8 Costs
8.1 EEA Extreme Event Attribution
- Newmann & Noy Abstract*
Extreme weather events lead to significant adverse societal costs. Extreme Event Attribution (EEA), a methodology that examines how anthropogenic greenhouse gas emissions had changed the occurrence of specific extreme weather events, allows us to quantify the climate change-induced component of these costs. We collect data from all available EEA studies, combine these with data on the socio-economic costs of these events and extrapolate for missing data to arrive at an estimate of the global costs of extreme weather attributable to climate change in the last twenty years. We find that US$ 143 billion per year of the costs of extreme events is attributable to climatic change. The majority (63%), of this is due to human loss of life. Our results suggest that the frequently cited estimates of the economic costs of climate change arrived at by using Integrated Assessment Models may be substantially underestimated.
- Newmann & Noy Memo*
The EEA methodology compares the probability of an event that occurred with the probability or intensity of the same event occurring in a counterfactual world without anthropogenic emissions. From a probabilistic perspective, a Fraction of Attributable Risk (FAR) metric is calculated to describe what portion of the risk of an extreme weather event occurring is the result of climate change. Methodologically, these probabilistic methods have been approached from both a frequentist or a Bayesian perspective5, with possibly important consequences for the results thus obtained. We do not distinguish between these in our work here, given the relative paucity of Bayesian attribution work. The attri- bution approach based on FAR is known as the risk-based approach6. The alternative intensity approach calculates what share of a specific aspect of the risk (e.g., rainfall) was due to climate change. For instance, the 2017 Hurricane Harvey’s climate change-induced economic costs were analyzed by both risk-based7 and intensity-based8 approaches.
The economic costs associated with extreme weather events can be measured in two ways: First, these include direct economic damage, which occurs during or immediately after the event. Using flooding as an example, where the hazard is heavy precipitation, direct economic damage may include destroyed housing and roads, or lost crops. However, an extreme weather event can also cause indirect economic losses. These are declines in economic value-added because of the direct economic damage. Examples of these indirect losses are wide- ranging. For the flood example, they could include microeconomic impacts such as revenue loss for businesses when access routes are inundated by floodwater, meso-economic impacts such as temporary unemployment in the affected area, or even wider-ranging macroscale supply-chain disruptions. These indirect economic losses can often spill out beyond the affected area, and indeed even beyond the affected country/region’s borders. Indirect losses may also have long time lags, making them difficult to quantify. Generally, events that cause more damage will also lead to more losses, ceteris paribus. However, this relationship between direct damage and indirect loss is nonlinear, with high-damage events causing disproportionately many more losses as well. Because of these difficulties in quantifying indirect (flow) losses over a large variety of extreme weather phenomena in a large diversity of countries/regions and economies (thereafter refer- red to as countries for ease of exposition) and affected regions, this paper only focuses on the more easily quantified stock of direct damages.
By combining the data on direct economic damages, with the attributable share of the risk, we can quantify the climate change- attributable cost of these events. This attribution-based method for calculating the costs of climate change (from extreme weather events) differs fundamentally from other approaches to climate change cost estimation. Those other approaches use macroeconomic modeling embedded within climate models in various types of Integrated Assessment Models (IAM).
Aim is to demonstrate the use-value of the methodology, rather than reach an unimpeachable set of estimates.
Most IAMs are substantially under- estimating the current economic costs of climate change.
Newmann & Noy (2023) The global costs of extreme weather that are attributable to climate change (pdf)
Carrington on Newmann & Noy
The damage caused by the climate crisis through extreme weather has cost $16m (£13m) an hour for the past 20 years, according to a new estimate. It found average costs of $140bn (£115bn) a year from 2000 to 2019, although the figure varies significantly from year to year. The latest data shows $280bn in costs in 2022. The researchers said lack of data, particularly in low-income countries, meant the figures were likely to be seriously underestimated. Additional climate costs, such as from crop yield declines and sea level rise, were also not included.
The researchers produced the estimates by combining data on how much global heating worsened extreme weather events with economic data on losses. The study also found that the number of people affected by extreme weather because of the climate crisis was 1.2 billion over two decades.
Hundreds of “attribution” studies have been done, calculating how much more frequent global heating made extreme weather events. This allows the fraction of the damages resulting from human-caused heating to be estimated.
The researchers applied these fractions to the damages recorded in the International Disaster Database, which compiles available data on all disasters in which 10 people died, or 100 were affected, or the country declared a state of emergency or requested international assistance.
The central estimate was an average climate cost of $140bn a year, with a range from $60bn to $230bn. These estimates are much higher than those from computer models, which are based on changes in average global temperature rather than on the extreme temperatures increasingly being seen in the world.
The analysis used a statistical value of a life lost of $7m, an average of the figures used by the US and UK governments.
Only considering the economic damage caused to infrastructure would heavily skew the cost estimates to rich countries, despite much of the damage from extreme weather hitting poorer ones.
This study looks at the attribution for the physical event – it’s much simpler, robust, and it provides a convincing case. It is an emerging field and uncertainties are really large. One lesson of the study is that global research centres – mostly located in rich countries – need to work more on what is happening in poorer countries.
Carrington (2023) Climate crisis costing $16m an hour in extreme weather damage
8.2 Insurance
Keen
Flawed economic thinking on climate has put your pension at risk
Investment consultants to pension funds have relied upon peer-reviewed economic research to provide advice to pension funds on the damages to pensions that will be caused by global warming.
Following the advice of investment consultants, pension funds have informed their members that global warming of 2-4.3 oC will have only a minimal impact upon their portfolios.
The economics papers informing the models used by investment consultants are at odds with the scientific literature on the impact of these levels of warming.
The economics of climate change is an interdisciplinary subject, but papers on the economics of climate damages were refereed by economists alone. Properly refereeing these papers required knowledge of the science of global warming that economists typically did not have. Consequently, economic referees approved the publication of papers that made claims about global warming that are seriously at odds with the scientific literature.
These claims have been fundamental to the predictions by economists of minimal impacts on the economy from global warming.
Economists have claimed, in refereed economics papers, that 6oC of global warming will reduce future global GDP by less than 10%, compared to what GDP would have been in the complete absence of climate change.
In contrast, scientists have claimed, in refereed science papers, that 5oC of global warming implies damages that are “beyond catastrophic, including existential threats,” while even 1oC of warming—which we have already passed—could trigger dangerous climate tipping points.
This results in a huge disconnect between what scientists expect from global warming, and what pensioners/investors/financial systems are prepared for.
Consequently, a wealth-damaging correction or “Minsky Moment” cannot be ruled out, and is virtually inevitable. Pension funds have a fiduciary duty to correct the erroneous predictions they have given their members.
Similarly, financial regulators, who have used the same erroneous and misleading economic damage predictions to stress test the exposure of financial institutions to climate change, must drastically revise their stress test studies.
This report calls on all stakeholders, from governments, regulators, investment professionals, all the way to civil society groups and individuals, to ensure that climate change policy is based upon the work of scientists.
Climate change must be treated as a potentially existential threat to the economy, rather than an issue which is suitably addressed by economic cost-benefit analysis.
Keen (2023) Loading the DICE against Pension Funds
Parshley
Insured losses from natural disasters in the U.S. now routinely approach $100 billion a year, compared to $4.6 billion in 2000. As a result, the average homeowner has seen their premiums spike 21 percent since 2015. Perhaps unsurprisingly, the states most likely to have disasters — like Texas and Florida — have some of the most expensive insurance rates. That means ever more people are forgoing coverage, leaving them vulnerable and driving prices even higher as the number of people paying premiums and sharing risk shrinks.
Reinsurers globally raised prices for property insurers by 37 percent in 2023, contributing to insurance companies pulling back from risky states like California and Florida.
In a worse-case scenario, this all leads to a massive stranded asset problem: Premiums get so high that property values plummet, families’ investments dissipate, and banks are stuck holding what’s left.
The global process for handling life’s risks is breaking down, leaving those who can least afford it unprotected.
In the last decade, the frequency of global natural catastrophes jumped by 28 percent. On a single day in July, 60 percent of the U.S. population faced an extreme weather alert. Costs have catapulted too: Since 1970, losses from disasters increased an average 5 percent a year, particularly in the United States. Tragically, the fastest-growing counties also face some of the highest risks. It doesn’t have to be one of these huge events. It’s [also] successive events, back-to-back - like the 12 atmospheric rivers that hit California this winter.
The reinsurance industry has paid dearly for much of the last decade; underwriting losses drove $115 billion in global reinsurance losses in 2022. There’s a tension over a business model that’s retrospective, with a risk that’s emerging. The financial foundation of insurance, in other words, is cracking.
Unlike insurers, who face political pressures from state regulators to keep rates affordable, reinsurance is much more of a free market. Reinsurers are reacting by raising their rates, limiting their coverage, and even deciding to reduce their exposure in places like Florida.
Because getting risk wrong is now so costly, there’s been a race in the private sector to model future odds. This rush to fine-tune risk predictions may potentially accelerate skyrocketing premiums.
The economic implications of all this are troubling. A new report by the U.S. Treasury Department, released at the end of June, found major gaps in the supervision and regulation of insurers. The report advised much closer attention to “the risks the insurance industry may pose to the overall financial sector.”
As disasters continue surging, what they call the “growing climate bubble in the housing market” will pop — leaving millions of homes uninsurable and destroying their value. If the value of their home plummets or if the credit agencies downgrade their communities we will have a lot of people trapped in places that are unsafe, economically trapped.
Insurers have played a major role in emissions for decades: Without insurance, fossil fuel companies have difficulty obtaining financing. Insurers have been slower to move away from oil and gas, in part because it’s a larger part of many companies’ business.
It is difficult to understand how the industry can carefully price and manage climate risk in some areas of its business while simultaneously having no apparent plan to phase out its underwriting of and investment in the projects and companies generating the emissions that are causing these very harms.
The economic and insured losses over time are a clear indicator that the past is not a representation of the future. With insurers themselves running out of insurance options, the stability of financial systems is far shakier than many realize.
Science is the easy part. Getting people to change their behavior, on the other hand, is difficult.
Parshley (2023) As climate risks mount, the insurance safety net is collapsing
8.3 Climate Change Inflation
Epp
Climate change is going to cost us, said Kenneth Gillingham, a professor of environmental and energy economics at Yale. It will create an upward force on prices in many sectors. Some will affect us over the long term, but we’re already feeling them now. For example, air pollution and hotter temperatures.
We are more likely to have, say, ground-level ozone, which will lead to asthma cases and hospital admissions.
That could inflate health care costs.
Epp (2023) Climate change effects likely to include long-term inflation
8.4 Productivity Loss
Benayad
The physical effects of climate change will significantly reduce economic productivity and damage economic assets this century.
Our analysis suggests that the cumulative economic output could be reduced by 15% to 34% if the global average temperature is allowed to rise by 3°C by 2100 rather than being limited to below 2°C. This is the equivalent of reducing annual GDP growth by 0.56%. It’s likely that the economic damages will be at the upper end of the range (or even higher) due to the limitations of current models. They do not, for example, fully account for the economic damage of passing tipping points, such as the loss of coral reefs or the Amazon forest dieback
Vetter on Benayad (2025) Climate Inaction Could Cost 1/3 Of Global GDP This Century