The COVID-19 pandemic created unexpected and prolonged disruptions to childcare access. Using survey evidence on time use by academic researchers before and after the pandemic, we analyze the extent to which greater access to either school-based or partner-provided childcare mitigated the severe disruptions to research observed among parents during COVID-19. We find that access to public schools offset the research time loss to a greater extent among mothers of young children relative to fathers, narrowing the emerging post-pandemic gender gap. Having a stay-at-home partner reduced the disruptions to research time equally for both genders.

Life expectancy varies substantially across local regions within a country, raising conjectures that place of residence affects health. However, population sorting and other confounders make it difficult to disentangle the effects of place on health from other geographic differences in life expectancy. Recent studies have overcome such challenges to demonstrate that place of residence substantially influences health and mortality. Whether policies that encourage people to move to places that are better for their health or that improve areas that are detrimental to health are desirable depends on the mechanisms behind place effects, yet these mechanisms remain poorly understood.

Forecast valuation studies play a key role in understanding the determinants of the value of weather and climate forecasts. Such understanding provides opportunities to increase the value that users can obtain from forecasts, which can in turn increase the use of forecasts. One of the most important factors that influences how users process forecast information and incorporate forecasts into their decision-making is trust in forecasts. Despite the evidence from empirical and field-based studies, modeling users’ trust in forecasts has not received much attention in the literature and is therefore the focus of our study. We propose a theoretical model of trust in information, built into a forecast valuation framework, to better understand 1) the role of trust in users’ processing of drought forecast information and 2) the dynamic process of users’ trust formation and evolution. Using a numerical experiment, we show that considering the dynamic nature of trust is critical in more realistic assessment of forecast value. We find that users may not perceive a potentially valuable forecast as such until they trust it enough, implying that exposure to even highly accurate forecasts may not immediately translate into forecast use. Ignoring this dynamic aspect could overestimate the economic gains from forecasts. Furthermore, the model offers hypotheses with regard to targeting strategies that can be tested with empirical and field-based studies and used to guide policy interventions.

Do natural disasters increase charitable giving or simply reallocate a fixed supply of donations? We study this question using IRS data in the context of deadly tornadoes. We find that, among ZIP Codes located in the same state but more than 20 miles away from a tornado’s path, donations by households increase by about $2 million per tornado fatality. We find no negative effects of tornado fatalities on donations to charities located in these ZIP Codes. The results imply that giving in response to new needs need not come at the expense of other causes.

The rapid spread of the COVID-19 pandemic and subsequent countermeasures, such as school closures, the shift to working from home, and social distancing are disrupting economic activity around the world. As with other major economic shocks, there are winners and losers, leading to increased inequality across certain groups. In this project, we investigate the effects of COVID-19 disruptions on the gender gap in academia. We administer a global survey to a broad range of academics across various disciplines to collect nuanced data on the respondents’ circumstances, such as a spouse’s employment, the number and ages of children, and time use. We find that female academics, particularly those who have children, report a disproportionate reduction in time dedicated to research relative to what comparable men and women without children experience. Both men and women report substantial increases in childcare and housework burdens, but women experienced significantly larger increases than men did.

The Coase Theorem has a central place in the theory of environmental economics and regulation. Its applicability for solving real-world externality problems remains debated. We first place this seminal contribution in its historical context. We then survey the experimental literature that has tested the importance of the many, often tacit assumptions in the Coase Theorem. We discuss a selection of applications of the Coase Theorem to actual environmental problems, distinguishing between situations in which the polluter or the pollutee pays. Most substantive examples of Coase-like bargaining involve more than two parties. It is not clear whether the outcomes of these bargains were Pareto optimal rather than merely Pareto improving. While limited in scope, Coasian bargaining over externalities offers a pragmatic solution to problems that are difficult to solve in any other way.

We follow Medicare cohorts to estimate Hurricane Katrina’s long-run mortality effects on victims initially living in New Orleans. Including the initial shock, the hurricane improved eight-year survival by 2.07 percentage points. Migration to lower-mortality regions explains most of this survival increase. Those migrating to low- versus high-mortality regions look similar at baseline, but their subsequent mortality is 0.83–1.01 percentage points lower per percentage-point reduction in local mortality, quantifying causal effects of place on mortality among this population. Migrants’ mortality is also lower in destinations with healthier behaviors and higher incomes but is unrelated to local medical spending and quality.

Policies aimed at reducing the harmful effects of air pollution exposure typically focus on areas with high levels of pollution. However, if a population’s vulnerability to air pollution is imperfectly correlated with current pollution levels, then this approach to air quality regulation may not efficiently target pollution reduction efforts. We examine the geographic and socioeconomic determinants of vulnerability to dying from acute exposure to fine particulate matter (PM2.5) pollution. We find that there is substantial local and regional variability in the share of individuals who are vulnerable to pollution both at the county and ZIP code level. Vulnerability tends to be negatively related to health and socioeconomic status. Surprisingly, we find that vulnerability is also negatively related to an area’s average PM2.5 pollution level, suggesting that basing air quality regulation only on current pollution levels may fail to effectively target regions with the most to gain by reducing exposure.

We study the dynamics of residential electricity demand by exploiting a natural experiment that produced large and long-lasting price changes in over 250 Illinois communities. Using a flexible difference-in-differences matching approach, we estimate that the price elasticity of demand grows from −0.09 in the first six months to −0.27 two years later. We find similar results with a dynamic model in which usage is a function of past and future prices. Our findings highlight the importance of accounting for consumption dynamics when evaluating energy policy

We estimate the causal effects of acute fine particulate matter exposure on mortality, health care use, and medical costs among the US elderly using Medicare data. We instrument for air pollution using changes in local wind direction and develop a new approach that uses machine learning to estimate the life-years lost due to pollution exposure. Finally, we characterize treatment effect heterogeneity using both life expectancy and generic machine learning inference. Both approaches find that mortality effects are concentrated in about 25 percent of the elderly population.

We evaluate the distributional consequences of building energy codes for home characteristics, energy use, and home value. We exploit spatial variation in California’s code strictness created by building climate zones, combined with information on over 350,000 homes located within 3 kilometers of climate zone borders. Our key findings are that stricter codes create a non-trivial reduction in homes’ square footage and the number of bedrooms at the lower end of the income distribution. On a per-dwelling basis, we observe energy use reductions only in the second lowest income quintile, driven by decreases in square footage. Energy use per square foot actually increases in the bottom quintile. Home values of lower-income households fall, while those of high-income households rise, suggesting that building energy codes result in more undesirable distortions for lower-income households.

Hurricane Katrina destroyed over 200,000 homes and led to massive economic and physical dislocation. Using a panel of tax return data, we provide one of the first comprehensive analyses of the hurricane’s long-term economic impact on its victims. Hurricane Katrina had large and persistent impacts on where people live, but small and surprisingly transitory effects on employment and income. Within just a few years, Katrina victims’ incomes actually surpass that of controls from similar unaffected cities. The strong economic performance of Hurricane Katrina victims is particularly remarkable given that the hurricane struck with essentially no warning.

The Samaritan’s dilemma posits a downside to charity: recipients may rely on free aid instead of their own efforts. Anecdotally, the expectation of free assistance is thought to be important for decisions about insurance and risky behavior in numerous settings, but reliable empirical evidence is scarce. We estimate whether the Samaritan’s dilemma exists in U.S. agriculture, where both private crop insurance and frequent federal disaster assistance are present. We find that bailout expectations are qualitatively and quantitatively important for the insurance decision. Furthermore, aid expectations reduce both expenditure on farm inputs and subsequent crop revenue.

Agricultural production remains particularly vulnerable to weather fluctuations and extreme events, such as droughts, floods, and heat waves. Crop insurance is a risk management tool developed to mitigate some of this weather risk and protect farmer income in times of poor production. However, crop insurance may have unintended consequences for water resources sustainability, as the vast majority of freshwater withdrawals go to agriculture. The causal impact of crop insurance on water use in agriculture remains poorly understood. Here, we determine the empirical relationship between crop insurance and irrigation water withdrawals in the United States. Importantly, we use an instrumental variables approach to establish causality. Our methodology exploits a major policy change in the crop insurance system – the 1994 Federal Crop Insurance Reform Act – which imposed crop insurance requirements on farmers. We find that a 1% increase in insured crop acreage leads to a 0.223% increase in irrigation withdrawals, with most coming from groundwater aquifers. We identify farmers growing more groundwater-fed cotton as an important mechanism contributing to increased withdrawals. A 1% increase in insured crop acreage leads to a 0.624% increase in cotton acreage, or 95,602 acres. These results demonstrate that crop insurance causally leads to more irrigation withdrawals. More broadly, this work underscores the importance of determining causality in the water-food nexus as we endeavor to achieve global food security and water resources sustainability.

Little is known about the fiscal costs of natural disasters, especially regarding social safety nets that do not specifically target extreme weather events. This paper shows that US hurricanes lead to substantial increases in non-disaster government transfers, such as unemployment insurance and public medical payments, in affected counties in the decade after a hurricane. The present value of this increase significantly exceeds that of direct disaster aid. This implies, among other things, that the fiscal costs of natural disasters have been significantly underestimated and that victims in developed countries are better insured against them than previously thought.

Despite over 20 years of research and scientific consensus on the topic, climate change continues to be a politically polarizing issue. We conducted a survey experiment to test whether providing the public with information on the exact extent of scientific agreement about the occurrence and causes of climate change affects respondents’ own beliefs and bridges the divide between conservatives and liberals. First, we show that the public significantly underestimated the extent of the scientific consensus. We then find that those given concrete information about scientists’ views were more likely to report believing that climate change was already underway and that it was caused by humans. However, their beliefs about the necessity of making policy decisions and their willingness to donate money to combat climate change were not affected. Information provision affected liberals, moderates, and conservatives similarly, implying that the gap in beliefs between liberals and conservatives is not likely to be bridged by information treatments similar to the one we study. Finally, we conducted a 6-month follow-up with respondents to see if the treatment effect persisted; the results were statistically inconclusive.

We design a laboratory experiment to test the extent to which the often-observed “beauty premium” – a positive relationship between attractiveness and wages – is context-specific. Using three realistic worker tasks, we find that the existence of the “beauty premium” indeed depends on the task: while relatively more attractive workers receive higher wage bids in a bargaining task, there is no such premium in either an analytical task or a data entry task. Our analysis shows that the premium in bargaining is driven by statistical discrimination based on biased beliefs about worker performance. We also find that there is substantial learning after worker specific performance information is revealed, highlighting the importance of accounting for longer-run interactions in studies of discrimination.

Physically attractive individuals achieve greater success in terms of earnings and status than those who are less attractive. However, whether this “beauty premium” arises primarily because of differences in ability or confidence, bias, or sorting remains unknown. We use a rich dataset from a women’s college to evaluate each of these three mechanisms at the college level. We find that students judged to be more attractive perform significantly worse on standardized tests but, conditional on test scores, are not evaluated more favorably at the point of admission, suggesting that more attractive people do not possess greater abilities at the beginning of college. Controlling for test scores, more attractive students receive only marginally better grades in some specifications, and the magnitudes of the differences are very small. Finally, there is substantial beauty-based sorting into areas of study and occupations.

Global warming has become a controversial public policy issue in spite of broad scientific consensus that it is real and that human activity is a contributing factor. It is likely that public consensus is also needed to support policies that might counteract it. It is therefore important to understand how people form and update their beliefs about climate change. Using unique survey data on beliefs about the occurrence of the effects of global warming, I estimate how local temperature fluctuations influence what individuals believe about these effects. I find that some features of the updating process are consistent with rational updating. I also test explicitly for the presence of several heuristics known to affect belief formation and find strong evidence for representativeness, some evidence for availability, and no evidence for spreading activation. I find that very short-run temperature fluctuations (1 day–2 weeks) have no effect on beliefs about the occurrence of global warming, but that longer-run fluctuations (1 month–1 year) are significant predictors of beliefs. Only respondents with a conservative political ideology are affected by temperature abnormalities.

Many environmental hazards produce health effects that take years to arise, but quasi-experimental studies typically measure outcomes and treatment over short time periods. We develop a new approach to overcome this challenge and use it to gauge the effect of exposure to air pollution on US life expectancy. Using changes in wind direction as an instrument for daily sulfur dioxide levels, we first characterize the short-run mortality effects of acute exposure during the time period 1972-1988. Exposure causes two distinct mortality patterns: a short-run mortality displacement effect, and a persistent accelerated aging effect. We then incorporate our estimates into a flexible health production model to quantify the lifelong effects of chronic air pollution exposure for a cohort born in 1972. Model calculations of the effect of chronic exposure on life expectancy are 7-8 times larger than the effect implied by simple extrapolation of our short-run empirical estimates. Ninety percent of the survival benefits accrue after the first fifty years of life, implying that most of the 1970 Clean Air Act’s health benefits have yet to emerge for cohorts born after its passage.

Climate change is increasing the frequency of natural disasters, which could make municipal bonds a riskier asset class. We study the effects of natural disasters on municipal bond returns, exploiting the repeat sales approach to overcome the challenge that municipal bonds trade extremely infrequently. We find substantial price effects that materialize gradually: returns of uninsured bonds fall slowly in the weeks following a disaster, by 0.31% on average, translating into investor losses of almost $10 billion. Source of bond revenue, bond insurance, disaster severity, federal disaster aid, and local financial conditions all affect the magnitude of the price effects.

COVID-19 has created a dual set of stresses on health care systems worldwide: a rise in expensive intensive care services and a dramatic decline in elective services. In the U.S., elective services are the major source of profits for many health care providers, leading to concerns that some providers may not survive the COVID-19 crisis. The U.S. government has responded with both grant and loan programs to help health care providers weather the storm. But the optimal size and nature of such programs are hard to evaluate without an understanding of the ability of providers to make up their lost elective service revenues over time. In this paper, we study the closest relevant parallel to the reduction in elective services seen under COVID-19: hurricanes. We match information on hurricanes to data on Medicare hospital elective visits and charges from 1997–2013, comparing counties impacted by hurricanes to nearby unaffected counties. We find that the average hurricane reduces elective services by about 7% in the month it makes landfall. For the most severe hurricanes, we estimate a reduction of more than 20%. Services return to baseline fairly rapidly, but for severe hurricanes it takes a year or more to make up lost revenues. Similar responses in the months after hurricanes of different severity suggest that capacity constraints limit the ability of providers to make up for lost revenues; correspondingly, we find a much larger “bounce-back” for outpatient than for inpatient services. Projections based on variation in hurricane severity suggest that it will take over 3 years for providers to make up the lost revenue from COVID-19.

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.

Using novel US environmental spill data, we document a robust negative relationship between the number of spills a firm experiences in a given year and its contemporaneous and lagged (but not future) cash flow. In addition, studying two natural experiments, we find an increase (decrease) in spills following negative (positive) shocks to a firm’s financial resources, relative to control firms. Overall, our results suggest that firms’ financial resources play an important role in their ability to mitigate environmental risk and that such resources therefore affect communities in which these firms operate.