Areas of Expertise
- Climate Change
- 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 global climate change, how natural disasters impact societies and the effectiveness of policy responses, and how environmental conditions influence social instability and violence.
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 and a Post-Doctoral Fellow in Science, Technology and Environmental Policy at Princeton University. He is a Faculty Research Fellow at the National Bureau of Economic Research and served as a contributing author to the Intergovernmental Panel on Climate Change.
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GSPP Working Paper (May 2013)
Uncertainty in regression can be eciently and eectively 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 condence even when readers are unfamiliar with the formal and abstract denitions of statistical uncertainty. Here we present examples where the color-saturation and contrast of regression lines and condence 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
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.
Hsiang, S.M., M. Burke, Climatic Change (2013) DOI:10.1007/s10584-013-0868-3
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.
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.
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.
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.
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.
Articles and Op-Eds
New York Times Sunday Review, September 1, 2013
Daily Nation, April 26, 2013
New York Times, November 9, 2012
New York Times, November 9, 2012
Washington Post, September 24, 2012
Scientific American, April 2, 2012
New York Times, October 6, 2011
Nature Climate Change, September 25, 2011
Significance Magazine, September 14, 2011
The National Conversation, August 30, 2011
The Economist, August 27, 2011
TIME, August 25, 2011
Science, August 25, 2011
National Public Radio, August 25, 2011
Scientific American, August 25, 2011
Nature, August 25, 2011
CBC/NPR, August 25, 2011
BBC World Service, August 25, 2011
Washington Post, August 24, 2011
Financial Times, August 24, 2011
CNN, August 24, 2011
Huffington Post, August 24, 2011
Slate, August 24, 2011
Economist, August 6, 2013
CNN , August 10, 2013
PBS NewsHour, August 7, 2013
BBC World Service, August 1, 2013
Reuters TV, September 26, 2013
NPR Science Friday, August 9, 2013
Wall Street Journal, November 20, 2013
The Atlantic, November 20, 2013
The Guardian, November 20, 2013
Slate, November 14, 2013
CNN, November 22, 2013