Climate Deals

Kevin Lewis

April 10, 2024

The Market and Climate Implications of U.S. LNG Exports
James Stock & Matthew Zaragoza-Watkins
NBER Working Paper, March 2024

From 2015 to 2023, the United States transformed from a net importer of natural gas to the world's largest liquified natural gas (LNG) exporter. We find that this surge in LNG exports has reconnected U.S. gas prices to world market prices, after a hiatus of “shut-in” fracked gas. We estimate that the domestic gas price effect of this recoupling is comparable to a $30/ton carbon tax. For coal prices, which are coupled to gas through competition in the power sector, this effect is comparable to a $20/ton carbon tax. Using the NREL ReEDS model, we estimate that this recoupling reduces U.S. 2030 power sector CO2 emissions by roughly 145 million metric tons. These domestic estimates contribute to estimating the overall climate impact of LNG exports.

Individualism, universalism and climate change
Elodie Douarin & Tim Hinks
Journal of Institutional Economics, February 2024

Is ‘individualism’ pure selfishness? The climate change literature often assumes so. However, individualism can be seen as capturing values aligned with self-determination and self-achievement but also universalism. Indeed, cultural psychology recognises individualism as reflecting both personal agency and one's embeddedness, not in narrowly defined in-groups, but in society broadly. Through this lens, individualism can be consistent with adopting pro-social behaviours, including climate-friendly behaviours. But the under-exploration of the concept means empirical evidence is limited. Using cross-country, cross-sectional data we find that individualistic values are associated with an increased willingness to take individual-level actions against climate change. Individualism is also not associated with less support for additional taxes levied to fight climate change, and those willing to take more individual level actions against climate change are also more supportive of additional climate change taxes. Overall, our results confirm that individualism can be associated with taking actions for the greater good.

Adaptation Using Financial Markets: Climate Risk Diversification through Securitization
Matthew Kahn, Amine Ouazad & Erkan Yönder
NBER Working Paper, March 2024

In the face of rising climate risk, financial institutions may adapt by transferring such risk to securitizers that have the skill and expertise to build diversified pools, such as Mortgage-Backed Securities. In diversified pools, exposure to climate risk may be a drop in the ocean of cash flows. This paper builds a data set of the entire securitization chain from mortgage-level to MBS deal-level cash flows, and observes the prices of the tranches at monthly frequency. Wildfires lead to higher rates of prepayment and foreclosure at the mortgage level, and larger losses during foreclosure sales. At the MBS deal level, a lower spatial concentration of dollar balances (lower spatial dollar Herfindahl), a lower spatial correlation in wildfire events (within-deal correlation), leads to a lower exposure to wildfire events. These quantifiable metrics of diversification identify those existing deals whose design makes them resilient to climate change. This paper builds optimal deals by finding the portfolio weights in an asset demand system that targets return and risk. Extrapolating wildfire risk using a granular wildfire probability model and temperature projections in 2050, we build climate resilient MBSs whose returns are minimally impacted by wildfire risk even as they supply mortgage credit to wildfire prone areas. Finally, we test whether the market prices the sensitivity of each deal’s cash flow to wildfire risk.

The Climate in Climate Economics
Doris Folini et al.
Review of Economic Studies, forthcoming

To analyze climate change mitigation strategies, economists rely on simplified climate models -- so-called climate emulators -- that provide a realistic quantitative link between CO2 emissions and global warming at low computational costs. In this paper, we propose a generic and transparent calibration and evaluation strategy for these climate emulators that is based on freely and easily accessible state-of-the-art benchmark data from climate sciences. We demonstrate that the appropriate choice of the free model parameters can be of key relevance for the predicted social cost of carbon. The key idea we put forward is to calibrate the simplified climate models to benchmark data from comprehensive global climate models that took part in the Coupled Model Intercomparison Project, Phase 5 (CMIP5). In particular, we propose to use four different test cases that are considered pivotal in the climate science literature: two highly idealized tests to separately calibrate and evaluate the carbon cycle and temperature response, an idealized test to quantify the transient climate response, and a final test to evaluate the performance for scenarios close to those arising from economic models, and that include exogenous forcing. As a concrete example, we re-calibrate the climate part of the widely used DICE-2016, fathoming the CMIP5 uncertainty range of model responses: the multi-model mean as well as extreme, but still permissible climate sensitivities and carbon cycle responses. We demonstrate that the functional form of the climate emulator of the DICE-2016 model is fit for purpose, despite its simplicity, but its carbon cycle and temperature equations are miscalibrated, leading to the conclusion that one may want to be skeptical about predictions derived from DICE-2016. We examine the importance of the calibration for the social cost of carbon in the context of a partial equilibrium setting where interest rates are exogenous, as well as the simple general equilibrium setting from DICE-2016. We find that the model uncertainty from different consistent calibrations of the climate system can change the social cost of carbon by a factor of four if one assumes a quadratic damage function. When calibrated to the multi-model mean, our model predicts similar values for the social cost of carbon as the original DICE-2016, but with a strongly reduced sensitivity to the discount rate and about one degree less long-term warming. The social cost of carbon in DICE-2016 is oversensitive to the discount rate, leading to extreme comparative statics responses to changes in preferences.

Global supply chains amplify economic costs of future extreme heat risk
Yida Sun et al.
Nature, 28 March 2024, Pages 797–804

Evidence shows a continuing increase in the frequency and severity of global heatwaves, raising concerns about the future impacts of climate change and the associated socioeconomic costs. Here we develop a disaster footprint analytical framework by integrating climate, epidemiological and hybrid input–output and computable general equilibrium global trade models to estimate the midcentury socioeconomic impacts of heat stress. We consider health costs related to heat exposure, the value of heat-induced labour productivity loss and indirect losses due to economic disruptions cascading through supply chains. Here we show that the global annual incremental gross domestic product loss increases exponentially from 0.03 ± 0.01 (SSP 245)–0.05 ± 0.03 (SSP 585) percentage points during 2030–2040 to 0.05 ± 0.01–0.15 ± 0.04 percentage points during 2050–2060. By 2060, the expected global economic losses reach a total of 0.6–4.6% with losses attributed to health loss (37–45%), labour productivity loss (18–37%) and indirect loss (12–43%) under different shared socioeconomic pathways. Small- and medium-sized developing countries suffer disproportionately from higher health loss in South-Central Africa (2.1 to 4.0 times above global average) and labour productivity loss in West Africa and Southeast Asia (2.0–3.3 times above global average). The supply-chain disruption effects are much more widespread with strong hit to those manufacturing-heavy countries such as China and the USA, leading to soaring economic losses of 2.7 ± 0.7% and 1.8 ± 0.5%, respectively.

Disappearing cities on US coasts
Leonard Ohenhen et al.
Nature, 7 March 2024, Pages 108–115

The sea level along the US coastlines is projected to rise by 0.25–0.3 m by 2050, increasing the probability of more destructive flooding and inundation in major cities. However, these impacts may be exacerbated by coastal subsidence -- the sinking of coastal land areas -- a factor that is often underrepresented in coastal-management policies and long-term urban planning. In this study, we combine high-resolution vertical land motion (that is, raising or lowering of land) and elevation datasets with projections of sea-level rise to quantify the potential inundated areas in 32 major US coastal cities. Here we show that, even when considering the current coastal-defence structures, further land area of between 1,006 and 1,389 km2 is threatened by relative sea-level rise by 2050, posing a threat to a population of 55,000–273,000 people and 31,000–171,000 properties. Our analysis shows that not accounting for spatially variable land subsidence within the cities may lead to inaccurate projections of expected exposure. These potential consequences show the scale of the adaptation challenge, which is not appreciated in most US coastal cities.

Temperature anomalies undermine the health of reproductive-age women in low- and middle-income countries
Clark Gray & Brian Thiede
Proceedings of the National Academy of Sciences, 12 March 2024

Climate change is expected to undermine population health and well-being in low- and middle-income countries, but relatively few analyses have directly examined these effects using individual-level data at global scales, particularly for reproductive-age women. To address this lacuna, we harmonize nationally representative data from the Demographic and Health Surveys on reproductive health, body mass index (BMI), and temporary migration from 2.5 million adult women (ages 15 to 49) in approximately 109,000 sites across 59 low- and middle-income countries, which we link to high-resolution climate data. We use this linked dataset to estimate fixed-effect logistic regression models of demographic and health outcomes as a function of climate exposures, woman-level and site-level characteristics, seasonality, and regional time trends, allowing us to plausibly isolate climate effects from other influences on health and migration. Specifically, we measure the effects of recent exposures to temperature and precipitation anomalies on the likelihood of having a live birth in the past year, desire for another child, use of modern contraception, underweight (BMI < 18.5), and temporary migration, and subsequently allow for nonlinearity as well as heterogeneity across education, rural/urban residence, and baseline climate. This analysis reveals that exposures to high temperatures increase live births, reduce desire for another child, increase underweight, and increase temporary migration, particularly in rural areas. The findings represent clear evidence that anthropogenic temperature increases contribute to temporary migration and are a significant threat to women’s health and reproductive autonomy in low- and middle-income countries.

Mortality Burden From Wildfire Smoke Under Climate Change
Minghao Qiu et al.
NBER Working Paper, April 2024

Wildfire activity has increased in the US and is projected to accelerate under future climate change. However, our understanding of the impacts of climate change on wildfire smoke and health remains highly uncertain. We quantify the past and future mortality burden in the US due to wildfire smoke fine particulate matter (PM2.5). We construct an ensemble of statistical and machine learning models that link variation in climate to wildfire smoke PM2.5, and empirically estimate smoke PM2.5-mortality relationships using georeferenced data on all recorded deaths in the US from 2006 to 2019. We project that climate-driven increases in future smoke PM2.5 could result in 27,800 excess deaths per year by 2050 under a high warming scenario, a 76% increase relative to estimated 2011-2020 averages. Cumulative excess deaths from wildfire smoke PM2.5 could exceed 700,000 between 2025-2055. When monetized, climate-induced smoke deaths result in annual damages of $244 billion by mid-century, comparable to the estimated sum of all other damages in the US in prior analyses. Our research suggests that the health cost of climate-driven wildfire smoke could be among the most important and costly consequences of a warming climate in the US.

US oil and gas system emissions from nearly one million aerial site measurements
Evan Sherwin et al.
Nature, 14 March 2024, Pages 328–334

As airborne methane surveys of oil and gas systems continue to discover large emissions that are missing from official estimates, the true scope of methane emissions from energy production has yet to be quantified. We integrate approximately one million aerial site measurements into regional emissions inventories for six regions in the USA, comprising 52% of onshore oil and 29% of gas production over 15 aerial campaigns. We construct complete emissions distributions for each, employing empirically grounded simulations to estimate small emissions. Total estimated emissions range from 0.75% (95% confidence interval (CI) 0.65%, 0.84%) of covered natural gas production in a high-productivity, gas-rich region to 9.63% (95% CI 9.04%, 10.39%) in a rapidly expanding, oil-focused region. The six-region weighted average is 2.95% (95% CI 2.79%, 3.14%), or roughly three times the national government inventory estimate. Only 0.05–1.66% of well sites contribute the majority (50–79%) of well site emissions in 11 out of 15 surveys. Ancillary midstream facilities, including pipelines, contribute 18–57% of estimated regional emissions, similarly concentrated in a small number of point sources. Together, the emissions quantified here represent an annual loss of roughly US$1 billion in commercial gas value and a US$9.3 billion annual social cost. Repeated, comprehensive, regional remote-sensing surveys offer a path to detect these low-frequency, high-consequence emissions for rapid mitigation, incorporation into official emissions inventories and a clear-eyed assessment of the most effective emission-finding technologies for a given region.

The visual effect of wind turbines on property values is small and diminishing in space and time
Wei Guo, Leonie Wenz & Maximilian Auffhammer
Proceedings of the National Academy of Sciences, 26 March 2024

Renewable power generation is the key to decarbonizing the electricity system. Wind power is the fastest-growing renewable source of electricity in the United States. However, expanding wind capacity often faces local opposition, partly due to a perceived visual disamenity from large wind turbines. Here, we provide a US-wide assessment of the externality costs of wind power generation through the visibility impact on property values. To this end, we create a database on wind turbine visibility, combining information on the site and height of each utility-scale turbine having fed power into the U.S. grid, with a high-resolution elevation map to account for the underlying topography of the landscape. Building on hedonic valuation theory, we statistically estimate the impact of wind turbine visibility on home values, informed by data from the majority of home sales in the United States since 1997. We find that on average, wind turbine visibility negatively affects home values in an economically and statistically significant way in close proximity (<5 miles/8 km). However, the effect diminishes over time and in distance and is indistinguishable from zero for larger distances and toward the end of our sample.

A global timekeeping problem postponed by global warming
Duncan Carr Agnew
Nature, forthcoming

The historical association of time with the rotation of Earth has meant that Coordinated Universal Time (UTC) closely follows this rotation. Because the rotation rate is not constant, UTC contains discontinuities (leap seconds), which complicates its use in computer networks. Since 1972, all UTC discontinuities have required that a leap second be added. Here we show that increased melting of ice in Greenland and Antarctica, measured by satellite gravity, has decreased the angular velocity of Earth more rapidly than before. Removing this effect from the observed angular velocity shows that since 1972, the angular velocity of the liquid core of Earth has been decreasing at a constant rate that has steadily increased the angular velocity of the rest of the Earth. Extrapolating the trends for the core and other relevant phenomena to predict future Earth orientation shows that UTC as now defined will require a negative discontinuity by 2029. This will pose an unprecedented problem for computer network timing and may require changes in UTC to be made earlier than is planned. If polar ice melting had not recently accelerated, this problem would occur 3 years earlier: global warming is already affecting global timekeeping.

Global prediction of extreme floods in ungauged watersheds
Grey Nearing et al.
Nature, 21 March 2024, Pages 559–563

Floods are one of the most common natural disasters, with a disproportionate impact in developing countries that often lack dense streamflow gauge networks. Accurate and timely warnings are critical for mitigating flood risks, but hydrological simulation models typically must be calibrated to long data records in each watershed. Here we show that artificial intelligence-based forecasting achieves reliability in predicting extreme riverine events in ungauged watersheds at up to a five-day lead time that is similar to or better than the reliability of nowcasts (zero-day lead time) from a current state-of-the-art global modelling system (the Copernicus Emergency Management Service Global Flood Awareness System). In addition, we achieve accuracies over five-year return period events that are similar to or better than current accuracies over one-year return period events. This means that artificial intelligence can provide flood warnings earlier and over larger and more impactful events in ungauged basins. The model developed here was incorporated into an operational early warning system that produces publicly available (free and open) forecasts in real time in over 80 countries. This work highlights a need for increasing the availability of hydrological data to continue to improve global access to reliable flood warnings.


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