Conference Agenda

This study investigates whether income inequality within a population influences the health effects of pollution. We first develop a stylized theoretical model to identify potential mechanisms through which income distribution may amplify vulnerability to pollution. The model highlights three main channels: differences in public health expenditure, unequal exposure to pollution, and variations in private health spending across income groups. We then empirically test these predictions by estimating the causal impact of particulate matter (PM10) on mortality in all French municipalities with more than 2,000 inhabitants over the period 2000–2015, using wind direction as an instrumental variable. Our findings reveal a statistically and economically significant impact of pollution exposure on the mortality of individuals aged 50 or older, which intensifies in municipalities with higher levels of income inequality. While the effect of PM10 is not significant in the least unequal municipalities (bottom 33%), it is significant and increases with inequality levels in others. The impact in the most unequal municipalities (top 33%) is up to twice as large as in those with intermediate inequality levels. This result is particularly striking given France's relatively low income inequality. Empirical tests of the theoretical mechanisms reveal that the observed variation in pollution vulnerability across inequality-stratified municipalities is not attributable to differences in public health expenditure, pollution exposure (between or within municipalities), or poverty prevalence and intensity. Our results suggest that inequality plays a significant role in shaping environmental health outcomes, likely related to private health expenditures, their determinants, or their effectiveness, warranting further research.

Air pollution creates inequitable environmental burdens through both hazard exposure and vulnerability. Using Emergency Medical Service records in NYC, we find that air pollution increases dispatches significantly across diverse health and behavioral outcomes, with disproportionate impacts on disadvantaged communities. EPA monitoring networks systematically underestimate pollution in disadvantaged areas, biasing causal estimates downward by up to 28%. Under everyday pollution levels, disadvantaged communities appear to manage certain respiratory conditions through accessible defensive technologies without relying on EMS. However, during the 2023 Canadian wildfires, an extreme pollution event, structural constraints limited the effectiveness of defensive behaviors, revealing increased vulnerability in these communities.

Environmental inequalities, such as unequal exposure to pollution and climate risks, persist across racial and socioeconomic groups in the United States. This paper re-examines the role of the Residential Security Maps created by the Home Owners’ Loan Corporation (HOLC) in the 1930s, which graded neighborhoods according to perceived mortgage risk and have been widely linked to long-run racial segregation and environmental disadvantage. A common view holds that these maps not only reinforced residential segregation but also directly shaped the spatial distribution of environmental hazards, including air pollution, flood risk, and extreme heat.

We evaluate this claim using a causal framework that combines machine-learning predictions of counterfactual HOLC grades in unmapped cities with a spatial difference-in-differences design. Our results confirm that the maps modestly increased racial sorting and segregation, consistent with prior work. However, we find no evidence that HOLC mapping independently affected the siting of environmental or climatic hazards. Differences in air pollution, flood risk, heat exposure, and mortality across historical grades are quantitatively similar in mapped and unmapped cities.

These findings suggest that contemporary environmental inequalities primarily reflect residential sorting and discriminatory practices that operated broadly across U.S. cities, rather than an additional siting effect uniquely induced by the HOLC maps, which we do not detect.

Does the death of a firm in a pollution-intensive industry prolong human life? While the labor market consequences of the China Shock are well established, this paper unveils its inadvertent environmental health dividends. Using Brazil as a laboratory—unique for its dual exposure to manufacturing import competition and commodity export demand—we estimate the causal effect of trade on pollution-related mortality and identify firm dynamics as transmission mechanism. Combining administrative microdata on 50 million firms with over two decades of cause-specific mortality records (2000–2019), we document a striking trade-off. We find that import competition acted as an environmental "cleansing" force: microregions more exposed to manufacturing imports experienced a robust decline in cardio-respiratory mortality, particularly among the elderly (75+). We trace this health benefit to the extensive margin of firm adjustment: the shock forced the net exit of firms in pollution-intensive ("dirty") sectors (empirically consistent with the Pollution Reduction by Rationalization Hypothesis) and accelerated the green transition of survivors (in contrast with the Distressed and Dirty Industry Hypothesis). Conversely, the agricultural export boom generated a scale effect in the frontier (Center-West), where the net entry of dirty firms increased mortality. However, we uncover a crucial heterogeneity in developed agricultural regions (South), where export shocks drove capital intensification—replacing labor with machinery—which paradoxically reduced mortality. These findings complement Bombardini & Li (2020). While they document an increase in child mortality linked to China’s export expansion, our evidence suggests that import exposure has, in contrast, reduced mortality among the elderly in Brazil.