This dissertation addresses three issues in environmental policy and health: (1) can prenatal pollution exposure shift long run life cycle outcomes, (2) can ambient pollution levels impact infant mortality rates, and (3) how can regulators go about correcting for the presence of such externalities?
Chapter 1 speaks to the potential long run consequences of prenatal exposure to air pollution by investigating the impact of prenatal particulate pollution on educational achievement. I use ambient total suspended particulates (TSPs) as a measure of particulate exposure, standardized test scores of exposed individuals as a measure of educational achievement, and the shock of the industrial recession of the early 1980s as a source of potentially exogenous variation in pollution levels. To overcome measurement error and potential omitted variables bias, I employ an instrumental variables strategy where I exploit the variation in how county employment and manufacturing makeup varied across regions during the recession. Instrumental variables results are statistically significant and suggest that a withincounty standard deviation decrease in ambient TSPs is associated with 5-10% of a within-county standard deviation increase in test scores. This implies that approximately 20% of the score gains seen by the 1978-1984 birth cohorts in my sample is attributable to the reduction in ambient TSPs, and suggests that prenatal exposure to pollutants can have long term life-cycle altering impacts.
Chapter 2 addresses more immediate health impacts of pollution exposure and attempts to better identify the causal links between automobile traffic, ambient air quality, and infant mortality rates. We add to our understanding of these issue by addressing two related research questions: (1) What is the impact of automobile driving (and especially congestion) on ambient air pollution levels; and (2) what is the impact of air pollution on infant health? Our setting is California (with a focus on the Central Valley and Southern California) in the years 2002-2007. Our findings suggest that ambient pollution levels have large impacts on weekly mortality rates, with the most precisely estimated and most stable effects appearing for particulate matter. Instrumental variables effects are greater than those found using OLS fixed effects methods, suggesting the presence of measurement error, avoidance behavior, and/or omitted variables bias.
Chapter 3 moves away from applied analysis and approaches the issue of environmental externalities and regulation from a theoretical perspective. We present a situation in which a government, with the intended goal of maximizing social welfare, must contend with an externality generating natural monopolist. We expand upon the existing non-Bayesian regulatory methods by constructing a regulatory tool that requires minimal knowledge about market conditions. Our Price-based Subsidy (PS) mechanisms provide transfers to the firm that match or approximate the incremental surplus generated each period. Unlike Bayesian regulatory methods, our mechanisms require no knowledge of the underlying firm cost distribution. In fact, an advantage of our mechanisms is that they allow the regulator to achieve marginal social cost pricing, either immediately or asymptotically depending on market conditions, without observing the abatement activity, demand, cost, or environmental damage functions of the firm.
|Advisor:||Knittel, Christopher R., Miller, Douglas L.|
|Commitee:||Hoynes, Hilary W.|
|School:||University of California, Davis|
|School Location:||United States -- California|
|Source:||DAI-A 71/11, Dissertation Abstracts International|
|Subjects:||Environmental economics, Economics, Public health|
|Keywords:||Environmental externalities, Environmental policy, Infant mortality, Prenatal pollution|
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