Much of what we know about the marginal effect of pollution on infant mortality is derived from developed country data. However, given the lower levels of air pollution in developed countries, these estimates may not be externally valid to the developing country context if there is a nonlinear dose relationship between pollution and mortality or if the costs of avoidance behavior differs considerably between the two contexts. In this paper, we estimate the relationship between pollution and infant mortality using data from Mexico. We find that an increase of 1 parts per billion in carbon monoxide (CO) over the last week results in 0.0032 deaths per 100,000 births, while a 1 µg/m 3 increase in particulate matter (PM 10 ) results in 0.24 infant deaths per 100,000 births. Our estimates for PM 10 tend to be similar (or even smaller) than the U.S. estimates, while our findings on CO tend to be larger than those derived from the U.S. context. We provide suggestive evidence that a non-linearity in the relationship between CO and health explains this difference.

Moderate effects of pollution on health may exert an important influence on labor market decisions. We exploit exogenous variation in pollution due to the closure of a large refinery in Mexico City to understand how pollution impacts labor supply. The closure led to an 8 percent decline in pollution in the surrounding neighborhoods. We find that a one percent increase in sulfur dioxide results in a 0.61 percent decrease in the hours worked. The effects do not appear to be driven by labor demand shocks nor differential migration as a result of the closure in the areas located near the refinery. AbstractModerate eects of pollution on health may exert an important inuence on labor market decisions. We exploit exogenous variation in pollution due to the closure of a large renery in Mexico City to understand how pollution impacts labor supply. The closure led to an 8 percent decline in pollution in the surrounding neighborhoods. We nd that a one percent increase in sulfur dioxide results in a 0.61 percent decrease in the hours worked. The eects do not appear to be driven by labor demand shocks nor dierential migration as a result of the closure in the areas located near the renery.

Moderate eects of pollution on health may exert an important inuence on labor market decisions. We exploit exogenous variation in pollution due to the closure of a large renery in Mexico City to understand how pollution impacts labor supply. The closure led to an 8 percent decline in pollution in the surrounding neighborhoods. We nd that a one percent increase in sulfur dioxide results in a 0.72 percent decrease in the hours worked. The eects do not appear to be driven by labor demand shocks nor dierential migration as a result of the closure in the areas located near the renery.

A large body of literature estimates the effect of air pollution on health. However, most of these studies have focused on physical health, while the effect on mental health is limited. Using the China Family Panel Studies (CFPS) covering 12,615 urban residents during 2014 -2015, we find significantly positive effect of air pollution -instrumented by thermal inversions -on mental illness. Specifically, a one-standard-deviation (18.04 μg/m3) increase in average PM 2.5 concentrations in the past month increases the probability of having a score that is associated with severe mental illness by 6.67 percentage points, or 0.33 standard deviations. Based on average health expenditures associated with mental illness and rates of treatment among those with symptoms, we calculate that these effects induce a total annual cost of USD 22.88 billion in health expenditures only. This cost is on a similar scale to pollution costs stemming from mortality, labor productivity, and dementia.

We thank Jianghao Wang for providing excellent research assistance. Any remaining errors are our own. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

Most regulations designed to reduce environmental externalities impose costs on individuals and firms. An active body of research has explored how these costs are disproportionately born by different sectors of the economy and/or across different groups of individuals. However, much less is known about the distributional characteristics of the environmental benefits created by these policies, or conversely, the differences in environmental damages associated with existing environmental externalities. We review this burgeoning literature and develop a simple and general framework for focusing future empirical investigations. We apply our framework to findings related to the economic impact of air pollution, deforestation, and climate, highlighting important areas for future research. A recurring challenge to understanding the distributional effects of environmental damages is distinguishing between cases where (i) populations are exposed to different levels or changes in an environmental good, and (ii) where an incremental change in the environment may have very different implications for some populations. In the latter case, it is often difficult to empirically identify the underlying sources of heterogeneity in marginal damages, as damages may stem from either non-linear and/or heterogeneous damage functions. Nonetheless, understanding the determinants of heterogeneity in environmental benefits and damages is crucial for welfare analysis and policy design.

Emission regulations become more prevalent in developing countries as carfleets grow; but they may be compromised by corruption. To shed light on this issue, I follow three steps. First, I develop a statistical test for identifying a specific type of cheating that involves bribing center technicians. Second, I predict fair probabilities of passing the test for the entire car-fleet by using lowcheating centers identified in step 1. Third, I estimate a structural model of car owner retesting and cheating decisions, whose parameters are recovered from observed testing outcomes and the empirical distribution of the probability of passing the test. No direct information on cheating decisions is required. I find that at least 9.6 percent of old-car owners paid bribe amounts of 20 U.S. dollars to circumvent the regulation. Simulations suggest that eliminating cheating and increasing the cost of retests would eliminate 1,443 tons of emissions, but would do so at a high cost for vehicle owners.

We thank Jianghao Wang for providing excellent research assistance. Any remaining errors are our own. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.