Conference Agenda

This study provides novel quasi-experimental evidence on the effects of air pollutants on defensive expenditures and economic productivity to retrieve spatially resolved estimates of the willingness to pay for air quality improvements. To address endogeneity concerns, atmospheric temperature inversions are exploited as a source of quasi-random variation in the spatial concentration of PM2.5. Using administrative data from England, I find that a plausibly exogenous 1 μg/m3 PM2.5 shock significantly affects pharmaceutical expenditures and GVA per capita, partly through increased work absenteeism. Leveraging a counterfactual reduction of 1 μg/m3 of PM2.5, I show that health benefits are more pronounced among the elderly and progressively distributed across income levels, while productivity gains are regressive and concentrated in urban areas. These findings imply that incorporating the spatial heterogeneity of pollution-reduction benefits into policy design could enhance the efficiency of environmental regulations and contribute to tackling health inequalities linked to pollution exposure.

Dirty cooking fuels contribute significantly to indoor air pollution in developing countries with potential consequences for health and human capital development. This paper investigates the impacts of early life exposure to a large-scale cooking fuel conversion program that took place in Indonesia between 2007 and 2015. This program provided cookstoves and cooking fuel subsidies to incentivize households to transition from kerosene, a dirty cooking fuel, to LPG, a cleaner cooking fuel. Using difference-in-differences and event study analyses, we find height and cognition benefits among children exposed to the LPG conversion policy within the first five years of life compared to those exposed to the policy later in life. These cognitive benefits are especially pronounced among girls. Our findings demonstrate how incentivizing clean cooking transitions can improve health and human capital, particularly for those exposed during critical periods of development, such as early life.

Persistent school absence can worsen learning outcomes and lead to substantial future socioeconomic setbacks. The linkage between overall school attendance and air quality has been documented in prior regional case studies. However, the impact of air pollution on chronic absenteeism, which matters most for socioeconomic outcomes, has yet to be examined. The literature also lacks national rather than regional scale assessment. We address this knowledge gap by leveraging a comprehensive national sample of K-12 schools and data for six criteria air pollutants monitored by the U.S. Environmental Protection Agency (EPA). We find a statistically significant and heterogeneous impact of air pollutants on chronic absenteeism, even when pollution is below the EPA-recommended thresholds. Using wind direction as an instrumental variable, we find that an additional bad CO, NO2, or PM2.5 air quality day can increase chronic absenteeism by 0.009% to 0.5%, 0.003% to 0.2%, and 0.002% to 0.2%, respectively. These estimates suggest that an additional bad air quality day across the U.S. can result in up to 45,000 more students absent from school for 15 or more days annually. We also document the uneven distribution of the impact on chronic absenteeism across racial, income, and age demographics. With a documented systematic impact of air quality on education, our work adds valuable insights to the ongoing conversation about the interplay between the environment and educational outcomes.

This study presents a randomized controlled trial involving 1,064 participants in Switzerland to investigate the effect of a Pigovian marginal cost pricing intervention on mobility behavior. The implemented transportation pricing system takes account of the social costs of different modes of transport, and thereby internalizes the external costs.

The study analyzes the potential for mode shifts and reductions in transportation externalities, including climate, congestion, accident and health externalities. The participants' movements are tracked by the GPS-based app ``Catch-My-Day'' which automatically determines their travel modes. Our results suggest the effectiveness of the intervention in both significantly reducing transportation externalities by 6.8%, and encouraging a shift from driving towards e-biking and walking. Participants reduce their car distance by 7.8% on average, whereas increasing their bicycling and walking distance by 11.6% and 5.6%, respectively.

This study is the first large-scale e-bike pricing experiment regarding externalities, estimating causal effects to be expected from a potential future implementation of mobility pricing and comparable policies.