Cost of climate change

Our knowledge of the costs of climate change impacts is still poor. The lack of adequate sectoral studies and understanding of local to regional interactions rules out establishing a central estimate of the social cost of carbon SCC with any confidence. Estimates of the SCC are particularly sensitive to the choice of discount rates and the temporal profile of net damages

Significant improvement in estimates of the SCC will require validated assessments at the regional scale of the dynamic of vulnerability and adaptation. Partnerships among researchers and stakeholders in developing countries are essential. The risk matrix of uncertainty in climate and economic value of impacts can be assessed based on evaluation of three sources of uncertainty, related to climate change, valuation of impacts and parameters in the decision framework. Economic valuation becomes increasingly tentative as the impacts move beyond market to non-market sectors, including effects on societies and economies as well as socially contingent feedbacks, such as conflict over water. The relative lack of studies of non-market and socially contingent effects increases uncertainty in estimates of the SCC. Modeling of trends in climate change also handles choices in the decision framework, such as discount rates, equity weighting, and risk ambiguity.

Framing of estimates of the SCC project future climate change and understanding of economic valuation ranging from projections of global and regional temperature, to scenarios of changes in precipitation and risk of storms, to systemic, large scale changes such as collapse of the West Antarctic Ice Sheet, shift in ocean circulations, or reversal of the biosphere carbon sink.

While the market effects can be described, the impacts over large areas and time scales are not linear and therefore difficult to value. For example, what would be the value of displacement of all of the major world coastal cities due to a 3-5m sea level rise?
Effects on non-market sectors are more difficult to value in that there are little empirical data on how people in different countries and economic classes value amenities, species, landscapes and other qualities of livelihoods. Contingent valuation based on willingness to pay or willingness to accept give some guidance, but such values are often contentious and may not scale up from local issues to the effects of climate change.

Catastrophic effects that lead to global losses of species are even more difficult to value, not least because the impacts of climate change on global ecosystems and species biodiversity is not well understood. The socially contingent column captures the secondary effects and multiple stresses of climate change across a range of sectors. For instance, it is possible that reasonably small changes in climate change could lead to significant impacts through multipliers such as the effect of water shortages on agriculture, high vulnerabilities such as migration from tropical storm and behavioural responses to the risk such as refuse to invest in agriculture due to perceived increase in drought risk.

The term, social cost of carbon (SCC), generally refers to the marginal cost of climate change impacts. The SCC is usually estimated as the present value of the impact over the next 100 years of one additional ton of carbon emitted to the atmosphere today.

Uncertainties and choices in the evaluation influence the final social cost of carbon. For instance:
• A high economic growth often lead to less vulnerability to climatic risks, at least in the loss of life, as wealthier societies can afford a wider range of adaptation strategies.
• Climate change effects of temperature are included, but quantified impacts of changes of drought over years are not
• Impacts of livelihood are not easily increased in a regional model based on GDP per capita or the share of agriculture in the economy.
• Adaptation over time weakens impacts in many sectors for instance as farmers adjust to new climate; while responses to climate changes could accelerate effective adaptation and lower the costs.
• The choice of valuation methods, for instance willingness to pay or willingness to avoid damages, is at least as important as the major scenario.
• Equity compensates for the different value of marginal impacts to poor people compared to rich people; but it does not account for rights or vulnerability.
• A precautionary approach seeks to avoid damages without offsetting benefits.


Perhaps the most controversial issue to have arisen in the context of estimating the social cost of carbon has been how to aggregate the valuation of impacts across geographical regions that exhibit huge disparities in income. This is important in the context of climate change because a significant proportion of the impacts do not have a market value; therefore, willingness to pay (which is income led) to avoid, or willingness to accept compensation to put up with, the impacts is generally used to proxy their value.

The effect of equity weighting is that it allows welfare equivalents to be compared since a “dollar to a poor man” is worth more than a “dollar to a rich man”. Therefore, it accounts for the fact that if a poor person were to be given an amount of money, then he/she would value that money far more than if it were given to a person who already was very rich. If money is to be used as a proxy for welfare then it is necessary to make assumptions regarding the change in marginal utility when income changes. Studies that simply aggregate impact valuations with no correction for relative incomes are implicitly assuming that the marginal utility of income is the same for everyone. In other words, the additional welfare gained from each additional unit of income received by any individual (irrespective of their state of income) is constant. However, a reasonable economic assumption that is mentioned/advocated in some studies is that the marginal utility of income declines as incomes rise. In other words, the income elasticity of the marginal utility of income is negative.

Our understanding of future climatic risks, trends and surprises in the climate system, exposure to impacts, and adaptive capacity, is improving, but knowledge of the cost of climate change impacts is still poor. A range of experts were asked to provide estimates of the SCC for some 30 prescribed scenarios of climate change, coverage of impacts sectors, and choices (such as discount rate). The experts included well-known advocates for a high SCC as well as for low SCC values. Each expert was asked to rate their confidence in each response. This question was not benchmarked in any way.the interviewer did not prompt the respondent to secure the range. The confidence ratings are subjective. The experts received the results with an opportunity to comment on the conclusions.but this was not an exercise nor was it designed to achieve a consensus among the experts.

Of the nearly 450 scenario-responses, fully 70% had a confidence rating of very low or low. None of the scenarios were judged a confidence of very high and only 3% had a high confidence. The lack of adequate studies of local to regional interactions prevents establishing a central estimate of the social cost of carbon with high confidence.

In a field where estimates are well understood, a probabilistic assessment can be made that produces a central estimate. Examination of the probability distributions for different scenarios and compared for different models then clarifies whether the central estimate is robust. Tol (2004) reviewed published estimates of the SCC. The 103 estimates from 28 published studies were used to calculate the distribution of the SCC.

Tol filtered the estimates using four schemes:
1. The simple average of all of the 103 estimates results in a mean value of the marginal damages of £80/tC, with a standard deviation of £175/tC
2. For studies that report more than one estimate, the authors generally provide a weight for the various estimates.
3. Tol calculated his own weights for each study based on six criteria: whether they had been peer reviewed, were independent impact assessments, had included dynamic climate change scenarios rather than equilibrium responses, used economic scenarios, calculated the marginal damage costs, and the year of publication. This weighting scheme results in a mean estimate of £85/tC, still with a high standard of deviation
4. If only the peer reviewed studies are included, with above weights applied, the estimates are much lower.

Pure Rate of Time Preference
The rate at which individuals discount future consumption, on the assumption of an unchanging level of consumption per capita over time, is called the Pure Rate of Time Preference (PRTP). The Green Book suggests a PRTP of around 1.5 per cent a year for the near future. If per capita consumption is expected to grow over time, future consumption will be plentiful relative to the present and thus have lower marginal utility.

Tol emphasises the discount rate and aggregation across countries as the two most significant factors explaining the range of results. However, it is likely that these are only two of the most salient differences recorded in the studies, and further uncertainties may be important.


What do we know about the decomposition of the estimates to the sectoral and regional level?
None of the methods provide sufficient disaggregation to analyse our confidence in the SCC estimates. Five concerns are apparent in the analysis of the disaggregated results:

- regional and sectoral balance of impacts,
- regional validation,
- independence of the sectoral damages,
- aggregating damages and distribution of winners and losers, and other constraints on impacts.

Regions with net costs near 0 including the Middle East, and small island states, are likely to have significant impacts in some sectors. Some justification can be made for treating a country or regional economy as one unit., to the extent that trade-offs between winners and losers within an economy can be addressed by specific policies. Even so, the balance of effects between one sector and another may be difficult to accommodate. For example, reduced heating costs will benefit northern Europe while increased cost of air conditioning and cooling will be significant in southern Europe. And, reduced heating costs might not compensate for loss of land and species due to sea level rise. The sectors where damages are significant may be a primary concern for decision makers.

A conclusion from this analysis is that regional-sectoral estimates of the SCC are not well validated, and those produced from global models should not be taken as reliable regional or sectoral estimates. This does not necessarily lead to the conclusion that existing global estimates of the SCC are unrealistic. The model results presented here are based on multiple runs using a range of input. To some extent, the uncertainty at the region-sector level should be reduced in aggregating to the global level.a specific region-sector may have a low estimate in one run and a high estimate in another run. This reinforces the need to understand the sources of uncertainty in the SCC and to evaluate the estimates in an explicit risk framework. The regional sectoral validation remains a high priority if better estimates of the SCC are to be developed and used.


SEI Oxford Univ, Social Cost of Carbon: A Closer Look at Uncertainty, 2006
Estimating Social Cost of Carbon Emission; Government Economic Service Working Paper 140,DEFRA, 2005