Governments monitor air quality for regulatory purposes and, more recently, to provide information so individuals can act to lower their exposure to air pollution. Recent developments in low-cost technologies have also led to private adoption of air-quality monitors that produce publicly accessible air-quality readings. We study the adoption of these private air-quality monitors. We find that shocks to air pollution from wildfire result in substantial adoption. We also find that additional private monitors are concentrated in white, wealthy, and politically liberal neighborhoods. In contrast, there is no evidence that pollution shocks lead to higher adoption in neighborhoods with lower pre-existing access to monitors, higher long-run pollution, or those with more vulnerable populations. Private provision increases inequality in the availability of localized air-quality information.

We estimate the impact of piped water and sewers on property values in late-19th century Chicago. The cost of sewer construction depends sensitively on imperceptible variation in elevation, and such variation delays water and sewer service to part of the city. This delay provides quasi-random variation for causal estimates. We extrapolate ATE estimates from our natural experiment to the area treated with water and sewer service during 1874-1880 using a new estimator. Water and sewer access increases property values by more than a factor of two. This exceeds costs by about a factor of 60. 

How does exposure to risk shape individual preferences for an expanded state? I examine this question in the context of climate change-related risk. Using variation in California wildfire activity, I show neighborhoods experiencing large fires increase support by 0.8 percentage points for ballot initiatives which expand the size of government and by 2.4 percentage points for ballot initiatives endorsed by pro-environment interest groups. The effect is stronger in Republican areas and is not driven by shifts in voter registration or turnout, suggesting the mechanism acts through changes in individual preferences rather than compositional changes in the electorate.

Does exposure to climate-related natural disasters affect individuals' willingness to engage in climate activism? Prior studies show that exposure to high temperatures and natural disasters affects pro-climate preferences, but there is little evidence on whether it changes individuals' willingness to participate in costly, public actions to influence climate policy. We assemble a novel panel dataset of nearly 150,000 reported attendances at more than 5,000 pro-climate events in the United States. Using this panel and a stacked event study approach, we show exposure to climate change-related natural disasters such as large wildfires and hurricanes causes an increase in attendance at pro-climate events. We also show that attendance increases in distant areas that are not physically affected by a disaster but are socially connected to disaster areas. Furthermore, public exposure to large pro-climate events itself transfers through the social network, producing increases in activism at distant locations. 

This paper studies how exposure to crime affects demand for policing using a unique setting where both crime and demand can be measured at the neighborhood level. Specifically, I use precinct level returns from ballot measures in San Francisco to provide the first causal evidence on how individuals’ support for pro-police policies responds to exposure to crime. Using variation in criminal activity across neighborhoods around election day, I find that each additional violent crime leads to an increase in support for police union-endorsed ballot positions ranging from 2.9 percentage points for homicides to 0.4 percentage points for lesser crimes. The effects are present during biennial congressional elections but not during municipal elections, suggesting the results are driven by lower-propensity voters. The effects are also largest in areas with high shares of white residents. 

This study analyzes the effect of sleep disruptions on the high-stakes standardized test performance of high school students. I leverage a natural experiment arising from a 2007 policy change in the United States which moved the transition date into Daylight Saving Time (DST) immediately prior to statewide graduation exams in Ohio. Using a difference-in-difference estimation with a panel of nearly 900 school districts, I find transition into DST lowered exam passage rates between 1.0 and 2.9 percentage points. Results suggest DST is not costless for adolescent students and contribute to a growing body of evidence on the negative cognitive effects of sleep disruption.