Economic analysis of climate change

Economic analysis of climate change is about using economic tools and models to calculate the magnitude and distribution of damages caused by climate change. It can also give guidance for the best policies for mitigation and adaptation to climate change from an economic perspective. There are many economic models and frameworks. For example, in a cost–benefit analysis, the trade offs between climate change impacts, adaptation, and mitigation are made explicit. For this kind of analysis, integrated assessment models (IAMs) are useful. Those models link main features of society and economy with the biosphere and atmosphere into one modelling framework. The total economic impacts from climate change are difficult to estimate. In general, they increase the more the global surface temperature increases (see climate change scenarios).

Most types of climate change effects are associated with an economic cost. Many of the effects have impacts that are linked to market transactions and therefore are directly affect GDP. However, there are also non-market impacts which are harder to translate into economic costs. These include the impacts of climate change on human health, biomes and ecosystem services. Economic analysis of climate change is challenging as climate change is a long-term problem. Furthermore, there is still a lot of uncertainty about the exact impacts of climate change and the associated damages to be expected. Future policy responses and socioeconomic development are also uncertain.

Economic analysis also looks at the economics of climate change mitigation and the cost of climate adaptation. Mitigation costs will vary according to how and when emissions are cut. Early, well-planned action will minimize the costs. Globally, the benefits of keeping warming under 2 °C exceed the costs. Cost estimates for mitigation for specific regions depend on the quantity of emissions allowed for that region in future, as well as the timing of interventions. Economists estimate the cost of climate change mitigation at between 1% and 2% of GDP. The costs of planning, preparing for, facilitating and implementing adaptation are also difficult to estimate, depending on different factors. Across all developing countries, they have been estimated to be about USD 215 billion per year up to 2030, and are expected to be higher in the following years.

Purposes
Economic analysis of climate change is an umbrella term for a range of investigations into the economic costs around the effects of climate change, and for preventing or softening those effects. These investigations can serve any of the following purposes:


 * estimating the potential global aggregate economic costs of climate change (i.e. global climate damages)
 * estimating sectoral or regional economic costs of climate change (e.g. costs to agriculture sector or energy services)
 * estimating economic costs of facilitating and implementing climate change mitigation and adaptation strategies (varying with the objectives and the levels of action required); see also economics of climate change mitigation.
 * monetising the projected impacts to society per additional metric tonne of carbon emissions (social cost of carbon)
 * informing decisions about global climate management strategy (through UN institutions) or policy decisions in some countries

The economic impacts of climate change also include any mitigation (for example, limiting the global average temperature below 2 °C) or adaption (for example, building flood defences) employed by nations or groups of nations, which might infer economic consequences. They also take into account that some regions or sectors benefit from low levels of warming, for example through lower energy demand or agricultural advantages in some markets.

There are wider policy (and policy coherence) considerations of interest. For example, in some areas, policies designed to mitigate climate change may contribute positively towards other sustainable development objectives, such as abolishing fossil fuel subsidies which would reduce air pollution and thus save lives. Direct global fossil fuel subsidies reached $319 billion in 2017, and $5.2 trillion when indirect costs such as air pollution are priced in. In other areas, the cost of climate change mitigation may divert resources away from other socially and environmentally beneficial investments (the opportunity costs of climate change policy).

Types of economic models
Various economic tools are employed to understand the economic aspects around impacts of climate change, climate change mitigation and adaptation. Several sets of tools or approaches exist. Econometric models (statistical models) are used to integrate the broad impacts of climate change with other economic drivers, to quantify the economic costs and assess the value of climate-related policies, often for a specific sector or region. Structural economic models look at market and non-market impacts affecting the whole economy through its inputs and outputs. Process models simulate physical, chemical and biological processes under climate change, and the economic effects.

Aggregate cost-benefit models
Integrated assessment models (IAMs) are also used make aggregate estimates of the costs of climate change. These (cost-benefit) models balance the economic implications of mitigation and climate damages to identify the pathway of emissions reductions that will maximize total economic welfare. In other words, the trade-offs between climate change impacts, adaptation, and mitigation are made explicit. The costs of each policy and the outcomes modelled are converted into monetary estimates.

The models incorporate aspects of the natural, social, and economic sciences in a highly aggregated way. Compared to other climate-economy models (including process-based IAMs), they do not have the structural detail necessary to model interactions with energy systems, land-use etc. and their economic implications.

Statistical (econometric) methods
A more recent modelling approach uses empirical, statistical methods to investigate how the economy is affected by weather variation. This approach can causatively identify effects of temperature, rainfall and other climate variables on agriculture, energy demand, industry and other economic activity. Panel data are used giving weather variation over time and spatial areas, eg. ground station observations or (interpolated) gridded data. These are typically aggregated for economic analysis eg. to investigate effects on national economies. These studies examine temperature and rainfall, and events such as droughts and windstorms. They show that for example, hot years are linked to lower income growth in poor countries, and low rainfall is linked to reduced incomes in Africa. Other econometric studies show that there are negative impacts of hotter temperatures on agricultural output, and on labour productivity in factories, call centres and in outdoor industries such as mining and forestry. The analyses are used to estimate the costs of climate change in the future.

Cost–benefit analysis
Standard cost–benefit analysis (CBA) has been applied to the problem of climate change. In a CBA framework, the negative and positive impacts associated with a given action are converted into monetary estimates. This is also referred to as a monetized cost–benefit framework. Various types of model can provide information for CBA, including energy-economy-environment models (process models) that study energy systems and their transitions. Some of these models may include a physical model of the climate. Computable General Equilibrium (CGE) structural models investigate effects of policies (including climate policies) on economic growth, trade, employment, and public revenues. However, most CBA analyses are produced using aggregate integrated assessment models. These aggregate-type IAMs are particularly designed for doing CBA of climate change.

The CBA framework requires (1) the valuation of costs and benefits using willingness to pay (WTP) or willingness to accept (WTA) compensation as a measure of value, and (2) a criterion for accepting or rejecting proposals:

For (1), in CBA where WTP/WTA is used, climate change impacts are aggregated into a monetary value, with environmental impacts converted into consumption equivalents, and risk accounted for using certainty equivalents. Values over time are then discounted to produce their equivalent present values. The valuation of costs and benefits of climate change can be controversial because some climate change impacts are difficult to assign a value to, 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. Another difficulty is quantifying the risks of future climate change.

For (2), the standard criterion is the Kaldor–Hicks compensation principle. 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. 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. On the other hand, should future generations bear most of the costs of climate change, compensation to them would not be possible. Another transfer for compensation exists between regions and populations. If, for example, some countries were to benefit from reducing climate change but others lose out, there would be no guarantee that the winners would compensate the losers.

In a CBA framework, the distribution of benefits from adaptation and mitigation policies are different in terms of damages avoided. 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.

The "optimal" levels of mitigation and adaptation are resolved by comparing the marginal costs of action with the marginal benefits of avoided climate change damages. 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. This approach might lead to a warming of more than 3 °C above the pre-industrial level.

CBA has several strengths: it offers an internally consistent and global comprehensive analysis of impacts. Furthermore, sensitivity analysis allows critical assumptions in CBA analysis to be changed. This can identify areas where the value of information is highest and where additional research might have the highest payoffs. However, there are many uncertainties that affect cost–benefit analysis, for example, sector- and country-specific damage functions.

Damage functions
Damage functions play an important role in estimating the costs associated with potential damages caused by climate-related hazards. They quantify the relationship between the intensity of the hazard, other factors such as the vulnerability of the system, and the resulting damages. For example, damage functions have been developed for sea level rise, agricultural productivity, or heat effects on labour productivity. In a CBA framework, damages are monetized to facilitate comparison with the benefits of proposed actions or policies. Sensitivity analysis is conducted to assess the robustness of the results to changes in assumptions and parameters, including those of the damage function.

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):
 * 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 how to hedge depends on society's aversion to climate change risks, and the potential costs of insuring against these risks.

Cost-effectiveness analysis
Cost-Effectiveness Analysis (CEA) is preferable to CBA when the benefits of impacts, adaptation and mitigation are difficult to estimate in monetary terms. A CEA can be used to compare different policy options for achieving a well-defined goal. This goal (i.e. the benefit) is usually expressed as the amount of GHG emissions reduction in the analysis of mitigation measures. For adaptation measures, there is no single common goal or metric for the economic benefits. Adaptation involves responding to different types of risks in different sectors and local contexts. For example, the goal might be the reduction of land area in hectares at risk to sea level rise.

CEA involves the costing of each option, and providing a cost per unit of effectiveness. For example, cost per tonne of GHG reduced ($/tCO2). This allows the ranking of policy options. This ranking can help decision-maker to understand which are the most cost-effective options, i.e. those that deliver high benefits for low costs. CEA can be used for minimising net costs for achieving pre-defined policy targets, such as meeting an emissions reduction target for a given sector.

CEA, like CBA, is a type of decision analysis method. Many of these methods work well when different stakeholders work together on a problem to understand and manage risks. For example, by discussing how well certain options might work in the real world. Or by helping in measuring the costs and benefits as part of a CEA.

Some authors have focused on a disaggregated analysis of climate change impacts. "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.

Scenario-based assessments
The long time scales and uncertainty associated with global warming have led analysts to develop "scenarios" of future environmental, social and economic changes. These scenarios can help governments understand the potential consequences of their decisions.

The projected temperature in climate change scenarios 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.

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, what the future impacts of climate change might be, as well as the level of future GHG emissions.

Scenarios are neither "predictions" nor "forecasts" but are stories of possible futures that provide alternate outcomes relevant to a decision-maker or other user. These alternatives usually also include a "baseline" or reference scenario for comparison. "Business-as-usual" scenarios have been developed in which there are no additional policies beyond those currently in place, and socio-economic development is consistent with recent trends. This term is now used less frequently than in the past.

In scenario analysis, scenarios are developed that are based on differing assumptions of future development patterns. An example of this are the shared socioeconomic pathways produced by the Intergovernmental Panel on Climate Change (IPCC). These project a wide range of possible future emissions levels.

Scenarios often support sector-specific analysis of the physical effects and economic costs of climate change. Scenarios are used with cost–benefit analysis or cost-effectiveness analysis of climate policies.

Risk management
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. Another approach is that of uncertainty analysis, where analysts attempt to estimate the probability of future changes in emission levels.

In a cost–benefit analysis, an acceptable risk means that the benefits of a climate policy outweigh the costs of the policy. 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. The expected value is the mean of the distribution of expected outcomes. 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
 * economic agents (people and organizations) can diversify their own risk through insurance and other markets.

On the second point, it has been suggested that insurance could be bought against climate change risks. Policymakers and investors are beginning to recognize the implications of climate change for the financial sector, from both physical risks (damage to property, infrastructure, and land) and transition risk due to changes in policy, technology, and consumer and market behavior. Financial institutions are becoming increasingly aware of the need to incorporate the economics of low carbon emissions into business models.

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

Analysts have also looked at how uncertainty over climate sensitivity affects economic estimates of climate change impacts. Policy guidance from cost-benefit analysis (CBA) can be extremely divergent depending on the assumptions employed. Hassler et al use integrated assessment modeling to examine a range of estimates and what happens at extremes.

Iterative risk management
Two related ways of thinking about the problem of climate change decision-making in the presence of uncertainty are iterative risk management and sequential decision making. Considerations in a risk-based approach might include, for example, the potential for low-probability, worst-case climate change impacts. One of the responses to the uncertainties of global warming is to adopt a strategy of sequential decision making. Sequential decision making refers to the process in which the decision maker makes consecutive observations of the process before making a final decision. 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 may use risk management as part of their policy response to global warming.

An approach based on sequential decision making recognizes that, over time, decisions related to climate change can be revised in the light of improved information. 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 favor stringent, near-term emissions reductions. As stated earlier, carbon dioxide accumulates in the atmosphere, and to stabilize the atmospheric concentration of, emissions would need to be drastically reduced from their present level. Stringent near-term emissions reductions allow for greater future flexibility with regard to a low stabilization target, e.g., 450 parts per million (ppm). 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.

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. Another way of viewing the problem is to look at the potential irreversibility of future climate change impacts (e.g., damages to biomes and ecosystems) against the irreversibility of making investments in efforts to reduce emissions.

Portfolio analysis
An example of a framework that is based on risk management is portfolio analysis. This approach is based on portfolio theory, originally applied in the areas of finance and investment. It has also been applied to the analysis of climate change. The idea is that a reasonable response to uncertainty is to invest in a wide portfolio of options. More specifically, the aim is to minimise the variance and co-variance of the performance of investments in the portfolio. In the case of climate change mitigation, performance is measured by how much GHG emissions reduction is achieved. On the other hand, climate change adaptation acts as insurance against the chance that unfavourable impacts occur. The performance of adaptation options could either be defined in economic terms, e.g. revenue, or as physical metrics, e.g. the quantity of water conserved.

It is important to compare alternative portfolios of options across different future climate change scenarios in order to take into account uncertainty in climate impacts, GHG emission trends etc. The options should ideally be diversified to be effective in different scenarios: i.e. some options suited for a no/low climate change scenario, with other options being suited for scenarios with severe climate changes.

Investment and financial flows
Investment and financial flow (I&FF) studies typically consider how much it might cost to increase the resilience of future investments or financial flows. They also investigate the potential sources of investment funds and the types of financing entities or actors. Aggregated studies assess the sensitivity of future investments, estimating the risk from climate change and estimating the additional investment needed to increase resilience. More detailed studies undertake investment and financial flow analysis at a sectoral level to provide detailed costing of the additional marginal costs needed for building resilience.

At the global level (aggregate costs)
Global aggregate costs (also known as global damages or losses) sum up the predicted impacts of climate change across all market sectors (e.g. including costs to agriculture, energy services and tourism) and can also include non-market impacts (e.g. on ecosystems and human health) for which it is possible to assign monetary values. A study in 2024 projected that by 2050, climate change will reduce average global incomes by likely 19 (confidence interval 11-29%), relative to a counterfactual where no climate change occurs. The global economy and per capita income would still grow relative to present, but the global annual damages would reach about $38 trillion (in 2005 International dollars) by 2050, and increase a lot further under high emissions. In comparison, limiting global warming to 2 °C would by 2050 cost about $6 trillion per year, or far less than the anticipated annual damages, emphasizing the economic benefits of proactive climate mitigation.

Global estimates are often based on an aggregation of independent sector and/or regional studies and results, with complex interactions modelled. For example, there is uncertainty in how physical and natural systems may respond to climate change. Potential socioeconomic changes, including how human societies might mitigate and adapt to climate change also need consideration. The uncertainty and complexities associated with climate change and have led analysts to develop "scenarios" with which they can explore different possibilities.

Global economic losses due to extreme weather, climate and water events are increasing. Costs have increased sevenfold from the 1970s to the 2010s. Direct losses from disasters have averaged above US$330 billion annually between 2015 and 2021. Climate change has contributed to the increased probability and magnitude of extreme events. When a vulnerable community is exposed to extreme climate or weather events, disasters can occur. Socio-economic factors have contributed to the observed trend of global disaster losses, such as population growth and increased wealth. This shows that increased exposure is the most important driver of losses. However, part of these are also due to human-induced climate change. Extreme Event Attribution quantifies how climate change is altering the probability and magnitude of extreme events. On a case-by-case basis, it is feasible to estimate how the magnitude and/or probability of the extreme event has shifted due to climate change. These attributable changes have been identified for many individual extreme heat events and rainfall events. Using all available data on attributable changes, one study estimated the global losses to average US$143 billion per year between 2000 and 2019. This includes a statistical loss of life value of 90 billion and economic damages of 53 billion per year.

Estimates of the economic impacts from climate change in future years are most often measured as percent global GDP change, relative to GDP without additional climate change. The 2022 IPCC report compared the latest estimates of many modelling and meta-analysis studies. It found wide variety in the results. These vary depending on the assumptions used in the IPCC socioeconomic scenarios. The same set of scenarios are used in all of the climate models.

Estimates are found to increase non-linearly with global average temperature change. Global temperature change projection ranges (corresponding to each cost estimate) are based on IPCC assessment on the physical science in the same report. It finds that with high warming (~4 °C) and low adaptation, annual global GDP might be reduced by 10–23% by 2100 because of climate change. The same assessment finds smaller GDP changes with reductions of 1–8%, assuming assuming low warming, more adaptation, and using different models. These global economic cost estimates do not take into account impacts on social well-being or welfare or distributional effects. Nor do they fully consider climate change adaptation responses.

One 2020 study estimated economic losses due to climate change could be between 127 and 616 trillion dollars extra until 2100 with current commitments, compared to 1.5 °C or well below 2 °C compatible action. Failure to implement current commitments raises economic losses to 150–792 trillion dollars until 2100.

High emissions scenarios
The total economic impacts from climate change increase for higher temperature changes. For instance, total damages are estimated to be 90% less if global warming is limited to 1.5 °C compared to 3.66 °C, a warming level chosen to represent no mitigation. In an Oxford Economics study high emission scenario, a temperature rise of 2 degrees by the year 2050 would reduce global GDP by 2.5–7.5%. By the year 2100 in this case, the temperature would rise by 4 degrees, which could reduce the global GDP by 30% in the worst case.

One 2018 study found that potential global economic gains if countries implement mitigation strategies to comply with the 2 °C target set at the Paris Agreement are in the vicinity of US$17 trillion per year up to 2100, compared to a very high emission scenario.

By region
Other studies investigate economic losses by GDP change per country or by per country per capita. Findings show large differences among countries and within countries. The estimated GDP changes in some developing countries are similar to some of the worst country-level losses during historical economic recessions. Economic losses are risks to living standards, which are more likely to be severe in developing countries. Climate change can push more people into extreme poverty or keep people poor, especially through particularly climate-sensitive sectors such as agriculture and fisheries. Climate change may also increase income inequality within countries as well as between them, particularly affecting low-income groups.

The economic impact of changes in annual mean temperature is estimated to be lower at higher latitudes despite higher temperature changes due to lower estimated economic vulnerability to temperature changes. Reduced daily temperature variability at high latitudes shows positive estimated economic impact, with opposite effects at lower latitudes and Europe. Economic effects due to changes in total annual precipitation show regional patterns generally opposite to changes in the number of wet days.

According to a study by reinsurance company Swiss Re in 2021 the economies of wealthy countries like the US would likely shrink by approximately 7%, while some developing nations would be devastated, losing around 20% or in some cases 40% of their economic output.

A United States government report in November 2018 raised the possibility of US GDP going down 10% as a result of the warming climate, including huge shifts in geography, demographics and technology.

By sector


A number of economic sectors will be affected by climate change, including the livestock, forestry, and fisheries industries. Other sectors sensitive to climate change include the energy, insurance, tourism and recreation industries.

Health and productivity
Among the health impacts that have been studied, aggregate costs of heat stress (through loss of work time) have been estimated, as have the costs of malnutrition. However, it is usual for studies to aggregate the number of 'years of life lost' adjusted for years living with disability to measure effects on health.

In 2019 the International Labour Organization published a report titled: "Working on a warmer planet: The impact of heat stress on labour productivity and decent work", in which it claims that even if the rise in temperature will be limited to 1.5 degree, by the year 2030, Climate Change will cause losses in productivity reaching 2.2% of all the working hours, every year. This is equivalent to 80 million full-time jobs, or 2,400 billion dollars. The sector expected to be most affected is agriculture, which is projected to account for 60% of this loss. The construction sector is also projected to be severely impacted and accounts for 19% of projected losses. Other sectors that are most at risk are environmental goods and services, refuse collection, emergency, repair work, transport, tourism, sports and some forms of industrial work.

It has been estimated that 3.5 million people die prematurely each year from air pollution from fossil fuels. The health benefits of meeting climate goals substantially outweigh the costs of action. The health benefits of phasing out fossil fuels measured in money (estimated by economists using the value of life for each country) are substantially more than the cost of achieving the 2 degree C goal of the Paris Agreement.



Agriculture and infrastructure

 * In the agriculture sector, there are substantial regional differences, Poorer countries are more exposed to climatic changes and extreme weather events because of the important role of agriculture and water resources in the economy.
 * With respect to water supply, a literature survey in 2007 predicted that costs would very likely exceed benefits. Predicted costs included the potential need for infrastructure investments to protect against floods and droughts.
 * It was estimated in 2007 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. 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.
 * 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.

Industry
Carbon-intensive industries and investors are expected to experience a significant increase in stranded assets with a potential ripple affect throughout the world economy.

Costs of climate change mitigation measures
Climate change mitigation consist of human actions to reduce greenhouse gas emissions or to enhance carbon sinks that absorb greenhouse gases from the atmosphere.

Utility of aggregated assessment
There are a number of benefits of using aggregated assessments to measure economic impacts of climate change. 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, where there are monetary costs of avoiding impacts, it may not be possible to avoid monetary valuation of those impacts.

Efficiency and equity
No consensus exists on who should bear the burden of adaptation and mitigation costs. 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. 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. These issues to do with equity and aggregation cannot be fully resolved by economics.

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. 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

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". In terms of efficiency, this view is not supported. This is because efficiency requires incentives to be forward-looking, and not retrospective. The question of historical responsibility is a matter of ethics. It has been suggested that developed countries could address the issue by making side-payments to developing countries.

A 2019 modelling study found climate change had contributed towards global economic inequality. Wealthy countries in colder regions had either felt little overall economic impact from climate change, or possibly benefited, whereas poor hotter countries very likely grew less than if global warming had not occurred. Part of this observation stems from the fact that greenhouse gas emissions come mainly from high-income countries, while low-income countries are affected by it negatively. So, high-income countries are producing significant amounts of emissions, but the impacts are unequally threatening low-income countries, who do not have access to the resources to recover from such impacts. This further deepens the inequalities within the poor and the rich, hindering sustainability efforts. Impacts of climate change could even push millions of people into poverty.

Insurance and markets
Traditional insurance works by transferring risk to those better able or more willing to bear risk, and also by the pooling of risk. 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.

Disease, rising seas, reduced crop yields, and other harms driven by climate change will likely have a major deleterious impact on the economy by 2050 unless the world sharply reduces greenhouse gas emissions in the near term, according to a number of studies, including a study by the Carbon Disclosure Project and a study by insurance giant Swiss Re. The Swiss Re assessment found that annual output by the world economy will be reduced by $23 trillion annually, unless greenhouse gas emissions are adequately mitigated. As a consequence, according to the Swiss Re study, climate change will impact how the insurance industry prices a variety of risks.

Authors have pointed to several reasons why commercial insurance markets cannot adequately cover risks associated with climate change. 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. 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.

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.

Underestimation of economic impacts
Studies in 2019 suggest that economic damages due to climate change have been underestimated, and may be severe, with the probability of disastrous tail-risk events.

Tipping points are critical thresholds that, when crossed, lead to large, accelerating and often irreversible changes in the climate system. The science of tipping points is complex and there is great uncertainty as to how they might unfold. Economic analyses often exclude the potential effect of tipping points. A 2018 study noted that the global economic impact is underestimated by a factor of two to eight, when tipping points are excluded from consideration.

The Stern Review from 2006 for the British Government predicted that world GDP would be reduced by several percent due to climate related costs. However, their calculations may omit ecological effects that are difficult to quantify economically (such as human deaths or loss of biodiversity) or whose economic consequences will manifest slowly. Therefore, their calculations may be an underestimate. The study has received both criticism and support from other economists (see Stern Review for more information).

Effects of economic growth on emissions
Some have said that economic growth is a key driver of CO2 emissions. However later (in late 2022) others have said that economic growth no longer means higher emissions. As the economy expands, demand for energy and energy-intensive goods increases, pushing up CO2 emissions. On the other hand, economic growth may drive technological change and increase energy efficiency. Economic growth may be associated with specialization in certain economic sectors. If specialization is in energy-intensive sectors, specifically carbon energy sources, then there will be a strong link between economic growth and emissions growth. If specialization is in less energy-intensive sectors, e.g. the services sector, then there might be a weak link between economic growth and emissions growth. A recent study found that in general, there is some degree of flexibility between economic growth and emissions growth.

Use of degrowth scenarios
Scientists report that degrowth scenarios, where economic output either "declines" or declines in terms of contemporary economic metrics such as current GDP, have been neglected in considerations of 1.5 °C scenarios reported by the Intergovernmental Panel on Climate Change (IPCC). They find that investigated degrowth scenarios "minimize many key risks for feasibility and sustainability compared to technology-driven pathways" with a core problem of such being feasibility in the context of contemporary decision-making of politics and globalized rebound- and relocation-effects. This is supported by other studies which state that absolute decoupling is highly unlikely to be achieved fast enough to prevent global warming over 1.5 °C or 2 °C, even under optimistic policy conditions.