Economic analysis of climate change

An economic analysis of climate change uses 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).
Many effects of climate change are linked to market transactions and therefore directly affect metrics like GDP or inflation. 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 and co-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 incremental cost of climate change mitigation at less than 1% 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.
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:
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).
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.
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.
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.
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.
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.
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 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.
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.
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 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:
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.
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 CO2, 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) 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.
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.
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 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.
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.
Another study, which checked the data from the last 120 years, found that climate change has already reduced welfare by 29% and further temperature rise will bring this number to 47%. The temperature rise during the years 1960-2019 alone has already cut current GDP per capita by 18%. A rise by 1 degree in global temperature reduces global GDP by 12%. An increase of 3 degrees by 2100, will reduce capital by 50%. The effects are like experiencing the 1929 Great Depression permanently. The appropriate social cost of carbon is 1065 dollars per tonne of CO2.
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.
Economic impacts also include inflation from rising insurance premiums, energy costs and food prices.
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.
Studies in 2019 suggested 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.
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.
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.
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.
Carbon-intensive industries and investors are expected to experience a significant increase in stranded assets with a potential ripple affect throughout the world economy.
The effects of climate change contribute to inflation due to additional costs. For example, food prices could rise by as much as 3% per year due to climate change impacts. Climate change was one of the factors involved in the world food crises (2022–2023), which led to higher food prices.
Natural disasters fueled by climate change have increased housing costs through insurance and by exacerbating housing shortages when those events make homes unlivable.
A study published in April 2025 in the journal Environmental Research Letters found that the average household would be 40% poorer if the world warms by 4 degrees Celsius.
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.
Climate change mitigation consist of human actions to reduce greenhouse gas emissions or to enhance carbon sinks that absorb greenhouse gases from the atmosphere.
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. Macroeconomic costs in 2030 were estimated 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.
Macroeconomic cost estimates 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. Relaxation of some or all these assumptions would lead to an appreciable increase in cost estimates. On the other hand, 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.
In most of the assessed studies, costs rose for increasingly stringent stabilization targets. In scenarios that had high baseline emissions, mitigation costs were generally higher for comparable stabilization targets. In scenarios with low emissions baselines, mitigation costs were generally lower for comparable stabilization targets.
Several studies have estimated regional mitigation costs. The conclusions of these studies are as follows:
There have been different proposals on how to allocate responsibility for cutting emissions:
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.
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.
Economic growth is one of the causes of increasing greenhouse gas 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, 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. In general, there is some degree of flexibility between economic growth and emissions growth.
Some studies found 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 some 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.
The economics of climate change mitigation is a contentious part of climate change mitigation – action aimed to limit the dangerous socio-economic and environmental consequences of climate change.
Climate change mitigation centres on two main strategies: the reduction of greenhouse gas (GHG) emissions and the preservation and expansion of sinks which absorb greenhouse gases, including the sea and forests.
The economics of climate change mitigation are a central point of contention whose considerations significantly affect the level of climate action at every level from local to global.
For example, higher interest rates are slowing solar panel installation in developing countries.
A carbon price is a system of applying a price to carbon emissions, as a method of emissions mitigation. Potential methods of pricing include carbon emission trading, results-based climate finance, crediting mechanisms and more. Carbon pricing can lend itself to the creation of carbon taxes, which allows governments to tax emissions.
Carbon taxes are considered useful because, once a number has been created, it will benefit the government either with currency or with a lowering in emissions or both, and therefore benefit the environment. It is almost a consensus that carbon taxing is the most cost-effective method of having a substantial and rapid response to climate change and carbon emissions. However, backlash to the tax includes that it can be considered regressive, as the impact can be damaging disproportionately to the poor who spend much of their income on energy for their homes. Still, even with near universal approval, there are issues regarding both the collection and redistribution of the taxes. One of the central questions being how the newly collected taxes will be redistributed.
Some or all of the proceeds of a carbon tax can be used to stop it disadvantaging the poor.
In addition to the implementation of command-and-control regulations (as with a carbon tax), governments can also use market-based approaches to mitigate emissions. One such method is emissions trading where governments set the total emissions of all polluters to a maximum and distribute permits, through auction or allocation, that allow entities to emit a portion, typically one ton of carbon dioxide equivalent (CO2e), of the mandated total emissions. In other words, the amount of pollution an entity can emit in an emissions trading system is limited by the number of permits they have. If a polluter wants to increase their emissions, they can only do so after buying permits from those who are willing to sell them. Many economists prefer this method of reducing emissions as it is market based and highly cost effective. That being said, emissions trading alone is not perfect since it fails to place a clear price on emissions. Without this price, emissions prices are volatile due to the supply of permits being fixed, meaning their price is entirely determined by shifts in demand. This uncertainty in price is especially disliked by businesses since it prevents them from investing in abatement technologies with confidence which hinders efforts for mitigating emissions. Regardless, while emissions trading alone has its problems and cannot reduce pollutants to the point of stabilizing the global climate, it remains an important tool for addressing climate change.
There is a debate about a potentially critical need for new ways of economic accounting, including directly monitoring and quantifying positive real-world environmental effects such as air quality improvements and related unprofitable work like forest protection, alongside far-reaching structural changes of lifestyles as well as acknowledging and moving beyond the limits of current economics such as GDP. Some argue that for effective climate change mitigation degrowth has to occur, while some argue that eco-economic decoupling could limit climate change enough while continuing high rates of traditional GDP growth. There is also research and debate about requirements of how economic systems could be transformed for sustainability – such as how their jobs could transition harmonously into green jobs – a just transition – and how relevant sectors of the economy – like the renewable energy industry and the bioeconomy – could be adequately supported.
While degrowth is often believed to be associated with decreased living standards and austerity measures, many of its proponents seek to expand universal public goods (such as public transport), increase health (fitness, wellbeing and freedom from diseases) and increase various forms of, often unconventional commons-oriented, labor. To this end, the application of both advanced technologies and reductions in various demands, including via overall reduced labor time or sufficiency-oriented strategies, are considered to be important by some.
The costs of mitigation and adaptation policies can be measured as a percentage of GDP. A problem with this method of assessing costs is that GDP is an imperfect measure of welfare. There are externalities in the economy which mean that some prices might not be truly reflective of their social costs.
Corrections can be made to GDP estimates to allow for these problems, but they are difficult to calculate. In response to this problem, some have suggested using other methods to assess policy. For example, the United Nations Commission for Sustainable Development has developed a system for "Green" GDP accounting and a list of sustainable development indicators.
The emissions baseline is, by definition, the emissions that would occur in the absence of policy intervention. Definition of the baseline scenario is critical in the assessment of mitigation costs. This because the baseline determines the potential for emissions reductions, and the costs of implementing emission reduction policies.
There are several concepts used in the literature over baselines, including the "efficient" and "business-as-usual" (BAU) baseline cases. In the efficient baseline, it is assumed that all resources are being employed efficiently. In the BAU case, it is assumed that future development trends follow those of the past, and no changes in policies will take place. The BAU baseline is often associated with high GHG emissions, and may reflect the continuation of current energy-subsidy policies, or other market failures.
Some high emission BAU baselines imply relatively low net mitigation costs per unit of emissions. If the BAU scenario projects a large growth in emissions, total mitigation costs can be relatively high. Conversely, in an efficient baseline, mitigation costs per unit of emissions can be relatively high, but total mitigation costs low.
These are the secondary or side effects of mitigation policies, and including them in studies can result in higher or lower mitigation cost estimates. Reduced mortality and morbidity costs are potentially a major ancillary benefit of mitigation. This benefit is associated with reduced use of fossil fuels, thereby resulting in less air pollution, which might even just by itself be a benefit greater than the cost. There may also be ancillary costs.
Flexibility is the ability to reduce emissions at the lowest cost. The greater the flexibility that governments allow in their regulatory framework to reduce emissions, the lower the potential costs are for achieving emissions reductions (Markandya et al., 2001:455).
Including carbon sinks in a policy framework is another source of flexibility. Tree planting and forestry management actions can increase the capacity of sinks. Soils and other types of vegetation are also potential sinks. There is, however, uncertainty over how net emissions are affected by activities in this area.
Assessing climate change impacts and mitigation policies involves a comparison of economic flows that occur in different points in time. The discount rate is used by economists to compare economic effects occurring at different times. Discounting converts future economic impacts into their present-day value. The discount rate is generally positive because resources invested today can, on average, be transformed into more resources later. If climate change mitigation is viewed as an investment, then the return on investment can be used to decide how much should be spent on mitigation.
Integrated assessment models (IAM) are used to estimate the social cost of carbon. The discount rate is one of the factors used in these models. The IAM frequently used is the Dynamic Integrated Climate-Economy (DICE) model developed by William Nordhaus. The DICE model uses discount rates, uncertainty, and risks to make benefit and cost estimations of climate policies and adapt to the current economic behavior.
The choice of discount rate has a large effect on the result of any climate change cost analysis (Halsnæs et al., 2007:136). Using too high a discount rate will result in too little investment in mitigation, but using too low a rate will result in too much investment in mitigation. In other words, a high discount rate implies that the present-value of a dollar is worth more than the future-value of a dollar.
Discounting can either be prescriptive or descriptive. The descriptive approach is based on what discount rates are observed in the behaviour of people making every day decisions (the private discount rate) (IPCC, 2007c:813). In the prescriptive approach, a discount rate is chosen based on what is thought to be in the best interests of future generations (the social discount rate).
The descriptive approach can be interpreted as an effort to maximize the economic resources available to future generations, allowing them to decide how to use those resources (Arrow et al., 1996b:133–134). The prescriptive approach can be interpreted as an effort to do as much as is economically justified to reduce the risk of climate change.
The DICE model incorporates a descriptive approach, in which discounting reflects actual economic conditions. In a recent DICE model, DICE-2013R Model, the social cost of carbon is estimated based on the following alternative scenarios: (1) a baseline scenario, when climate change policies have not changed since 2010, (2) an optimal scenario, when climate change policies are optimal (fully implemented and followed), (3) when the optimal scenario does not exceed 2˚C limit after 1900 data, (4) when the 2˚C limit is an average and not the optimum, (5) when a near-zero (low) discount rate of 0.1% is used (as assumed in the Stern Review), (6) when a near-zero discount rate is also used but with calibrated interest rates, and (7) when a high discount rate of 3.5% is used.
According to Markandya et al. (2001:466), discount rates used in assessing mitigation programmes need to at least partly reflect the opportunity costs of capital. In developed countries, Markandya et al. (2001:466) thought that a discount rate of around 4–6% was probably justified, while in developing countries, a rate of 10–12% was cited. The discount rates used in assessing private projects were found to be higher – with potential rates of between 10% and 25%.
When deciding how to discount future climate change impacts, value judgements are necessary (Arrow et al., 1996b:130). IPCC (2001a:9) found that there was no consensus on the use of long-term discount rates in this area. The prescriptive approach to discounting leads to long-term discount rates of 2–3% in real terms, while the descriptive approach leads to rates of at least 4% after tax – sometimes much higher (Halsnæs et al., 2007:136).
Even today, it is difficult to agree on an appropriate discount rate. The approach of discounting to be either prescriptive or descriptive stemmed from the views of Nordhaus and Stern. Nordhaus takes on a descriptive approach which "assumes that investments to slow climate change must compete with investments in other areas". While Stern takes on a prescriptive approach in which "leads to the conclusion that any positive pure rate of time preference is unethical".
In Nordhaus' view, his descriptive approach translates that the impact of climate change is slow, thus investments in climate change should be on the same level of competition with other investments. He defines the discount rate to be the rate of return on capital investments. The DICE model uses the estimated market return on capital as the discount rate, around an average of 4%. He argues that a higher discount rate will make future damages look small, thus have less effort to reduce emissions today. A lower discount rate will make future damages look larger, thus put more effort to reduce emissions today.
In Stern's view, the pure rate of time preference is defined as the discount rate in a scenario where present and future generations have equal resources and opportunities. A zero pure rate of time preference in this case would indicate that all generations are treated equally. The future generation do not have a "voice" on today's current policies, so the present generation are morally responsible to treat the future generation in the same manner. He suggests for a lower discount rate in which the present generation should invest in the future to reduce the risks of climate change.
Assumptions are made to support estimating high and low discount rates. These estimates depend on future emissions, climate sensitivity relative to increase in greenhouse gas concentrations, and the seriousness of impacts over time. Long-term climate policies will significantly impact future generations and this is called intergenerational discounting. Factors that make intergenerational discounting complicated include the great uncertainty of economic growth, future generations are affected by today's policies, and private discounting will be affected due to a longer "investment horizon".
Discounting is a relatively controversial issue in both climate change mitigation and environmental economics due to the ethical implications of valuing future generations less than present ones. Non-economists often find it difficult to grapple with the idea that thousands of dollars of future costs and benefits can be valued at less than a cent in the present after discounting.
Economic components like the stock market underestimate or cannot value social benefits of climate change mitigation. Climate change is largely an externality, despite a limited recent internalization of impacts that previously were fully 'external' to the economy.
Consumers can be and are affected by policies that relate to e.g. ethical consumer literacy, the available choices they have, transportation policy, product transparency policies, and larger-order economic policies that for example facilitate large-scale shifts of jobs. Such policies or measures are sometimes unpopular with the population. Therefore, they may be difficult for politicians to enact directly or help facilitate indirectly.
Climate policies-induced future lost financial profits from global stranded fossil-fuel assets would lead to major losses for freely managed wealth of investors in advanced economies in current economics.