Economics of global warming

The economics of global warming concerns the economic aspects of global warming; this can inform policies that governments might consider in response. A number of factors make this a difficult problem from both economic and political perspectives: it is a long-term, intergenerational problem;^[1] benefits and costs are distributed unequally both within and across countries; and scientific and public opinions may diverge.

One of the most important greenhouse gases is carbon dioxide (CO₂).^[2] Around 20% of carbon dioxide which is emitted due to human activities can remain in the atmosphere for many thousands of years.^[3] The long time scales and uncertainty associated with global warming have led analysts to develop "scenarios" of future environmental, social and economic changes.^[4] These scenarios can help governments understand the potential consequences of their decisions.

The impacts of climate change include the loss of biodiversity, sea level rise, increased frequency and severity of some extreme weather events, and acidification of the oceans.^[5] Economists have attempted to quantify these impacts in monetary terms, but these assessments can be controversial.^[6][7]

The two main policy responses to global warming are to reduce greenhouse gas emissions (climate change mitigation) and to adapt to the impacts of global warming (e.g., by building levees in response to sea level rise). Another policy response which has recently received greater attention is geoengineering of the climate system (e.g. injecting aerosols into the atmosphere to reflect sunlight away from the Earth's surface).^[8]

One of the responses to the uncertainties of global warming is to adopt a strategy of sequential decision making.^[9] This strategy recognizes that decisions on global warming need to be made with incomplete information, and that decisions in the near term will have potentially long-term impacts. Governments might choose to use risk management as part of their policy response to global warming.^[10] For instance, a risk-based approach can be applied to climate impacts which are difficult to quantify in economic terms,^[10] e.g., the impacts of global warming on indigenous peoples.

Analysts have assessed global warming in relation to sustainable development.^[11] Sustainable development considers how future generations might be affected by the actions of the current generation. In some areas, policies designed to address global warming may contribute positively towards other development objectives.^[12][13] In other areas, the cost of global warming policies may divert resources away from other socially and environmentally beneficial investments (the opportunity costs of climate change policy).^[12][13]

Scenarios

One of the economic aspects of climate change is producing scenarios of future economic development. Future economic developments can, for example, affect how vulnerable society is to future climate change,^[14] what the future impacts of climate change might be, as well as the level of future GHG emissions.^[15]

Emissions scenarios

In scenarios designed to project future GHG emissions, economic projections, e.g., changes in future income levels, will often necessarily be combined with other projections that affect emissions, e.g., future population levels.^[16] Since these future changes are highly uncertain, one approach is that of scenario analysis.^[4] In scenario analysis, scenarios are developed that are based on differing assumptions of future development patterns. An example of this are the "SRES" emissions scenarios produced by the Intergovernmental Panel on Climate Change (IPCC). The SRES scenarios project a wide range of possible future emissions levels.^[17] The SRES scenarios are "baseline" or "non-intervention" scenarios, in that they assume no specific policy measures to control future GHG emissions.^[18] The different SRES scenarios contain widely differing assumptions of future social and economic changes. For example, the SRES "A2" emissions scenario projects a future population level of 15 billion people in the year 2100, but the SRES "B1" scenario projects a lower population level of 7 billion people.^[19] The SRES scenarios were not assigned probabilities by the IPCC, but some authors^[20][21] have argued that particular SRES scenarios are more likely to occur than others.

Some analysts have developed scenarios that project a continuation of current policies into the future. These scenarios are sometimes called "business-as-usual" scenarios.^[22]

Experts who work on scenarios tend to prefer the term "projections" to "forecasts" or "predictions".^[23] This distinction is made to emphasize the point that probabilities are not assigned to the scenarios,^[23] and that future emissions depend on decisions made both now and into the future.^[24]:75

Another approach is that of uncertainty analysis,^[4] where analysts attempt to estimate the probability of future changes in emission levels.

Global futures scenarios

"Global futures" scenarios can be thought of as stories of possible futures.^[25] They allow for the description of factors which are difficult to quantify but are important in affecting future GHG emissions. The IPCC Third Assessment Report (Morita et al., 2001)^[26] includes an assessment of 124 global futures scenarios. These scenarios project a wide range of possible futures. Some are pessimistic, for example, 5 scenarios project the future breakdown of human society.^[27] Others are optimistic, for example, in 5 other scenarios, future advances in technology solve most or all of humanity's problems. Most scenarios project increasing damage to the natural environment, but many scenarios also project this trend to reverse in the long-term.^[28]

In the scenarios, Morita et al. (2001)^[29] found no strong patterns in the relationship between economic activity and GHG emissions. By itself, this relationship is not proof of causation, and is only reflective of the scenarios that were assessed.

In the assessed scenarios, economic growth is compatible with increasing or decreasing GHG emissions.^[29] In the latter case, emissions growth is mediated by increased energy efficiency, shifts to non-fossil energy sources, and/or shifts to a post-industrial (service-based) economy. Most scenarios projecting rising GHGs also project low levels of government intervention in the economy. Scenarios projecting falling GHGs generally have high levels of government intervention in the economy.^[29]

Factors affecting emissions growth

Changes in components of the Kaya identity between 1971 and 2009. Includes global energy-related CO
2 emissions, world population, world GDP per capita, energy intensity of world GDP and carbon intensity of world energy use.^[30]

Historically, growth in GHG emissions have been driven by economic development.^[31]:169 One way of understanding trends in GHG emissions is to use the Kaya identity.^[16] The Kaya identity breaks down emissions growth into the effects of changes in human population, economic affluence, and technology:^[16][31]:177

CO
2 emissions from energy ≡

Population × (gross domestic product (GDP) per head of population) × (energy use / GDP) × (CO
2 emissions / energy use)

GDP per person (or "per capita") is used as a measure of economic affluence, and changes in technology are described by the other two terms: (energy use / GDP) and (energy-related CO
2 emissions / energy use). These two terms are often referred to as "energy intensity of GDP" and "carbon intensity of energy", respectively.^[32] Note that the abbreviated term "carbon intensity" may also refer to the carbon intensity of GDP, i.e., (energy-related CO
2 emissions / GDP).^[32]

Reductions in the energy intensity of GDP and/or carbon intensity of energy will tend to reduce energy-related CO
2 emissions.^[31]:177 Increases in population and/or GDP per capita will tend to increase energy-related CO
2 emissions. If, however, energy intensity of GDP or carbon intensity of energy were reduced to zero (i.e., complete decarbonization of the energy system), increases in population or GDP per capita would not lead to an increase in energy-related CO
2 emissions.

The graph on the right shows changes in global energy-related CO
2 emissions between 1971 and 2009. Also plotted are changes in world population, world GDP per capita, energy intensity of world GDP, and carbon intensity of world energy use. Over this time period, reductions in energy intensity of GDP and carbon intensity of energy use have been unable to offset increases in population and GDP per capita. Consequently, energy-related CO
2 emissions have increased. Between 1971 and 2009, energy-related CO
2 emissions grew on average by about 2.8% per year.^[30] Population grew on average by about 2.1% per year and GDP per capita by 2.6% per year.^[30] Energy intensity of GDP on average fell by about 1.1% per year, and carbon intensity of energy fell by about 0.2% per year.^[30]

Trends and projections

Emissions

Equity and GHG emissions

In considering GHG emissions, there are a number of areas where equity is important. In common language equity means "the quality of being impartial" or "something that is fair and just."^[33] One example of the relevance of equity to GHG emissions are the different ways in which emissions can be measured.^[34] These include the total annual emissions of one country, cumulative emissions measured over long time periods (sometimes measured over more than 100 years), average emissions per person in a country (per capita emissions), as well as measurements of energy intensity of GDP, carbon intensity of GDP, or carbon intensity of energy use (discussed earlier).^[34] Different indicators of emissions provide different insights relevant to climate change policy, and have been an important issue in international climate change negotiations (e.g., see Kyoto Protocol#Negotiations).^[35]

Developed countries' past contributions to climate change were in the process of economically developing to their current level of prosperity; developing countries are attempting to rise to this level, this being one cause of their increasing greenhouse gas emissions.^[36]

Equity is an issue in GHG emissions scenarios. For example, the scenarios used in the Intergovernmental Panel on Climate Change's (IPCC) First Assessment Report of 1990 were criticized by Parikh (1992).^[37] Parikh (1992)^[37] argued that the stabilization scenarios contained in the Report "stabilize the lifestyles of the rich and adversely affect the development of the poor". The IPCC's later "SRES" scenarios, published in 2000, explicitly explore scenarios with a narrowing income gap (convergence) between the developed and developing countries.^[38] Projections of convergence in the SRES scenarios have been criticized for lacking objectivity (Defra/HM Treasury, 2005).^[39]

Emissions projections

Projected total carbon dioxide emissions between 2000–2100 using the six illustrative "SRES" marker scenarios.^[40]

Changes in future greenhouse gas emission levels are highly uncertain, and a wide range of quantitative emission projections have been produced.^[41] Rogner et al. (2007)^[42] assessed these projections. Some of these projections aggregate anthropogenic emissions into a single figure as a "carbon dioxide equivalent" (CO₂-eq). By 2030, baseline scenarios projected an increase in greenhouse emissions (the F-gases, nitrous oxide, methane, and CO₂, measured in CO₂-eq)^[43] of between 25% and 90%, relative to the 2000 level.^[42] For CO₂ only, two-thirds to three-quarters of the increase in emissions was projected to come from developing countries, although the average per capita CO₂ emissions in developing country regions were projected to remain substantially lower than those in developed country regions.^[42]

By 2100, CO₂-eq projections ranged from a 40% reduction to an increase in emissions of 250% above their levels in 2000.^[42]

Concentrations and temperatures

As mentioned earlier, impacts of climate change are determined more by the concentration of GHGs in the atmosphere than annual GHG emissions.^[44] Changes in the atmospheric concentrations of the individual GHGs are given in greenhouse gas.

Rogner et al. (2007)^[45] reported that the then-current estimated total atmospheric concentration of long-lived GHGs^[46] was around 455 parts-per-million (ppm) CO₂-eq (range: 433-477 ppm CO₂-eq). The effects of aerosol and land-use changes (e.g., deforestation) reduced the physical effect (the radiative forcing) of this to 311 to 435 ppm CO₂-eq, with a central estimate of about 375 ppm CO₂-eq. The 2011 estimate of CO₂-eq concentrations (the long-lived GHGs, made up of CO₂, methane (CH
4), nitrous oxide (N
2O), chlorofluorocarbon-12 (CFC-12), CFC-11, and fifteen other halogenated gases)^[47] is 473 ppm CO₂-eq (NOAA, 2012).^[48] The NOAA (2012)^[48] estimate excludes the overall cooling effect of aerosols (e.g., sulfate).

Six of the SRES emissions scenarios have been used to project possible future changes in atmospheric CO₂ concentrations.^[49][50] For the six illustrative SRES scenarios, IPCC (2001)^[49] projected the concentration of CO₂ in the year 2100 as ranging between 540 and 970 parts-per-million (ppm) . Uncertainties such as the removal of carbon from the atmosphere by "sinks" (e.g., forests) increase the projected range to between 490 and 1,260 ppm.^[49] This compares to a pre-industrial (taken as the year 1750) concentration of 280 ppm, and a concentration of 390.5 ppm in 2011.^[51]

Temperature

Indicative probabilities of exceeding various increases in global mean temperature for different stabilization levels of atmospheric GHG concentrations.

Atmospheric GHG concentrations can be related to changes in global mean temperature by the climate sensitivity.^[52] Projections of future global warming are affected by different estimates of climate sensitivity.^[53] For a given increase in the atmospheric concentration of GHGs, high estimates of climate sensitivity suggest that relatively more future warming will occur, while low estimates of climate sensitivity suggest that relatively less future warming will occur.^[52] Lower values would correspond with less severe climate impacts, while higher values would correspond with more severe impacts.^[54]

In the scientific literature, there is sometimes a focus on "best estimate" or "likely" values of climate sensitivity.^[55] However, from a risk management perspective (discussed below), values outside of "likely" ranges are relevant, because, though these values are less probable, they could be associated with more severe climate impacts^[54] (the statistical definition of risk = probability of an impact × magnitude of the impact).^[56]

Analysts have also looked at how uncertainty over climate sensitivity affects economic estimates of climate change impacts. Hope (2005),^[57] for example, found that uncertainty over the climate sensitivity was the most important factor in determining the social cost of carbon (an economic measure of climate change impacts).

Cost–benefit analysis

Standard cost–benefit analysis (CBA)^[58] (also referred to as a monetized cost–benefit framework)^[59] can be applied to the problem of climate change.^[60] This requires (1) the valuation of costs and benefits using willingness to pay (WTP) or willingness to accept (WTA) compensation^{[59][61][62][63]} as a measure of value,^[58] and (2) a criterion for accepting or rejecting proposals:^[58]

For (1), in CBA where WTP/WTA is used, climate change impacts are aggregated into a monetary value,^[59] with environmental impacts converted into consumption equivalents,^[64] and risk accounted for using certainty equivalents.^[64][65] Values over time are then discounted to produce their equivalent present values.^[66]

The valuation of costs and benefits of climate change can be controversial^[67] because some climate change impacts are difficult to assign a value to, e.g., ecosystems and human health.^[6][68] It is also impossible to know the preferences of future generations, which affects the valuation of costs and benefits.^[69]:4 Another difficulty is quantifying the risks of future climate change.^[70]

For (2), the standard criterion is the (Kaldor-Hicks)^[69]:3 compensation principle.^[58] According to the compensation principle, so long as those benefiting from a particular project compensate the losers, and there is still something left over, then the result is an unambiguous gain in welfare.^[58] If there are no mechanisms allowing compensation to be paid, then it is necessary to assign weights to particular individuals.^[58]

One of the mechanisms for compensation is impossible for this problem: mitigation might benefit future generations at the expense of current generations, but there is no way that future generations can compensate current generations for the costs of mitigation.^[69]:4 On the other hand, should future generations bear most of the costs of climate change, compensation to them would not be possible.^[60] Another transfer for compensation exists between regions and populations. If, for example, some countries were to benefit from future climate change but others lose out, there is no guarantee that the winners would compensate the losers;^[60] similarly, if some countries were to benefit from reducing climate change but others lose out, there would likewise be no guarantee that the winners would compensate the losers.

Cost–benefit analysis and risk

In a cost–benefit analysis, an acceptable risk means that the benefits of a climate policy outweigh the costs of the policy.^[70] The standard rule used by public and private decision makers is that a risk will be acceptable if the expected net present value is positive.^[70] The expected value is the mean of the distribution of expected outcomes.^[71]:25 In other words, it is the average expected outcome for a particular decision. This criterion has been justified on the basis that:

• a policy's benefits and costs have known probabilities^[70]
• economic agents (people and organizations) can diversify their own risk through insurance and other markets.^[70]

On the first point, probabilities for climate change are difficult to calculate.^[70] Also, some impacts, such as those on human health and biodiversity, are difficult to value.^[70] On the second point, it has been suggested that insurance could be bought against climate change risks.^[70] In practice, however, there are difficulties in implementing the necessary policies to diversify climate change risks.^[70]

Risk

In order to stabilize the atmospheric concentration of CO
2, emissions worldwide would need to be dramatically reduced from their present level.^[72]

Granger Morgan et al. (2009)^[73] recommend that an appropriate response to deep uncertainty is to adopt an iterative and adaptive decision-making strategy. This contrasts with a strategy in which no action is taken until research resolves all key uncertainties.

One of the problems of climate change are the large uncertainties over the potential impacts of climate change, and the costs and benefits of actions taken in response to climate change, e.g., in reducing GHG emissions.^[74] Two related ways of thinking about the problem of climate change decision-making in the presence of uncertainty are iterative risk management^[75][76] and sequential decision making^[77] Considerations in a risk-based approach might include, for example, the potential for low-probability, worst-case climate change impacts.^[78]

An approach based on sequential decision making recognises that, over time, decisions related to climate change can be revised in the light of improved information.^[9] This is particularly important with respect to climate change, due to the long-term nature of the problem. A near-term hedging strategy concerned with reducing future climate impacts might favour stringent, near-term emissions reductions.^[77] As stated earlier, carbon dioxide accumulates in the atmosphere, and to stabilize the atmospheric concentration of CO₂, emissions would need to be drastically reduced from their present level (refer to diagram opposite).^[72] Stringent near-term emissions reductions allow for greater future flexibility with regard to a low stabilization target, e.g., 450 parts-per-million (ppm) CO₂. To put it differently, stringent near-term emissions abatement can be seen as having an option value in allowing for lower, long-term stabilization targets. This option may be lost if near-term emissions abatement is less stringent.^[79]

On the other hand, a view may be taken that points to the benefits of improved information over time. This may suggest an approach where near-term emissions abatement is more modest.^[80] Another way of viewing the problem is to look at the potential irreversibility of future climate change impacts (e.g., damages to ecosystems) against the irreversibility of making investments in efforts to reduce emissions (see also Economics of climate change mitigation#Irreversible impacts and policy).^[9] Overall, a range of arguments can be made in favour of policies where emissions are reduced stringently or modestly in the near-term (see: Economics of climate change mitigation#The mitigation portfolio).^[81]

Resilient and adaptive strategies

Granger Morgan et al. (2009)^[73] suggested two related decision-making management strategies that might be particularly appealing when faced with high uncertainty. The first were resilient strategies. This seeks to identify a range of possible future circumstances, and then choose approaches that work reasonably well across all the range. The second were adaptive strategies. The idea here is to choose strategies that can be improved as more is learned as the future progresses. Granger Morgan et al. (2009)^[73] contrasted these two approaches with the cost–benefit approach, which seeks to find an optimal strategy.

Portfolio theory

An example of a strategy that is based on risk is portfolio theory. This suggests that a reasonable response to uncertainty is to have a wide portfolio of possible responses. In the case of climate change, mitigation can be viewed as an effort to reduce the chance of climate change impacts (Goldemberg et al., 1996, p. 24).^[71] Adaptation acts as insurance against the chance that unfavourable impacts occur. The risk associated with these impacts can also be spread. As part of a policy portfolio, climate research can help when making future decisions. Technology research can help to lower future costs.

Optimal choices and risk aversion

The optimal result of decision analysis depends on how "optimal" is defined (Arrow et al., 1996.^[82] See also the section on trade offs). Decision analysis requires a selection criterion to be specified. In a decision analysis based on monetized cost–benefit analysis (CBA), the optimal policy is evaluated in economic terms. The optimal result of monetized CBA maximizes net benefits. Another type of decision analysis is cost-effectiveness analysis. Cost-effectiveness analysis aims to minimize net costs.

Monetized CBA may be used to decide on the policy objective, e.g., how much emissions should be allowed to grow over time. The benefits of emissions reductions are included as part of the assessment.

Unlike monetized CBA, cost-effectiveness analysis does not suggest an optimal climate policy. For example, cost-effectiveness analysis may be used to determine how to stabilize atmospheric greenhouse gas concentrations at lowest cost. However, the actual choice of stabilization target (e.g., 450 or 550 ppm carbon dioxide equivalent), is not "decided" in the analysis.

The choice of selection criterion for decision analysis is subjective.^[82] The choice of criterion is made outside of the analysis (it is exogenous). One of the influences on this choice on this is attitude to risk. Risk aversion describes how willing or unwilling someone is to take risks. Evidence indicates that most, but not all, individuals prefer certain outcomes to uncertain ones. Risk-averse individuals prefer decision criteria that reduce the chance of the worst possible outcome, while risk-seeking individuals prefer decision criteria that maximize the chance of the best possible outcome. In terms of returns on investment, if society as a whole is risk-averse, we might be willing to accept some investments with negative expected returns, e.g., in mitigation.^[83] Such investments may help to reduce the possibility of future climate damages or the costs of adaptation.

Alternative views

As stated, there is considerable uncertainty over decisions regarding climate change, as well as different attitudes over how to proceed, e.g., attitudes to risk and valuation of climate change impacts. Risk management can be used to evaluate policy decisions based a range of criteria or viewpoints, and is not restricted to the results of particular type of analysis, e.g., monetized CBA.^[84] Some authors have focused on a disaggregated analysis of climate change impacts.^[85][86] "Disaggregated" refers to the choice to assess impacts in a variety of indicators or units, e.g., changes in agricultural yields and loss of biodiversity. By contrast, monetized CBA converts all impacts into a common unit (money), which is used to assess changes in social welfare.

International insurance

Traditional insurance works by transferring risk to those better able or more willing to bear risk, and also by the pooling of risk (Goldemberg et al., 1996, p. 25).^[71] Since the risks of climate change are, to some extent, correlated, this reduces the effectiveness of pooling. However, there is reason to believe that different regions will be affected differently by climate change. This suggests that pooling might be effective. Since developing countries appear to be potentially most at risk from the effects of climate change, developed countries could provide insurance against these risks.

Authors have pointed to several reasons why commercial insurance markets cannot adequately cover risks associated with climate change (Arrow et al., 1996, p. 72).^[87] For example, there is no international market where individuals or countries can insure themselves against losses from climate change or related climate change policies.

Financial markets for risk

There are several options for how insurance could be used in responding to climate change (Arrow et al., 1996, p. 72).^[87] One response could be to have binding agreements between countries. Countries suffering greater-than-average climate-related losses would be assisted by those suffering less-than-average losses. This would be a type of mutual insurance contract. Another approach would be to trade "risk securities" among countries. These securities would amount to betting on particular climate outcomes.

These two approaches would allow for a more efficient distribution of climate change risks. They would also allow for different beliefs over future climate outcomes. For example, it has been suggested that these markets might provide an objective test of the honesty of a particular country's beliefs over climate change. Countries that honestly believe that climate change presents little risk would be more prone to hold securities against these risks.

Impacts

Distribution of impacts

Climate change impacts can be measured as an economic cost (Smith et al., 2001, pp. 936–941).^[88] This is particularly well-suited to market impacts, that is impacts that are linked to market transactions and directly affect GDP. Monetary measures of non-market impacts, e.g., impacts on human health and ecosystems, are more difficult to calculate. Other difficulties with impact estimates are listed below:

• Knowledge gaps: Calculating distributional impacts requires detailed geographical knowledge, but these are a major source of uncertainty in climate models.
• Vulnerability: Compared with developed countries, there is a limited understanding of the potential market sector impacts of climate change in developing countries.
• Adaptation: The future level of adaptive capacity in human and natural systems to climate change will affect how society will be impacted by climate change. Assessments may under- or overestimate adaptive capacity, leading to under- or overestimates of positive or negative impacts.
• Socioeconomic trends: Future predictions of development affect estimates of future climate change impacts, and in some instances, different estimates of development trends lead to a reversal from a predicted positive, to a predicted negative, impact (and vice versa).

In a literature assessment, Smith et al. (2001, pp. 957–958) concluded, with medium confidence, that:

• climate change would increase income inequalities between and within countries.
• a small increase in global mean temperature (up to 2 °C, measured against 1990 levels) would result in net negative market sector impacts in many developing countries and net positive market sector impacts in many developed countries.

With high confidence, it was predicted that with a medium (2–3 °C) to high level of warming (greater than 3 °C), negative impacts would be exacerbated, and net positive impacts would start to decline and eventually turn negative.

Water scarcity due to climate change is predicted to decrease global gross domestic product (gross world product) according to a recent report by the World Bank, which predicts that this “severe hit” will spur conflict and migration across the Middle East, Central Asia, and Africa.^[89]

Aggregate impacts

Aggregating impacts adds up the total impact of climate change across sectors and/or regions (IPCC, 2007a, p. 76).^[90] In producing aggregate impacts, there are a number of difficulties, such as predicting the ability of societies to adapt climate change, and estimating how future economic and social development will progress (Smith et al., 2001, p. 941).^[88] It is also necessary for the researcher to make subjective value judgements over the importance of impacts occurring in different economic sectors, in different regions, and at different times.

Smith et al. (2001, p. 958) assessed the literature on the aggregate impacts of climate change. With medium confidence, they concluded that a small increase in global average temperature (up to 2 °C, measured against 1990 levels) would result in an aggregate market sector impact of plus or minus a few percent of world GDP. Smith et al. (2001) found that for a small to medium (2-3 °C) global average temperature increase, some studies predicted small net positive market impacts. Most studies they assessed predicted net damages beyond a medium temperature increase, with further damages for greater (more than 3 °C) temperature rises.

Comparison with SRES projections

IPCC (2001, p. 74) compared their literature assessment of the aggregate market sector impacts of climate change against projections of future increases in global mean temperature.^[91] Temperature projections were based on the six illustrative SRES emissions scenarios. Projections for the year 2025 ranged from 0.4 to 1.1 °C. For 2050, projections ranged from 0.8 to 2.6 °C, and for 2100, 1.4 to 5.8 °C. These temperature projections correspond to atmospheric CO₂ concentrations of 405–460 ppm for the year 2025, 445–640 ppm for 2050, and 540–970 ppm for 2100.

Adaptation and vulnerability

IPCC (2007a) defined adaptation (to climate change) as "[initiatives] and measures to reduce the vulnerability of natural and human systems against actual or expected climate change effects" (p. 76).^[90] Vulnerability (to climate change) was defined as "the degree to which a system is susceptible to, and unable to cope with, adverse effects of climate change, including climate variability and extremes" (p. 89).

Autonomous and planned adaptation

Autonomous adaptation are adaptations that are reactive to climatic stimuli, and are done as a matter of course without the intervention of a public agency. Planned adaptation can be reactive or anticipatory, i.e., undertaken before impacts are apparent. Some studies suggest that human systems have considerable capacity to adapt autonomously (Smit et al., 2001:890).^[92] Others point to constraints on autonomous adaptation, such as limited information and access to resources (p. 890). Smit et al. (2001:904) concluded that relying on autonomous adaptation to climate change would result in substantial ecological, social, and economic costs. In their view, these costs could largely be avoided with planned adaptation.

Costs and benefits

A literature assessment by Adger et al. (2007:719) concluded that there was a lack of comprehensive, global cost and benefit estimates for adaptation.^[93] Studies were noted that provided cost estimates of adaptation at regional level, e.g., for sea-level rise. A number of adaptation measures were identified as having high benefit-cost ratios.

Adaptive capacity

Adaptive capacity is the ability of a system to adjust to climate change. Smit et al. (2001:895–897) described the determinants of adaptive capacity:^[92]

• Economic resources: Wealthier nations are better able to bear the costs of adaptation to climate change than poorer ones.
• Technology: Lack of technology can impede adaptation.
• Information and skills: Information and trained personnel are required to assess and implement successful adaptation options.
• Social infrastructure
• Institutions: Nations with well-developed social institutions are believed to have greater adaptive capacity than those with less effective institutions, typically developing nations and economies in transition.
• Equity: Some believe that adaptive capacity is greater where there are government institutions and arrangements in place that allow equitable access to resources.

Smit et al. (2001) concluded that:

• countries with limited economic resources, low levels of technology, poor information and skills, poor infrastructure, unstable or weak institutions, and inequitable empowerment and access to resources have little adaptive capacity and are highly vulnerable to climate change (p. 879).
• developed nations, broadly speaking, have greater adaptive capacity than developing regions or countries in economic transition (p. 897).

Enhancing adaptive capacity

Smit et al. (2001:905) concluded that enhanced adaptive capacity would reduce vulnerability to climate change. In their view, activities that enhance adaptive capacity are essentially equivalent to activities that promote sustainable development.^[92] These activities include (p. 899):

• improving access to resources
• reducing poverty
• lowering inequities of resources and wealth among groups
• improving education and information
• improving infrastructure
• improving institutional capacity and efficiency

Goklany (1995) concluded that promoting free trade – e.g., through the removal of international trade barriers – could enhance adaptive capacity and contribute to economic growth.^[94]

Regions

With high confidence, Smith et al. (2001:957–958) concluded that developing countries would tend to be more vulnerable to climate change than developed countries.^[88] Based on then-current development trends, Smith et al. (2001:940–941) predicted that few developing countries would have the capacity to efficiently adapt to climate change.

• Africa: In a literature assessment, Boko et al. (2007:435) concluded, with high confidence, that Africa's major economic sectors had been vulnerable to observed climate variability.^[95] This vulnerability was judged to have contributed to Africa's weak adaptive capacity, resulting in Africa having high vulnerability to future climate change. It was thought likely that projected sea-level rise would increase the socio-economic vulnerability of African coastal cities.
• Asia: Lal et al. (2001:536) reviewed the literature on adaptation and vulnerability. With medium confidence, they concluded that climate change would result in the degradation of permafrost in boreal Asia, worsening the vulnerability of climate-dependent sectors, and affecting the region's economy.^[96]
• Australia and New Zealand: Hennessy et al. (2007:509) reviewed the literature on adaptation and vulnerability.^[97] With high confidence, they concluded that in Australia and New Zealand, most human systems had considerable adaptive capacity. With medium confidence, some Indigenous communities were judged to have low adaptive capacity.
• Europe: In a literature assessment, Kundzewicz et al. (2001:643) concluded, with very high confidence, that the adaptation potential of socioeconomic systems in Europe was relatively high.^[98] This was attributed to Europe's high GNP, stable growth, stable population, and well-developed political, institutional, and technological support systems.
• Latin America: In a literature assessment, Mata et al. (2001:697) concluded that the adaptive capacity of socioeconomic systems in Latin America was very low, particularly in regard to extreme weather events, and that the region's vulnerability was high.^[99]
• Polar regions: Anisimov et al. (2001, pp. 804–805) concluded that:^[100]
  • within the Antarctic and Arctic, at localities where water was close to melting point, socioeconomic systems were particularly vulnerable to climate change.
  • the Arctic would be extremely vulnerable to climate change. Anisimov et al. (2001) predicted that there would be major ecological, sociological, and economic impacts in the region.
• Small islands: Mimura et al. (2007, p. 689) concluded, with very high confidence, that small islands were particularly vulnerable to climate change.^[101] Partly this was attributed to their low adaptive capacity and the high costs of adaptation in proportion to their GDP.

Systems and sectors

• Coasts and low-lying areas: According to Nicholls et al. (2007, p. 336), societal vulnerability to climate change is largely dependent on development status.^[102] Developing countries lack the necessary financial resources to relocate those living in low-lying coastal zones, making them more vulnerable to climate change than developed countries. With high confidence, Nicholls et al. (2007, p. 317) concluded that on vulnerable coasts, the costs of adapting to climate change are lower than the potential damage costs.^[103]
• Industry, settlements and society:
  • At the scale of a large nation or region, at least in most industrialized economies, the economic value of sectors with low vulnerability to climate change greatly exceeds that of sectors with high vulnerability (Wilbanks et al., 2007, p. 366).^[104] Additionally, the capacity of a large, complex economy to absorb climate-related impacts, is often considerable. Consequently, estimates of the aggregate damages of climate change – ignoring possible abrupt climate change – are often rather small as a percentage of economic production. On the other hand, at smaller scales, e.g., for a small country, sectors and societies might be highly vulnerable to climate change. Potential climate change impacts might therefore amount to very severe damages.
  • Wilbanks et al. (2007, p. 359) concluded, with very high confidence, that vulnerability to climate change depends considerably on specific geographic, sectoral and social contexts. In their view, these vulnerabilities are not reliably estimated by large-scale aggregate modelling.^[105]

Mitigation

Mitigation of climate change involves actions that are designed to limit the amount of long-term climate change (Fisher et al., 2007:225).^[106] Mitigation may be achieved through the reduction of GHG emissions or through the enhancement of sinks that absorb GHGs, e.g., forests.

International public goods

The atmosphere is an international public good, and GHG emissions are an international externality (Goldemberg et al., 1996:21, 28, 43).^[71] A change in the quality of the atmosphere does not affect the welfare of all individuals equally. In other words, some individuals may benefit from climate change, while others may lose out. This uneven distribution of potential climate change impacts, plus the uneven distribution of emissions globally, make it difficult to secure a global agreement to reduce emissions (Halsnæs et al., 2007:127).^[107]

Policies

National

Both climate and non-climate policies can affect emissions growth. Non-climate policies that can affect emissions are listed below (Bashmakov et al., 2001:409-410):^[108]

• Market-orientated reforms can have important impacts on energy use, energy efficiency, and therefore GHG emissions.
• Price and subsidy policies: Many countries provide subsidies for activities that impact emissions, e.g., subsidies in the agriculture and energy sectors, and indirect subsidies for transport.
• Market liberalization: Restructuring of energy markets has occurred in several countries and regions. These policies have mainly been designed to increase competition in the market, but they can have a significant impact on emissions.

There are a number of policies that might be used to mitigate climate change, including *The Green Marshall Plan (http://nb.referata.com/w/index.php?title=Green_Marshall_Plan&action=edit) which calls for global central bank money creation to fund green infrastructure, (Bashmakov et al., 2001:412–422):

• Regulatory standards, e.g., technology or performance standards.
• Market-based instruments, such as emissions taxes and tradable permits.
• Voluntary agreements between public agencies and industry.
• Informational instruments, e.g., to increase public awareness of climate change.
• Use of subsidies and financial incentives, e.g., feed-in tariffs for renewable energy (Gupta et al., 2007:762).^[109]
• Removal of subsidies, e.g., for coal mining and burning (Barker et al., 2001:567–568).^[110]
• Demand-side management, which aims to reduce energy demand through energy audits, product labelling, etc.

International

• The Kyoto Protocol to the UNFCCC sets out legally binding emission reduction commitments for the "Annex B" countries (Verbruggen, 2007, p. 817).^[111] The Protocol defines three international policy instruments ("Flexibility Mechanisms") which can be used by the Annex B countries to meet their emission reduction commitments. According to Bashmakov et al. (2001:402), use of these instruments could significantly reduce the costs for Annex B countries in meeting their emission reduction commitments.^[108]
• Other possible policies include internationally coordinated carbon taxes and/or regulation (Bashmakov et al., 2001:430).

Finance

The International Energy Agency estimates that US$197 billion is required by states in the developing world above and beyond the underlying investments needed by various sectors regardless of climate considerations, this is twice the amount promised by the developed world at the UN Framework Convention on Climate Change (UNFCCC) Cancún Agreements.^[112] Thus, a new method is being developed to help ensure that funding is available for climate change mitigation.^[112] This involves financial leveraging, whereby public financing is used to encourage private investment.^[112]

Cost estimates

According to a literature assessment by Barker et al. (2007b:622), mitigation cost estimates depend critically on the baseline (in this case, a reference scenario that the alternative scenario is compared with), the way costs are modelled, and assumptions about future government policy.^[113] Fisher et al. (2007:204–206)^[106] (summarized by IPCC, 2007b:11)^[114] estimated macroeconomic costs in 2030 for multi-gas mitigation (reducing emissions of carbon dioxide and other GHGs, such as methane) as between a 3% decrease in global GDP to a small increase, relative to baseline. This was for an emissions pathway consistent with atmospheric stabilization of GHGs between 445 and 710 ppm CO₂-eq. In 2050, the estimated costs for stabilization between 710 and 445 ppm CO₂-eq ranged between a 1% gain to a 5.5% decrease in global GDP, relative to baseline. These cost estimates were supported by a moderate amount of evidence and much agreement in the literature (IPCC, 2007b:11,18).^[114]

Macroeconomic cost estimates made by Fisher et al. (2007:204) were mostly based on models that assumed transparent markets, no transaction costs, and perfect implementation of cost-effective policy measures across all regions throughout the 21st century. According to Fisher et al. (2007), relaxation of some or all these assumptions would lead to an appreciable increase in cost estimates. On the other hand, IPCC (2007b:8)^[114] noted that cost estimates could be reduced by allowing for accelerated technological learning, or the possible use of carbon tax/emission permit revenues to reform national tax systems.

• Regional costs were estimated as possibly being significantly different from the global average. Regional costs were found to be largely dependent on the assumed stabilization level and baseline scenario.
• Sectoral costs: In a literature assessment, Barker et al. (2001:563–564), predicted that the renewables sector could potentially benefit from mitigation.^[110] The coal (and possibly the oil) industry was predicted to potentially lose substantial proportions of output relative to a baseline scenario, with energy-intensive sectors, such as heavy chemicals, facing higher costs.

Adaptation and mitigation

The distribution of benefits from adaptation and mitigation policies are different in terms of damages avoided (Toth et al., 2001:653).^[115] Adaptation activities mainly benefit those who implement them, while mitigation benefits others who may not have made mitigation investments. Mitigation can therefore be viewed as a global public good, while adaptation is either a private good in the case of autonomous adaptation, or a national or regional public good in the case of public sector policies.

Paying for an international public good

Economists generally agree on the following two principles (Goldemberg, et al.., 1996:29):^[71]

• For the purposes of analysis, it is possible to separate equity from efficiency. This implies that all emitters, regardless of whether they are rich or poor, should pay the full social costs of their actions. From this perspective, corrective (Pigouvian) taxes should be applied uniformly (see carbon tax#Economic theory).
• It is inappropriate to redress all equity issues through climate change policies. However, climate change itself should not aggravate existing inequalities between different regions.

Some early studies suggested that a uniform carbon tax would be a fair and efficient way of reducing emissions (Banuri et al., 1996, pp. 103–104).^[116] A carbon tax is a Pigouvian tax, and taxes fuels based on their carbon content (Hoeller and Wallin, 1991, p. 92).^[117] A literature assessment by Banuri et al. (1996:103–104)^[116] summarized criticisms of such a system:

• A carbon tax would impose different burdens on countries due to existing differences in tax structures, resource endowments, and development.^[116]
• Most observers^[118] argue that such a tax would not be fair because of differences in historical emissions and current wealth.
• A uniform carbon tax would not be Pareto efficient unless lump sum transfers were made between countries.^[116] Pareto efficiency requires that the carbon tax would not make any countries worse off than they would be without the tax (Chichilnisky and Heal, 1994, p. 445;^[119] Tol, 2001, p. 72).^[120] Also, at least one country would need to be better off.

An alternative approach to having a Pigouvian tax is one based on property rights. A practical example of this would be a system of emissions trading, which is essentially a privatization of the atmosphere (Hepburn, 2007).^[121] The idea of using property rights in response to an externality was put forward by Coase (1960). Coase's model of social cost assumes a situation of equal bargaining power among participants and equal costs of making the bargain (Toth et al.., 2001:668).^[115] Assigning property rights can be an efficient solution. This is based on the assumption that there are no bargaining/transaction costs involved in buying or selling these property rights, and that buyers and sellers have perfect information available when making their decisions.

If these assumptions are correct, efficiency is achieved regardless of how property rights are allocated. In the case of emissions trading, this suggests that equity and efficiency can be addressed separately: equity is taken care of in the allocation of emission permits, and efficiency is promoted by the market system. In reality, however, markets do not live up to the ideal conditions that are assumed in Coase's model, with the result that there may be trade-offs between efficiency and equity (Halsnæs et al., 2007).^[122]

Efficiency and equity

No scientific consensus exists on who should bear the burden of adaptation and mitigation costs (Goldemberg et al.., 1996:29).^[71] Several different arguments have been made over how to spread the costs and benefits of taxes or systems based on emissions trading.

One approach considers the problem from the perspective of who benefits most from the public good. This approach is sensitive to the fact that different preferences exist between different income classes. The public good is viewed in a similar way as a private good, where those who use the public good must pay for it. Some people will benefit more from the public good than others, thus creating inequalities in the absence of benefit taxes. A difficulty with public goods is determining who exactly benefits from the public good, although some estimates of the distribution of the costs and benefits of global warming have been made – see above. Additionally, this approach does not provide guidance as to how the surplus of benefits from climate policy should be shared.

A second approach has been suggested based on economics and the social welfare function. To calculate the social welfare function requires an aggregation of the impacts of climate change policies and climate change itself across all affected individuals. This calculation involves a number of complexities and controversial equity issues (Markandya et al., 2001:460).^[123] For example, the monetization of certain impacts on human health. There is also controversy over the issue of benefits affecting one individual offsetting negative impacts on another (Smith et al.., 2001:958).^[88] These issues to do with equity and aggregation cannot be fully resolved by economics (Banuri et al.., 1996:87).^[116]

On a utilitarian basis, which has traditionally been used in welfare economics, an argument can be made for richer countries taking on most of the burdens of mitigation (Halsnæs et al., 2007).^[124] However, another result is possible with a different modeling of impacts. If an approach is taken where the interests of poorer people have lower weighting, the result is that there is a much weaker argument in favour of mitigation action in rich countries. Valuing climate change impacts in poorer countries less than domestic climate change impacts (both in terms of policy and the impacts of climate change) would be consistent with observed spending in rich countries on foreign aid (Hepburn, 2005;^[125] Helm, 2008:229).^[126]

In terms of the social welfare function, the different results depend on the elasticity of marginal utility. A declining marginal utility of consumption means that a poor person is judged to benefit more from increases in consumption relative to a richer person. A constant marginal utility of consumption does not make this distinction, and leads to the result that richer countries should mitigate less.

A third approach looks at the problem from the perspective of who has contributed most to the problem. Because the industrialized countries have contributed more than two-thirds of the stock of human-induced GHGs in the atmosphere, this approach suggests that they should bear the largest share of the costs. This stock of emissions has been described as an "environmental debt" (Munasinghe et al., 1996, p. 167).^[127] In terms of efficiency, this view is not supported. This is because efficiency requires incentives to be forward-looking, and not retrospective (Goldemberg et al., 1996, p. 29). The question of historical responsibility is a matter of ethics. Munasinghe et al. (1996, p. 167) suggested that developed countries could address the issue by making side-payments to developing countries.

Trade offs

It is often argued in the literature that there is a trade-off between adaptation and mitigation, in that the resources committed to one are not available for the other (Schneider et al., 2001:94).^[128] This is debatable in practice because the people who bear emission reduction costs or benefits are often different from those who pay or benefit from adaptation measures.

There is also a trade off in how much damage from climate change should be avoided. The assumption that it is always possible to trade off different outcomes is viewed as problematic by many people (Halsnæs et al., 2007).^[129] For example, a trade off might exist between economic growth and damages faced by indigenous cultures.

Some of the literature has pointed to difficulties in these kinds of assumptions. For instance, there may be aversion at any price towards losing particular species. It has also been suggested that low-probability, extreme outcomes are overweighted when making choices. This is related to climate change, since the possibility of future abrupt changes in the climate or the Earth system cannot be ruled out. For example, if the West Antarctic ice sheet was to disintegrate, it could result in a sea level rise of 4–6 meters over several centuries.

Cost–benefit analysis

In a cost–benefit analysis, the trade offs between climate change impacts, adaptation, and mitigation are made explicit. Cost–benefit analyses of climate change are produced using integrated assessment models (IAMs), which incorporate aspects of the natural, social, and economic sciences.

In an IAM designed for cost–benefit analysis, the costs and benefits of impacts, adaptation and mitigation are converted into monetary estimates. Some view the monetization of costs and benefits as controversial (see Economic impacts of climate change#Aggregate impacts). The "optimal" levels of mitigation and adaptation are then resolved by comparing the marginal costs of action with the marginal benefits of avoided climate change damages (Toth et al., 2001:654).^[115] The decision over what "optimal" is depends on subjective value judgements made by the author of the study (Azar, 1998).^[130]

There are many uncertainties that affect cost–benefit analysis, for example, sector- and country-specific damage functions (Toth et al., 2001:654). Another example is with adaptation. The options and costs for adaptation are largely unknown, especially in developing countries.

Results

A common finding of cost–benefit analysis is that the optimum level of emissions reduction is modest in the near-term, with more stringent abatement in the longer-term (Stern, 2007:298;^[131] Heal, 2008:20;^[132] Barker, 2008).^[133] This approach might lead to a warming of more than 3 °C above the pre-industrial level (World Bank, 2010:8).^[134] In most models, benefits exceed costs for stabilization of GHGs leading to warming of 2.5 °C. No models suggest that the optimal policy is to do nothing, i.e., allow "business-as-usual" emissions.

Along the efficient emission path calculated by Nordhaus and Boyer (2000) (referred to by Fisher et al.., 2007), the long-run global average temperature after 500 years increases by 6.2 °C above the 1900 level.^[135] Nordhaus and Boyer (2000) stated their concern over the potentially large and uncertain impacts of such a large environmental change. It should be noted that the projected temperature in this IAM, like any other, is subject to scientific uncertainty (e.g., the relationship between concentrations of GHGs and global mean temperature, which is called the climate sensitivity). Projections of future atmospheric concentrations based on emission pathways are also affected by scientific uncertainties, e.g., over how carbon sinks, such as forests, will be affected by future climate change. Klein et al. (2007) concluded that there were few high quality studies in this area, and placed low confidence in the results of cost–benefit analysis.^[136]

Hof et al. (2008) (referred to by World Bank, 2010:8) examined the sensitivity of the optimal climate target to assumptions about the time horizon, climate sensitivity, mitigation costs, likely damages, and discount rates. The optimal target was defined as the concentration that would result in the lowest reduction in the present value (i.e., discounted) of global consumption. A set of assumptions that included a relatively high climate sensitivity (i.e., a relatively large global temperature increase for a given increase in GHGs), high damages, a long time horizon, low discount rates (i.e., future consumption is valued relatively highly), and low mitigation costs, produced an optimum peak in the concentration of CO₂e at 540 parts per million (ppm). Another set of assumptions that assumed a lower climate sensitivity (lower global temperature increase), lower damages, a shorter time horizon, and a higher discount rate (present consumption is valued relatively more highly), produced an optimum peaking at 750 ppm.

Strengths

In spite of various uncertainties or possible criticisms of cost–benefit analysis, it does have several strengths:

• It offers an internally consistent and global comprehensive analysis of impacts (Smith et al., 2001:955).^[88]
• Sensitivity analysis allows critical assumptions in the analysis to be changed. This can identify areas where the value of information is highest and where additional research might have the highest payoffs (Downing, et al., 2001:119).^[137]
• As uncertainty is reduced, the integrated models used in producing cost–benefit analysis might become more realistic and useful.

Geoengineering

Geoengineering are technological efforts to stabilize the climate system by direct intervention in the Earth-atmosphere-system's energy balance (Verbruggen, 2007, p. 815).^[138] The intent of geoengineering is to reduce the amount of global warming (the observed trend of increased global average temperature (NRC, 2008, p. 2)).^[139] IPCC (2007b:15) concluded that reliable cost estimates for geoengineering options had not been published.^[114] This finding was based on medium agreement in the literature and limited evidence.

Major reports considering economics of climate change

The Intergovernmental Panel on Climate Change (IPCC) has produced several reports where the economics literature on climate change is assessed. In 1995, the IPCC produced its second set of assessment reports on climate change. Working Group III of the IPCC produced a report on the "Economic and Social Dimensions of Climate Change." In the later third and fourth IPCC assessments, published in 2001 and 2007 respectively, the assessment of the economics literature is divided across two reports produced by IPCC Working Groups II and III. In 2011 IPCC Working Group III published a Special Report on Renewable Energy Sources and Climate Change Mitigation.

The Stern Review on the Economics of Climate Change is a 700-page report released for the British government on 30 October 2006, by economist Nicholas Stern, chair of the Grantham Research Institute on Climate Change and the Environment at the London School of Economics. The report discusses the effect of global warming on the world economy.

The Garnaut Climate Change Review was a study by Professor Ross Garnaut, commissioned by then Opposition Leader, Kevin Rudd^[140] and by the Australian State and Territory Governments on 30 April 2007. After his election on 24 November 2007 Prime Minister of Australia Kevin Rudd confirmed the participation of the Commonwealth Government in the Review.

A report by the United Nations Environment Program and the World Trade Organization "provides an overview of the key linkages between trade and climate change based on a review of available literature and a survey of relevant national policies".^[141]

See also

• Business action on climate change
• Carbon credit
• Carbon finance
• Carbon neutral fuel
• Carbon tax
• CDM Gold Standard
• Climate change and agriculture
• Climate change denial
• Emissions trading
• Politics of global warming

Notes

1. IPCC, "Synthesis Report – Question 5", Climate Change 2001:Synthesis Report, Figure 5-2, in IPCC TAR SYR 2001
2. IPCC, "Summary for Policymakers", Climate Change 2007: Synthesis Report, 2. Causes of change, p.5, in IPCC AR4 SYR 2007
3. Meehl, G. A., "Chapter 10: Global Climate Projections", Climate Change 2007: Working Group I: The Physical Science Basis, Frequently Asked Question 10.3: If Emissions of Greenhouse Gases are Reduced, How Quickly do Their Concentrations in the Atmosphere Decrease?, in IPCC AR4 WG1 2007
4. Webster, M.; et al. (December 2002), Report 95: Uncertainty Analysis of Climate Change and Policy Response (PDF), Cambridge MA, USA: Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change, Joint Program Report Series, pp. 3–4
5. Smith, J.B.; et al. (Mar 2009). "Assessing dangerous climate change through an update of the Intergovernmental Panel on Climate Change (IPCC) "reasons for concern"". Proceedings of the National Academy of Sciences of the United States of America. 106 (11): 4133–4137. Bibcode:2009PNAS..106.4133S. doi:10.1073/pnas.0812355106. ISSN 0027-8424. PMC 2648893. PMID 19251662.
6. DeCanio, S.J.; et al. (2008-11-03), "3. Predicting the unpredictable and pricing the priceless", Limitations of Integrated Assessment Models of Climate Change (PDF), pp. 9–11
7. Promising Signs That Economies Can Rise as Carbon Emissions Decline April 5, 2016
8. UK Royal Society (September 2009), "Summary", RS Policy document 10/09: Geoengineering the climate: science, governance and uncertainty (PDF), London, UK: UK Royal Society, ISBN 978-0-85403-773-5. Report website
9. Goldemberg, J.; et al., "Introduction: Scope of the assessment", Sec 1.3.2 Sequential decision making, IPCC SAR WG3 1996, p. 26 (32 of PDF)
10. Abstract, in: Yohe 2010, p. 203
11. Yohe, G. W.; et al., "Ch. 20: Perspectives on Climate Change and Sustainability", Climate Change 2007: Working Group II: Impacts, Adaptation and Vulnerability, Sec 20.1 Introduction – setting the context, in IPCC AR4 WG2 2007
12. Parry, M. L.; et al., "Technical summary", Climate Change 2007: Working Group II: Impacts, Adaptation and Vulnerability, TS.5.4 Perspectives on climate change and sustainability, in IPCC AR4 WG2 2007
13. Sathaye, J.; et al., "Ch. 12: Sustainable Development and mitigation", Climate Change 2007: Working Group III: Mitigation of Climate Change, Sec. 12.3 Implications of mitigation choices for sustainable development goals, in IPCC AR4 WG3 2007
14. Wilbanks, T. J.; et al., "Chapter 7: Industry, Settlement and Society", Climate Change 2007: Working Group II: Impacts, Adaptation and Vulnerability, 7.4 Key future impacts and vulnerabilities, in IPCC AR4 WG2 2007
15. Fisher, B. S.; et al., "Chapter 3: Issues related to mitigation in the long-term context", Climate Change 2007: Working Group III: Mitigation of Climate Change, 3.1.4 Economic growth and convergence, in IPCC AR4 WG3 2007
16. Fisher, B. S.; et al., "Chapter 3: Issues related to mitigation in the long-term context", Climate Change 2007: Working Group III: Mitigation of Climate Change, 3.2.1 Drivers of emissions, in IPCC AR4 WG3 2007
17. Morita, T.; et al., "2. Greenhouse Gas Emission Mitigation Scenarios and Implications", Climate Change 2001: Working Group III: Mitigation, 2.5.1.4 Emissions and Other Results of the SRES Scenarios, in IPCC TAR WG3 2001
18. Fisher, B. S.; et al., "Chapter 3: Issues related to mitigation in the long-term context", Climate Change 2001: Working Group III: Mitigation, 3.1.2 Introduction to mitigation and stabilization scenarios, in IPCC AR4 WG3 2007
19. "Chapter 3 How climate change will affect people around the world" (PDF), Part II: The Impacts of Climate Change on Growth and Development (PDF), p. 61, in Stern 2006
20. Dietz, S.; et al. (2007). "Reflections on the Stern review (1): a robust case for strong action to reduce the risks of climate change" (PDF). World economics. 8 (1): 164. ISSN 1468-1838.
21. Tol, R. S. J. (15 January 2005), Memorandum by Professor Richard S J Tol, Hamburg, Vrije and Carnegie Mellon Universities. In (section): Select Committee on Economic Affairs Minutes of Evidence. In (report): The Economics of Climate Change, the Second Report of the 2005-2006 session, produced by the UK Parliament House of Lords Economics Affairs Select Committee, London, UK: UK Parliament website
22. "7 Projecting the Growth of Greenhouse-Gas Emissions" (PDF), Part III: The Economics of Stabilisation (PDF), p. 176, in Stern 2006
23. Ahmad, Q. K.; et al., "2. Methods and Tools", Climate Change 2001: Working Group II: Impacts, Adaptation and Vulnerability, 2.6.1. Treatments of Uncertainties in Previous IPCC Assessments, in IPCC TAR WG2 2001
24. International Energy Agency (IEA) (2009), World Energy Outlook 2009 (PDF), Paris, France: IEA, ISBN 978-92-64-06130-9
25. Morita, T.; et al., "2. Greenhouse Gas Emission Mitigation Scenarios and Implications", Climate Change 2001: Working Group III: Mitigation, 2.4.1 The Role of Global Futures Scenarios, p.137 in IPCC TAR WG3 2001
26. Morita, T.; et al., "2. Greenhouse Gas Emission Mitigation Scenarios and Implications", Climate Change 2001: Working Group III: Mitigation, 2.4.2 Global Futures Scenario Database, p.137 in IPCC TAR WG3 2001
27. Morita, T.; et al., "2. Greenhouse Gas Emission Mitigation Scenarios and Implications", Climate Change 2001: Working Group III: Mitigation, Table 2.3: Global futures scenario groups, p.139 in IPCC TAR WG3 2001
28. Morita, T.; et al., "2. Greenhouse Gas Emission Mitigation Scenarios and Implications", Climate Change 2001: Working Group III: Mitigation, 2.4.3 Global Futures Scenarios: Range of Possible Futures, p.138 in IPCC TAR WG3 2001
29. Morita, T.; et al., "2. Greenhouse Gas Emission Mitigation Scenarios and Implications", Climate Change 2001: Working Group III: Mitigation, 2.4.4 Global Futures Scenarios, Greenhouse Gas Emissions, and Sustainable Development, pp.140–141 in IPCC TAR WG3 2001
30. Based on data from the International Energy Agency (IEA, 2011), which is available to download as an Excel (XLS) spreadsheet (1,008 KB). International Energy Agency (IEA) (2011), CO₂ Emissions From Fuel Combustion: Highlights (2011 edition), Paris, France: IEA
31. "7. Projecting the Growth of Greenhouse-Gas Emissions" (PDF), Part III: The Economics of Stabilisation (PDF), in Stern 2006
32. Fisher, B. S.; et al., "Chapter 3: Issues related to mitigation in the long-term context", Climate Change 2007: Working Group III: Mitigation of Climate Change, 3.4.1 Carbon-free energy and decarbonization, pp.219-220, in IPCC AR4 WG3 2007
33. "Summary for Policymakers", IPCC SAR WG3 1996, p. 7
34. Banuri, T.; et al., "3. Equity and Social Considerations", IPCC SAR WG3 1996, pp. 92–97, 3.3.3 Patterns of greenhouse gas emissions
35. Liverman, D. M. (2008). "Conventions of climate change: constructions of danger and the dispossession of the atmosphere" (PDF). Journal of Historical Geography. 35 (2): 288–292. doi:10.1016/j.jhg.2008.08.008.
36. Sonali P. Chitre (4 April 2011). "India's Role in an International Legal Solution to the Global Climate Change Problem". SSRN. Retrieved 20 November 2011.
37. Parikh, J. (10 December 1992). "IPCC strategies unfair to the South". Nature. 360: 507–508. Bibcode:1992Natur.360..507P. doi:10.1038/360507a0.; referred to by: Banuri, T.; et al., "3. Equity and Social Considerations", IPCC SAR WG3 1996, p. 95, 3.3.3.3 Future emissions
38. Banuri, T.; et al., "1. Setting the Stage: Climate Change and Sustainable Development", Climate Change 2001: Working Group III: Mitigation, Box 1.1 A Numbers Game, in IPCC TAR WG3 2001
39. Defra/HM Treasury (February 2005). Memorandum by Defra/HM Treasury, paragraph 20. In (section): Select Committee on Economic Affairs Minutes of Evidence. In (report): The Economics of Climate Change, the Second Report of the 2005-2006 session, produced by the UK Parliament House of Lords Economics Affairs Select Committee. London, UK: The Stationery Office Ltd. Castles and Henderson have replied that [...] [the] convergence scenarios modelled by the IPCC reflect [a] normative judgement about "what is equitable and fair" (ie, a rapid closing of the gap in income per capita between industrialised countries and developing countries) rather than an objective projection.
40. SRES Final Data (version 1.1, July 2000), City of New York, USA: Socioeconomic Data and Applications Center (SEDAC), hosted by the Center for International Earth Science Information Network (CIESIN), Earth Institute, at Columbia University
41. Fisher, B. S.; et al., "3. Issues related to mitigation in the long-term context", Climate Change 2007: Working Group III: Mitigation of Climate Change, Sec 3.1 Emissions scenarios, in IPCC AR4 WG3 2007
42. Rogner, H.-H.; et al., "1. Introduction", Climate Change 2007: Working Group III: Mitigation of Climate Change, 1.3.2.4 Total GHG emissions, in IPCC AR4 WG3 2007, p. 111
43. Rogner, H.-H.; et al., "Ch 1: Introduction", Climate Change 2007: Working Group III: Mitigation of Climate Change, Figure 1.7, in IPCC AR4 WG3 2007
44. Munasinghe, M.; et al., "5. Applicability of Techniques of Cost–Benefit Analysis to Climate Change", Climate Change 1995: Economic and Social Dimensions of Climate Change in IPCC SAR WG3 1996
45. Rogner, H.-H.; et al., "Ch. 1: Introduction", Climate Change 2007: Working Group III: Mitigation of Climate Change, Sec 1.3.1 Review of the last three decades, in IPCC AR4 WG3 2007, p. 102
46. the atmospheric lifetimes of GHGs is discussed in greenhouse gas
47. CFC-113, tetrachloromethane (CCl
    4), trichloromethane (CH
    3CCl
    3), HCFCs 22, 141b and 142b, hydrofluorocarbons (HFCs) 134a, 152a, 23, 143a, and 125, SF₆, and halons 1211, 1301 and 2402
48. NOAA (Summer 2012), NOAA/ESRL Global Monitoring Division – The NOAA Annual Greenhouse Gas Index (AGGI), Boulder, Colorado, USA: NOAA/ESRL's Global Monitoring Division (formerly CMDL) of the National Oceanic and Atmospheric Administration
49. "Question 3", Climate Change 2007: Synthesis Report, 3.3, in IPCC TAR SYR 2001
50. The six "illustrative marker" scenarios cover a wide range of possible future emissions: "Synthesis report", Climate Change 2007: Working Group II: Impacts, Adaptation and Vulnerability, Sec 3.1 Emissions scenarios, in IPCC AR4 SYR 2007
51. Blasing, T. J. (February 2012), Current Greenhouse Gas Concentrations, Oak Ridge, Tennessee, USA: Carbon Dioxide Information Analysis Center (CDIAC), doi:10.3334/CDIAC/atg.032
52. "Box 8.1 Likelihood of exceeding a temperature increase at equilibrium, in: Ch 8: The Challenge of Stabilisation" (PDF), PART III: The economics of stabilisation, in Stern 2006, p. 195
53. Meehl, G. A.; et al., "Ch 10: Global Climate Projections", Climate Change 2007: Working Group I: The Physical Science Basis, Sec 10.5.4.6 Synthesis of Projected Global Temperature at Year 2100, in IPCC AR4 WG1 2007
54. Schneider, S. H.; et al., "Ch 19: Assessing Key Vulnerabilities and the Risk from Climate Change", Climate Change 2007: Working Group II: Impacts, Adaptation and Vulnerability, Sec 19.4.2.2 Scenario analysis and analysis of stabilisation targets, in IPCC AR4 WG2 2007, p. 801
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References

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• IPCC SAR WG3 (1996), Bruce, J. P.; Lee, H.; Haites, E. F., eds., Climate Change 1995: Economic and Social Dimensions of Climate Change (PDF), Contribution of Working Group III (WG3) to the Second Assessment Report (SAR) of the Intergovernmental Panel on Climate Change (IPCC), Cambridge University Press, ISBN 0-521-56051-9 (pb: 0-521-56854-4)
• IPCC TAR WG2 (2001), McCarthy, J. J.; Canziani, O. F.; Leary, N. A.; Dokken, D. J.; White, K. S., eds., Climate Change 2001: Impacts, Adaptation and Vulnerability, Contribution of Working Group II (WG2) to the Third Assessment Report (TAR) of the Intergovernmental Panel on Climate Change (IPCC), Cambridge University Press, ISBN 0-521-80768-9 (pb: 0-521-01500-6).
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• IPCC AR4 WG2 (2007), Parry, M. L.; Canziani, O. F.; Palutikof, J. P.; van der Linden, P. J.; Hanson, C. E., eds., Climate Change 2007: Impacts, Adaptation and Vulnerability, Contribution of Working Group II (WG2) to the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), Cambridge University Press, ISBN 978-0-521-88010-7 (pb: 978-0-521-70597-4).
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• IPCC AR4 SYR (2007), Core Writing Team; Pachauri, R.K; Reisinger, A., eds., Climate Change 2007: Synthesis Report (SYR), Contribution of Working Groups I, II and III to the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), Geneva, Switzerland: IPCC, ISBN 92-9169-122-4
• Stern, N. (2006), Stern Review Report on the Economics of Climate Change (pre-publication edition), London, UK: HM Treasury

• Stern, N. (2008), "The Economics of Climate Change", American Economic Review, 98 (2), p. 23. Paper website at the American Economic Association.

• US NRC (2011), America's Climate Choices. A report by the Committee on America's Climate Choices, National Research Council (US NRC), Washington, D.C., USA: The National Academy Press, ISBN 978-0-309-14585-5

• Yohe, G.W. (May 2010), Addressing Climate Change through a Risk Management Lens. In: Assessing the Benefits of Avoided Climate Change: Cost-Benefit Analysis and Beyond. (Gulledge, J., L. J. Richardson, L. Adkins, and S. Seidel (eds.)), Proceedings of Workshop on Assessing the Benefits of Avoided Climate Change, March 16–17, 2009 (PDF), Arlington, Virginia, USA: Pew Center on Global Climate Change. Link to workshop.

Further reading

• DESA (2009). World Economic and Social Survey 2009: Promoting Development, Saving the Planet. Produced by the Department of Economic and Social Affairs of the United Nations Secretariat (PDF). Printed by the United Nations, Publishing Section, New York. ISBN 978-92-1-109159-5. Retrieved 2010-06-08.
• International Monetary Fund (April 2008). "Chapter 4. Climate Change and the Global Economy. In: World Economic and Financial Surveys: World Economic Outlook: Housing and the Business Cycle". IMF website. Retrieved 2010-04-21.
• Working Group III to the Second Assessment Report of the Intergovernmental Panel on Climate Change (1996). "Summary for Policymakers". In Bruce, JP; Lee Hoesung; Haites, EF. Climate Change 1995: Economic and Social Dimensions of Climate Change (PDF). Cambridge, UK: Press Syndicate of the University of Cambridge.
• Nordhaus, W. D., ed. (1998). Economics and Policy Issues in Climate Change. Washington, D.C.: RFF Press. p. 336. ISBN 0-915707-95-0.
• Touffut, Jean-Philippe, ed. (2009). Changing Climate, Changing Economy. Cheltenham, UK & Northampton, Massachusetts, USA: Edward Elgar. ISBN 978-1-84844-836-0. Contributors: Michel Armatte, Jean-Pierre Dupuy, Olivier Godard, Inge Kaul, Thomas Schelling, Robert M. Solow, Nicholas Stern, Thomas Sterner and Martin L. Weitzman.
• Mendelsohn, Robert (Editor-in-Chief). "Climate Change Economics (CCE)". Hackensack, New Jersey, USA: World Scientific. ISSN 2010-0078.
• Curated bibliography at IDEAS/RePEc

External links

• Intergovernmental Panel on Climate Change Working Groups II and III
• Climate change on the United Nations Economic and Social Development (UNESD) Division for Sustainable Development website.
• Climate change at the World Bank.
• Centre for Climate Change Economics and Policy at University of Leeds and London School of Economics.
• IMF and the International Energy Agency websites – these sites contain publications on climate change.
• Climate change on the OECD website.
• The multilateral trading system and climate change: introduction, the World Trade Organization.
• Task Force on Low-Carbon Economic Prosperity, the World Economic Forum.

Videos

• Conference: "The Economic Cost of Climate Change". Speakers: Masahiko Aoki (Stanford University), Michel Armatte (Centre A. Koyré), Jean-Pierre Dupuy (Stanford University), Olivier Godard (C.N.R.S.), Jean-Charles Hourcade (C.I.R.E.D.), Inge Kaul (Hertie School), Philippe Quirion (C.N.R.S.), Thomas Schelling (University of Maryland), Robert Solow (MIT), Nicholas Stern (London School of Economics), Thomas Sterner (University of Gothenburg), and Martin Weitzman (Harvard University). Recorded in 2008.
• "Climate Change and Disasters – Risk and Policy". A discussion based on the work of William Nordhaus, Sterling Professor of Economics at Yale University. This discussion was held at the World Bank in 2008.
• "Can We Afford the Future? The Economics of a Warming World". A lecture given by Frank Ackerman at Boston University, April 28, 2009.
• "Negotiating a New International Climate Treaty". A talk given by Scott Barrett, Lenfest-Earth Institute Professor of Natural Resource Economics, School of International and Public Affairs, Columbia University. October 8, 2009.
• On the Science and Economics of Climate Change – Prof. Christopher Williams on Reality Asserts Itself (5 parts), Part 1 – Climate Change and Waiting for Bruce Willis, Part 2 – Wall Street to Planet Earth, Part 3 – Has the Financial Success of Fracking Shut Down US Climate Change Policy?, Part 4 – Can we Trust technological fixes Such as Nuclear Energy or Geo-engineering When the Driving Force is Financial Profit?, Part 5 – To Ameliorate the Detrimental Effects of Climate Change, Both Short-Term Reform and Long-Term Radical Transformation of Economic, Financial, Social and Political Power Relations are Needed, The Real News