Goldman School of Public Policy - University of California, Berkeley

Solomon Hsiang

Chancellor's Associate Professor of Public Policy

Areas of Expertise

  • Agriculture
  • Climate Change
  • Environment
  • International
  • Coupled Natural and Human Systems
  • Political Economy
  • Development Economics
  • Applied Econometrics


Solomon Hsiang combines data with mathematical models to understand how society and the environment influence one another. In particular, he focuses on how policy can encourage economic development while managing the global climate. His research has been published in NatureScience, and the Proceedings of the National Academy of Sciences

Hsiang earned a BS in Earth, Atmospheric and Planetary Science and a BS in Urban Studies and Planning from the Massachusetts Institute of Technology, and he received a PhD in Sustainable Development from Columbia University. He was a Post-Doctoral Fellow in Applied Econometrics at the National Bureau of Economic Research (NBER) and a Post-Doctoral Fellow in Science, Technology and Environmental Policy at Princeton University. Hsiang is currently the Chancellor's Associate Professor of Public Policy at the University of California, Berkeley and a Research Associate at the NBER. 


Working Papers

  • Tropical Economics

    Co-author: Kyle C. Meng

    GSPP Working Paper (February 2015)

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  • Geography, Depreciation, and Growth

    Co-author: Amir S. Jina

    GSPP Working Paper (February 2015)

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  • Does the Environment Still Matter? Daily Temperature and Income in the United States

    Co-author: Tatyana Deryugina

    GSPP Working Paper (December 2014)

    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.

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  • American Climate Prospectus: Economic Risks in the United States

    Co-authors: Robert Kopp, DJ Rasmussen, Michael Mastrandrea, Amir Jina, James Rising, Robert Muir-Wood , Paul Wilson , Michael Delgado, Shashank Mohan, Kate Larsen, Trevor Houser

    GSPP Working Paper (October 2014)

    The United States faces a range of economic risks from global climate change — from increased flooding and storm damage, to climate-driven changes in crop yields and labor productivity, to heat-related strains on energy and public health systems. The American Climate Prospectus (ACP) provides a groundbreaking new analysis of these and other climate risks by region of the country and sector of the economy. By linking state-of-the-art climate models with econometric research of human responses to climate variability and cutting edge private sector risk assessment tools, the ACP offers decision-makers a data driven assessment of the specific risks they face.

    The ACP is the result of an independent assessment of the economic risks of climate change commissioned by the Risky Business Project. In conducting this assessment, RHG convened a research team, co-led by climate scientist Dr. Robert Kopp of Rutgers University and economist Dr. Solomon Hsiang of the University of California, Berkeley, and partnered with Risk Management Solutions (RMS), the world’s largest catastrophe-modeling company for insurance, reinsurance, and investment-management companies. The team’s research methodology and draft work was reviewed by an Expert Review Panel (ERP) composed of leading climate scientists and economists, acknowledged within the report.

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    Technical Appendix I: Physical Climate Projections (6MB)

    Technical Appendix II: Econometrics and Impacts (6MB)

    Technical Appendix III: Detailed Sectoral Models (433KB)

    Technical Appendix IV: Integrated Economic Analysis (512KB)

    Technical Appendix V: Valuation Risk and Unequal Impacts (129KB)

  • Climate and Conflict

    Co-authors: Marshall Burke, Edward Miguel

    GSPP Working Paper (October 2014)

    Until recently, neither climate nor conflict have been core areas of inquiry within economics, but there has been an explosion of research on both topics in the past decade, with a particularly large body of research emerging at their intersection. In this review, we survey this literature on the interlinkages between climate and conflict, by necessity drawing from both economics and other disciplines given the inherent interdisciplinarity of research in this field. We consider many types of human conflict in the review, including both interpersonal conflict - such as domestic violence, road rage, assault, murder, and rape - and intergroup conflict - including riots, ethnic violence, land invasions, gang violence, civil war, and other forms of political instability, such as coups. We discuss the key methodological issues in estimating causal relationships in this area, and largely focus on "natural experiments" that exploit variation in climate variables over time, helping to address omitted variable bias concerns. After harmonizing statistical specifications and standardizing estimated effect sizes within each conflict category, we carry out a hierarchical meta-analysis that allows us to estimate the mean effect of climate variation on conflict outcomes as well as to quantify the degree of variability in this effect size across studies. Looking across 55 studies, we find that deviations from moderate temperatures and precipitation patterns systematically increase the risk of conflict, often substantially, with average effects that are highly statistically significant. We find that contemporaneous temperature has the largest average effect by far, with each 1σ increase toward warmer temperatures increasing the frequency of contemporaneous interpersonal conflict by 2.4% and of intergroup conflict by 11.3%, but that 2-period cumulative effect of rainfall on intergroup conflict is also substantial (3.5%/σ). We also quantify heterogeneity in these effect estimates across settings that is likely important. We conclude by highlighting remaining challenges in this field and the approaches we expect will be most effective at solving them, including identifying mechanisms that link climate to conflict, measuring the ability of societies to adapt to climate changes, and understanding the likely impacts of future global warming. 

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  • Reconciling climate-conflict meta-analyses: reply to Buhaug et al.

    Co-authors: Edward Miguel, Marshall Burke

    GSPP Working Paper (July 2014)

    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.

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  • The Causal Effect of Environmental Catastrophe on Long-Run Economic Growth: Evidence from 6,700 Cyclones

    Co-author: Amir S. Jina

    GSPP Working Paper (July 2014)

    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.

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  • Visually-Weighted Regression

    GSPP Working Paper (May 2013)

    Uncertainty in regression can be eciently and e ectively communicated using the visual properties of statistical objects in a regression display. Altering the visual weight" of lines and shapes to depict the quality of information represented clearly communicates statistical con dence even when readers are unfamiliar with the formal and abstract de nitions of statistical uncertainty. Here we present examples where the color-saturation and contrast of regression lines and con dence intervals are parametrized by local measures of an estimate's variance. The results are simple, visually intuitive and graphically compact displays of statistical uncertainty. This approach is generalizable to almost all forms of regression

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  • Destruction, Disinvestment, and Death: Economic and Human Losses Following Environmental Disaster

    Co-author: Jesse Keith Anttila-Hughes

    GSPP Working Paper (February 2013)

    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.

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Selected Publications

  • Nonlinear Permanent Migration Response to Climatic Variations but Minimal Response to Disasters

    P. Bohra-Mishraa,M. Oppenheimer, S.M. Hsiang, Proceedings of the National Academy of Sciences (2014) DOI: 10.1073/pnas.1317166111

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  • Temperature and Violence

    Bohra-Mishra, P., M. Oppenheimer, S.M. Hsiang, Proceedings of the National Academy of Sciences (2014) doi: 10.1073/pnas.1317166111

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  • Reconciling disagreement over climate-conflict results in Africa

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  • Climate, Conflict and Social Stability: What does the evidence say?

    Hsiang, S.M., M. Burke, Climatic Change (2013) DOI:10.1007/s10584-013-0868-3

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  • Quantifying the Influence of Climate on Human Conflict

    Hsiang, S.M., M. Burke, E. Miguel, Science (2013) DOI:10.1126/science.1235367

    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.

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  • Using Weather Data and Climate Model Output in Economic Analyses of Climate Change

    Auffhammer, M.,  and S.M. Hsiang, W. Schlenker, A. Sobel. "Using Weather Data and Climate Model Output in Economic Analyses of Climate Change." Review of Environmental Economics and Policy, Vol. 7, No. 2 p. 181-198.

    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.

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  • Adaptation to Cyclone Risk: Evidence from the Global Cross-Section

    Hsiang, S.M., Narita, D. (2012). "Adaptation to Cyclone Risk: Evidence from the Global Cross-Section." Climate Change Economics, Vol. 3 No. 2.

    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.

  • Civil Conflicts Are Associated with the Global Cimate

    Hsiang, S.M., K.C. Meng, M.A. Cane. "Civil Conflicts are associated with the global climate." Nature, Vol. 476, p. 438-441.

    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.

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  • Temperatures and cyclones strongly associated with economic production in the Caribbean and Central

    Hsiang, S.M. "Temperatures and cyclones strongly associated with economic production in the Caribbean and Central America." Proceedings of the National Academy of Sciences,  Vol. 107, p. 15367-15372.

    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.

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California and the Climate Fight: Cal Day 2017

California and the Climate Fight: Cal Day 2017

Solomon Hsiang, Ned Helme, Meredith Fowlie, Carol Zabin

Event: Cal Day 2017

Date: April 22, 2017 Duration: 60 minutes

The Emerging Age of Data-Driven Policy Design: Examples from Trying to Manage the Global Climate

The Emerging Age of Data-Driven Policy Design: Examples from Trying to Manage the Global Climate

Solomon Hsiang

Event: 2015 Strata + Hadoop World

Date: February 19, 2015 Duration: 8 minutes

Risky Business: The Economic Risks of Climate Change with Sol Hsiang

Risky Business: The Economic Risks of Climate Change with Sol Hsiang

Sol Hsiang, Henry E. Brady

Date: August 10, 2014 Duration: 28 minutes

Quantifying the Economic Cost of Climate Change

Quantifying the Economic Cost of Climate Change

Solomon Hsiang

Date: April 30, 2014 Duration: 20 minutes

Tempers May Flare as Climate Change Heats Up, Study Finds

Tempers May Flare as Climate Change Heats Up, Study Finds

Solomon Hsiang

Date: August 7, 2013 Duration: 0 minutes