Essays in Suface Water Quality Valuation

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Virginia Tech


This dissertation is comprised of three essays examining methods for surface water quality valuation. The first essay uses Zillow's ZTRAX property transaction database to investigate variation in hedonic price effects of water clarity on single-family houses throughout the United States. I consider five spatial scales and estimate models using different sample selection criteria and model specifications. The results indicate considerable spatial heterogeneity both within and across the four U.S. Census regions. However, I also find heterogeneity resulting from different types of investigator decisions, including sample selection and modelling choices. Thus, it is necessary to use practical knowledge to consider the limits of market areas and to investigate the robustness of estimation results to investigator choices.

In the second essay, I integrate a coastal recreation demand model for Southern New England with property sales in Massachusetts and Rhode Island to estimate the impacts of water quality improvements for freshwater and saltwater resources throughout the region. While traditional hedonic studies for water quality reveal the direct effects of local water quality on housing prices, the spatial extent of the models is limited to 2 km from the waterfront. Integrating recreation demand models with hedonic models allows identification of additional indirect effects of water quality at recreation sites that are capitalized in housing markets through a recreational index (i.e., the potential recreational benefits for a neighborhood). However, the spatial extent of these models is currently untested. I compare the spatial extent of indirect and direct effects of water quality for multiple water quality inputs isolating spatial and temporal sources of variation. The results indicate heterogeneity in the direct effects of freshwater and saltwater clarity depending on whether the source of variation is spatial or temporal. Conflating spatial and temporal water quality variation can lead to anomalous conclusions on the impacts of coastal recreation on housing markets.

In the third essay, I evaluate meta-regression models (MRMs) that are used by policy makers in calculating the potential benefits of improvements in environmental quality resulting from proposed regulatory actions. MRMs lay the foundation for benefit transfers applied by EPA to recent rulemakings under the Clean Water Act (CWA) in addition to other environmental contexts (e.g., health benefits under the Clean Air Act). While recent literature has emphasized the necessity that MRMs satisfy key theoretical conditions, including scope sensitivity and the adding up condition, existing MRMs that fulfil these properties require imposing structural model restrictions or removing relevant explanatory variables from the MRM at the expense of model fit and predictive performance. This study presents a method for defining MRMs that draws on characteristics of the given benefits transfer scenario and its relationship to the metadata while satisfying the adding up condition. This modelling framework outperforms the model used by EPA in model fit and predictive performance. Applying the results to a recent CWA rule, I find the model used by EPA substantially underestimates the potential benefits.



Environmental Economics, Nonmarket Valuation, Water Quality