Essays on Environmental Economics with a Focus on Non-market Valuation
This dissertation consists of two research projects in the area of Environmental Economics: water-recycling technology adoption and its cost-effectiveness in the U.S. horticulture industry (in Chapter 2), and urban tree cover's impact on residential location decision making in Milwaukee, WI (in Chapter 3).
Chapter 2 evaluates the economic effects of labeling plants grown with water-recycling technology (WRT) practices in selected nursery operations in the Mid-Atlantic region of Virginia, Maryland and Pennsylvania. Partial budgeting, whole enterprise-level budgeting, sensitivity and break-even analyses are conducted to determine whether consumer premiums for plants grown with recycled water are sufficient to make WRT economically feasible combined with plant eco-labeling, and how such a labeling program would affect greenhouse/nursery production costs, gross revenues and net revenues. It is concluded that consumer premiums for plants grown with recycled water could offer nursery growers a method to improve their net returns while reducing pollution runoff and improving irrigation water usage efficiency.
Chapter 3 focuses on non-market valuation of environmental (dis)amenities. Specifically, this chapter investigates the impact of urban tree cover on residential property location decision in the housing market of Milwaukee, WI. Residential sorting model embedded with "horizontal preference structure" is established to estimate the heterogeneous preferences for tree cover and other land cover attributes that vary by household socio-economic characteristics and then to identify the housing property owners' demand for these land cover attributes. The first part of this chapter mainly recovers the demand for "community trees" at the census block group level combined with 10 years property transaction data and neighborhood characteristics where the median income is aggregated to represent the household annual income. It is found that "community trees" are positively valued by the housing property owners and have a positive impact on housing price due to its positive externalities. Furthermore, income is found to be a strong exogenous demand shifter, leading to heterogeneous preference for the tree cover.
The second part of Chapter 3 further investigates the impacts of both nearby trees and distant trees on residential property location decision using different spatial scales of land covers measurements. Instead of aggregating block group level median income, this study matches and merges disaggregated individual household annual incomes from the Home Mortgage Disclosure Act (HMDA) dataset to mitigate the potential aggregation bias. It is found that different spatial scales of land cover measurement result in varying willingness to pay estimates, implying that housing property owners have heterogeneous demands for nearby trees and distant trees. In other words, preferences for urban tree cover not only vary by household annual income, but also differ across spatial scales of the tree cover measurement.