Conference Agenda

Air pollution harms labor productivity, yet little is known about whether workers adapt to chronic exposure. We address this question using 14 years of individual-level performance data from India's premier cricket league, a setting characterized by some of the highest levels of particulate matter air pollution (PM2.5) and whose schedule and geography result in variation in both acute and chronic exposure histories. We pair these granular performance metrics with an India-specific machine learning data product that incorporates remotely sensed and ground-monitor measures of PM2.5. Our results reveal that both chronic and acute exposure to pollution are costly, but in different ways. A 10 microgram-per-cubic-meter increase in same-day PM2.5 concentration (half a standard deviation in our sample) reduces productivity by about 1 percent, with effects concentrated at the highest pollution levels, implying a nonlinear dose-response. The dose-response also exhibits surprising heterogeneity: same-day shocks harm those chronically exposed at the highest levels approximately 40 percent less than those with median exposure histories, indicating adaptation. Nevertheless, chronic exposure itself results in performance declines that, though smaller in magnitude than the declines resulting from same-day shocks, far outweigh any protective effect from adaptation. Our findings suggest that standard estimates from low-pollution environments do not capture the dynamics between acute and chronic exposure in high-pollution settings.

Short-term regulatory measures, such as the Air Quality Alerts (AQAs), are widely used to mitigate pollution during acute air pollution episodes. Yet, little is known about how industrial plants respond to these temporary interventions. We examine plant-level responses in the heavily polluted Guanzhong region of northwestern China, exploiting the timing of alert activations and terminations between 2013 and 2020 as a natural experiment. Using hourly emission data from 234 plants equipped with continuous emission monitoring systems (CEMS) and employing regression discontinuity in time (RDiT), we find that the activation of orange- and yellow-level alerts induce significant reductions in NOx and SO2 emissions, primarily through intensified inspections and improved operation of pollution-control facilities, with minimal impact on production intensity. Blue-level alerts elicit weaker, more variable responses. We also document “alert fatigue”, where frequent and rapidly adjusted alerts reduce plants’ responsiveness. Our finding underscore the crucial role of environmental inspections during alert periods and highlight the importance of aligning alert timing and frequency with plants’ operational capacity to enhance compliance and air quality outcomes.

This paper examines how the U.S. Environmental Protection Agency advances environmental justice through enforcement of the Clean Air Act. Using a comprehensive panel of regulated facilities from 2000 to 2018, we implement an event-study design that exploits variation in the timing and location of racial demographic shifts. We find that increases in the share of non-White residents are followed by a persistent decline in inspection rates by state regulators. This decline is not observed for federal inspections, which follow more standardized enforcement protocols. To understand the pattern, we first rule out changes in regulatory need by showing that compliance outcomes and ambient air quality do not improve following demographic shifts. We then examine three aspects of regulatory discretion: local economic conditions, political engagement, and institutional targeting. Inspection rates fall only when discretion is unconstrained. Most notably, the decline disappears after 2012 when the EPA introduced the Environmental Justice Screening Tool, which standardized the use of demographic and environmental risk information in enforcement decisions.

Over the past two decades, coastal areas in the United States have experienced significant improvements in air quality, driven by stricter federal PM2.5 standards and cleaner fuel requirements for maritime shipping. However, the impact of these improvements on outdoor recreation, a major and growing sector of many coastal economies, remains unclear. Our study examines how changes in air pollution along the East and Gulf Coasts affected shoreline recreational fishing from 2004 to 2018, using one of the largest outdoor recreation datasets ever assembled. Through a linked model of angler participation and site choice, we found a strong negative and statistically significant relationship between PM2.5 levels and shoreline recreational fishing. This relationship suggests substantial welfare gains from recent air quality improvements. Our results also show significant regional variations across the U.S., with anglers in the Southeast and New England/Mid-Atlantic regions benefiting the most economically. Sensitivity analyses confirm that our baseline estimates remain robust when accounting for factors such as changes in local recreation patterns, income effects, nonlinear air pollution effects, heat effects, and alternative distributional assumptions.