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This article describes the economics of global warming and climate change.

Climate change science

This section describes the science of climate change in relation to economics (Munasinghe et al., 1995:39-41):^[1]

• Greenhouse gases:
  • These gases have been linked with current climate change and may result in further climate change in the future (e.g., see US NRC, 2001).^[2] Greenhouse gases (GHGs) are stock pollutants, and not flow pollutants. This means that it is the concentration of GHGs in the atmosphere that is important in determining climate change impacts, rather than the flow of GHGs into the atmosphere.
  • The stocks of different GHGs in the atmosphere depreciate at various rates, e.g., the atmospheric lifetime of carbon dioxide is over 100 years. If the atmospheric lifetime of the GHG is a year or longer, then the winds have time to spread the gas throughout the lower atmosphere, and its absorption of terrestrial infrared radiation occurs at all latitudes and longitudes (US NRC, 2001:10). It is the flows from all the GHG sources of all nations that contribute to the stock of long-lived GHGs in the atmosphere.
• Inertia: The emissions of GHGs in any one year represent a relatively small fraction of the total global stock, meaning that the system as a whole has great inertia. If emissions were to be reduced to zero, it would take decades to centuries for stock levels to decline significantly. The time required for stocks to depreciate depends on the physical process of GHG removal. The stocks of GHGs with relatively short atmospheric lifetimes, such as methane, depreciate more quickly than the stocks of GHGs with longer atmospheric lifetimes, e.g., HFCs.
• Impact data: Predictions of the physical impacts of climate change are based on the work of climate scientists. Only once (or if) further climate change occurs, will the true social and economic impacts of climate change be known.

Scenarios

Socioeconomic scenarios are used by analysts to make projections of future GHG emissions and to assess future vulnerability to climate change (Carter et al., 2001:151).^[3] Producing scenarios requires estimates of future population levels, economic activity, the structure of governance, social values, and patterns of technological change. Economic and energy modelling (such as via the World3 or the POLES models) can be used to analyse and quantify the effects of such drivers.

Emissions scenarios

Global futures scenarios

These scenarios can be thought of as stories of possible futures. They allow the description of factors that are difficult to quantify, such as governance, social structures, and institutions. Morita et al. (2001:137-142) assessed the literature on global futures scenarios.^[4] They found considerable variety among scenarios, ranging from variants of sustainable development, to the collapse of social, economic, and environmental systems. In the majority of studies, the following relationships were found:

• Rising GHGs: This was associated with scenarios having a growing, post-industrial economy with globalization, mostly with low government intervention and generally high levels of competition. Income equality declined within nations, but there was no clear pattern in social equity or international income equality.
• Falling GHGs: In some of these scenarios, GDP rose. Other scenarios showed economic activity limited at an ecologically sustainable level. Scenarios with falling emissions had a high level of government intervention in the economy. The majority of scenarios showed increased social equity and income equality within and among nations.

Morita et al. (2001) noted that these relationships were not proof of causation.

No strong patterns were found in the relationship between economic activity and GHG emissions. Economic growth was found to be compatible with increasing or decreasing GHG emissions. 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.

Factors affecting emissions growth

• Development trends: In producing scenarios, an important consideration is how social and economic development will progress in developing countries (Fisher et al., 2007:176).^[5] If, for example, developing countries were to follow a development pathway similar to the current industrialized countries, it could lead to a very large increase in emissions.
• GHG emissions and economic growth: Emissions do not only depend on the growth rate of the economy. Other factors are listed below:
  • Structural changes in the production system.
  • Technological patterns in sectors such as energy.
  • Geographical distribution of human settlements and urban structures. This affects, for example, transportation requirements.
  • Consumption patterns: e.g., housing patterns, leisure activities, etc.
  • Trade patterns: the degree of protectionism and the creation of regional trading blocks can affect availability to technology.

Baseline scenarios

A baseline scenario is used as a reference for comparison against an alternative scenario, e.g., a mitigation scenario (IPCC, 2007c:810).^[6] Fisher et al. (2007:178-194) assessed the baseline scenarios literature.^[5] They found that baseline CO₂ emission projections covered a large range. Factors affecting these emission projections are described below:

• Population projections: All other factors being equal, lower population projections result in lower emissions projections.
• Economic development: Economic activity is a dominant driver of energy demand and thus of GHG emissions.
• Energy use: Future changes in energy systems are a fundamental determinant of future GHG emissions.
  • Energy intensity: This is the total primary energy supply (TPES) per unit of GDP (Rogner et al., 2007:107).^[7] In all of the baseline scenarios Fisher et al. (2007) assessed, energy intensity was projected to improve significantly over the 21^st century. The uncertainty range in projected energy intensity was large.
  • Carbon intensity: This is the CO₂ emissions per unit of TPES. Compared with other scenarios, Fisher et al. (2007) found that the carbon intensity was more constant in scenarios where no climate policy had been assumed. The uncertainty range in projected carbon intensity was large. At the high end of the range, some scenarios contained the projection that energy technologies without CO₂ emissions would become competitive without climate policy. These projections were based on the assumption of increasing fossil fuel prices and rapid technological progress in carbon-free technologies. Scenarios with a low improvement in carbon intensity coincided with scenarios that had a large fossil fuel base, less resistance to coal consumption, or lower technology development rates for fossil-free technologies.
• Land-use change: Land-use change plays an important role in climate change, impacting on emissions, sequestration and albedo. One of the dominant drivers in land-use change is food demand. Population and economic growth are the most significant drivers of food demand.^[8]

Trends and projections

Emissions

The Kaya identity expresses the level of energy related CO₂ emissions as the product of four indicators (Rogner et al., 2007:107):^[7]

• Carbon intensity
• Energy intensity
• Gross domestic product per capita (GDP/cap)
• Population

GDP/capita and population growth were the main drivers of the increase in global emissions during the last three decades of the 20^th century. At the global scale, declining carbon and energy intensities have been unable to offset these effects, and consequently, carbon emissions have risen.

• Projections:
  • Without additional policies to cut GHG emissions (including efforts to reduce deforestation), they are projected to increase between 25% and 90% by 2030 relative to their 2000 levels (Rogner et al., 2007:111). Two thirds to three quarters of the increase in CO₂ emissions are projected to come from developing countries, although the average per capita CO₂ emissions in developing country regions will remain substantially lower than those in developed country regions.
  • By 2100, projections range from a 40% reduction to an increase in emissions of 250% above their levels in 2000. Atmospheric concentrations of GHG emissions are unlikely to stabilize this century without major policy changes.

Concentrations

Rogner et al. (2007:102) reported that the then-current estimated total atmospheric concentration of long-lived GHGs was around 455 ppm CO₂-eq (range: 433-477 ppm CO₂-eq). The effects of aerosol and land-use change changes 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.

• SRES Projections: At the time they were developed, the range of global emissions projected across all forty of the SRES scenarios covered the 5^th% to 95^th% percentile range of the emission scenarios literature (Morita et al., 2001:146).^[4] The forty SRES scenarios are classified into six groups, with an illustrative scenario for each group. Under these six illustrative scenarios, the projected concentration of CO₂ in the year 2100 ranges from 540 to 970 ppm (IPCC, 2001b:8).^[9] Uncertainties over aspects of climate science, such as the GHG removal process of carbon sinks, mean that the total projected concentration ranges from 490 to 1,260 ppm. This compares to a pre-industrial (taken as the year 1750) concentration of about 280 ppm, and a concentration of about 368 ppm in the year 2000.

Cost-benefit analysis

Standard cost-benefit analysis can be applied to the problem of climate change (Goldemberg et al., 1996:24,31-32).^[10] This requires (1) the valuation of costs and benefits using the willingness to pay as a measure of value, and (2) a criterion for accepting or rejecting proposals:

(1) The valuation of costs and benefits of climate change is difficult because some climate change impacts are difficult value, e.g., ecosystems and human health. It is also impossible to know the preferences of future generations, which affects the valuation of costs and benefits (DeCanio, 2007:4).^[11]

(2) The standard criterion is the compensation principle. According to the compensation principle, so long as those benefitting from a particular project compensate the losers, and there is still something left over, then the result is an unambiguous gain in welfare. If there are no mechanisms allowing compensation to be paid, then it is necessary to assign weights to particular individuals.

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 (DeCanio, 2007:4). On the other hand, should future generations bear most of the costs of climate change, compensation to them would not be possible (Goldemberg et al., 1996:32). 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.

Impacts

Distribution of impacts

Climate change impacts can be measured as an economic cost (Smith et al., 2001:936-941).^[12] 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 developing 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. (2001:957-958) 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 by 2100, 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.

Non-market impacts

Smith et al. (2001:942) predicted that climate change would likely result in pronounced non-market impacts.^[12] Most of impacts were predicted to be negative. The literature assessmented by Smith et al. (2001) suggested that climate change would cause substantial negative health impacts in developing countries. Smith et al. (2001) noted that few of the studies they reviewed had adequately accounted for adaptation. In a literature assessment, Confalonieri et al. (2007:415) found that in the studies that had included health impacts, those impacts contributed substantially to the total costs of climate change.^[13]

Market sector

Agriculture

Depending on underlying assumptions, studies of the economic impacts of a doubling in atmospheric carbon dioxide (CO₂) from pre-industrial levels conclude that this would have a slightly negative to moderately positive aggregate effect (i.e., total impacts across all regions) on the agricultural sector (Smith et al., 2001:938).^[12] This aggregate effect hides substantial regional differences, with benefits mostly predicted in the developed world and strongly negative impacts for populations poorly connected to regional and global trading systems.

Other sectors

A number of other sectors will be affected by climate change, including the livestock, forestry, and fisheries industries. Other sectors sensitive to climate change include the energy, construction, insurance, tourism and recreation industries. The aggregate impact of climate change on most of these sectors is highly uncertain (Schneider et al., 2007:790).^[14]

Regions

• Africa: In Africa, coastal facilities are economically significant. In a literature assessment, Desanker et al. (2001:490) concluded that climate change would result in sea-level rise, coastal erosion, saltwater intrusion, and flooding. Desanker et al. (2001) predicted that these changes would have a significant impact on African communities and economies.^[15]
• Coasts and low-lying areas: In literature assessment, Nicholls et al. (2007:338-339) concluded that the socio-economic impacts of climate change on coastal and low-lying areas would be overwhelmingly adverse.^[16] Some benefits, however, were noted, e.g., the opening of new ocean routes due to reduced sea ice. Compared with developed countries, the protection costs associated with projected sea level rise were found to be relatively higher for developing countries.
• Polar regions: Anisimov et al. (2001:804) reviewed the literature on climate change impacts in polar regions.^[17] With very high confidence, they concluded that the impact of climate change on infrastructure would increase economic costs. New opportunities for trading and shipping across the Arctic ocean, lower operational costs for the oil and gas industry, lower heating costs, and easier access for ship-based tourism, were expected to bring economic benefits.
• Small islands: In a literature assessment, Mimura et al. (2007:689) concluded, with high confidence, that on small islands, tourism would, for the most part, be negatively affected by climate change.^[18] On many small islands, tourism is a major contributor to GDP and employment.

Other systems and sectors

• Freshwater resources: In this sector, costs and benefits of climate change may take several forms, including monetary costs and benefits, and ecosystem and human impacts, e.g., loss of aquatic species and household flooding. In a literature assessment, Kundzewicz et al. (2007:191) found that few of these costs had been estimated in monetary terms.^[19] In respect to the water supply, they predicted that costs would very likely exceed benefits. Predicted costs included the potential need for infrastructure investments to protect against floods and droughts.
• Industry, settlements and society:
  • In a literature assessment, Wilbanks et al. (2007:377) concluded, with high confidence, that the economic costs of extreme weather events, at large national or large regional scale, would be unlikely to exceed more than a few percent of the total economy in the year of the event, except for possible abrupt changes.^[20] In smaller locations, particularly developing countries, it was estimated with high confidence that, in the year of the extreme event, short-run damages could amount to more than 25% GDP.
  • Infrastructure: According to Tol (2008), roads, airport runways, railway lines and pipelines, (including oil pipelines, sewers, water mains etc) may require increased maintenance and renewal as they become subject to greater temperature variation and are exposed to weather that they were not designed for.^[21]

Aggregate impacts

Aggregating impacts adds up the total impact of climate change across sectors and/or regions (IPCC, 2007a:76).^[22] 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., 2001:941).^[12] 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) 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 by 2100, 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.

With low confidence, Smith et al. (2001) concluded that the non-market impacts of climate change would be negative. Smith et al. (2001:942) decided that studies might have understated the true costs of climate change, e.g., by not correctly estimating the impact of extreme weather events. It was thought possible that some of the positive impacts of climate change had been overlooked, and that adaptive capacity had possibly been underestimated.

Some of the studies assessed by Schneider et al. (2007:790) predicted that gross world product could increase for 1-3 °C warming (by 2100, relative to temperatures over the 1990-2000 period), largely because of aggregate benefits in the agricultural sector.^[14] In the view of Schneider et al. (2007), these estimates carried low confidence. Stern (2007) assessed climate change impacts using the basic economics of risk premiums (Yohe et al., 2007:821).^[23] He found that unmitigated climate change could result in a reduction in welfare equivalent to a persistent average fall in global per-capita consumption of at least 5%. The study by Stern (2007) has received both criticism and support from other economists (see Stern Review for more information). IPCC (2007a) concluded that "Aggregate estimates of costs mask significant differences in impacts across sectors, regions and populations and very likely underestimate damage costs because they cannot include many non-quantifiable impacts."^[22]

Marginal impacts

The social cost of carbon (SCC) is an aggregate measure of the impacts of climate change. It is defined as the incremental (or marginal) social cost of emitting one more tonne of carbon (as carbon dioxide) into the atmosphere at any point in time (Yohe et al., 2007:821).^[23] Different GHGs have different social costs. For example, due to their greater physical capacity to trap infrared radiation, HFCs have a considerably higher social cost per tonne of emission than carbon dioxide. Another physical property that affects the social cost is the atmospheric lifetime of the GHG.

Estimates of the SCC are given in the carbon tax article. These estimates are highly uncertain and cover a wide range (Klein et al., 2007:756).^[24] The discrepancies in estimates can be broken down into normative and empirical parameters (Fisher et al., 2007:232).^[5] Key normative parameters include the aggregation of impacts across time and regions. The other parameters relate to the empirical validity of SCC estimates. This reflects the poor quality of data on which estimates are based, and the difficulty in predicting how society will react to future climate change. In a literature assessment, Klein et al. (2007:757) placed low confidence in SCC estimates.

Sensitivity analysis

Sensitivity analysis allows assumptions to be changed in aggregate analysis to see what effect it has on results (Smith et al., 2001:943):^[12]

• Shape of the damage function: This relates impacts to the change in atmospheric greenhouse gas (GHG) concentrations. There is little information on what the correct shape (e.g., linear or cubic) of this function is. Compared with a linear function, a cubic function shows relatively small damages for small increases in temperature, but more sharply increasing damages at greater temperatures.
• Rate of climate change: This is believed to be an important determinant of impacts, often because it affects the time available for adaptation.
• Discount rate and time horizon: Models used in aggregate studies suggest that the most severe impacts of climate change will occur in the future. Estimated impacts are therefore sensitive to the time horizon (how far a given study projects impacts into the future) and the discount rate (the value assigned to consumption in the future versus consumption today).
• Welfare criteria: Aggregate analysis is particularly sensitive to the weighting (i.e., relative importance) of impacts occurring in different regions and at different times. Studies by Fankhauser et al. (1997) and Azar (1999) found that greater concern over the distribution of impacts lead to more severe predictions of aggregate impacts.
• Uncertainty: Usually assessed through sensitivity analysis, but can also be viewed as a hedging problem. EMF (1997) found that deciding on how to hedge depends on society's aversion to climate change risks, and the potential costs of insuring against these risks.

Advantages and disadvantages

There are a number of benefits of using aggregated assessments to measure climate change impacts (Smith et al., 2001:954).^[12] They allow impacts to be directly compared between different regions and times. Impacts can be compared with other environmental problems and also with the costs of avoiding those impacts. A problem of aggregated analyses is that they often reduce different types of impacts into a small number of indicators. It can be argued that some impacts are not well-suited to this, e.g., the monetization of mortality and loss of species diversity. On the other hand, Pearce (2003:364) argued that where there are monetary costs of avoiding impacts, it is not possible to avoid monetary valuation of those impacts.^[25]

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).^[22] 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).^[26] 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.^[27] 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:^[26]

• 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.^[26] 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.^[28]

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.^[12] 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.^[29] 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.^[30]
• Australia and New Zealand: Hennessy et al. (2007:509) reviewed the literature on adaptation and vulnerability.^[31] 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.^[32] 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.^[33]
• Polar regions: Anisimov et al. (2001:804-805) concluded that:^[17]
  • 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. (2007:689) concluded, with very high confidence, that small islands were particularly vulnerable to climate change.^[18] 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. (2007:336), societal vulnerability to climate change is largely dependent on development status.^[16] 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. (2007:317) concluded that on vulnerable coasts, the costs of adapting to climate change are lower than the potential damage costs.
• 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., 2007:366).^[20] 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. (2007:359) 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.

Mitigation

Mitigation of climate change involves actions that are designed to limit the amount of long-term climate change (Fisher et al., 2007:225).^[5] 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).^[10] 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).^[34]

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):^[35]

• 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 (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).^[36]
• Removal of subsidies, e.g., for coal mining and burning (Barker et al., 2001:567-568).^[37]
• 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 (IPCC, 2007c:817).^[6] 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.^[35]
• Other possible policies include internationally coordinated carbon taxes and/or regulation (Bashmakov et al., 2001:430).

Cost estimates

According to a literature assessment by Barker et al. (2007:622), 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.^[38] Fisher et al. (2007) 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.^[5] 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).^[39]

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) 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.^[37] 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).^[40] 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.

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).^[41] 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.

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 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).^[40] The decision over what "optimal" is depends on subjective value judgements made by the author of the study (Azar, 1998).^[42]

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.

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;^[43] Heal, 2008:20;^[44] Barker, 2008).^[45] Klein et al. (2007:757) found that there were few high quality studies in this area, and placed low confidence in the results of cost-benefit analysis.^[24]

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).^[12]
• 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).^[46]
• 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 (IPCC, 2007c:815).^[6] The intent of geoengineering is to reduce the amount of global warming (the observed trend of increased global average temperature (Staudt et al., 2008:2)).^[47] IPCC (2007b:15) concluded that reliable cost estimates for geoengineering options had not been published.^[39] This finding was based on medium agreement in the literature and limited evidence.

See also

• Carbon tax
• Carbon credit
• Carbon finance
• Emissions trading
• Energy model
• CDM Gold Standard

References

Further reading

• IPCC (1996). "Summary for Policymakers. In: Climate Change 1995: Economic and Social Dimensions of Climate Change. Contribution of Working Group III to the Second Assessment Report of the Intergovernmental Panel on Climate Change [J.P. Bruce et al. Eds."]. Cambridge University Press, Cambridge, U.K., and New York, N.Y., U.S.A.. http://www.ipcc.ch/pdf/climate-changes-1995/spm-economic-social-dimensions.pdf. Retrieved 2009-09-03. 
• Nordhaus, W.D. (ed) (1998). Economics and Policy Issues in Climate Change. RFF Press, Washington, D.C., U.S.A.. pp. 336. ISBN 0-915707-95-0. 

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.
• Climate change on the OECD website.

Videos

• Cournot Centre Conference on "The Economic Cost of Climate Change". Roundtable discussion: "Economics and Climate Change: Where Do We Stand and Where Do We Go from Here?", Part 1 and Part 2. Discussants are Inge Kaul (Hertie School of Governance), 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, Colombia University. October 8, 2009.