captured if investment timing is decided using a simple alternative decision-making rule.

This project is funded by the Deep South Challenge as part of its “Impacts and implications” research programme.


Adapting to rising sea levels: How short-term responses complement long-term investment

Coastal communities can adapt to rising sea levels using a combination of irreversible investment in infrastructure (e.g., sea walls) and activities that only provide temporary protection (e.g., beach scraping). This paper shows how costs can be minimised by delaying investment in infrastructure until the present value of the benefits exceeds upfront investment costs by a margin that can exceed 50% of investment costs. Spending on temporary protection should be incurred even when the marginal cost of increasing the effectiveness of defences this way is significantly greater than the equivalent annual cost of permanently increasing effectiveness by investment. 


Real-options analysis of climate-change adaptation: Investment flexibility and extreme weather events

One of the difficulties associated with climate change is that we cannot directly observe the consequences of climate change for the parameters that we need to know to make good investment decisions. For example, a changing climate may increase the frequency of storms, but the effect on the probability that a storm may happen in the next year is unobservable. We can only learn about that probability by observing actual weather patterns—and it takes time to learn enough to be useful. This paper presents a new model that can be used for decision-making when we use observed weather patterns to continuously update our beliefs about the underlying climate.