Technical Policy Briefing Notes - 2
Cost-Effectiveness Analysis
The Application to Adaptation
Policy Briefs
Cost-Effectiveness Analysis
The Application to Adaptation
Cost-effectiveness is already used in many
sectors
that are relevant to adaptation, such as health and
flooding, and therefore has potential for appraising options
to address future climate change. The MEDIATION project has
reviewed the application of CEA to adaptation, including existing
case studies in the academic and grey literature.
The first issue that the review has identified is the choice of cost-effectiveness metrics for adaptation, and the related sector policy objectives. This recognises there are a wide range of potential risks, across and between sectors that could be considered. As part of the review, MEDIATION has identified possible by sector, presented in Table 1.
Table 1. Possible cost effectiveness metrics / objectives for adaptation.
Sources used in compiling the table: Nicholls et al (2006); Boyd et al, 2006: Rosenzweig and Tubiello (2007): Watkiss, Hunt and Markandya (2009); UNFCCC (2009).
This does highlight a particular issue for the application of CEA to adaptation, namely that it can be often be difficult to identify a single common metric for analysis, because there are many types of risks across and even between sectors. In the case of sea level rise for example, using a headline metric of the number of people at risk, or an objective of acceptable levels of risk, will omit consideration of coastal erosion and coastal ecosystems. This means such a CEA will not consider all relevant costs and benefits for coastal adaptation and may not identify the most holistic option. For this reason, CEA is less suitable for complex or cross-sectoral risks.
The second key area identified in the application of CEA to adaptation is the consideration of uncertainty, one of the key areas of investigation in the MEDIATION review.
Most previous CEA applications, e.g. in areas such as environmental policy and mitigation, ignore uncertainty, presenting single cost curves. Early applications of CEA to adaptation have also followed this approach, largely presenting individual cost curves, or at best, a few cost curves (each representing a central estimate for a different emission scenario, or a central and high scenario). As highlighted in Policy Note 1, the use of central estimates for future climate change assessments can often provide misleading results for adaptation.
Indeed, the range of climate model outputs for a given scenario, whether from the degree of temperature change, or for precipitation projections where even the sign of the change is uncertain, will alter the cost-effectiveness of options, their relative CEA ranking, and their total effectiveness and the cost curve. It is possible to address this by sampling across multiple scenarios/model outputs, or using stochastic approaches, but this has resource implications.
The first issue that the review has identified is the choice of cost-effectiveness metrics for adaptation, and the related sector policy objectives. This recognises there are a wide range of potential risks, across and between sectors that could be considered. As part of the review, MEDIATION has identified possible by sector, presented in Table 1.
Table 1. Possible cost effectiveness metrics / objectives for adaptation.
| Sector | Possible Metric | Issues |
| Health | Cost per DALY,
cost per fatality or cost per life year saved (impact metrics). | Different
cost per life year used across Europe. |
| Health
thresholds (maximum occupational temperatures, comfort levels) | Consistency
issues with other sectors where health a part of wider risks (e.g. floods, transport) | |
| Sea level rise | Cost per
reduction in land area at risk or number of people at risk (exposure metric) or e xpected annual damages (economic metric) | Land
area and ha only covers a sub-set of SLR impacts. Issue of non-market values, loss of biodiversity and ecosystem services. |
| Cost per ha. For the measure relative to
value of land protected per ha (impact metric). | ||
| Pre-defined
acceptable risks of flooding as objective / threshold level for adaptation. | Very different levels of acceptable risk and protection across Member States | |
| Floods | As above. | As above. |
| Agriculture | Impact based
metrics include cost per unit of crop yield, production or land value, but depends on risk (e.g. could be reduction in water stress). | Issue
of capturing wider environmental and multi-functionality of agriculture. |
Possible headline indicator is cost per change in value added as a result of adaptation measures. | Highly
aggregated and only one element of potential impacts. | |
| Water resources | Impact metrics
for water availability resources (household) and cost per M3 of water provided. | Issues with wider attributes of water including quality (environmental). |
| Possible
thresholds in terms of environmental quality (Directives) or acceptable flows. Possible thresholds for risk of supply disruption. | Issue of
multi-functionality and multiple users and sectors (agriculture, industry, etc.) | |
| Ecosystems and Biodiversity | Critical targets (sustainable levels) and standards (overall objective). | Issue if standards are available (and complex and contentious to set). |
| Possible cost per unit of ecosystem services. | ||
| Business & industry | Possible
headline indicator is cost per change in value added as a result of adaptation measures. Could also include acceptable risk levels for infrastructure or service supply. | Broad nature of sector and potential risk. |
| Extreme Events including to infrastructure | Possible metric
in terms of cost per level of risk reduction, or pre-defined acceptable levels of risks as objective | Very different
levels of acceptable risk and protection across Member States Variability in risk acceptability across different extremes, and for different infrastructure. |
This does highlight a particular issue for the application of CEA to adaptation, namely that it can be often be difficult to identify a single common metric for analysis, because there are many types of risks across and even between sectors. In the case of sea level rise for example, using a headline metric of the number of people at risk, or an objective of acceptable levels of risk, will omit consideration of coastal erosion and coastal ecosystems. This means such a CEA will not consider all relevant costs and benefits for coastal adaptation and may not identify the most holistic option. For this reason, CEA is less suitable for complex or cross-sectoral risks.
The second key area identified in the application of CEA to adaptation is the consideration of uncertainty, one of the key areas of investigation in the MEDIATION review.
Most previous CEA applications, e.g. in areas such as environmental policy and mitigation, ignore uncertainty, presenting single cost curves. Early applications of CEA to adaptation have also followed this approach, largely presenting individual cost curves, or at best, a few cost curves (each representing a central estimate for a different emission scenario, or a central and high scenario). As highlighted in Policy Note 1, the use of central estimates for future climate change assessments can often provide misleading results for adaptation.
Indeed, the range of climate model outputs for a given scenario, whether from the degree of temperature change, or for precipitation projections where even the sign of the change is uncertain, will alter the cost-effectiveness of options, their relative CEA ranking, and their total effectiveness and the cost curve. It is possible to address this by sampling across multiple scenarios/model outputs, or using stochastic approaches, but this has resource implications.
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