Cost effectiveness analysis (CEA), as defined by the IPCC, "takes a predetermined objective (often an outcome negotiated by key stakeholder groups in a society) and seeks ways to accomplish it as inexpensively as possible" (Ahmad et al. 2001). The aim of CEA is to find the least costly option or options for meeting selected physical targets.
The easiest way to think about CEA is to assume that there is a single indicator of effectiveness, E, and this is to be compared to a cost of C. The usual procedure is toproduce a cost-effectiveness ratio (CER): CER = E/C . If we suppose that there are i=1, 2,..., n potential policies, with corresponding costs Ci and effectiveness Ei then CEA requires that we rank the policies according to CERi = Ei / Ci.
A classic application of CEA is to derive cost curves, in order to explore the least cost way of achieving pre-defined ambitions or targets. This can be undertaken for adaptation, at a sectoral or sub-sectoral or to assess individual types of risk. However, cost effectiveness cannot be used to compare adaptation between sectors, as has been applied for mitigation, because there are no common metrics. An emerging issue is the recognition that climateproofing of all human activities through adaptation would be extremely expensive, and there will be many cases where benefits will certainly exceed costs. At the other extreme is a policy of doing nothing, i.e. living with the risks of climate change. Optimal policy will be somewhere between these two extremes (i.e. 'cost- effective and proportionate'). The concept of cost-effective and proportionate adaptation is a sound one, but assessing this in practice will clearly be complex. Whilst there has been much attention focused on the effectiveness of adaptation in reducing climate change vulnerability, and so potential impacts, it is rarely appreciated that if done badly, adaptation responses can actually exacerbate the effects of climate change. In analyzing the costs and benefits of adaptation it is also necessary to consider such "mal-adaptation" as a non-cost-effective adaptation measure. A strong theme will be to identify low cost and no regret measures.
This toolbox entry has been labelled with the following tags:
| Sector: | independent | |
| Spatial scale: | independent | |
| Temporal focus: | independent | |
| Onset: | independent | |
| Role in decision process: | prescriptive | |
| Level of skills required: | ||
| Data requirements: | ||
| Adaptation tasks: | Expected outcomes: utility, welfare, effect etc. (e.g. CEA, CBA) |
There are a number of potential barriers to ranking adaptation options according to cost-effectiveness: (a) adaptation responds to a local impact and the benefit achieved by adaptation is primarily local/regional, and is determined strongly by local conditions, and (b) adaptation is sector specific, addressing different types of climate signals and impacts.
There are therefore no universal or consistent metrics in relation to what a given level of adaptation achieves - it varies according to whether the option is responding to impacts from average temperature changes or sea-level rise, or the change in probability (or magnitude/frequency) of extreme events such as flooding. Thus it is not easy to compare the cost-effectiveness of adaptation options across different sectors, or between different types of measures (for instance, there is not a common metric of benefit between a reduction in risk from coastal flooding vs. cooling demand delivered from a passive air cooling system in response to higher summer temperatures). There may be complex issues of additionality - separating out the climate change component of current weather variability from improved climate resilience to climate change. There may also be differences in the adaptation response achieved (in magnitude) according to whether implementation is proactive or reactive, or according to the specific time period when the measure is implemented, both in terms of costs, but also in relation to the adaptation benefits achieved. Furthermore, the effectiveness of adaptation measures may vary across actors depending on their ability to adapt (adaptive capacity) and their exposure to risk (vulnerability). Finally, the cost-effectiveness of options may vary according to the discount rate used, and this may be important particularly for longer-term options.
A further issue with CEA is the process of selecting the effectiveness measures. The measure of effectiveness could be based on some attitude survey of a random sample of individuals. In practice, CEA tends to proceed with indicators of effectiveness chosen by experts. Rationales for using expert choices are: a) that experts are better informed than individuals, especially on issues such as habitat conservation, landscape etc., and b) that securing indicators from experts is quicker and cheaper than eliciting individuals' attitudes (Pearce et al., 2006).
CEA has been applied to sectoral assessment of many national studies e.g. health, freshwater systems, coastal and river flood risks, extreme weather events and biodiversity and ecosystem services. Examples in the health sector include the calculation the climate related health effects in terms of life years lost or disability-adjusted life years lost (Markandya and Chiabai, 2009; McMichael et al, 2004).
CEA is suitable for assessment between options, using units other than money, thus it has potential for effects that are difficult to value. CEA can only offer guidance on which of several alternative policies (or projects) to select, given that one has to select one, i.e. it is a relative measure. CEA can be done in conjunction with standards of acceptable risk or acceptable cost per unit of impact removed. For example, when it is difficult to value the consequences of extreme events such as flooding, CEA can be used for defined or acceptable levels of risks. Alternatively, we can set expected losses from such events at an agreed level (such as the current level of losses) and to undertake adaptation measures at the lowest cost, so as to not exceed that level.
The limitation of CEA is that an entire list of policies, ranked by their cost- effectiveness, could be adopted without any assurance that any one of them is actually worth doing, i.e. that they are justified in absolute terms. The notion of "worth doing" only has meaning if one can compare costs and benefits in a manner that enables one to say costs are smaller than benefits.
CEA is not a proprietary tool or software package, and is discussed in the toolbox as the operationalization of the method. Thus, only limitation to access is the knowledge required to perform CEA.
Further information on CEA can be found via the in-depth
Pearce, D., Atkinson G., and S. Mourato. 2006. Cost-Benefit Analysis and the Environment: Recent developments. OECD publishing.
Markandya A. and A. Chiabai. 2009 Valuing climate change impacts on human health: empirical evidence from the literature. International Journal of Environmental Research and Public Health 6: 759-786.
McMichael AJ, Campbell-Lendrum D, Kovats RS, Edwards S, Wilkinson P, Edmonds N, Nicholls N,Hales S, Tanser FC, Le Sueur D, Schlesinger M and Andronova N. 2004. Climate Change. In: Ezzati, M.,AD Lopez, A Rodgers and CJL Murray. Global and Regional Burden of Diseases Attributable to Selected Major Risk Factors. World Health Organization, Geneva.
The case study pool contains the following steps that were performed applying the described entry:
| NE2 - Biodiversity change | |
| Exploring risks: What are the impacts, including costs, of the adaptation options? | |
Available related training material
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CEA
Training material for CEA |
