targets laid out in the Government’s Carbon Budget. SCC would continue to be monitored but would no longer provide the basis for setting the carbon price because of the uncertainty surrounding SCC estimates (Pindyck 2013). Two prices are now in use. For appraising policies in sectors covered by the EU Emissions Trading System (ETS), estimates of future traded carbon price are used, giving a carbon price of £25 in 2020, with a range of £14 - £31. For appraising policies in sectors not covered by the EU ETS, a “non-traded price of carbon‟ will be used, based on estimates of the marginal abatement cost required to meet a specific emission reduction target, with a price of £60 tCO2e in 2020, and a range of £30 - £90. These estimates are periodically revised.

_Sources:_ (Wolverton et al. 2012; Price, Thornton, and Nelson 2007; UK Department of Energy & Climate Change 2009) 27. **In general, the value of costs and benefits can be deeply uncertain in the absence of readily available market prices or if market prices do not adequately capture value** . This includes valuations of environmental costs and benefits and intangibles such as the well-being of persons. The benefits of building a sea wall, for example, are likely to be higher than the damage costs alone because of the suffering and inconvenience from flooding. In these cases cost-benefit analysis requires the construction of ‘shadow’ prices that better reflect utility. There are many different approaches to establishing shadow pricing, each of which may reveal a different shadow price and each of which has different strengths and weaknesses nearly all of which are data intensive. These include surveys, choice modeling (Bennett, Van Bueren, and Whitten 2004), and hedonmic price modeling (Mahan, Polasky, and Adams 2000). The choice of method can be controversial, particularly if the resulting shadow price has a significant impact on the performance of the policies or investments being considered.

28. **Choice of discount rate is particularly contentious in the context of climate change** . The discount rate determines the viability of climate change mitigation and adaptation projects, given that costs are incurred in the short-term and benefits may only accrue in the distant future. High discount rates will discourage these investments. As with market prices, there is little agreement among economists as to the theoretically ‘correct’ method of setting discount rates, particularly for programs and projects that will generate costs and benefits over several generations. In practice, discount rates are set by the central finance agency as a ‘plug-in value’ for use in policy, program or program appraisal. Most developed countries apply much lower discount rates, mostly in the range of 3 to7 per cent, with many reducing their rates in recent years. Developing countries use a much higher discount rate, reflecting the higher opportunity cost of capital, in the range of 8 to 15 percent. Multilateral development banks follow similar practices with high discount rates (Zhuang et al. 2007).

29. **CBA or RO approaches often ignore the distribution of costs and benefits between different social groups, since those who benefit can theoretically compensate those who bear the costs.** In practice, however, it will rarely be the case that the beneficiaries of a government project will actually compensate the losers. There are multiple ways of taking this into account, including through distributional weights (Fleurbaey and Hammond 2004; Harberger 1984; Harberger 1978). In many instances, it is extremely difficult to build a consensus on which distributional weights should be applied; and the large impact of these weights on decisions makes it even more difficult to create a consensus. Given the many potential perspectives on the issue of equity, it is unlikely that any particular evaluation tool can provide a satisfactory resolution to the problem: it is typically recommended in CBA that an unweighted analysis be carried out in addition to any weighting exercise.

30. **These problems suggest that we should seek to encompass the whole set of possible assumptions to check the robustness of our assessment of options according to whatever metric we have chosen.** The example of New Orleans and hurricane protection shows that we can arrive at very 14