Effects of accessibility and environmental health risk on housing prices: a case of Salt Lake County, Utah

While transportation infrastructure can increase housing price by improving accessibility to opportunities, it generates environmental health risks, such as noise and air pollution, which may have negative effects on housing price. However, the combined effects of accessibility and environmental health risk on housing price have not been well examined in the literature, especially in the auto-oriented urban context of the United States. In this study, we use assessed housing value data and the hedonic model to examine the single-family housing market's reaction to accessibility and environment health risks in Salt Lake County, a growing metropolitan area in Utah experiencing significant air pollution. Three regression models are employed with the consideration of spatial effects: ordinary least squares (OLS), spatial lag regression (SLR), and hierarchical linear modeling (HLM, or multilevel modeling/MLM). By controlling for the influences of structural attributes and socioeconomic conditions, we find that the negative impacts (traffic noise and air pollution) of transportation systems on single-family housing prices are greater than the positive impact (accessibility). Single-family residents in Salt Lake County are willing to pay more to reduce environmental health risks than to get better accessibility. These findings are different from what have been found in some dense and compact urban areas in the literature. These findings suggest that people's willingness to pay for minimizing environmental health risks varies across different urban contexts.