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.

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.