The design of regulations to mitigate environmental externalities poses numerous challenges, including risk and uncertainty, information asymmetries, and complex and heterogeneous ecosystems. This research addresses a subset of these challenges within three distinct contexts: (1) agricultural production, (2) urban sprawl, and (3) exhaustible resource extraction.
Agricultural nonpoint pollution is difficult to regulate for numerous reasons, including uncertainty regarding the relationship between farm practices and pollutant levels, stochastic weather patterns that affect pollution levels and yields, and inability to monitor the flow of pollutants from individual farms. Two commonly proposed regulatory mechanisms are uniform taxes and standards. Prior research in this literature assumes producers are risk neutral. However, empirical evidence suggests farmers are risk-averse. To increase the model's applicability to agricultural nonpoint pollution regulation I incorporate risk aversion into the model. An empirical application is used to illustrate how risk preferences might affect the regulatory mechanism choice.
The second paper addresses urban sprawl. The magnitudes of many externalities associated with urban development are higher for sprawl-type developments. This suggests that regulations aimed at reducing sprawl may be an indirect means of mitigating the environmental impacts of urban development and sprawl. An econometric model is used to analyze and predict residential land use change patterns in Albuquerque, New Mexico and surrounding areas. Results are used to assess the effectiveness of using zoning restrictions to control sprawl.
The final paper examines the regulation of stock pollutants stemming from exhaustible resource extraction. Pigovian taxes are one option for regulating such externalities. Because the resource in question is exhaustible, the Pigovian tax is dynamic. However, due to the analytical and managerial complexities of implementing a dynamic tax, most taxes are static or nearly static. A theoretical model is used to derive the extraction, resource stock, and pollution stock time paths under a static and dynamic tax. An example of how the time paths might differ is provided through use of a simulation model.