Solomon Hsiang

We develop empirically-grounded estimates of willingness-to-pay to avoid excess mortality risks caused by climate change. Using 40 countries' subnational data, we estimate a mortality-temperature relationship that enables global extrapolation to countries without data and projection of its future evolution, accounting for adaptation benefits. Further, we develop a revealed preference approach to recover unobserved adaptation costs. We combine these components with 33 high-resolution climate simulations, which produces a right-skewed distribution of global WTP with a mean of $38.1 per tCO2 under a high emissions scenario. Projections generally indicate increased mortality in today's poor locations and higher adaptation expenditures in rich ones.

We develop a simple cross-sectional research design to identify causal effects that is robust to unobservable heterogeneity. When many observational units are dense in physical space, it may be sufficient to regress the “spatial first differences” (SFD) of the outcome on the treatment and omit all covariates. This approach is conceptually similar to first differencing approaches in timeseries or panel models, except the index for time is replaced with an index for locations in space. The SFD design identifies plausibly causal effects, even when no instruments are available, so long as local changes in the treatment and unobservable confounders are not systematically correlated between immediately adjacent neighbors. We demonstrate the SFD approach by recovering new cross-sectional estimates for the effects of time-invariant geographic factors, soil and climate, on long-run average crop productivities across US counties — relationships that are notoriously confounded by unobservables but crucial for guiding economic decisions, such as land management and climate policy.

Accumulating evidence indicates that environmental temperature substantially affects economic outcomes and violence, but the reasons for this linkage are not well understood. We systematically evaluate the effect of thermal stress on multiple dimensions of economic decisionmaking, judgment, and destructive behavior with 2,000 participants in Kenya and the US who were randomly assigned to different temperatures in a laboratory. We find that most dimensions of decision-making are unaffected by temperature. However, heat causes individuals to voluntarily destroy other participants’ assets, with more pronounced effects during a period of heightened political conflict in Kenya.

This paper shows that greater global spatial correlation of productivities can increase crosscountry welfare dispersion by increasing the correlation between a country’s productivity and its gains from trade. We causally validate this general-equilibrium prediction using a global climatic phenomenon as a natural experiment. We find that gains from trade in cereals over the last halfcentury were larger for more productive countries and smaller for less productive countries when cereal productivity was more spatially correlated. Incorporating this general-equilibrium effect into a projection of climate-change impacts raises projected international inequality, with higher welfare losses across most of Africa.

We develop an empirical approach to value changes to a climate in terms of total market output given optimal factor allocations in general equilibrium. Our approach accounts for unobservable heterogeneity across locations as well as the costs and benefits of adaptation in climates of arbitrary dimension. Importantly, we demonstrate that the Envelope Theorem implies the marginal product of a long-run climate can be exactly identified using only idiosyncratic weather variation. We apply this method to the temperature climate of the modern United States and find that, despite evidence that populations adapt, the marginal product of temperature has remained unchanged during 1970-2010, with high temperatures having low net value. Integrating marginal products recovers a value function for temperature, describing the causal effect of non-marginal climate changes net of adaptive re-optimization. We use this value function to consider the influence of temperature in the current cross-section and a future climate change scenario.

Black markets are estimated to represent a fifth of global economic activity, but their response to policy is poorly understood because participants systematically hide their actions. It is widely hypothesized that relaxing trade bans in illegal goods allows legal supplies to competitively displace illegal supplies, but a richer economic theory provides more ambiguous predictions. Here we evaluate the first major global legalization experiment in an internationally banned market, where a monitoring system established before the experiment enables us to observe the behavior of illegal suppliers before and after. International trade of ivory was banned in 1989, with global elephant poaching data collected by field researchers since 2003. A one-time legal sale of ivory stocks in 2008 was designed as an experiment, but its global impact has not been evaluated. We find that international announcement of the legal ivory sale corresponds with an abrupt ~66% increase in illegal ivory production across two continents, and a possible ten-fold increase in its trend. An estimated ~71% increase in ivory smuggling out of Africa corroborates this finding, while corresponding patterns are absent from natural mortality and alternative explanatory variables. These data suggest the widely documented recent increase in elephant poaching likely originated with the legal sale. More generally, these results suggest that changes to producer costs and/or consumer demand induced by legal sales can have larger effects than displacement of illegal production in some global black markets, implying that partial legalization of banned goods does not necessarily reduce black market activity.

It is widely hypothesized that incomes in wealthy countries are insulated from environmental conditions because individuals have the resources needed to adapt to their environment. We test this idea in the wealthiest economy in human history. Using within-county variation in weather, we estimate the effect of daily temperature on annual income in United States counties over a 40-year period. We find that this single environmental parameter continues to play a large role in overall economic performance: productivity of individual days declines roughly 1.7% for each 1°C (1.8°F) increase in daily average temperature above 15°C (59°F). A weekday above 30°C (86°F) costs an average county $20 per person. Hot weekends have little effect. These estimates are net of many forms of adaptation, such as factor reallocation, defensive investments, transfers, and price changes. Because the effect of temperature has not changed since 1969, we infer that recent uptake or innovation in adaptation measures have been limited. The non-linearity of the effect on different components of income suggest that temperature matters because it reduces the productivity of the economy's basic elements, such as workers and crops. If counties could choose daily temperatures to maximize output, rather than accepting their geographicallydetermined endowment, we estimate that annual income growth would rise by 1.7 percentage points. Applying our estimates to a distribution of "business as usual" climate change projections indicates that warmer daily temperatures will lower annual growth by 0.06-0.16 percentage points in the United States unless populations engage in new forms of adaptation.

Does the environment have a causal effect on economic development? Using meteorological data, we reconstruct every country's exposure to the universe of tropical cyclones during 1950-2008. We exploit random within-country year-to-year variation in cyclone strikes to identify the causal effect of environmental disasters on long-run growth. We compare each country's growth rate to itself in the years immediately before and after exposure, accounting for the distribution of cyclones in preceding years. The data reject hypotheses that disasters stimulate growth or that short-run losses disappear following migrations or transfers of wealth. Instead, we find robust evidence that national incomes decline, relative to their pre-disaster trend, and do not recover within twenty years. Both rich and poor countries exhibit this response, with losses magnified in countries with less historical cyclone experience. Income losses arise from a small but persistent suppression of annual growth rates spread across the fifteen years following disaster, generating large and significant cumulative effects: a 90th percentile event reduces per capita incomes by 7.4% two decades later, effectively undoing 3.7 years of average development. The gradual nature of these losses render them inconspicuous to a casual observer, however simulations indicate that they have dramatic influence over the long-run development of countries that are endowed with regular or continuous exposure to disaster. Linking these results to projections of future cyclone activity, we estimate that under conservative discounting assumptions the present discounted cost of "business as usual" climate change is roughly $9.7 trillion larger than previously thought.

The immediate physical damages caused by environmental disasters are conspicuous and often the focus of media and government attention. In contrast, the nature and magnitude of post-disaster losses remain largely unknown because they are not easily observable. Here we exploit annual variation in the incidence of typhoons (West-Pacific hurricanes) to identify post-disaster losses within Filipino households. We find that unearned income and excess infant mortality in the year after typhoon exposure outnumber immediate damages and death tolls roughly 15-to-1. Typhoons destroy durable assets and depress incomes, leading to broad expenditure reductions achieved in part through disinvestments in health and human capital. Infant mortality mirrors these economic responses, and additional findings -- that only female infants are at risk, that sibling competition elevates risk, and that infants conceived after a typhoon are also at risk -- indicate that this excess mortality results from household decisions made while coping with post-disaster economic conditions. We estimate that these post-typhoon "economic deaths" constitute 13% of the overall infant mortality rate in the Philippines. Taken together, these results indicate that economic and human losses due to environmental disaster may be an order of magnitude larger than previously thought and that adaptive decision-making may amplify, rather than dampen, disasters' social cost.

We assess scientific evidence that has emerged since the U.S. Environmental Protection Agency’s 2009 Endangerment Finding for six well-mixed greenhouse gases and find that this new evidence lends increased support to the conclusion that these gases pose a danger to public health and welfare. Newly available evidence about a wide range of observed and projected impacts strengthens the association between the risk of some of these impacts and anthropogenic climate change, indicates that some impacts or combinations of impacts have the potential to be more severe than previously understood, and identifies substantial risk of additional impacts through processes and pathways not considered in the Endangerment Finding.

Most regulations designed to reduce environmental externalities impose costs on individuals and firms. A large and growing literature examines whether these costs are disproportionately borne by different sectors of the economy and/or across different groups of individuals. However, much less is known about how the environmental benefits created by these policies are distributed, which mirror the differences in environmental damages associated with existing environmental externalities. We review this burgeoning literature and develop a simple general framework for empirical analysis. We apply this framework to findings concerning the distributional impacts of environmental damages from air pollution, deforestation, and climate change and highlight priorities for future research. A recurring challenge to understanding the distributional effects of environmental damages is distinguishing between cases in which populations are exposed to different levels or changes in an environmental good and those in which an incremental change in the environment may have very different implications for some populations. In the latter case, it is often difficult to empirically identify the underlying sources of heterogeneity in marginal damages because damages may stem from nonlinear and/or heterogeneous damage functions. Nevertheless, understanding the determinants of heterogeneity in environmental benefits and damages is crucial for welfare analysis and policy design.

This article provides a brief introduction to the physical science of climate change, aimed towards economists. We begin by describing the physics that controls global climate, how scientists measure and model the climate system, and the magnitude of human-caused emissions of carbon dioxide. We then summarize many of the climatic changes of interest to economists that have been documented and that are projected in the future. We conclude by highlighting some key areas in which economists are in a unique position to help climate science advance. An important message from this final section, which we believe is deeply underappreciated among economists, is that all climate change forecasts rely heavily and directly on economic forecasts for the world. On timescales of a half-century or longer, the largest source of uncertainty in climate science is not physics, but economics.

Solar radiation management is increasingly considered to be an option for managing global temperatures, yet the economic effects of ameliorating climatic changes by scattering sunlight back to space remain largely unknown. Although solar radiation management may increase crop yields by reducing heat stress, the effects of concomitant changes in available sunlight have never been empirically estimated. Here we use the volcanic eruptions that inspired modern solar radiation management proposals as natural experiments to provide the first estimates, to our knowledge, of how the stratospheric sulfate aerosols created by the eruptions of El Chichón and Mount Pinatubo altered the quantity and quality of global sunlight, and how these changes in sunlight affected global crop yields. We find that the sunlight-mediated effect of stratospheric sulfate aerosols on yields is negative for both C4 (maize) and C3 (soy, rice and wheat) crops. Applying our yield model to a solar radiation management scenario based on stratospheric sulfate aerosols, we find that projected mid-twenty-first century damages due to scattering sunlight caused by solar radiation management are roughly equal in magnitude to benefits from cooling. This suggests that solar radiation management—if deployed using stratospheric sulfate aerosols similar to those emitted by the volcanic eruptions it seeks to mimic—would, on net, attenuate little of the global agricultural damage from climate change. Our approach could be extended to study the effects of solar radiation management on other global systems, such as human health or ecosystem function.

Linkages between climate and mental health are often theorized but remain poorly quantified. In particular, it is unknown whether the rate of suicide, a leading cause of death globally, is systematically affected by climatic conditions. Using comprehensive data from multiple decades for both the United States and Mexico, we find that suicide rates rise 0.7% in US counties and 2.1% in Mexican municipalities for a 1 °C increase in monthly average temperature. This effect is similar in hotter versus cooler regions and has not diminished over time, indicating limited historical adaptation. Analysis of depressive language in >600 million social media updates further suggests that mental well-being deteriorates during warmer periods. We project that unmitigated climate change (RCP8.5) could result in a combined 9–40 thousand additional suicides (95% confidence interval) across the United States and Mexico by 2050, representing a change in suicide rates comparable to the estimated impact of economic recessions, suicide prevention programmes or gun restriction laws.

Estimates of climate change damage are central to the design of climate policies. Here, we develop a flexible architecture for computing damages that integrates climate science, econometric analyses, and process models. We use this approach to construct spatially explicit, probabilistic, and empirically derived estimates of economic damage in the United States from climate change. The combined value of market and nonmarket damage across analyzed sectors—agriculture, crime, coastal storms, energy, human mortality, and labor—increases quadratically in global mean temperature, costing roughly 1.2% of gross domestic product per +1°C on average. Importantly, risk is distributed unequally across locations, generating a large transfer of value northward and westward that increases economic inequality. By the late 21st century, the poorest third of counties are projected to experience damages between 2 and 20% of county income (90% chance) under business-as-usual emissions (Representative Concentration Pathway 8.5).

For centuries, thinkers have considered whether and how climatic conditions—such as temperature, rainfall, and violent storms—influence the nature of societies and the performance of economies. A multidisciplinary renaissance of quantitative empirical research is illuminating important linkages in the coupled climate-human system. We highlight key methodological innovations and results describing effects of climate on health, economics, conflict, migration, and demographics. Because of persistent “adaptation gaps,”current climate conditions continue to play a substantial role in shaping modern society, and future climate changes will likely have additional impact. For example, we compute that temperature depresses current U.S. maize yields by ~48%, warming since 1980 elevated conflict risk in Africa by ~11%, and future warming may slow global economic growth rates by ~0.28 percentage points per year. In general, we estimate that the economic and social burden of current climates tends to be comparable in magnitude to the additional projected impact caused by future anthropogenic climate changes. Overall, findings from this literature point to climate as an important influence on the historical evolution of the global economy, they should inform how we respond to modern climatic conditions, and they can guide how we predict the consequences of future climate changes.

Identifying the effect of climate on societies is central to understanding historical economic development, designing modern policies that react to climatic events, and managing future global climate change. Here, I review, synthesize, and interpret recent advances in methods used to measure effects of climate on social and economic outcomes. Because weather variation plays a large role in recent progress, I formalize the relationship between climate and weather from an econometric perspective and discuss the use of these two factors as identifying variation, highlighting trade-offs between key assumptions in different research designs and deriving conditions when weather variation exactly identifies the effects of climate. I then describe recent advances, such as the parameterization of climate variables from a social perspective, use of nonlinear models with spatial and temporal displacement, characterization of uncertainty, measurement of adaptation, cross-study comparison, and use of empirical estimates to project the impact of future climate change. I conclude by discussing remaining methodological challenges.

Evidence increasingly suggests that as climate warms, some plant, animal and human populations may move to preserve their environmental temperature. The distances they must travel to do this depends on how much cooler nearby surfaces temperatures are. Because large-scale atmospheric dynamics constrain surface temperatures to be nearly uniform near the equator, these displacements can grow to extreme distances in the tropics, even under relatively mild warming scenarios. Here we show that in order to preserve their annual mean temperatures, tropical populations would have to travel distances greater than 1000 km over less than a century if global mean temperature rises by 2 °C over the same period. The disproportionately rapid evacuation of the tropics under such a scenario would cause migrants to concentrate in tropical margins and the subtropics, where population densities would increase 300% or more. These results may have critical consequences for ecosystem and human wellbeing in tropical contexts where alternatives to geographic displacement are limited.

Growing evidence demonstrates that climatic conditions can have a profound impact on the functioning of modern human societies, but effects on economic activity appear inconsistent. Fundamental productive elements of modern economies, such as workers and crops, exhibit highly non-linear responses to local temperature even in wealthy countries. In contrast, aggregate macroeconomic productivity of entire wealthy countries is reported not to respond to temperature, while poor countries respond only linearly. Resolving this conflict between micro and macro observations is critical to understanding the role of wealth in coupled human–natural systems and to anticipating the global impact of climate change. Here we unify these seemingly contradictory results by accounting for non-linearity at the macro scale. We show that overall economic productivity is non-linear in temperature for all countries, with productivity peaking at an annual average temperature of 13 °C and declining strongly at higher temperatures. The relationship is globally generalizable, unchanged since 1960, and apparent for agricultural and non-agricultural activity in both rich and poor countries. These results provide the first evidence that economic activity in all regions is coupled to the global climate and establish a new empirical foundation for modelling economic loss in response to climate change, with important implications. If future adaptation mimics past adaptation, unmitigated warming is expected to reshape the global economy by reducing average global incomes roughly 23% by 2100 and widening global income inequality, relative to scenarios without climate change. In contrast to prior estimates, expected global losses are approximately linear in global mean temperature, with median losses many times larger than leading models indicate.

We review the emerging literature on climate and conflict. We consider multiple types of human conflict, including both interpersonal conflict, such as assault and murder, and intergroup conflict, including riots and civil war. We discuss key methodological issues in estimating causal relationships and largely focus on natural experiments that exploit variation in climate over time. Using a hierarchical meta-analysis that allows us to both estimate the mean effect and quantify the degree of variability across 55 studies, we find that deviations from moderate temperatures and precipitation patterns systematically increase conflict risk. Contemporaneous temperature has the largest average impact, with each 1σ increase in temperature increasing interpersonal conflict by 2.4% and intergroup conflict by 11.3%. We conclude by highlighting research priorities, including a better understanding of the mechanisms linking climate to conflict, societies’ ability to adapt to climatic changes, and the likely impacts of future global warming.

Why wealth is systematically lower in the tropics remains a puzzle. We point out that latitude may have fundamental economic consequence because it plays a key role in how countries experience geophysical processes that have economic implications. We demonstrate that annual fluctuations in the El Nino Southern Oscillation (ENSO) leads to hotter and dryer local weather across tropical countries and subsequently to substantial losses in agricultural yields, output, and value-added. If volatility in agricultural production impedes economic growth, the relatively stronger influence of ENSO on the tropics may offer yet another partial explanation for slower historical growth in the tropics.

It has been proposed that geography influences economic growth for many reasons. Previous analyses of comparative development seem to have sidestepped the question of location-dependent depreciation. However the construction of new measures of tropical cyclone exposure enables us to consider the potential impact of this single source of capital depreciation. Using an estimate of asset destruction due to tropical cyclones, we identify the "sandcastle depreciation" rate, and find support for location-dependent depreciation by looking at average growth rates. This leads us to propose that heterogeneous and geographically-dependent depreciation rates may play an important role in global patterns of economic development.

A comment by Buhaug et al. attributes disagreement between our recent analyses and their review articles to biased decisions in our meta-analysis and a difference of opinion regarding statistical approaches. The claim is false. Buhaug et al.’s alteration of our metaanalysis misrepresents findings in the literature, makes statistical errors, misclassifies multiple studies, makes coding errors, and suppresses the display of results that are consistent with our original analysis. We correct these mistakes and obtain findings in line with our original results, even when we use the study selection criteria proposed by Buhaug et al. We conclude that there is no evidence in the data supporting the claims raised in Buhaug et al.

Climate change threatens the economy of the United States in myriad ways, including increased flooding and storm damage, altered crop yields, lost labor productivity, higher crime, reshaped public-health patterns, and strained energy systems, among many other effects. Combining the latest climate models, state-of-the-art econometric research on human responses to climate, and cutting-edge private-sector risk-assessment tools, Economic Risks of Climate Change: An American Prospectus crafts a game-changing profile of the economic risks of climate change in the United States.

This prospectus is based on a critically acclaimed independent assessment of the economic risks posed by climate change commissioned by the Risky Business Project. With new contributions from Karen Fisher-Vanden, Michael Greenstone, Geoffrey Heal, Michael Oppenheimer, and Nicholas Stern and Bob Ward, as well as a foreword from Risky Business cochairs Michael Bloomberg, Henry Paulson, and Thomas Steyer, the book speaks to scientists, researchers, scholars, activists, and policy makers. It depicts the distribution of escalating climate-change risk across the country and assesses its effects on aspects of the economy as varied as hurricane damages and violent crime. Beautifully illustrated and accessibly written, this book is an essential tool for helping businesses and governments prepare for the future.

Abstract Are violent conflict and socio-political stability associated with changes in climatological variables? We examine 50 rigorous quantitative studies on this question and find consistent support for a causal association between climatological changes and various conflict outcomes, at spatial scales ranging from individual buildings to the entire globe and at temporal scales ranging from an anomalous hour to an anomalous millennium.Multiplemechanisms that could explain this association have been proposed and are sometimes supported by findings, but the literature is currently unable to decisively exclude any proposed pathway. Several mechanisms likely contribute to the outcomes that we observe.

There is a long history of using weather measures as explanatory variables in statistical models. For example, Fisher (1925) examined the effects of rainfall on wheat yields, andWright (1928) used weather as an instrumental variable to identify a demand function for oils. Because weather is exogenous and random in most economic applications, it acts like a “natural experiment” and thus in some settings allows researchers to identify statistically the causal effect of one variable on an economic outcome of interest (Angrist and Krueger 2001). The relatively recent literature on the economic impacts of climate change has turned the spotlight onto quantifying the effect of climate on a number of economic outcomes of interest (e.g., agricultural yields, mortality rates, electricity and water demand). This literature has often found a nonlinear relationship between climate and these outcomes, with extremely warm temperatures being especially important (e.g., Schlenker and Roberts 2009). Climate is a long average of weather at a given location. To identify the causal effect of climate on these outcomes, the literature has generally relied on either climate normals (i.e., long averages of observed weather in a cross-sectional setting) or day-to-day (or year-to-year) fluctuations in observed weather as explanatory variables across time and space. The econometrician’s
choice of a weather versus a climate measure as an explanatory variable critically affects the interpretation of the estimated coefficients in the econometric model: that is, whether the outcome is a true climate response or a short-run weather elasticity.

Understanding the feasibility and cost of adaptation is essential to management of the global climate. Unfortunately, we lack general estimates of adaptive responses to almost all climatological processes. To address this for one phenomenon, we estimate the extent of adaptation to tropical cyclones (TCs) using the global cross-section of countries. We reconstruct every TC observed during 1950–2008 to parameterize countries' TC climate and year-to-year TC exposure. We then look for evidence of adaptation by comparing deaths and damages from physically similar TC events across countries with different TC climatologies. We find that countries with more intense TC climates suffer lower marginal losses from an actual TC event, indicating that adaptation to this climatological risk occurs but that it is costly. Overall, there is strong evidence that it is both feasible and cost-effective for countries with intense TC climatologies to invest heavily in adaptation. However, marginal changes from countries' current TC climates generate persistent losses, of which only ~3% is "adapted away" in the long run.

It has been proposed that changes in global climate have been responsible for episodes of widespread violence and even the collapse of civilizations. Yet previous studies have not shown that violence can be attributed to the global climate, only that random weather events might be correlated with conflict in some cases. Here we directly associate planetary-scale climate changes with global patterns of civil conflict by examining the dominant interannual mode of the modern climate, the El Nin˜o/Southern Oscillation (ENSO). Historians have argued that ENSO may have driven global patterns of civil conflict in the distant past, a hypothesis that we extend to the modern era and test quantitatively. Using data from 1950 to 2004, we show that the probability of new civil conflicts arising throughout the tropics doubles during El Nin˜o years relative to La Nin˜a years. This result, which indicates that ENSO may have had a role in 21% of all civil conflicts since 1950, is the first demonstration that the stability of modern societies relates strongly to the global climate.

Understanding the economic impact of surface temperatures is an important question for both economic development and climate change policy. This study shows that in 28 Caribbean-basin countries, the response of economic output to increased temperatures is structurally similar to the response of labor productivity to high temperatures, a mechanism omitted from economic models of future climate change. This similarity is demonstrated by isolating the direct influence of temperature from that of tropical cyclones, an important correlate. Notably, output losses occurring in nonagricultural production (–2.4%/+1 °C) substantially exceed losses occurring in agricultural production (–0.1%/+1 °C). Thus, these results suggest that current models of future climate change that focus on agricultural impacts but omit the response of workers to thermal stress may underestimate the global economic costs of climate change.