Cost-benefit analysis (CBA) involves valuing all costs and benefits of a proposed project over time on the basis of willingness to pay (or willingness to accept compensation) on the part of project beneficiaries (affected people) and specifying a decision criterion to accept or turn down the project (see Ray, 1984; Morgenstern, 1997). This criterion usually is the compensation principle, implying that those who benefit from the project should be able to compensate the losers. The applicability of CBA as a DAF for climate policy has been a fiercely debated issue. Although the debate continues about the extent to which traditional CBA can provide useful information for global-level decisionmaking, there is more agreement on its usefulness in adaptation decisions at the national and regional scales.
In practical applications, all costs (C) and benefits (B) are defined as follows:
where i is the social discount rate, n is the project life, and t denotes the year. One can use different cost-benefit criteria for ranking projects or choosing the best among them: the cost-benefit ratio, CBR = B/C > 1; the net present value, NPV = B - C > 0; and the internal rate of return, IRR > i, where IRR is the discount rate to make B = C. When we evaluate a single project, these criteria lead to the same conclusion. In choosing the most desirable alternative, however, these criteria indicate different orders of desirability.
A CBA in the adaptation context takes potential regional climate change scenarios and their impacts as its starting point. The next step is to establish costs of alternative adaptive measures as a function of their scales of application—the marginal cost curve. A related task is to estimate how much damage can be averted by increasing the adaptation effort—WTP (marginal benefit curve). The decision principle suggests undertaking adaptive measures as long as marginal averted damages (benefits) exceed marginal costs. This rule of thumb is easier to apply in sectoral adaptation decisions, in which costs and benefits can be derived from market prices. Difficulties arise in nonmarket sectors in which the valuation behind the marginal cost and benefit curves often is debated. Difficulties multiply, in a regional context, when costs and benefits must be aggregated across many sectors.
A frequent critique of CBA and its applicability in adaptation studies is that the underlying measurements are incomplete (especially in regional studies, which do not cover all important aspects), inaccurate (even the costs and benefits of adaptive actions included in the analysis are impossible to measure precisely), and debated (related to the two preceding points; the inclusion and exact valuation of many costs and benefits involve inherently subjective value judgments). These criticisms are largely valid. However, it is still better to get at least the measurable components right and complement them with a combination of judgments on hard-to-measure items and sensitivity tests to assess their implications than to abandon the whole method simply because it does not get everything perfect. Nevertheless, it is important that users of these tools and their results fully understand the limitations and confidence attached to them. Duke and Kammen (1999) argue that accounting for dynamic feedback between the demand response and price reductions from production experience can be used to account for deadweight loss and other market dynamics that determine the benefit-cost ratio of economic and policy measures to expand the market for clean energy technologies. These results further support a broader role for market transformation programs to commercialize new environmentally attractive technologies. The same dynamic feedback processes also are relevant for CBA applications to adaptation decisions. For example, consider changing precipitation patterns that would increase the frequency of high-water conditions. Take flood-related damages as the function of flood return periods: Annual flooding may cause the least damages, whereas a 5-year return flood will cause somewhat more, a 20-year return flood even more, and so on. Adaptation costs increase along the same axis because it takes higher dikes and larger flood protection reservoirs to control a 50-year return flood than a 5-year return flood. The level at which a given society will decide to protect itself against floods depends on local economic conditions and geographical and technological endowments. A CBA suggests that it should be in the neighborhood of where marginal costs of additional flood protection would be equal to WTP for additional flood protection.
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