Technical Policy Briefing Notes - 4
Real Options Analysis
Discussion and Applicability
Policy Briefs
Real Options Analysis
Discussion and Applicability
The
review and case studies provide a number of practical lessons on the
application of real options analysis to adaptation. They provide useful
information on the types of adaptation problem types where ROA might be
appropriate, as well as data needs, resource requirements and good
practice.
In summary, ROA is considered most useful for project based investment analysis, for major irreversible capital investment, particularly where there is an existing adaptation deficit (because this involves a trade-off between acting now and waiting). It also has applications such as the second case study, where there is an existing maintenance backlog, and in cases where there is the possibility of receiving new information in the future. In general it is less useful for new projects that address future climate change, where benefits arise in the long-term only, especially if these are highly uncertain, because in such cases it will make more sense to wait.
It also has the potential to assess flexible versus conventional options, which is a particularly important component of iterative risk management. It can also be used to support initial enabling steps to help secure projects for future development, even if they are not expected to be cost-efficient on the basis of traditional, static CBA/CEA appraisal.
The application requires inputs related to probability or probabilistic assumptions for climate change and the identification of decision points. It is therefore less applicable under situations of (deep) uncertainty, where probabilistic information is low or missing. For such cases, alternative approaches, such as robust optimisation, may be considered (see briefing note 3). It also requires the analysis of quantitative data on costs and benefits, the latter which have to match to the decision trees and outcomes: this usually requires a linked modelling system or a large number of assessments, coupled with some form of sampling (e.g. Monte Carlo analysis). For this reason, the resources and level of expert knowledge needed to apply the approach are high. The focus of the approach on economic costs and benefits makes the application to nonmarket sectors more challenging.
Given the high resource requirements, the review also identifies the potential for more informal application of ROA, e.g. through the use of decision trees and more qualitative analysis of information and flexibility.
In summary, ROA is considered most useful for project based investment analysis, for major irreversible capital investment, particularly where there is an existing adaptation deficit (because this involves a trade-off between acting now and waiting). It also has applications such as the second case study, where there is an existing maintenance backlog, and in cases where there is the possibility of receiving new information in the future. In general it is less useful for new projects that address future climate change, where benefits arise in the long-term only, especially if these are highly uncertain, because in such cases it will make more sense to wait.
It also has the potential to assess flexible versus conventional options, which is a particularly important component of iterative risk management. It can also be used to support initial enabling steps to help secure projects for future development, even if they are not expected to be cost-efficient on the basis of traditional, static CBA/CEA appraisal.
The application requires inputs related to probability or probabilistic assumptions for climate change and the identification of decision points. It is therefore less applicable under situations of (deep) uncertainty, where probabilistic information is low or missing. For such cases, alternative approaches, such as robust optimisation, may be considered (see briefing note 3). It also requires the analysis of quantitative data on costs and benefits, the latter which have to match to the decision trees and outcomes: this usually requires a linked modelling system or a large number of assessments, coupled with some form of sampling (e.g. Monte Carlo analysis). For this reason, the resources and level of expert knowledge needed to apply the approach are high. The focus of the approach on economic costs and benefits makes the application to nonmarket sectors more challenging.
Given the high resource requirements, the review also identifies the potential for more informal application of ROA, e.g. through the use of decision trees and more qualitative analysis of information and flexibility.
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