188.8.131.52 Cost-benefit analysis, damage cost estimates and social costs of carbon
The above analysis provides a means of eliminating those emissions scenarios that are outside sets of pre-determined guardrails for climate protection and provides the raw material for cost-effectiveness analysis of optimal pathways for GHG emissions. If one wants to determine these pathways through a cost-benefit analysis it is necessary to assess the trade-off between mitigation, adaptation and damages, and consequently, to measure damages in the same monetary metric as mitigation and adaptation expenditures. Such assessment can be carried out directly in the form of ‘willingness to pay for’ avoiding certain physical consequences.
Some argue that it is necessary to specify more precisely why certain impacts are undesirable and to comprehensively itemize the economic consequences of climate change in monetary terms. The credibility of such efforts has often been questioned, given the uncertainty surrounding climate impacts and the efficacy of societal responses to them, plus the controversial meaning of a monetary metric across different regions and generations (Jacoby, 2004). This explains why few economists have taken the step of monetizing global climate impacts. At the time of the TAR, only three such comprehensive studies had been published (Mendelsohn et al., 2000; Nordhaus and Boyer, 2000; and Tol, 2002a, 2002b). Their estimates ranged from negligible to 1.5% of the GDP for a global mean temperature rise of +2.5°C and Nordhaus and Boyer carefully warned: ‘Along the economically efficient emission path, the long-run global average temperature after 500 years is projected to increase 6.2°C over the 1900 global climate. While we have only the foggiest idea of what this would imply in terms of ecological, economic, and social outcomes, it would make the most thoughtful people, even economists, nervous to induce such a large environmental change. Given the potential for unintended and potentially disastrous consequences….’
Progress has been made since the TAR in assessing the impacts of climate change. Nonetheless, as noted in Watkiss et al. (2005), estimates of the social costs of carbon (SCC) in the recent literature still reflect an incomplete subset of relevant impacts; many significant impacts have not yet been monetized (see also IPCC, 2007b; for SCC see IPCC (2007b, Section 20.6) and others are calibrated in numeraires that may defy monetization for some time to come. Existing reviews of available SCC estimates show that they span several orders of magnitude – ranges that reflect uncertainties in climate sensitivity, response lags, discount rates, the treatment of equity, the valuation of economic and non-economic impacts, and the treatment of possible catastrophic losses (IPCC, 2007b, Chapter 20). The majority of available estimates in the literature also capture only impacts driven by lower levels of climate change (e.g. 3°C above 1990 levels). IPCC (2007b) highlights available estimates of SCC that run from -3 to 95 US$ /tCO2 from one survey, but also note that another survey includes a few estimates as high as 400 US$/tCO2 (IPCC, 2007b, Chapter 20, ES and Section 20.6.1). However the lower boundary of this range includes studies where climate change is presumed to be low and aggregate benefits accrue. Moreover, none of the aggregate estimates reflect the significant differences in impacts that will be felt across different regions; nor do they capture any of the social costs of other greenhouse gases. A more recent estimate by Stern (2006) is at the high end of these estimates (at 85 US$/tCO2) because an extremely low discount rate (of 1.4%) is used in calculating damages that include additional costs attributed to abrupt change and increases in global mean temperature for some scenarios in excess of 7°C (Nordhaus, 2006a; Yohe, 2006; Tol and Yohe, 2006). The long-term high-temperature scenarios are due to inclusion of feedback processes. IPCC (2007b) also highlights the fact that the social costs of carbon and other greenhouse gases could increase over time by 2–4% per year (IPCC, 2007b; Chapter 20, ES and Section 20.6.1).
For a given level of climate change, the discrepancies in estimates of the social costs of carbon can be explained by a number of parameters highlighted in Figure 3.39. These stem from two different types of questions: normative and empirical. Key normative parameters include the inter-temporal aggregation of damages through discount rates and aggregation methods for impacts across diverse populations within the same time period (Azar and Lindgren, 2003; Howarth, 2003; Mastrandrea and Schneider, 2004) and are responsible for much of the variation.
Figure 3.39: Factors influencing the social costs of carbon.
The other parameters relate to the empirical validity of their assessment, given the poor quality of data and the difficulty of predicting how society will react to climate impacts in a given sector, at a given scale in future decades. Pearce (2003) suggests that climate damages and SCC may be over-estimated due to the omission of possible amenity benefits in warmer climates or high-latitude regions (Maddison 2001) and possible agricultural benefits. However, overall, it is likely that current SCC estimates are understated due to the omission of significant impacts that have not yet been monetized (IPCC, 2007b, Chapters 19 and 20; Watkiss et al., 2005).
Key empirical parameters that increase the social value of damages include:
- Climate sensitivity and response lag. Equilibrium temperature rise for a doubling of CO2, and the modelled response time of climate to such a change in forcing. Hope (2006) in his PAGE 2002 model found that, as climate sensitivity was varied from 1.5°–5°C, the model identified a strong correlation with SCC.
- Coverage of abrupt or catastrophic changes, such as the crossing of the THC threshold (Keller et al., 2000 and 2004; Mastrandrea and Schneider, 2001; Hall and Behl, 2006) or the release of methane from permafrost and the weakening of carbon sinks. The Stern Review (2006) finds that such abrupt changes may more than double the market damages (e.g. from 2.1% to 5% of global GDP) if temperatures were to rise by 7.4°C in 2200.
- Inclusion and social value of non-market impacts: what value will future generations place on impacts, such as the quality of landscape or biodiversity?
- Valuation methods for market impacts such as the value of life.
- Adaptative capacity: social costs will be magnified if climate change impacts fall on fragile economies.
- Predictive capacity: studies finding efficient adaptation assume that actors decide using perfect foresight (after a learning process; see Mendelsohn and Williams, 2004). Higher costs are found if one considers the volatility of climate signals and transaction costs. For agriculture, Parry et al. (2004) shows the costs of a mismatch between expectations and real climate change (sunk costs, value of real estates, and of capital stock).
- Geographic downscaling: using a geographic-economic cross-sectional (1990) database, Nordhaus (2006a) concludes that this downscaling leads to increased damage costs, from previous 0.7% estimates to 3% of world output for a 3°C increase in global mean temperature.
- The propagation of local economic and social shocks: this blurs the distinction between winners and losers. The magnitude of this type of indirect impact depends on the existence of compensation mechanisms, including direct assistance and insurance as well as on how the cross-sectoral interdependences and transition costs are captured by models (see Section 3.5.1).
The influence of this set of parameters, which is set differently in various studies, explains the wide range of estimates for the SCC.
In an economically-efficient mitigation response, the marginal costs of mitigation should be equated to the marginal benefits of emission reduction. The marginal benefits are the avoided damages for an additional tonne of carbon abated within a given emission pathway, also known as the SCC. As discussed in Section 3.6, both sides of this equation are uncertain, which is why a sequential or iterative decision-making framework, with progressive resolution of information, is needed. Despite a paucity of analytical results in this area, it is possible to draw on today’s literature to make a first comparison between the range of SCC estimates and the range of marginal costs of mitigation across different scenarios. IPCC (2007b, Chapter 20) reviews ranges of SCC from available literature. Allowing for a range of SCC between 4–95 US$/tCO2 (14–350 US$/tC from Tol (2005b) median and 95th percentile estimates) and assuming a 2.4% per year increase (IPCC, 2007b, Chapter 20), produces a range of estimates for 2030 of 8–189 US$/tCO2. The mitigation studies in this chapter suggest carbon prices in 2030 of 1–24 US$/tCO2-eq for category IV scenarios, 18–79 US$/tCO2-eq for category III scenarios, and 31–121 US$/tCO2-eq for category I and II scenarios (see Sections 3.3 and 3.6).